From 4edec158d0f679df0df7be70092c197c014aed56 Mon Sep 17 00:00:00 2001 From: stroblme Date: Thu, 13 Oct 2022 22:23:15 +0200 Subject: [PATCH 01/92] complexer model and more data --- conf/base/parameters/data_generation.yml | 2 +- conf/base/parameters/data_science.yml | 6 +++--- 2 files changed, 4 insertions(+), 4 deletions(-) diff --git a/conf/base/parameters/data_generation.yml b/conf/base/parameters/data_generation.yml index c3d8811..8e72ed1 100644 --- a/conf/base/parameters/data_generation.yml +++ b/conf/base/parameters/data_generation.yml @@ -7,7 +7,7 @@ max_depth: 3 # this will control the dimensionality of the classes max_children: 3 # careful, this only controls how many children a single particle can have min_children: 2 isp_weight: 1.0 -train_events_per_top: 500 +train_events_per_top: 1000 val_events_per_top: 100 test_events_per_top: 10 seed: 1111 diff --git a/conf/base/parameters/data_science.yml b/conf/base/parameters/data_science.yml index efab448..35c3a52 100644 --- a/conf/base/parameters/data_science.yml +++ b/conf/base/parameters/data_science.yml @@ -5,11 +5,11 @@ post_model_sel: "pqgnn" # only for split training n_momenta: 4 # Classical -epochs: 30 -normalize: "zmuv" +epochs: 60 +normalize: "smartone" # one, smartone, zmuv normalize_individually: False zero_mean: False -dim_feedforward: 512 +dim_feedforward: 1024 dim_feedforward_range: [4, 2048, "log"] batchnorm: True From 373edfd9212c71eeacf9e64532f5141efe5b96c6 Mon Sep 17 00:00:00 2001 From: stroblme Date: Thu, 13 Oct 2022 22:24:07 +0200 Subject: [PATCH 02/92] inc val samples --- conf/base/parameters/data_generation.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/conf/base/parameters/data_generation.yml b/conf/base/parameters/data_generation.yml index 8e72ed1..291ae4f 100644 --- a/conf/base/parameters/data_generation.yml +++ b/conf/base/parameters/data_generation.yml @@ -8,7 +8,7 @@ max_children: 3 # careful, this only controls how many children a single particl min_children: 2 isp_weight: 1.0 train_events_per_top: 1000 -val_events_per_top: 100 +val_events_per_top: 300 test_events_per_top: 10 seed: 1111 iso_retries: 0 From 66269d8ccf5eeb68077640b7627428f66b3297f3 Mon Sep 17 00:00:00 2001 From: stroblme Date: Fri, 14 Oct 2022 09:45:00 +0200 Subject: [PATCH 03/92] minimum setting to get a comparison with qmlp --- conf/base/parameters/data_generation.yml | 4 ++-- conf/base/parameters/data_science.yml | 10 +++++----- 2 files changed, 7 insertions(+), 7 deletions(-) diff --git a/conf/base/parameters/data_generation.yml b/conf/base/parameters/data_generation.yml index 291ae4f..2dd55ff 100644 --- a/conf/base/parameters/data_generation.yml +++ b/conf/base/parameters/data_generation.yml @@ -7,8 +7,8 @@ max_depth: 3 # this will control the dimensionality of the classes max_children: 3 # careful, this only controls how many children a single particle can have min_children: 2 isp_weight: 1.0 -train_events_per_top: 1000 -val_events_per_top: 300 +train_events_per_top: 100 +val_events_per_top: 20 test_events_per_top: 10 seed: 1111 iso_retries: 0 diff --git a/conf/base/parameters/data_science.yml b/conf/base/parameters/data_science.yml index 35c3a52..e5f3211 100644 --- a/conf/base/parameters/data_science.yml +++ b/conf/base/parameters/data_science.yml @@ -5,11 +5,11 @@ post_model_sel: "pqgnn" # only for split training n_momenta: 4 # Classical -epochs: 60 +epochs: 20 normalize: "smartone" # one, smartone, zmuv normalize_individually: False zero_mean: False -dim_feedforward: 1024 +dim_feedforward: 64 dim_feedforward_range: [4, 2048, "log"] batchnorm: True @@ -28,11 +28,11 @@ skip_block: True # activates skip connections on local scales skip_global: True # activates skip connections on global scales # GNN -n_blocks: 4 +n_blocks: 3 n_blocks_range: [1, 5, "linear"] -n_layers_mlp: 2 # initial mlp layers before the blocks +n_layers_mlp: 4 # initial mlp layers before the blocks n_layers_mlp_range: [1, 5, "linear"] -n_additional_mlp_layers: 3 # additional layers within a block +n_additional_mlp_layers: 0 # additional layers within a block n_additional_mlp_layers_range: [1, 5, "linear"] n_final_mlp_layers: 2 # layers after the blocks n_final_mlp_layers_range: [1, 5, "linear"] From 1bd95df1d91b023311b343786266a01dad731493 Mon Sep 17 00:00:00 2001 From: stroblme Date: Fri, 14 Oct 2022 09:50:38 +0200 Subject: [PATCH 04/92] one more initial block to account for the lack of the qnn layer --- conf/base/parameters/data_science.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/conf/base/parameters/data_science.yml b/conf/base/parameters/data_science.yml index e5f3211..a3268be 100644 --- a/conf/base/parameters/data_science.yml +++ b/conf/base/parameters/data_science.yml @@ -28,7 +28,7 @@ skip_block: True # activates skip connections on local scales skip_global: True # activates skip connections on global scales # GNN -n_blocks: 3 +n_blocks: 4 n_blocks_range: [1, 5, "linear"] n_layers_mlp: 4 # initial mlp layers before the blocks n_layers_mlp_range: [1, 5, "linear"] From fef1a9d5c8270379d3d0547ab24d984bfadb6983 Mon Sep 17 00:00:00 2001 From: stroblme Date: Fri, 14 Oct 2022 09:58:40 +0200 Subject: [PATCH 05/92] reduced do --- conf/base/parameters/data_science.yml | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/conf/base/parameters/data_science.yml b/conf/base/parameters/data_science.yml index a3268be..95d66ae 100644 --- a/conf/base/parameters/data_science.yml +++ b/conf/base/parameters/data_science.yml @@ -13,7 +13,7 @@ dim_feedforward: 64 dim_feedforward_range: [4, 2048, "log"] batchnorm: True -dropout_rate: 0.4 +dropout_rate: 0.2 dropout_rate_range: [0.1, 1.0, "linear"] learning_rate: 0.001 learning_rate_range: [1e-5, 1e-1, "log"] @@ -28,7 +28,7 @@ skip_block: True # activates skip connections on local scales skip_global: True # activates skip connections on global scales # GNN -n_blocks: 4 +n_blocks: 3 n_blocks_range: [1, 5, "linear"] n_layers_mlp: 4 # initial mlp layers before the blocks n_layers_mlp_range: [1, 5, "linear"] From aa5ab379465458a0c85baf7468f7e305c3607c28 Mon Sep 17 00:00:00 2001 From: stroblme Date: Fri, 14 Oct 2022 10:52:48 +0200 Subject: [PATCH 06/92] reduced model complexity further --- conf/base/parameters/data_science.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/conf/base/parameters/data_science.yml b/conf/base/parameters/data_science.yml index 95d66ae..254f04b 100644 --- a/conf/base/parameters/data_science.yml +++ b/conf/base/parameters/data_science.yml @@ -30,7 +30,7 @@ skip_global: True # activates skip connections on global scales # GNN n_blocks: 3 n_blocks_range: [1, 5, "linear"] -n_layers_mlp: 4 # initial mlp layers before the blocks +n_layers_mlp: 2 # initial mlp layers before the blocks n_layers_mlp_range: [1, 5, "linear"] n_additional_mlp_layers: 0 # additional layers within a block n_additional_mlp_layers_range: [1, 5, "linear"] From 092464457227fb13dcb153813246e030714c09b8 Mon Sep 17 00:00:00 2001 From: stroblme Date: Fri, 14 Oct 2022 11:30:51 +0200 Subject: [PATCH 07/92] reduced ff dim --- conf/base/parameters/data_science.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/conf/base/parameters/data_science.yml b/conf/base/parameters/data_science.yml index 254f04b..c8fe22d 100644 --- a/conf/base/parameters/data_science.yml +++ b/conf/base/parameters/data_science.yml @@ -9,7 +9,7 @@ epochs: 20 normalize: "smartone" # one, smartone, zmuv normalize_individually: False zero_mean: False -dim_feedforward: 64 +dim_feedforward: 32 dim_feedforward_range: [4, 2048, "log"] batchnorm: True From b09907f91ca6c5bb671c28f8ab4611d2afee1ad0 Mon Sep 17 00:00:00 2001 From: lc3267 Date: Fri, 14 Oct 2022 14:58:44 +0200 Subject: [PATCH 08/92] qmlp params --- conf/base/parameters/data_generation.yml | 4 ++-- conf/base/parameters/data_science.yml | 18 +++++++++--------- 2 files changed, 11 insertions(+), 11 deletions(-) diff --git a/conf/base/parameters/data_generation.yml b/conf/base/parameters/data_generation.yml index c3d8811..2dd55ff 100644 --- a/conf/base/parameters/data_generation.yml +++ b/conf/base/parameters/data_generation.yml @@ -7,8 +7,8 @@ max_depth: 3 # this will control the dimensionality of the classes max_children: 3 # careful, this only controls how many children a single particle can have min_children: 2 isp_weight: 1.0 -train_events_per_top: 500 -val_events_per_top: 100 +train_events_per_top: 100 +val_events_per_top: 20 test_events_per_top: 10 seed: 1111 iso_retries: 0 diff --git a/conf/base/parameters/data_science.yml b/conf/base/parameters/data_science.yml index efab448..97873f1 100644 --- a/conf/base/parameters/data_science.yml +++ b/conf/base/parameters/data_science.yml @@ -1,26 +1,26 @@ --- # General -model_sel: "gnn" # qmlp, qftgnn, qgnn +model_sel: "qmlp" post_model_sel: "pqgnn" # only for split training n_momenta: 4 # Classical -epochs: 30 -normalize: "zmuv" +epochs: 20 +normalize: "smartone" normalize_individually: False zero_mean: False -dim_feedforward: 512 +dim_feedforward: 64 dim_feedforward_range: [4, 2048, "log"] batchnorm: True -dropout_rate: 0.4 +dropout_rate: 0.2 dropout_rate_range: [0.1, 1.0, "linear"] learning_rate: 0.001 learning_rate_range: [1e-5, 1e-1, "log"] learning_rate_decay: 100 learning_rate_decay_range: [1, 1000, "log"] gamma: 0.5 -batch_size: 8 +batch_size: 4 batch_size_range: [1, 64, "log"] gradients_clamp: 1000 gradients_spreader: 1e-10 @@ -28,11 +28,11 @@ skip_block: True # activates skip connections on local scales skip_global: True # activates skip connections on global scales # GNN -n_blocks: 4 +n_blocks: 3 n_blocks_range: [1, 5, "linear"] -n_layers_mlp: 2 # initial mlp layers before the blocks +n_layers_mlp: 3 # initial mlp layers before the blocks n_layers_mlp_range: [1, 5, "linear"] -n_additional_mlp_layers: 3 # additional layers within a block +n_additional_mlp_layers: 0 # additional layers within a block n_additional_mlp_layers_range: [1, 5, "linear"] n_final_mlp_layers: 2 # layers after the blocks n_final_mlp_layers_range: [1, 5, "linear"] From 49f35e8fc6f8e245876ea5964fe1c0833b93d074 Mon Sep 17 00:00:00 2001 From: lc3267 Date: Fri, 14 Oct 2022 16:36:35 +0200 Subject: [PATCH 09/92] refactoring --- src/partiqlegan/pipelines/data_science/instructor.py | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/src/partiqlegan/pipelines/data_science/instructor.py b/src/partiqlegan/pipelines/data_science/instructor.py index ed84358..b91aad6 100644 --- a/src/partiqlegan/pipelines/data_science/instructor.py +++ b/src/partiqlegan/pipelines/data_science/instructor.py @@ -608,22 +608,22 @@ def convToPair(pair: t.Tensor): def edge_accuracy(self, logits: t.Tensor, labels: t.Tensor, ignore_index: int=None) -> float: correct = 0.0 - for labe, logit in zip(labels, logits): + for label, logit in zip(labels, logits): # logits: [Batch, Classes, LCA_0, LCA_1] probs = logit.softmax(0) # get softmax for probabilities prediction = probs.max(0)[1] # find maximum across the classes (batches are on 0) if ignore_index is not None: # set everything to -1 which is not relevant for grading - prediction = t.where(labe==ignore_index, labe, prediction) + prediction = t.where(label==ignore_index, label, prediction) # which are the correct predictions - a = (labe == prediction) + a = (label == prediction) if ignore_index is not None: # create a mask hiding the irrelevant entries - b = (labe != t.ones(labe.shape)*ignore_index) + b = (label != t.ones(label.shape)*ignore_index) else: - b = (labe == labe) # simply create an "True"-matrix to hide the mask + b = (label == label) # simply create an "True"-matrix to hide the mask correct += (a == b).float().sum()/b.sum() # divide by the size of the matrix From e83bac53cbcc693d95813eaeb7d4c2657141fcea Mon Sep 17 00:00:00 2001 From: lc3267 Date: Fri, 14 Oct 2022 16:36:56 +0200 Subject: [PATCH 10/92] int conv to catch float preds --- src/partiqlegan/pipelines/data_science/instructor.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/partiqlegan/pipelines/data_science/instructor.py b/src/partiqlegan/pipelines/data_science/instructor.py index b91aad6..63133ac 100644 --- a/src/partiqlegan/pipelines/data_science/instructor.py +++ b/src/partiqlegan/pipelines/data_science/instructor.py @@ -549,7 +549,7 @@ def plotBatchGraphs(self, batch_logits, batch_ref, rows=4, cols=2): def logic_accuracy(self, logits: t.Tensor, labels: t.Tensor, ignore_index: int=None) -> float: def two_child_fix(lcag): - max_c = lcag.max() + max_c = lcag.max().int() def convToPair(pair: t.Tensor): return (int(pair[0]), int(pair[1])) From aa6b0c67a3d9c2a270bd11bf3d123468b70d4657 Mon Sep 17 00:00:00 2001 From: lc3267 Date: Fri, 14 Oct 2022 16:37:14 +0200 Subject: [PATCH 11/92] some test cases to elaborate of this is actually working --- .../pipelines/data_science/instructor.py | 21 +++++++++++++++++++ 1 file changed, 21 insertions(+) diff --git a/src/partiqlegan/pipelines/data_science/instructor.py b/src/partiqlegan/pipelines/data_science/instructor.py index 63133ac..0231c92 100644 --- a/src/partiqlegan/pipelines/data_science/instructor.py +++ b/src/partiqlegan/pipelines/data_science/instructor.py @@ -588,6 +588,27 @@ def convToPair(pair: t.Tensor): # set everything to -1 which is not relevant for grading prediction = t.where(label==ignore_index, label, prediction) + # test_lcag_a = t.Tensor([ [-1, 1, 2, 2], + # [ 1, -1, 2, 1], + # [ 2, 2, -1, 2], + # [ 2, 1, 2, -1]]) + # test_lcag_b = t.Tensor([ [-1, 1, 2, 2], + # [ 1, -1, 2, 0], + # [ 2, 2, -1, 2], + # [ 2, 0, 2, -1]]) + # test_lcag_c = t.Tensor([ [-1, 1, 3, 3], + # [ 1, -1, 3, 3], + # [ 3, 3, -1, 1], + # [ 3, 3, 1, -1]]) + # test_lcag_d = t.Tensor([ [-1, 1, 3, -1], + # [ 1, -1, 3, -1], + # [ 3, 3, -1, -1], + # [-1, -1, -1, -1]]) + + # test_lcag_a = two_child_fix(test_lcag_a) + # test_lcag_b = two_child_fix(test_lcag_b) + # test_lcag_c = two_child_fix(test_lcag_c) + # test_lcag_d = two_child_fix(test_lcag_d) prediction = two_child_fix(prediction) From fca41c169ed0c75c3edcfdc08cc0d7b8e526eb44 Mon Sep 17 00:00:00 2001 From: lc3267 Date: Fri, 14 Oct 2022 17:06:57 +0200 Subject: [PATCH 12/92] exception printing in log --- src/partiqlegan/pipelines/data_science/instructor.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/src/partiqlegan/pipelines/data_science/instructor.py b/src/partiqlegan/pipelines/data_science/instructor.py index 0231c92..7ebfa79 100644 --- a/src/partiqlegan/pipelines/data_science/instructor.py +++ b/src/partiqlegan/pipelines/data_science/instructor.py @@ -451,10 +451,10 @@ def train(self, start_epoch=1): self.scheduler.step() except GradientsNanException as e: - log.error(f"Gradients became NAN during training\n{e}") + log.error(f"Gradients became NAN during training\n{traceback.print_exc()}") except Exception as e: - log.error(f"Exception occured during training\n{e}\n") - traceback.print_exc() + log.error(f"Exception occured during training\n{traceback.print_exc()}\n") + # quickly print the gradients.. if self.log_gradients and len(all_grads) > 0: From e833a2fdce0fd2d9b67f151a7cac1359cdcf26c8 Mon Sep 17 00:00:00 2001 From: lc3267 Date: Fri, 14 Oct 2022 17:18:39 +0200 Subject: [PATCH 13/92] started creating qbb --- .../pipelines/data_science/nodes.py | 2 +- .../pipelines/data_science/qgnn.py | 630 ++++++++++-------- .../pipelines/data_science/qgnn_new.py | 510 ++++++++++++++ 3 files changed, 880 insertions(+), 262 deletions(-) create mode 100644 src/partiqlegan/pipelines/data_science/qgnn_new.py diff --git a/src/partiqlegan/pipelines/data_science/nodes.py b/src/partiqlegan/pipelines/data_science/nodes.py index 0604986..5baeb94 100644 --- a/src/partiqlegan/pipelines/data_science/nodes.py +++ b/src/partiqlegan/pipelines/data_science/nodes.py @@ -13,7 +13,7 @@ from .instructor import Instructor from .gnn import gnn from .qftgnn import qftgnn -from .qgnn import qgnn +from .qgnn_new import qgnn from .dqgnn import dqgnn from .dgnn import dgnn from .pqgnn import pqgnn diff --git a/src/partiqlegan/pipelines/data_science/qgnn.py b/src/partiqlegan/pipelines/data_science/qgnn.py index 1c0941d..fa709e9 100644 --- a/src/partiqlegan/pipelines/data_science/qgnn.py +++ b/src/partiqlegan/pipelines/data_science/qgnn.py @@ -1,21 +1,8 @@ import numpy as np -import matplotlib.pyplot as plt - -from enum import Enum -import time - -from .graph_visualization import hierarchy_pos import torch as t from torch import nn import torch.nn.functional as F -from torch.autograd import Function - -import networkx as nx -import torch_geometric as tg -from torch_geometric.utils.convert import to_networkx -from torch_geometric.utils import add_self_loops, degree -import mlflow from .utils import * @@ -23,15 +10,13 @@ from qiskit import transpile, assemble from qiskit.visualization import * from qiskit_machine_learning.neural_networks import CircuitQNN, TwoLayerQNN -from qiskit_machine_learning.connectors import TorchConnector import logging qiskit_logger = logging.getLogger("qiskit") qiskit_logger.setLevel(logging.WARNING) log = logging.getLogger(__name__) - -import os +from qiskit_machine_learning.connectors import TorchConnector os.environ["CUDA_VISIBLE_DEVICES"] = "" @@ -39,27 +24,18 @@ class MLP(nn.Module): """Two-layer fully-connected ELU net with batch norm.""" - def __init__( - self, - n_in, - n_hid, - n_out, - do_prob, - batchnorm=True, - activation=F.elu, - device=t.device("cpu"), - ): + def __init__(self, n_in, n_hid, n_out, do_prob, batchnorm=True): super(MLP, self).__init__() self.batchnorm = batchnorm - self.fc1 = nn.Linear(n_in, n_hid, device=device) - self.fc2 = nn.Linear(n_hid, n_out, device=device) + self.fc1 = nn.Linear(n_in, n_hid) + self.fc2 = nn.Linear(n_hid, n_out) if self.batchnorm: self.bn = nn.BatchNorm1d(n_out, momentum=0.1, track_running_stats=True) # self.bn = nn.BatchNorm1d(n_out, momentum=0.1, track_running_stats=False) # Use this to overfit self.dropout_prob = do_prob - self.activation = activation + self.init_weights() def init_weights(self): @@ -82,56 +58,13 @@ def forward(self, inputs): Output: (b, l, d) """ # Input shape: [num_sims, num_things, num_features] - x = self.activation(self.fc1(inputs)) # (b, l, d) + x = F.elu(self.fc1(inputs)) # (b, l, d) x = F.dropout(x, self.dropout_prob, training=self.training) # (b, l, d) - x = self.activation(self.fc2(x)) # (b, l, d) + x = F.elu(self.fc2(x)) # (b, l, d) return self.batch_norm_layer(x) if self.batchnorm else x # (b, l, d) -class qMessagePassing(tg.nn.MessagePassing): - def __init__(self, in_channels, out_channels): - super().__init__(aggr='add', flow='target_to_source') # "Add" aggregation (Step 5). - self.lin = t.nn.Linear(in_channels, out_channels, bias=False) - self.bias = t.nn.Parameter(t.Tensor(out_channels)) - - self.reset_parameters() - - def reset_parameters(self): - self.lin.reset_parameters() - self.bias.data.zero_() - - def forward(self, x, edge_index): - # x has shape [N, in_channels] - # edge_index has shape [2, E] - - # Step 1: Add self-loops to the adjacency matrix. - # edge_index, _ = add_self_loops(edge_index, num_nodes=x.size(0)) - - # Step 2: Linearly transform node feature matrix. - x = self.lin(x) - - # Step 3: Compute normalization. - row, col = edge_index - deg = degree(col, x.size(0), dtype=x.dtype) - deg_inv_sqrt = deg.pow(-0.5) - deg_inv_sqrt[deg_inv_sqrt == float('inf')] = 0 - norm = deg_inv_sqrt[row] * deg_inv_sqrt[col] - - # Step 4-5: Start propagating messages. - out = self.propagate(edge_index, x=x, norm=norm) # internally calls message, aggregate, update - - # Step 6: Apply a final bias vector. - out += self.bias - - return out - - def message(self, x_j, norm): - # x_j has shape [E, out_channels] - - # Step 4: Normalize node features. - return norm.view(-1, 1) * x_j - -class qgnn(nn.Module): +class gnn(nn.Module): """NRI model built off the official implementation. Contains adaptations to make it work with our use case, plus options for extra layers to give it some more oomph @@ -155,11 +88,18 @@ def __init__( self, n_momenta, # d n_classes, # l - dim_feedforward=6, # ff + n_blocks=3, + dim_feedforward=128, # ff n_layers_mlp=2, n_layers_vqc=3, - skip_block=False, + n_additional_mlp_layers=2, + n_final_mlp_layers=2, + skip_block=True, + skip_global=True, dropout_rate=0.3, + factor=True, + tokenize=-1, + embedding_dims=-1, batchnorm=True, symmetrize=True, n_fsps: int = -1, @@ -168,20 +108,20 @@ def __init__( add_rot_gates=True, **kwargs, ): - super(qgnn, self).__init__() + super(gnn, self).__init__() assert dim_feedforward % 2 == 0, "dim_feedforward must be an even number" - # n_fsps = 4 - self.layers = n_layers_vqc # dim_feedforward//8 - self.total_n_fsps = n_fsps # used for padding in forward path + self.num_classes = n_classes + self.layers = n_layers_vqc # dim_feedforward//8 + self.factor = factor + self.tokenize = tokenize self.symmetrize = symmetrize + self.block_additional_mlp_layers = n_additional_mlp_layers self.skip_block = skip_block + self.skip_global = skip_global # self.max_leaves = max_leaves - # self.initial_mlp = pre_trained_module.initial_mlp - # self.blocks = pre_trained_module.blocks - # self.final_mlp = pre_trained_module.final_mlp self.qi = q.utils.QuantumInstance( q.Aer.get_backend("aer_simulator_statevector") @@ -204,22 +144,22 @@ def gen_encoding_params(n_qubits, identifier): def encoding(qc, n_qubits, q_params, identifier): for i in range(n_qubits): - energy = q_params[i][0] + energy = q_params[i][3] px = ( - q_params[i][1] * energy * t.pi, + q_params[i][0] * energy * t.pi, i, f"{identifier[:-3]}_rx_{i}", ) qc.rx(*px) py = ( - q_params[i][2] * energy * t.pi, + q_params[i][1] * energy * t.pi, i, f"{identifier[:-3]}_ry_{i}", ) qc.ry(*py) pz = ( - q_params[i][3] * energy * t.pi, + q_params[i][2] * energy * t.pi, i, ) # rz does not accept identifier qc.rz(*pz) @@ -311,200 +251,368 @@ def interpreter(x): print(f"Interpreter Input {x}") return x - # start = time.time() - # self.qnn = CircuitQNN( - # self.qc, - # self.enc_params, - # self.var_params, - # quantum_instance=self.qi, - # # interpret=interpreter, - # # output_shape=(n_fsps**2, n_classes), - # # sampling=True, - # input_gradients=True, - # ) - # self.initial_weights = 0.1 * ( - # 2 * q.utils.algorithm_globals.random.random(self.qnn.num_weights) - 1 - # ) - # log.info(f"Transpilation took {time.time() - start}") - # self.quantum_layer = TorchConnector( - # self.qnn, initial_weights=self.initial_weights - # ) - # log.info(f"Initialization done") - - # last layer input size depends if we do a concat before (use skip cons) - final_input_dim = 2 * dim_feedforward if self.skip_block else dim_feedforward - - self.block = nn.ModuleList( + start = time.time() + self.qnn = CircuitQNN( + self.qc, + self.enc_params, + self.var_params, + quantum_instance=self.qi, + # interpret=interpreter, + # output_shape=(n_fsps**2, n_classes), + # sampling=True, + input_gradients=True, + ) + self.initial_weights = 0.1 * ( + 2 * q.utils.algorithm_globals.random.random(self.qnn.num_weights) - 1 + ) + log.info(f"Transpilation took {time.time() - start}") + self.quantum_layer = TorchConnector( + self.qnn, initial_weights=self.initial_weights + ) + log.info(f"Initialization done") + + + + + + + # Set up embedding for tokens and adjust input dims + if self.tokenize != -1: + assert (embedding_dims is not None) and isinstance( + embedding_dims, int + ), "embedding_dims must be set to an integer is tokenize is given" + + # Initialise the embedding layers, ignoring pad values + self.embed = nn.ModuleDict({}) + for idx, n_tokens in self.tokenize.items(): + # NOTE: This assumes a pad value of 0 for the input array x + self.embed[str(idx)] = nn.Embedding( + n_tokens, embedding_dims, padding_idx=0 + ) + + # And update the infeatures to include the embedded feature dims and delete the original, now tokenized feats + n_momenta = n_momenta + (len(self.tokenize) * (embedding_dims - 1)) + print(f"Set up embedding for {len(self.tokenize)} inputs") + + # Create first half of inital NRI half-block to go from leaves to edges + initial_mlp = [ + MLP(n_momenta, dim_feedforward, dim_feedforward, dropout_rate, batchnorm) + ] + # Add any additional layers as per request + initial_mlp.extend( [ MLP( - self.num_classes, + dim_feedforward, dim_feedforward, dim_feedforward, dropout_rate, batchnorm, - activation=F.elu, - device=self.device, - ), - nn.Sequential( - *[ - MLP( - dim_feedforward, - dim_feedforward, - dim_feedforward, - dropout_rate, - batchnorm, - activation=F.elu, - device=self.device, - ) - for _ in range(n_layers_mlp) - ] - ), + ) + for _ in range(n_layers_mlp - 1) + ] + ) + self.initial_mlp = nn.Sequential(*initial_mlp) + + # MLP to reduce feature dimensions from first Node2Edge before blocks begin + self.pre_blocks_mlp = MLP( + dim_feedforward * 2, + dim_feedforward, + dim_feedforward, + dropout_rate, + batchnorm, + ) + + block_dim = 3 * dim_feedforward if self.skip_block else 2 * dim_feedforward + global_dim = 2 * dim_feedforward if self.skip_global else dim_feedforward + + if self.factor: + # MLPs within NRI blocks + # The blocks have minimum 1 MLP layer, and if specified they add more with a skip connection + # List of blocks + self.blocks = nn.ModuleList( + [ + # List of MLP sequences within each block + nn.ModuleList( + [ + # MLP layers before Edge2Node (start of block) + nn.ModuleList( + [ + MLP( + dim_feedforward, + dim_feedforward, + dim_feedforward, + dropout_rate, + batchnorm, + ), + nn.Sequential( + *[ + MLP( + dim_feedforward, + dim_feedforward, + dim_feedforward, + dropout_rate, + batchnorm, + ) + for _ in range(n_additional_mlp_layers) + ] + ), + # This is what would be needed for a concat instead of addition of the skip connection + # MLP(dim_feedforward * 2, dim_feedforward, dim_feedforward, dropout, batchnorm) if (block_additional_mlp_layers > 0) else None, + ] + ), + # MLP layers between Edge2Node and Node2Edge (middle of block) + nn.ModuleList( + [ + MLP( + dim_feedforward, + dim_feedforward, + dim_feedforward, + dropout_rate, + batchnorm, + ), + nn.Sequential( + *[ + MLP( + dim_feedforward, + dim_feedforward, + dim_feedforward, + dropout_rate, + batchnorm, + ) + for _ in range(n_additional_mlp_layers) + ] + ), + # This is what would be needed for a concat instead of addition of the skip connection + # MLP(dim_feedforward * 2, dim_feedforward, dim_feedforward, dropout, batchnorm) if (block_additional_mlp_layers > 0) else None, + ] + ), + # MLP layer after Node2Edge (end of block) + # This is just to reduce feature dim after skip connection was concatenated + MLP( + block_dim, + dim_feedforward, + dim_feedforward, + dropout_rate, + batchnorm, + ), + ] + ) + for _ in range(n_blocks) + ] + ) + print("Using factor graph MLP encoder.") + else: + self.mlp3 = MLP( + dim_feedforward, + dim_feedforward, + dim_feedforward, + dropout_rate, + batchnorm, + ) + self.mlp4 = MLP( + dim_feedforward * 2, + dim_feedforward, + dim_feedforward, + dropout_rate, + batchnorm, + ) + print("Using MLP encoder.") + + # Final linear layers as requested + # self.final_mlp = nn.Sequential(*[MLP(dim_feedforward, dim_feedforward, dim_feedforward, dropout, batchnorm) for _ in range(final_mlp_layers)]) + final_mlp = [ + MLP(global_dim, dim_feedforward, dim_feedforward, dropout_rate, batchnorm) + ] + # Add any additional layers as per request + final_mlp.extend( + [ MLP( - final_input_dim, - final_input_dim // 2, - self.num_classes, + dim_feedforward, + dim_feedforward, + dim_feedforward, dropout_rate, batchnorm, - activation=F.elu, - device=self.device, ) - # This is what would be needed for a concat instead of addition of the skip connection - # MLP(dim_feedforward * 2, dim_feedforward, dim_feedforward, dropout, batchnorm) if (block_additional_mlp_layers > 0) else None, + for _ in range(n_final_mlp_layers - 1) ] ) + self.final_mlp = nn.Sequential(*final_mlp) + + self.fc_out = nn.Linear(dim_feedforward, self.num_classes) + + self.init_weights() + + def init_weights(self): + for m in self.modules(): + if isinstance(m, nn.Linear): + nn.init.xavier_normal_(m.weight.data) + m.bias.data.fill_(0.1) + + def edge2node(self, x, rel_rec): + """ + Input: (b, l*l, d), (b, l*l, l) + Output: (b, l, d) + """ + # TODO assumes that batched matrix product just works + # TODO these do not have to be members + incoming = t.matmul(rel_rec.permute(0, 2, 1), x) # (b, l, d) + denom = rel_rec.sum(1)[:, 1] + return incoming / denom.reshape(-1, 1, 1) # (b, l, d) + # return incoming / incoming.size(1) # (b, l, d) + + def node2edge(self, x, rel_rec, rel_send): + """ + Input: (b, l, d), (b, l*(l-1), l), (b, l*(l-1), l) + Output: (b, l*l(l-1), 2d) + """ + # TODO assumes that batched matrix product just works + receivers = t.matmul(rel_rec, x) # (b, l*l, d) + senders = t.matmul(rel_send, x) # (b, l*l, d) + edges = t.cat([senders, receivers], dim=2) # (b, l*l, 2d) - self.qgat = qMessagePassing(4, 4) + return edges def forward(self, inputs): """ Input: (l, b, d) Output: (b, c, l, l) """ + # inputs=inputs.view(inputs.size(1), inputs.size(0), -1) + if isinstance(inputs, (list, tuple)): - ( - x, - rel_rec, - rel_send, - ) = inputs # get the actual state from the list of states, rel_rec and rel_send - else: # in case we are running torchinfo, rel_rec and rel_send are not provided + inputs, rel_rec, rel_send = inputs + else: rel_rec = None rel_send = None - x = inputs - - n_leaves, batch, feats = x.size() # get the representative sizes - assert x.device == self.device # check if we are running on the same device - - x = x.permute(1, 0, 2) # (b, l, f) - - def build_fully_connected(input): - batch, n_leaves, n_feats = input.size() - - max_nodes = np.sum(range(n_leaves+1)) - graph_list = [] - for data_batch in input: - - edges = [] - for level in range(n_leaves-1): - for n_level in range(level+1): - level_node_idx = n_level + (2**level-1) - max_level_node_idx = level + (2**level-1) - for n_other in range(max_level_node_idx+1, max_nodes): - edges.append([level_node_idx, n_other]) - - edges = t.Tensor(edges).long().permute(1,0) - embeddings = t.zeros(max_nodes, n_feats) - embeddings[-n_leaves:] = data_batch - # edges = t.combinations(t.Tensor(range(n_leaves)).long()).permute(1,0) - graph_batch = tg.data.Data(x=embeddings, edge_index=edges) - - graph_list.append(graph_batch) - - return tg.data.Batch().from_data_list(graph_list) - - x = build_fully_connected(x) - - vis = to_networkx(x) - plt.close() - plt.figure(1,figsize=(8,8)) - pos=nx.circular_layout(vis) - # pos = hierarchy_pos(vis, max(max(x.edge_index))) - nx.draw(vis, pos, cmap=plt.get_cmap('Set3'),node_size=70,linewidths=6) - plt.savefig("graph.png") - - - x.x = self.qgat(x.x, x.edge_index) # messages flow to uninitialized nodes in graph - - x = x.reshape(batch, n_leaves * feats) # flatten the last two dims - x = t.nn.functional.pad( - x, (0, (self.total_n_fsps * feats) - (n_leaves * feats)), mode="constant", value=0 - ) # pad up to the largest lcag size. subtract the current size to prevent unnecessary padding. - # note that x.size() is here n_leaves * feats - - # set the weights to zero which are either involved in a controlled operation or directly operating on qubits not relevant to the current graph (i.e. where the input was zero padded before) - # this is supposed to ensure, that the actual measurement of the circuit is not impacted by any random weights contributing to meaningless - # print(self.quantum_layer._weights) - with t.no_grad(): - for i, p in enumerate(self.var_params): - if int(p._name[-1]) > n_leaves or int(p._name[-3]) > n_leaves: - self.quantum_layer._weights[i] = 0.0 - # print(self.quantum_layer._weights) - - x = self.quantum_layer(x) - - - - def build_binary_permutation_indices(digits): - """ - Generate the binary permutation indices. - :param digits: - :return: - """ - n_permutations = (digits**2 - digits) // 2 - permutations_indices = [] - for i in range(2**digits): - if bin(i).count("1") == 2: - permutations_indices.append(i) - assert len(permutations_indices) == n_permutations - return permutations_indices - - def get_binary_shots(result, permutations_indices, out_shape): - """ - Generate the binary shots. - :param result: - :param permutations_indices: - :param out_shape: - :return: - """ - lcag = t.zeros(out_shape) - lcag = lcag.to(result.device) - for i in range(out_shape[0]): - lcag[i][np.tril_indices_from(lcag[0], k=-1)] = result[ - i, permutations_indices - ] - # lcag[:, np.tril_indices_from(lcag[:], k=-1)] = result[:, permutations_indices] - lcag = lcag + t.transpose(lcag, 1, 2) - return lcag - - x = get_binary_shots( - x, build_binary_permutation_indices(n_leaves), (batch, n_leaves, n_leaves) - ) - x = x.reshape(batch, 1, n_leaves * n_leaves).repeat( - 1, self.num_classes, 1 - ) # copy the vqc output across n_classes dimensions and let the nn handle the decoding - x = x.permute(0, 2, 1) # (b, c, l, l) -> split the leaves + n_leaves, batch, feats = inputs.size() + device = inputs.device + + # NOTE create rel matrices on the fly if not given as input + if rel_rec is None: + # rel_rec = t.eye( + # n_leaves, + # device=device + # ).repeat_interleave(n_leaves-1, dim=1).T # (l*(l-1), l) + # rel_rec = rel_rec.unsqueeze(0).expand(inputs.size(1), -1, -1) + rel_rec = construct_rel_recvs([inputs.size(0)], device=device) + + if rel_send is None: + # rel_send = t.eye(n_leaves, device=device).repeat(n_leaves, 1) + # rel_send[t.arange(0, n_leaves*n_leaves, n_leaves + 1)] = 0 + # rel_send = rel_send[rel_send.sum(dim=1) > 0] # (l*(l-1), l) + # rel_send = rel_send.unsqueeze(0).expand(inputs.size(1), -1, -1) + rel_send = construct_rel_sends([inputs.size(0)], device=device) + + # Input shape: [batch, num_atoms, num_timesteps, num_dims] + # Input shape: [num_sims, num_atoms, num_timesteps, num_dims] + # x = inputs.view(inputs.size(0), inputs.size(1), -1) + # New shape: [num_sims, num_atoms, num_timesteps*num_dims] + # Need to match expected shape + # TODO should batch_first be a dataset parameter? + # (l, b, m) -> (b, l, m) + x = inputs.permute(1, 0, 2) # (b, l, m) + + # Create embeddings and merge back into x + # TODO: Move mask creation to init, optimise this loop + if self.tokenize != -1: + emb_x = [] + # We'll use this to drop tokenized features from x + mask = t.ones(feats, dtype=t.bool, device=device) + for idx, emb in self.embed.items(): + # Note we need to convert tokens to type long here for embedding layer + emb_x.append(emb(x[..., int(idx)].long())) # List of (b, l, emb_dim) + mask[int(idx)] = False + + # Now merge the embedding outputs with x (mask has deleted the old tokenized feats) + x = t.cat([x[..., mask], *emb_x], dim=-1) # (b, l, d + embeddings) + del emb_x + + # Initial set of linear layers + # (b, l, m) -> (b, l, d) + x = self.initial_mlp( + x + ) # Series of 2-layer ELU net per node (b, l, d) optionally includes embeddings + + # (b, l, d), (b, l*l, l), (b, l*l, l) -> (b, l, 2*d) + x = self.node2edge(x, rel_rec, rel_send) # (b, l*l, 2d) + + # All things related to NRI blocks are in here + if self.factor: + x = self.pre_blocks_mlp(x) # (b, l*l, d) + + # Skip connection to jump over all NRI blocks + x_global_skip = x + + for block in self.blocks: + x_skip = x # (b, l*l, d) + + # First MLP sequence + x = block[0][0](x) # (b, l*l, d) + if self.block_additional_mlp_layers > 0: + x_first_skip = x # (b, l*l, d) + x = block[0][1](x) # (b, l*l, d) + x = x + x_first_skip # (b, l*l, d) + del x_first_skip + + # Create nodes from edges + x = self.edge2node(x, rel_rec) # (b, l, d) + + # Second MLP sequence + x = block[1][0](x) # (b, l, d) + if self.block_additional_mlp_layers > 0: + x_second_skip = x # (b, l*l, d) + x = block[1][1](x) # (b, l*l, d) + x = x + x_second_skip # (b, l*l, d) + del x_second_skip + + # Create edges from nodes + x = self.node2edge(x, rel_rec, rel_send) # (b, l*l, 2d) + + if self.skip_block: + # Final MLP in block to reduce dimensions again + x = t.cat((x, x_skip), dim=2) # Skip connection # (b, l*l, 3d) + x = block[2](x) # (b, l*l, d) + del x_skip + + if self.skip_global: + # Global skip connection + x = t.cat( + (x, x_global_skip), dim=2 + ) # Skip connection # (b, l*(l-1), 2d) + + # Cleanup + del rel_rec, rel_send + + # else: + # x = self.mlp3(x) # (b, l*(l-1), d) + # x = t.cat((x, x_skip), dim=2) # Skip connection # (b, l*(l-1), 2d) + # x = self.mlp4(x) # (b, l*(l-1), d) + + # Final set of linear layers + x = self.final_mlp(x) # Series of 2-layer ELU net per node (b, l, d) + + # Output what will be used for LCA + x = self.fc_out(x) # (b, l*l, c) + out = x.reshape(batch, n_leaves, n_leaves, self.num_classes) + + # Change to LCA shape + # x is currently the flattened rows of the predicted LCA but without the diagonal + # We need to create an empty LCA then populate the off-diagonals with their corresponding values + # out = t.zeros((batch, n_leaves, n_leaves, self.num_classes), device=device) # (b, l, l, c) + # ind_upper = t.triu_indices(n_leaves, n_leaves, offset=1) + # ind_lower = t.tril_indices(n_leaves, n_leaves, offset=-1) + + # Assign the values to their corresponding position in the LCA + # The right side is just some quick mafs to get the correct edge predictions from the flattened x array + # out[:, ind_upper[0], ind_upper[1], :] = x[:, (ind_upper[0] * (n_leaves - 1)) + ind_upper[1] - 1, :] + # out[:, ind_lower[0], ind_lower[1], :] = x[:, (ind_lower[0] * (n_leaves - 1)) + ind_lower[1], :] + + # Need in the order for cross entropy loss + out = out.permute(0, 3, 1, 2) # (b, c, l, l) + + # Symmetrize + if self.symmetrize: + out = t.div(out + t.transpose(out, 2, 3), 2) # (b, c, l, l) - skip = x if self.skip_block else None - x = self.block[0](x) # initial mlp - for seq_mlp in self.block[1]: - x = seq_mlp(x) - - x = t.cat((x, skip), dim=2) if self.skip_block else x # Skip connection - x = self.block[2](x) # (b, c, l, l) -> final mlp - - x = x.reshape(batch, n_leaves, n_leaves, self.num_classes) - x = x.permute(0, 3, 1, 2) # (b, c, l, l) - - x = t.div(x + t.transpose(x, 2, 3), 2) if self.symmetrize else x # (b, c, l, l) - - return x + return out diff --git a/src/partiqlegan/pipelines/data_science/qgnn_new.py b/src/partiqlegan/pipelines/data_science/qgnn_new.py new file mode 100644 index 0000000..1c0941d --- /dev/null +++ b/src/partiqlegan/pipelines/data_science/qgnn_new.py @@ -0,0 +1,510 @@ +import numpy as np +import matplotlib.pyplot as plt + +from enum import Enum +import time + +from .graph_visualization import hierarchy_pos + +import torch as t +from torch import nn +import torch.nn.functional as F +from torch.autograd import Function + +import networkx as nx +import torch_geometric as tg +from torch_geometric.utils.convert import to_networkx +from torch_geometric.utils import add_self_loops, degree +import mlflow + +from .utils import * + +import qiskit as q +from qiskit import transpile, assemble +from qiskit.visualization import * +from qiskit_machine_learning.neural_networks import CircuitQNN, TwoLayerQNN +from qiskit_machine_learning.connectors import TorchConnector + +import logging + +qiskit_logger = logging.getLogger("qiskit") +qiskit_logger.setLevel(logging.WARNING) +log = logging.getLogger(__name__) + +import os + +os.environ["CUDA_VISIBLE_DEVICES"] = "" + + +class MLP(nn.Module): + """Two-layer fully-connected ELU net with batch norm.""" + + def __init__( + self, + n_in, + n_hid, + n_out, + do_prob, + batchnorm=True, + activation=F.elu, + device=t.device("cpu"), + ): + super(MLP, self).__init__() + + self.batchnorm = batchnorm + + self.fc1 = nn.Linear(n_in, n_hid, device=device) + self.fc2 = nn.Linear(n_hid, n_out, device=device) + if self.batchnorm: + self.bn = nn.BatchNorm1d(n_out, momentum=0.1, track_running_stats=True) + # self.bn = nn.BatchNorm1d(n_out, momentum=0.1, track_running_stats=False) # Use this to overfit + self.dropout_prob = do_prob + self.activation = activation + self.init_weights() + + def init_weights(self): + for m in self.modules(): + if isinstance(m, nn.Linear): + nn.init.xavier_normal_(m.weight.data) + m.bias.data.fill_(0.1) + elif isinstance(m, nn.BatchNorm1d): + m.weight.data.fill_(1) + m.bias.data.zero_() + + def batch_norm_layer(self, inputs): + x = inputs.view(inputs.size(0) * inputs.size(1), -1) + x = self.bn(x) + return x.view(inputs.size(0), inputs.size(1), -1) + + def forward(self, inputs): + """ + Input: (b, l, c) + Output: (b, l, d) + """ + # Input shape: [num_sims, num_things, num_features] + x = self.activation(self.fc1(inputs)) # (b, l, d) + x = F.dropout(x, self.dropout_prob, training=self.training) # (b, l, d) + x = self.activation(self.fc2(x)) # (b, l, d) + return self.batch_norm_layer(x) if self.batchnorm else x # (b, l, d) + + +class qMessagePassing(tg.nn.MessagePassing): + def __init__(self, in_channels, out_channels): + super().__init__(aggr='add', flow='target_to_source') # "Add" aggregation (Step 5). + self.lin = t.nn.Linear(in_channels, out_channels, bias=False) + self.bias = t.nn.Parameter(t.Tensor(out_channels)) + + self.reset_parameters() + + def reset_parameters(self): + self.lin.reset_parameters() + self.bias.data.zero_() + + def forward(self, x, edge_index): + # x has shape [N, in_channels] + # edge_index has shape [2, E] + + # Step 1: Add self-loops to the adjacency matrix. + # edge_index, _ = add_self_loops(edge_index, num_nodes=x.size(0)) + + # Step 2: Linearly transform node feature matrix. + x = self.lin(x) + + # Step 3: Compute normalization. + row, col = edge_index + deg = degree(col, x.size(0), dtype=x.dtype) + deg_inv_sqrt = deg.pow(-0.5) + deg_inv_sqrt[deg_inv_sqrt == float('inf')] = 0 + norm = deg_inv_sqrt[row] * deg_inv_sqrt[col] + + # Step 4-5: Start propagating messages. + out = self.propagate(edge_index, x=x, norm=norm) # internally calls message, aggregate, update + + # Step 6: Apply a final bias vector. + out += self.bias + + return out + + def message(self, x_j, norm): + # x_j has shape [E, out_channels] + + # Step 4: Normalize node features. + return norm.view(-1, 1) * x_j + +class qgnn(nn.Module): + """NRI model built off the official implementation. + + Contains adaptations to make it work with our use case, plus options for extra layers to give it some more oomph + + Args: + infeatures (int): Number of input features + num_classes (int): Number of classes in ouput prediction + nblocks (int): Number of NRI blocks in the model + dim_feedforward (int): Width of feedforward layers + initial_mlp_layers (int): Number of MLP (2 feedforward, 1 batchnorm (optional)) before NRI blocks + block_additional_mlp_layers (int): Number of additional MLP (2 feedforward, 1 batchnorm (optional)) within NRI blocks, when 0 the total number is one. + final_mlp_layers (int): Number of MLP (2 feedforward, 1 batchnorm (optional)) after NRI blocks + dropout (float): Dropout rate + factor (bool): Whether to use NRI blocks at all (useful for benchmarking) + tokenize ({int: int}): Dictionary of tokenized features to embed {index_of_feature: num_tokens} + embedding_dims (int): Number of embedding dimensions to use for tokenized features + batchnorm (bool): Whether to use batchnorm in MLP layers + """ + + def __init__( + self, + n_momenta, # d + n_classes, # l + dim_feedforward=6, # ff + n_layers_mlp=2, + n_layers_vqc=3, + skip_block=False, + dropout_rate=0.3, + batchnorm=True, + symmetrize=True, + n_fsps: int = -1, + device: str = "cpu", + data_reupload=True, + add_rot_gates=True, + **kwargs, + ): + super(qgnn, self).__init__() + + assert dim_feedforward % 2 == 0, "dim_feedforward must be an even number" + # n_fsps = 4 + self.layers = n_layers_vqc # dim_feedforward//8 + self.total_n_fsps = n_fsps # used for padding in forward path + self.num_classes = n_classes + self.symmetrize = symmetrize + self.skip_block = skip_block + # self.max_leaves = max_leaves + + # self.initial_mlp = pre_trained_module.initial_mlp + # self.blocks = pre_trained_module.blocks + # self.final_mlp = pre_trained_module.final_mlp + + self.qi = q.utils.QuantumInstance( + q.Aer.get_backend("aer_simulator_statevector") + ) + + self.enc_params = [] + self.var_params = [] + + self.device = t.device( + "cuda" if t.cuda.is_available() and device != "cpu" else "cpu" + ) + + def gen_encoding_params(n_qubits, identifier): + q_params = [] + for i in range(n_qubits): + q_params.append([]) + for j in range(n_momenta): + q_params[i].append(q.circuit.Parameter(f"{identifier}_{i}_{j}")) + return q_params + + def encoding(qc, n_qubits, q_params, identifier): + for i in range(n_qubits): + energy = q_params[i][0] + + px = ( + q_params[i][1] * energy * t.pi, + i, + f"{identifier[:-3]}_rx_{i}", + ) + qc.rx(*px) + py = ( + q_params[i][2] * energy * t.pi, + i, + f"{identifier[:-3]}_ry_{i}", + ) + qc.ry(*py) + pz = ( + q_params[i][3] * energy * t.pi, + i, + ) # rz does not accept identifier + qc.rz(*pz) + # qc.ry(*param) + + def variational(qc, n_qubits, identifier): + for i in range(n_qubits): + if add_rot_gates: + qc.rx( + q.circuit.Parameter(f"{identifier}_rx_0_{i}"), + i, + f"{identifier}_rx_{i}", + ) + qc.ry( + q.circuit.Parameter(f"{identifier}_ry_0_{i}"), + i, + f"{identifier}_ry_{i}", + ) + qc.rz( + q.circuit.Parameter(f"{identifier}_rz_0_{i}"), + i, + ) + if i == 0: + qc.crx( + q.circuit.Parameter(f"{identifier}_crx_{n_qubits - 1}_{i}"), + i, + n_qubits - 1, + f"{identifier}_crx_{n_qubits - 1}_{i}", + ) + qc.cry( + q.circuit.Parameter(f"{identifier}_cry_{n_qubits - 1}_{i}"), + i, + n_qubits - 1, + f"{identifier}_cry_{n_qubits - 1}_{i}", + ) + qc.crz( + q.circuit.Parameter(f"{identifier}_crz_{n_qubits - 1}_{i}"), + i, + n_qubits - 1, + f"{identifier}_crz_{n_qubits - 1}_{i}", + ) + else: + qc.crx( + q.circuit.Parameter(f"{identifier}_crx_{n_qubits - i - 1}_{n_qubits - i}"), + n_qubits - i, + n_qubits - i - 1, + f"{identifier}_crx_{n_qubits - i - 1}_{n_qubits - i}", + ) + qc.cry( + q.circuit.Parameter(f"{identifier}_cry_{n_qubits - i - 1}_{n_qubits - i}"), + n_qubits - i, + n_qubits - i - 1, + f"{identifier}_cry_{n_qubits - i - 1}_{n_qubits - i}", + ) + qc.crz( + q.circuit.Parameter(f"{identifier}_crz_{n_qubits - i - 1}_{n_qubits - i}"), + n_qubits - i, + n_qubits - i - 1, + f"{identifier}_crz_{n_qubits - i - 1}_{n_qubits - i}", + ) + + def circuit_builder(qc, n_qubits, n_hidden): + enc_params = gen_encoding_params(n_qubits, f"enc") + for i in range(n_hidden): + if data_reupload or i == 0: + encoding(qc, n_qubits, enc_params, f"enc_{i}") + qc.barrier() + variational(qc, n_qubits, f"var_{i}") + qc.barrier() + + log.info( + f"Building Quantum Circuit with {self.layers} layers and {n_fsps} qubits" + ) + self.qc = q.QuantumCircuit(n_fsps) + circuit_builder(self.qc, n_fsps, self.layers) + + mlflow.log_figure(self.qc.draw(output="mpl"), f"circuit.png") + + for param in self.qc.parameters: + if "enc" in param.name: + self.enc_params.append(param) + else: + self.var_params.append(param) + log.info( + f"Encoding Parameters: {len(self.enc_params)}, Variational Parameters: {len(self.var_params)}" + ) + + def interpreter(x): + print(f"Interpreter Input {x}") + return x + + # start = time.time() + # self.qnn = CircuitQNN( + # self.qc, + # self.enc_params, + # self.var_params, + # quantum_instance=self.qi, + # # interpret=interpreter, + # # output_shape=(n_fsps**2, n_classes), + # # sampling=True, + # input_gradients=True, + # ) + # self.initial_weights = 0.1 * ( + # 2 * q.utils.algorithm_globals.random.random(self.qnn.num_weights) - 1 + # ) + # log.info(f"Transpilation took {time.time() - start}") + # self.quantum_layer = TorchConnector( + # self.qnn, initial_weights=self.initial_weights + # ) + # log.info(f"Initialization done") + + # last layer input size depends if we do a concat before (use skip cons) + final_input_dim = 2 * dim_feedforward if self.skip_block else dim_feedforward + + self.block = nn.ModuleList( + [ + MLP( + self.num_classes, + dim_feedforward, + dim_feedforward, + dropout_rate, + batchnorm, + activation=F.elu, + device=self.device, + ), + nn.Sequential( + *[ + MLP( + dim_feedforward, + dim_feedforward, + dim_feedforward, + dropout_rate, + batchnorm, + activation=F.elu, + device=self.device, + ) + for _ in range(n_layers_mlp) + ] + ), + MLP( + final_input_dim, + final_input_dim // 2, + self.num_classes, + dropout_rate, + batchnorm, + activation=F.elu, + device=self.device, + ) + # This is what would be needed for a concat instead of addition of the skip connection + # MLP(dim_feedforward * 2, dim_feedforward, dim_feedforward, dropout, batchnorm) if (block_additional_mlp_layers > 0) else None, + ] + ) + + self.qgat = qMessagePassing(4, 4) + + def forward(self, inputs): + """ + Input: (l, b, d) + Output: (b, c, l, l) + """ + if isinstance(inputs, (list, tuple)): + ( + x, + rel_rec, + rel_send, + ) = inputs # get the actual state from the list of states, rel_rec and rel_send + else: # in case we are running torchinfo, rel_rec and rel_send are not provided + rel_rec = None + rel_send = None + x = inputs + + n_leaves, batch, feats = x.size() # get the representative sizes + assert x.device == self.device # check if we are running on the same device + + x = x.permute(1, 0, 2) # (b, l, f) + + def build_fully_connected(input): + batch, n_leaves, n_feats = input.size() + + max_nodes = np.sum(range(n_leaves+1)) + graph_list = [] + for data_batch in input: + + edges = [] + for level in range(n_leaves-1): + for n_level in range(level+1): + level_node_idx = n_level + (2**level-1) + max_level_node_idx = level + (2**level-1) + for n_other in range(max_level_node_idx+1, max_nodes): + edges.append([level_node_idx, n_other]) + + edges = t.Tensor(edges).long().permute(1,0) + embeddings = t.zeros(max_nodes, n_feats) + embeddings[-n_leaves:] = data_batch + # edges = t.combinations(t.Tensor(range(n_leaves)).long()).permute(1,0) + graph_batch = tg.data.Data(x=embeddings, edge_index=edges) + + graph_list.append(graph_batch) + + return tg.data.Batch().from_data_list(graph_list) + + x = build_fully_connected(x) + + vis = to_networkx(x) + plt.close() + plt.figure(1,figsize=(8,8)) + pos=nx.circular_layout(vis) + # pos = hierarchy_pos(vis, max(max(x.edge_index))) + nx.draw(vis, pos, cmap=plt.get_cmap('Set3'),node_size=70,linewidths=6) + plt.savefig("graph.png") + + + x.x = self.qgat(x.x, x.edge_index) # messages flow to uninitialized nodes in graph + + x = x.reshape(batch, n_leaves * feats) # flatten the last two dims + x = t.nn.functional.pad( + x, (0, (self.total_n_fsps * feats) - (n_leaves * feats)), mode="constant", value=0 + ) # pad up to the largest lcag size. subtract the current size to prevent unnecessary padding. + # note that x.size() is here n_leaves * feats + + # set the weights to zero which are either involved in a controlled operation or directly operating on qubits not relevant to the current graph (i.e. where the input was zero padded before) + # this is supposed to ensure, that the actual measurement of the circuit is not impacted by any random weights contributing to meaningless + # print(self.quantum_layer._weights) + with t.no_grad(): + for i, p in enumerate(self.var_params): + if int(p._name[-1]) > n_leaves or int(p._name[-3]) > n_leaves: + self.quantum_layer._weights[i] = 0.0 + # print(self.quantum_layer._weights) + + x = self.quantum_layer(x) + + + + def build_binary_permutation_indices(digits): + """ + Generate the binary permutation indices. + :param digits: + :return: + """ + n_permutations = (digits**2 - digits) // 2 + permutations_indices = [] + for i in range(2**digits): + if bin(i).count("1") == 2: + permutations_indices.append(i) + assert len(permutations_indices) == n_permutations + return permutations_indices + + def get_binary_shots(result, permutations_indices, out_shape): + """ + Generate the binary shots. + :param result: + :param permutations_indices: + :param out_shape: + :return: + """ + lcag = t.zeros(out_shape) + lcag = lcag.to(result.device) + for i in range(out_shape[0]): + lcag[i][np.tril_indices_from(lcag[0], k=-1)] = result[ + i, permutations_indices + ] + # lcag[:, np.tril_indices_from(lcag[:], k=-1)] = result[:, permutations_indices] + lcag = lcag + t.transpose(lcag, 1, 2) + return lcag + + x = get_binary_shots( + x, build_binary_permutation_indices(n_leaves), (batch, n_leaves, n_leaves) + ) + + x = x.reshape(batch, 1, n_leaves * n_leaves).repeat( + 1, self.num_classes, 1 + ) # copy the vqc output across n_classes dimensions and let the nn handle the decoding + x = x.permute(0, 2, 1) # (b, c, l, l) -> split the leaves + + skip = x if self.skip_block else None + x = self.block[0](x) # initial mlp + for seq_mlp in self.block[1]: + x = seq_mlp(x) + + x = t.cat((x, skip), dim=2) if self.skip_block else x # Skip connection + x = self.block[2](x) # (b, c, l, l) -> final mlp + + x = x.reshape(batch, n_leaves, n_leaves, self.num_classes) + x = x.permute(0, 3, 1, 2) # (b, c, l, l) + + x = t.div(x + t.transpose(x, 2, 3), 2) if self.symmetrize else x # (b, c, l, l) + + return x From c0a3b6195f1dedba4781f253f8c019bf7e244010 Mon Sep 17 00:00:00 2001 From: lc3267 Date: Fri, 14 Oct 2022 17:43:28 +0200 Subject: [PATCH 14/92] straight qgnn implementation --- conf/base/parameters/data_science.yml | 2 +- .../pipelines/data_science/nodes.py | 2 +- .../pipelines/data_science/qgnn.py | 76 ++++++++++++++++++- 3 files changed, 75 insertions(+), 5 deletions(-) diff --git a/conf/base/parameters/data_science.yml b/conf/base/parameters/data_science.yml index c8fe22d..d9c0e89 100644 --- a/conf/base/parameters/data_science.yml +++ b/conf/base/parameters/data_science.yml @@ -1,6 +1,6 @@ --- # General -model_sel: "gnn" # qmlp, qftgnn, qgnn +model_sel: "qgnn" # qmlp, qftgnn, qgnn post_model_sel: "pqgnn" # only for split training n_momenta: 4 diff --git a/src/partiqlegan/pipelines/data_science/nodes.py b/src/partiqlegan/pipelines/data_science/nodes.py index 5baeb94..0604986 100644 --- a/src/partiqlegan/pipelines/data_science/nodes.py +++ b/src/partiqlegan/pipelines/data_science/nodes.py @@ -13,7 +13,7 @@ from .instructor import Instructor from .gnn import gnn from .qftgnn import qftgnn -from .qgnn_new import qgnn +from .qgnn import qgnn from .dqgnn import dqgnn from .dgnn import dgnn from .pqgnn import pqgnn diff --git a/src/partiqlegan/pipelines/data_science/qgnn.py b/src/partiqlegan/pipelines/data_science/qgnn.py index fa709e9..3cc2986 100644 --- a/src/partiqlegan/pipelines/data_science/qgnn.py +++ b/src/partiqlegan/pipelines/data_science/qgnn.py @@ -1,9 +1,12 @@ import numpy as np +import time import torch as t from torch import nn import torch.nn.functional as F +import mlflow + from .utils import * import qiskit as q @@ -64,7 +67,7 @@ def forward(self, inputs): return self.batch_norm_layer(x) if self.batchnorm else x # (b, l, d) -class gnn(nn.Module): +class qgnn(nn.Module): """NRI model built off the official implementation. Contains adaptations to make it work with our use case, plus options for extra layers to give it some more oomph @@ -108,12 +111,13 @@ def __init__( add_rot_gates=True, **kwargs, ): - super(gnn, self).__init__() + super(qgnn, self).__init__() assert dim_feedforward % 2 == 0, "dim_feedforward must be an even number" self.num_classes = n_classes self.layers = n_layers_vqc # dim_feedforward//8 + self.total_n_fsps = n_fsps # used for padding in forward path self.factor = factor self.tokenize = tokenize self.symmetrize = symmetrize @@ -295,8 +299,11 @@ def interpreter(x): print(f"Set up embedding for {len(self.tokenize)} inputs") # Create first half of inital NRI half-block to go from leaves to edges + # initial_mlp = [ + # MLP(n_momenta, dim_feedforward, dim_feedforward, dropout_rate, batchnorm) + # ] initial_mlp = [ - MLP(n_momenta, dim_feedforward, dim_feedforward, dropout_rate, batchnorm) + MLP(n_fsps, dim_feedforward, dim_feedforward, dropout_rate, batchnorm) ] # Add any additional layers as per request initial_mlp.extend( @@ -528,6 +535,69 @@ def forward(self, inputs): x = t.cat([x[..., mask], *emb_x], dim=-1) # (b, l, d + embeddings) del emb_x + + + x = x.reshape(batch, n_leaves * feats) # flatten the last two dims + x = t.nn.functional.pad( + x, (0, (self.total_n_fsps * feats) - (n_leaves * feats)), mode="constant", value=0 + ) # pad up to the largest lcag size. subtract the current size to prevent unnecessary padding. + # note that x.size() is here n_leaves * feats + + # set the weights to zero which are either involved in a controlled operation or directly operating on qubits not relevant to the current graph (i.e. where the input was zero padded before) + # this is supposed to ensure, that the actual measurement of the circuit is not impacted by any random weights contributing to meaningless + # print(self.quantum_layer._weights) + with t.no_grad(): + for i, p in enumerate(self.var_params): + if int(p._name[-1]) > n_leaves or int(p._name[-3]) > n_leaves: + self.quantum_layer._weights[i] = 0.0 + # print(self.quantum_layer._weights) + + x = self.quantum_layer(x) + + + + def build_binary_permutation_indices(digits): + """ + Generate the binary permutation indices. + :param digits: + :return: + """ + n_permutations = (digits**2 - digits) // 2 + permutations_indices = [] + for i in range(2**digits): + if bin(i).count("1") == 2: + permutations_indices.append(i) + assert len(permutations_indices) == n_permutations + return permutations_indices + + def get_binary_shots(result, permutations_indices, out_shape): + """ + Generate the binary shots. + :param result: + :param permutations_indices: + :param out_shape: + :return: + """ + lcag = t.zeros(out_shape) + lcag = lcag.to(result.device) + for i in range(out_shape[0]): + lcag[i][np.tril_indices_from(lcag[0], k=-1)] = result[ + i, permutations_indices + ] + # lcag[:, np.tril_indices_from(lcag[:], k=-1)] = result[:, permutations_indices] + lcag = lcag + t.transpose(lcag, 1, 2) + return lcag + + x = get_binary_shots( + x, build_binary_permutation_indices(n_leaves), (batch, n_leaves, n_leaves) + ) + + + + + + + # Initial set of linear layers # (b, l, m) -> (b, l, d) x = self.initial_mlp( From 3102c1b7e300355e5c1aea1b7f9c0d7ba8fcabdd Mon Sep 17 00:00:00 2001 From: lc3267 Date: Sat, 15 Oct 2022 10:38:33 +0200 Subject: [PATCH 15/92] fixed sizing issue --- src/partiqlegan/pipelines/data_science/qgnn.py | 6 +++++- 1 file changed, 5 insertions(+), 1 deletion(-) diff --git a/src/partiqlegan/pipelines/data_science/qgnn.py b/src/partiqlegan/pipelines/data_science/qgnn.py index 3cc2986..8d6dfb9 100644 --- a/src/partiqlegan/pipelines/data_science/qgnn.py +++ b/src/partiqlegan/pipelines/data_science/qgnn.py @@ -588,8 +588,12 @@ def get_binary_shots(result, permutations_indices, out_shape): lcag = lcag + t.transpose(lcag, 1, 2) return lcag + # x = get_binary_shots( + # x, build_binary_permutation_indices(n_leaves), (batch, n_leaves, n_leaves) + # ) + x = get_binary_shots( - x, build_binary_permutation_indices(n_leaves), (batch, n_leaves, n_leaves) + x, build_binary_permutation_indices(self.total_n_fsps), (batch, self.total_n_fsps, self.total_n_fsps) ) From 9561fe4c451a7a4481b66318a5cb25830a6946f3 Mon Sep 17 00:00:00 2001 From: stroblme Date: Sat, 15 Oct 2022 10:39:35 +0200 Subject: [PATCH 16/92] increased validation and test size --- conf/base/parameters/data_generation.yml | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/conf/base/parameters/data_generation.yml b/conf/base/parameters/data_generation.yml index 2dd55ff..38b21ec 100644 --- a/conf/base/parameters/data_generation.yml +++ b/conf/base/parameters/data_generation.yml @@ -8,8 +8,8 @@ max_children: 3 # careful, this only controls how many children a single particl min_children: 2 isp_weight: 1.0 train_events_per_top: 100 -val_events_per_top: 20 -test_events_per_top: 10 +val_events_per_top: 30 +test_events_per_top: 15 seed: 1111 iso_retries: 0 pad_to: -1 From 691f115f5fad167e70ad6bbbb8f22e8daab896c9 Mon Sep 17 00:00:00 2001 From: lc3267 Date: Sat, 15 Oct 2022 12:29:51 +0200 Subject: [PATCH 17/92] optional padding dropout --- conf/base/parameters/data_science.yml | 1 + src/partiqlegan/pipelines/data_science/nodes.py | 2 ++ src/partiqlegan/pipelines/data_science/pipeline.py | 2 ++ src/partiqlegan/pipelines/data_science/qgnn.py | 13 ++++++++----- src/partiqlegan/pipelines/data_science/qmlp.py | 12 +++++++----- 5 files changed, 20 insertions(+), 10 deletions(-) diff --git a/conf/base/parameters/data_science.yml b/conf/base/parameters/data_science.yml index d9c0e89..4a9e686 100644 --- a/conf/base/parameters/data_science.yml +++ b/conf/base/parameters/data_science.yml @@ -48,6 +48,7 @@ add_rot_gates: True add_rot_gates_range: [True, False] n_layers_vqc: 3 n_layers_vqc_range: [1, 5, "linear"] +padding_dropout: False #TODO specify when available redis_host: "localhost" redis_port: 6379 diff --git a/src/partiqlegan/pipelines/data_science/nodes.py b/src/partiqlegan/pipelines/data_science/nodes.py index 0604986..8c8bc3c 100644 --- a/src/partiqlegan/pipelines/data_science/nodes.py +++ b/src/partiqlegan/pipelines/data_science/nodes.py @@ -221,6 +221,7 @@ def create_model( data_reupload: bool, add_rot_gates: bool, n_layers_vqc: bool, + padding_dropout: bool, pre_trained_model: DataParallel = None, **kwargs, ) -> DataParallel: @@ -246,6 +247,7 @@ def create_model( data_reupload=data_reupload, add_rot_gates=add_rot_gates, n_layers_vqc=n_layers_vqc, + padding_drouput=padding_dropout, pre_trained_model=pre_trained_model, **kwargs, ) diff --git a/src/partiqlegan/pipelines/data_science/pipeline.py b/src/partiqlegan/pipelines/data_science/pipeline.py index 1dfaa09..f33231b 100644 --- a/src/partiqlegan/pipelines/data_science/pipeline.py +++ b/src/partiqlegan/pipelines/data_science/pipeline.py @@ -62,6 +62,7 @@ def create_training_qgnn_pipeline(**kwargs) -> Pipeline: "data_reupload": "params:data_reupload", "add_rot_gates": "params:add_rot_gates", "n_layers_vqc": "params:n_layers_vqc", + "padding_dropout": "params:padding_dropout", "n_fsps": "n_fsps", "device": "params:device", }, @@ -205,6 +206,7 @@ def create_resume_training_qgnn_pipeline(**kwargs) -> Pipeline: "data_reupload": "params:data_reupload", "add_rot_gates": "params:add_rot_gates", "n_layers_vqc": "params:n_layers_vqc", + "padding_dropout": "params:padding_dropout", "n_fsps": "n_fsps", "device": "params:device", }, diff --git a/src/partiqlegan/pipelines/data_science/qgnn.py b/src/partiqlegan/pipelines/data_science/qgnn.py index 8d6dfb9..dee7f84 100644 --- a/src/partiqlegan/pipelines/data_science/qgnn.py +++ b/src/partiqlegan/pipelines/data_science/qgnn.py @@ -109,6 +109,7 @@ def __init__( device: str = "cpu", data_reupload=True, add_rot_gates=True, + padding_dropout=True, **kwargs, ): super(qgnn, self).__init__() @@ -125,6 +126,7 @@ def __init__( self.skip_block = skip_block self.skip_global = skip_global # self.max_leaves = max_leaves + self.padding_dropout = padding_dropout self.qi = q.utils.QuantumInstance( @@ -546,11 +548,12 @@ def forward(self, inputs): # set the weights to zero which are either involved in a controlled operation or directly operating on qubits not relevant to the current graph (i.e. where the input was zero padded before) # this is supposed to ensure, that the actual measurement of the circuit is not impacted by any random weights contributing to meaningless # print(self.quantum_layer._weights) - with t.no_grad(): - for i, p in enumerate(self.var_params): - if int(p._name[-1]) > n_leaves or int(p._name[-3]) > n_leaves: - self.quantum_layer._weights[i] = 0.0 - # print(self.quantum_layer._weights) + if self.padding_dropout: + with t.no_grad(): + for i, p in enumerate(self.var_params): + if int(p._name[-1]) > n_leaves or int(p._name[-3]) > n_leaves: + self.quantum_layer._weights[i] = 0.0 + # print(self.quantum_layer._weights) x = self.quantum_layer(x) diff --git a/src/partiqlegan/pipelines/data_science/qmlp.py b/src/partiqlegan/pipelines/data_science/qmlp.py index 74fc5f3..88e1970 100644 --- a/src/partiqlegan/pipelines/data_science/qmlp.py +++ b/src/partiqlegan/pipelines/data_science/qmlp.py @@ -117,6 +117,7 @@ def __init__( device: str = "cpu", data_reupload=True, add_rot_gates=True, + padding_drouput=True, **kwargs, ): super(qmlp, self).__init__() @@ -129,7 +130,7 @@ def __init__( self.symmetrize = symmetrize self.skip_block = skip_block # self.max_leaves = max_leaves - + self.padding_drouput = padding_drouput # self.initial_mlp = pre_trained_module.initial_mlp # self.blocks = pre_trained_module.blocks # self.final_mlp = pre_trained_module.final_mlp @@ -354,10 +355,11 @@ def forward(self, inputs): # set the weights to zero which are either involved in a controlled operation or directly operating on qubits not relevant to the current graph (i.e. where the input was zero padded before) # this is supposed to ensure, that the actual measurement of the circuit is not impacted by any random weights contributing to meaningless # print(self.quantum_layer._weights) - with t.no_grad(): - for i, p in enumerate(self.var_params): - if int(p._name[-1]) > n_leaves or int(p._name[-3]) > n_leaves: - self.quantum_layer._weights[i] = 0.0 + if self.padding_drouput: + with t.no_grad(): + for i, p in enumerate(self.var_params): + if int(p._name[-1]) > n_leaves or int(p._name[-3]) > n_leaves: + self.quantum_layer._weights[i] = 0.0 # print(self.quantum_layer._weights) x = self.quantum_layer(x) From 82721a733ca36c8474337875b3a53bd388975e9f Mon Sep 17 00:00:00 2001 From: lc3267 Date: Sat, 15 Oct 2022 12:30:55 +0200 Subject: [PATCH 18/92] fixed issues with dynamic number of leaves --- .../pipelines/data_science/qgnn.py | 22 +++++-------------- 1 file changed, 6 insertions(+), 16 deletions(-) diff --git a/src/partiqlegan/pipelines/data_science/qgnn.py b/src/partiqlegan/pipelines/data_science/qgnn.py index dee7f84..713f932 100644 --- a/src/partiqlegan/pipelines/data_science/qgnn.py +++ b/src/partiqlegan/pipelines/data_science/qgnn.py @@ -305,7 +305,7 @@ def interpreter(x): # MLP(n_momenta, dim_feedforward, dim_feedforward, dropout_rate, batchnorm) # ] initial_mlp = [ - MLP(n_fsps, dim_feedforward, dim_feedforward, dropout_rate, batchnorm) + MLP(1, dim_feedforward, dim_feedforward, dropout_rate, batchnorm) ] # Add any additional layers as per request initial_mlp.extend( @@ -565,12 +565,11 @@ def build_binary_permutation_indices(digits): :param digits: :return: """ - n_permutations = (digits**2 - digits) // 2 permutations_indices = [] for i in range(2**digits): - if bin(i).count("1") == 2: + if bin(i).count("1") == 1: permutations_indices.append(i) - assert len(permutations_indices) == n_permutations + assert len(permutations_indices) == digits return permutations_indices def get_binary_shots(result, permutations_indices, out_shape): @@ -584,26 +583,17 @@ def get_binary_shots(result, permutations_indices, out_shape): lcag = t.zeros(out_shape) lcag = lcag.to(result.device) for i in range(out_shape[0]): - lcag[i][np.tril_indices_from(lcag[0], k=-1)] = result[ + lcag[i] = result[ i, permutations_indices ] # lcag[:, np.tril_indices_from(lcag[:], k=-1)] = result[:, permutations_indices] - lcag = lcag + t.transpose(lcag, 1, 2) return lcag - # x = get_binary_shots( - # x, build_binary_permutation_indices(n_leaves), (batch, n_leaves, n_leaves) - # ) - x = get_binary_shots( - x, build_binary_permutation_indices(self.total_n_fsps), (batch, self.total_n_fsps, self.total_n_fsps) + x, build_binary_permutation_indices(n_leaves), (batch, n_leaves) ) - - - - - + x = x.reshape(batch, n_leaves, 1) # Initial set of linear layers # (b, l, m) -> (b, l, d) From 4cf8b6c9836fdae1b3b3e26d318fcf413985a591 Mon Sep 17 00:00:00 2001 From: lc3267 Date: Sat, 15 Oct 2022 14:37:10 +0200 Subject: [PATCH 19/92] spelling --- src/partiqlegan/pipelines/data_science/qmlp.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/src/partiqlegan/pipelines/data_science/qmlp.py b/src/partiqlegan/pipelines/data_science/qmlp.py index 88e1970..4e2f2d0 100644 --- a/src/partiqlegan/pipelines/data_science/qmlp.py +++ b/src/partiqlegan/pipelines/data_science/qmlp.py @@ -117,7 +117,7 @@ def __init__( device: str = "cpu", data_reupload=True, add_rot_gates=True, - padding_drouput=True, + padding_dropout=True, **kwargs, ): super(qmlp, self).__init__() @@ -130,7 +130,7 @@ def __init__( self.symmetrize = symmetrize self.skip_block = skip_block # self.max_leaves = max_leaves - self.padding_drouput = padding_drouput + self.padding_dropout = padding_dropout # self.initial_mlp = pre_trained_module.initial_mlp # self.blocks = pre_trained_module.blocks # self.final_mlp = pre_trained_module.final_mlp @@ -355,7 +355,7 @@ def forward(self, inputs): # set the weights to zero which are either involved in a controlled operation or directly operating on qubits not relevant to the current graph (i.e. where the input was zero padded before) # this is supposed to ensure, that the actual measurement of the circuit is not impacted by any random weights contributing to meaningless # print(self.quantum_layer._weights) - if self.padding_drouput: + if self.padding_dropout: with t.no_grad(): for i, p in enumerate(self.var_params): if int(p._name[-1]) > n_leaves or int(p._name[-3]) > n_leaves: From 12ed16a22a8cbdf2a92141f9df36472e9c37a652 Mon Sep 17 00:00:00 2001 From: lc3267 Date: Sat, 15 Oct 2022 14:43:38 +0200 Subject: [PATCH 20/92] fixed parameter naming --- src/partiqlegan/pipelines/data_science/nodes.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/partiqlegan/pipelines/data_science/nodes.py b/src/partiqlegan/pipelines/data_science/nodes.py index 8c8bc3c..477f1e1 100644 --- a/src/partiqlegan/pipelines/data_science/nodes.py +++ b/src/partiqlegan/pipelines/data_science/nodes.py @@ -247,7 +247,7 @@ def create_model( data_reupload=data_reupload, add_rot_gates=add_rot_gates, n_layers_vqc=n_layers_vqc, - padding_drouput=padding_dropout, + padding_dropout=padding_dropout, pre_trained_model=pre_trained_model, **kwargs, ) From c08afc2e7f0cfb3286bbdaeafe90abaa973a2d6a Mon Sep 17 00:00:00 2001 From: lc3267 Date: Sat, 15 Oct 2022 14:46:29 +0200 Subject: [PATCH 21/92] adapted from qgnn settings --- conf/base/parameters/data_science.yml | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/conf/base/parameters/data_science.yml b/conf/base/parameters/data_science.yml index fdef730..4a9e686 100644 --- a/conf/base/parameters/data_science.yml +++ b/conf/base/parameters/data_science.yml @@ -1,6 +1,6 @@ --- # General -model_sel: "qmlp" +model_sel: "qgnn" # qmlp, qftgnn, qgnn post_model_sel: "pqgnn" # only for split training n_momenta: 4 @@ -9,7 +9,7 @@ epochs: 20 normalize: "smartone" # one, smartone, zmuv normalize_individually: False zero_mean: False -dim_feedforward: 64 +dim_feedforward: 32 dim_feedforward_range: [4, 2048, "log"] batchnorm: True @@ -20,7 +20,7 @@ learning_rate_range: [1e-5, 1e-1, "log"] learning_rate_decay: 100 learning_rate_decay_range: [1, 1000, "log"] gamma: 0.5 -batch_size: 4 +batch_size: 8 batch_size_range: [1, 64, "log"] gradients_clamp: 1000 gradients_spreader: 1e-10 @@ -30,7 +30,7 @@ skip_global: True # activates skip connections on global scales # GNN n_blocks: 3 n_blocks_range: [1, 5, "linear"] -n_layers_mlp: 3 # initial mlp layers before the blocks +n_layers_mlp: 2 # initial mlp layers before the blocks n_layers_mlp_range: [1, 5, "linear"] n_additional_mlp_layers: 0 # additional layers within a block n_additional_mlp_layers_range: [1, 5, "linear"] From 55b36e639b5f6602d029a8d6342989a4349944f1 Mon Sep 17 00:00:00 2001 From: stroblme Date: Sat, 15 Oct 2022 22:04:30 +0200 Subject: [PATCH 22/92] increased ff size --- conf/base/parameters/data_science.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/conf/base/parameters/data_science.yml b/conf/base/parameters/data_science.yml index 4a9e686..f4638a5 100644 --- a/conf/base/parameters/data_science.yml +++ b/conf/base/parameters/data_science.yml @@ -9,7 +9,7 @@ epochs: 20 normalize: "smartone" # one, smartone, zmuv normalize_individually: False zero_mean: False -dim_feedforward: 32 +dim_feedforward: 64 dim_feedforward_range: [4, 2048, "log"] batchnorm: True From 8f3d67f6d87525134bc5ec897bc903ce407d61d9 Mon Sep 17 00:00:00 2001 From: lc3267 Date: Mon, 17 Oct 2022 12:34:11 +0200 Subject: [PATCH 23/92] sync mutually exclusive parameter from qgnn --- .../pipelines/data_science/nodes.py | 2 ++ .../pipelines/data_science/pipeline.py | 2 ++ .../pipelines/data_science/qgnn.py | 29 +++++++++++++++---- 3 files changed, 27 insertions(+), 6 deletions(-) diff --git a/src/partiqlegan/pipelines/data_science/nodes.py b/src/partiqlegan/pipelines/data_science/nodes.py index 477f1e1..0a682c9 100644 --- a/src/partiqlegan/pipelines/data_science/nodes.py +++ b/src/partiqlegan/pipelines/data_science/nodes.py @@ -222,6 +222,7 @@ def create_model( add_rot_gates: bool, n_layers_vqc: bool, padding_dropout: bool, + mutually_exclusive_meas: bool, pre_trained_model: DataParallel = None, **kwargs, ) -> DataParallel: @@ -248,6 +249,7 @@ def create_model( add_rot_gates=add_rot_gates, n_layers_vqc=n_layers_vqc, padding_dropout=padding_dropout, + mutually_exclusive_meas=mutually_exclusive_meas, pre_trained_model=pre_trained_model, **kwargs, ) diff --git a/src/partiqlegan/pipelines/data_science/pipeline.py b/src/partiqlegan/pipelines/data_science/pipeline.py index f33231b..f3baafe 100644 --- a/src/partiqlegan/pipelines/data_science/pipeline.py +++ b/src/partiqlegan/pipelines/data_science/pipeline.py @@ -63,6 +63,7 @@ def create_training_qgnn_pipeline(**kwargs) -> Pipeline: "add_rot_gates": "params:add_rot_gates", "n_layers_vqc": "params:n_layers_vqc", "padding_dropout": "params:padding_dropout", + "mutually_exclusive_meas": "params:mutually_exclusive_meas", "n_fsps": "n_fsps", "device": "params:device", }, @@ -207,6 +208,7 @@ def create_resume_training_qgnn_pipeline(**kwargs) -> Pipeline: "add_rot_gates": "params:add_rot_gates", "n_layers_vqc": "params:n_layers_vqc", "padding_dropout": "params:padding_dropout", + "mutually_exclusive_meas": "params:mutually_exclusive_meas", "n_fsps": "n_fsps", "device": "params:device", }, diff --git a/src/partiqlegan/pipelines/data_science/qgnn.py b/src/partiqlegan/pipelines/data_science/qgnn.py index 713f932..cf7f380 100644 --- a/src/partiqlegan/pipelines/data_science/qgnn.py +++ b/src/partiqlegan/pipelines/data_science/qgnn.py @@ -110,6 +110,7 @@ def __init__( data_reupload=True, add_rot_gates=True, padding_dropout=True, + mutually_exclusive_meas=True, **kwargs, ): super(qgnn, self).__init__() @@ -127,7 +128,7 @@ def __init__( self.skip_global = skip_global # self.max_leaves = max_leaves self.padding_dropout = padding_dropout - + self.mutually_exclusive_meas = mutually_exclusive_meas self.qi = q.utils.QuantumInstance( q.Aer.get_backend("aer_simulator_statevector") @@ -589,14 +590,30 @@ def get_binary_shots(result, permutations_indices, out_shape): # lcag[:, np.tril_indices_from(lcag[:], k=-1)] = result[:, permutations_indices] return lcag - x = get_binary_shots( - x, build_binary_permutation_indices(n_leaves), (batch, n_leaves) - ) + def get_all_shots(result, out_shape): + lcag = t.zeros(out_shape) + lcag = lcag.to(result.device) + for i in range(out_shape[0]): + lcag[i] = result[ + i, out_shape[1] + ] + return lcag + + if self.mutually_exclusive_meas: + x = get_binary_shots( + x, build_binary_permutation_indices(n_leaves), (batch, n_leaves) + ) + + x = x.reshape(batch, n_leaves, 1) + else: + x = get_all_shots( + x, (batch, 2**n_leaves-1) + ) - x = x.reshape(batch, n_leaves, 1) + x = x.reshape(batch, 2**n_leaves-1, 1) # Initial set of linear layers - # (b, l, m) -> (b, l, d) + # (b, l, 1) -> (b, l, d) x = self.initial_mlp( x ) # Series of 2-layer ELU net per node (b, l, d) optionally includes embeddings From c73f3618ae623d9fd6effe0632735bb97a9d368e Mon Sep 17 00:00:00 2001 From: lc3267 Date: Mon, 17 Oct 2022 12:35:24 +0200 Subject: [PATCH 24/92] updated reqs --- requirements.txt | 312 +++++++++++++++++++++++++++++++++++++++++++---- 1 file changed, 291 insertions(+), 21 deletions(-) diff --git a/requirements.txt b/requirements.txt index 7f00240..38e483c 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,21 +1,291 @@ -black -decaylanguage -httptools -kedro-mlflow -kedro-viz -libclang -matplotlib -phasespace -pip-chill -pylatexenc -python-dotenv -qiskit -qiskit-aer-gpu -qiskit-machine-learning -tensorflow-io-gcs-filesystem -torchdata -torchinfo -torchvision -tqdm -uvloop -zfit-physics +absl-py==1.0.0 +aiofiles==0.6.0 +alembic==1.8.0 +algopy==0.5.7 +anyconfig==0.10.1 +anyio==3.6.1 +arrow==1.2.2 +asgiref==3.5.2 +astunparse==1.6.3 +async-timeout==4.0.2 +attrs==20.3.0 +autopage==0.5.1 +autopep8==1.6.0 +backcall==0.2.0 +binaryornot==0.4.4 +black==22.6.0 +boost-histogram==1.3.1 +CacheControl==0.12.11 +cached-property==1.5.2 +cachetools==4.2.4 +cachy==0.3.0 +CD==1.1.0 +certifi==2021.5.30 +cffi==1.15.0 +chardet==4.0.0 +charset-normalizer==2.0.12 +cirq==0.14.1 +cirq-aqt==0.14.1 +cirq-core==0.14.1 +cirq-google==0.14.1 +cirq-ionq==0.14.1 +cirq-pasqal==0.14.1 +cirq-rigetti==0.14.1 +cirq-web==0.14.1 +clang==5.0 +cleo==1.0.0a5 +click==8.1.3 +cliff==4.0.0 +cloudpickle==2.0.0 +cmaes==0.8.2 +cmd2==2.4.2 +colorama==0.4.4 +colored==1.4.3 +colorlog==6.6.0 +cookiecutter==1.7.3 +crashtest==0.3.1 +cryptography==36.0.2 +cycler==0.11.0 +databricks-cli==0.17.0 +debugpy==1.6.0 +DecayLanguage==0.14.1 +decorator==5.1.1 +Deprecated==1.2.13 +dill==0.3.4 +distlib==0.3.6 +dm-tree==0.1.6 +docker==5.0.3 +dotmap==1.3.26 +duet==0.2.6 +dulwich==0.20.46 +dynaconf==3.1.7 +entrypoints==0.4 +fastapi==0.66.1 +fastdtw==0.3.4 +filelock==3.8.0 +Flask==2.1.2 +flatbuffers==1.12 +fonttools==4.33.3 +fsspec==2022.1.0 +gast==0.4.0 +gitdb==4.0.9 +GitPython==3.1.27 +google-api-core==1.21.0 +google-auth==1.18.0 +google-auth-oauthlib==0.4.6 +google-pasta==0.2.0 +googleapis-common-protos==1.52.0 +graphql-core==3.1.7 +graphviz==0.19.1 +greenlet==1.1.2 +grpcio==1.44.0 +gunicorn==20.1.0 +h11==0.9.0 +h5py==3.1.0 +hepunits==2.2.0 +hist==2.6.1 +histoprint==2.4.0 +html5lib==1.1 +httpcore==0.11.1 +httptools==0.4.0 +httpx==0.15.5 +idna==2.10 +iminuit==2.10.0 +importlib-metadata==4.11.2 +importlib-resources==5.4.0 +ipykernel==6.11.0 +ipyopt==0.11.0 +ipython==7.32.0 +iso8601==0.1.16 +itsdangerous==2.1.2 +jaraco.classes==3.2.3 +jedi==0.18.1 +jeepney==0.8.0 +Jinja2==3.0.3 +jinja2-time==0.2.0 +jmespath==0.10.0 +joblib==1.1.0 +jsonschema==4.16.0 +jupyter-client==6.1.12 +jupyter-core==4.9.2 +kedro==0.18.1 +kedro-mlflow==0.11.0 +kedro-viz==4.7.1 +keras==2.9.0 +Keras-Preprocessing==1.1.2 +keyring==23.9.3 +kiwisolver==1.4.2 +lark==0.11.3 +lark-parser==0.12.0 +libclang==14.0.1 +lockfile==0.12.2 +Mako==1.2.0 +Markdown==3.3.6 +MarkupSafe==2.1.0 +matplotlib==3.5.2 +matplotlib-inline==0.1.3 +mlflow==1.29.0 +more-itertools==8.14.0 +mpmath==1.2.1 +msgpack==0.6.2 +mypy-extensions==0.4.3 +nest-asyncio==1.5.5 +networkx==2.7.1 +nlopt==2.7.0 +ntlm-auth==1.5.0 +numdifftools==0.9.40 +numpy==1.22.4 +oauthlib==3.2.0 +opt-einsum==3.3.0 +optuna==3.0.0 +ordered-set==4.1.0 +packaging==21.3 +pandas==1.4.1 +parso==0.8.3 +particle==0.20.0 +pathspec==0.9.0 +patsy==0.5.2 +pbr==5.8.1 +pep517==0.12.0 +pexpect==4.8.0 +phasespace==1.6.0 +pickleshare==0.7.5 +Pillow==9.0.1 +pip-chill==1.0.1 +pip-tools==6.5.1 +pkginfo==1.8.3 +pkgutil_resolve_name==1.3.10 +platformdirs==2.5.2 +plotly==5.6.0 +pluggy==1.0.0 +plumbum==1.7.2 +ply==3.11 +poetry==1.2.1 +poetry-core==1.2.0 +poetry-plugin-export==1.0.7 +portalocker==2.5.1 +poyo==0.5.0 +prettytable==3.4.0 +prometheus-client==0.14.1 +prometheus-flask-exporter==0.20.2 +prompt-toolkit==3.0.28 +protobuf==3.17.3 +psutil==5.9.0 +ptyprocess==0.7.0 +py==1.11.0 +pyarrow==7.0.0 +pyasn1==0.4.8 +pyasn1-modules==0.2.8 +pycodestyle==2.8.0 +pycparser==2.21 +pydantic==1.8.2 +Pygments==2.11.2 +PyJWT==1.7.1 +pylatexenc==2.10 +pylev==1.4.0 +pyparsing==3.0.7 +pyperclip==1.8.2 +pyquil==3.0.1 +pyrsistent==0.18.1 +python-constraint==1.4.0 +python-dateutil==2.8.2 +python-dotenv==0.19.2 +python-json-logger==2.0.2 +python-multipart==0.0.5 +python-rapidjson==1.6 +python-slugify==6.1.1 +pytz==2021.3 +PyYAML==5.4.1 +pyzmq==22.3.0 +qcs-api-client==0.8.0 +qiskit==0.38.0 +qiskit-aer==0.11.0 +qiskit-ibmq-provider==0.19.2 +qiskit-machine-learning==0.4.0 +qiskit-terra==0.21.2 +querystring-parser==1.2.4 +redis==4.3.4 +requests==2.27.1 +requests-ntlm==1.1.0 +requests-oauthlib==1.3.1 +requests-toolbelt==0.9.1 +retry==0.9.2 +retrying==1.3.3 +retworkx==0.11.0 +rfc3339==6.2 +rfc3986==1.5.0 +rope==0.21.1 +rpcq==3.10.0 +rsa==4.8 +ruamel.yaml==0.17.21 +ruamel.yaml.clib==0.2.6 +scikit-learn==1.0.2 +scipy==1.8.0 +SecretStorage==3.3.3 +semver==2.13.0 +sentinel==0.3.0 +shellingham==1.5.0 +six==1.16.0 +smmap==5.0.0 +sniffio==1.2.0 +sortedcontainers==2.4.0 +SQLAlchemy==1.4.32 +sqlparse==0.4.2 +starlette==0.14.2 +statsmodels==0.13.2 +stevedore==3.5.0 +strawberry-graphql==0.93.23 +symengine==0.9.2 +sympy==1.8 +tabulate==0.8.9 +tenacity==8.0.1 +tensorboard==2.9.0 +tensorboard-data-server==0.6.1 +tensorboard-plugin-wit==1.8.1 +tensorflow==2.9.1 +tensorflow-addons==0.16.1 +tensorflow-estimator==2.9.0 +tensorflow-io-gcs-filesystem==0.26.0 +tensorflow-probability==0.17.0 +termcolor==1.1.0 +text-unidecode==1.3 +texttable==1.6.4 +tf-quant-finance==0.0.1.dev30 +threadpoolctl==3.1.0 +toml==0.10.2 +tomli==2.0.1 +tomlkit==0.11.5 +toposort==1.7 +torch==1.12.1+cpu +torch-cluster==1.6.0 +torch-geometric==2.1.0.post1 +torch-scatter==2.0.9 +torch-sparse==0.6.15 +torch-spline-conv==1.2.1 +torchaudio==0.12.1+cpu +torchinfo==1.7.1 +torchvision==0.13.1+cpu +tornado==6.1 +tqdm==4.64.0 +traitlets==5.1.1 +tweedledum==1.1.1 +typeguard==2.13.3 +typing-extensions==3.10.0.2 +uhi==0.3.1 +uproot==4.2.1 +urllib3==1.26.8 +uvicorn==0.17.6 +uvloop==0.16.0 +virtualenv==20.16.5 +watchgod==0.8.2 +wcwidth==0.2.5 +webencodings==0.5.1 +websocket-client==1.3.2 +websockets==10.3 +Werkzeug==2.0.3 +wrapt==1.12.1 +xxhash==3.0.0 +zfit==0.10.0 +zfit-interface==0.0.3 +zfit-physics==0.2.0 +zipp==3.7.0 From cd62cbbd95f192eaf17703eea159bd99462ce87c Mon Sep 17 00:00:00 2001 From: lc3267 Date: Mon, 17 Oct 2022 12:39:39 +0200 Subject: [PATCH 25/92] parameter to yml file --- conf/base/parameters/data_science.yml | 1 + 1 file changed, 1 insertion(+) diff --git a/conf/base/parameters/data_science.yml b/conf/base/parameters/data_science.yml index f4638a5..921b8e8 100644 --- a/conf/base/parameters/data_science.yml +++ b/conf/base/parameters/data_science.yml @@ -49,6 +49,7 @@ add_rot_gates_range: [True, False] n_layers_vqc: 3 n_layers_vqc_range: [1, 5, "linear"] padding_dropout: False +mutually_exclusive_meas: False #TODO specify when available redis_host: "localhost" redis_port: 6379 From fcef49ad26960d2010eb39d9bf589432ef733326 Mon Sep 17 00:00:00 2001 From: lc3267 Date: Mon, 17 Oct 2022 15:09:43 +0200 Subject: [PATCH 26/92] fixed shaping problem --- src/partiqlegan/pipelines/data_science/qgnn.py | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/src/partiqlegan/pipelines/data_science/qgnn.py b/src/partiqlegan/pipelines/data_science/qgnn.py index cf7f380..8c72912 100644 --- a/src/partiqlegan/pipelines/data_science/qgnn.py +++ b/src/partiqlegan/pipelines/data_science/qgnn.py @@ -610,7 +610,9 @@ def get_all_shots(result, out_shape): x, (batch, 2**n_leaves-1) ) - x = x.reshape(batch, 2**n_leaves-1, 1) + x = x.reshape(batch, 1, 2**n_leaves-1).repeat( + 1, n_leaves, 1 + ) # Initial set of linear layers # (b, l, 1) -> (b, l, d) From ec1a148d870c4342ec4731eff6d011111094e93f Mon Sep 17 00:00:00 2001 From: lc3267 Date: Mon, 17 Oct 2022 15:58:08 +0200 Subject: [PATCH 27/92] fixed sizes... again --- src/partiqlegan/pipelines/data_science/qgnn.py | 13 ++++++++++--- 1 file changed, 10 insertions(+), 3 deletions(-) diff --git a/src/partiqlegan/pipelines/data_science/qgnn.py b/src/partiqlegan/pipelines/data_science/qgnn.py index 8c72912..2320f51 100644 --- a/src/partiqlegan/pipelines/data_science/qgnn.py +++ b/src/partiqlegan/pipelines/data_science/qgnn.py @@ -305,9 +305,14 @@ def interpreter(x): # initial_mlp = [ # MLP(n_momenta, dim_feedforward, dim_feedforward, dropout_rate, batchnorm) # ] - initial_mlp = [ - MLP(1, dim_feedforward, dim_feedforward, dropout_rate, batchnorm) - ] + if self.mutually_exclusive_meas: + initial_mlp = [ + MLP(1, dim_feedforward, dim_feedforward, dropout_rate, batchnorm) + ] + else: + initial_mlp = [ + MLP(2**self.total_n_fsps-1, dim_feedforward, dim_feedforward, dropout_rate, batchnorm) + ] # Add any additional layers as per request initial_mlp.extend( [ @@ -613,6 +618,8 @@ def get_all_shots(result, out_shape): x = x.reshape(batch, 1, 2**n_leaves-1).repeat( 1, n_leaves, 1 ) + # x = x.permute(0, 2, 1) # (b, c, l, l) -> split the leaves + # Initial set of linear layers # (b, l, 1) -> (b, l, d) From 99da71dac347c5bf630526ac96bcf81be90e2cd5 Mon Sep 17 00:00:00 2001 From: stroblme Date: Mon, 17 Oct 2022 16:29:23 +0200 Subject: [PATCH 28/92] reduced ff dim --- conf/base/parameters/data_science.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/conf/base/parameters/data_science.yml b/conf/base/parameters/data_science.yml index 921b8e8..9e68909 100644 --- a/conf/base/parameters/data_science.yml +++ b/conf/base/parameters/data_science.yml @@ -9,7 +9,7 @@ epochs: 20 normalize: "smartone" # one, smartone, zmuv normalize_individually: False zero_mean: False -dim_feedforward: 64 +dim_feedforward: 32 dim_feedforward_range: [4, 2048, "log"] batchnorm: True From 57b87e656b9bb8cc68ce98fd3daed387059c2f4b Mon Sep 17 00:00:00 2001 From: stroblme Date: Mon, 17 Oct 2022 16:39:55 +0200 Subject: [PATCH 29/92] static number of fsps, using all qubit states --- src/partiqlegan/pipelines/data_science/qgnn.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/partiqlegan/pipelines/data_science/qgnn.py b/src/partiqlegan/pipelines/data_science/qgnn.py index 2320f51..122cee7 100644 --- a/src/partiqlegan/pipelines/data_science/qgnn.py +++ b/src/partiqlegan/pipelines/data_science/qgnn.py @@ -612,7 +612,7 @@ def get_all_shots(result, out_shape): x = x.reshape(batch, n_leaves, 1) else: x = get_all_shots( - x, (batch, 2**n_leaves-1) + x, (batch, 2**self.total_n_fsps-1) ) x = x.reshape(batch, 1, 2**n_leaves-1).repeat( From 6cd8da092464d544f6ad51090ea190b5fcf7d6b9 Mon Sep 17 00:00:00 2001 From: lc3267 Date: Mon, 17 Oct 2022 16:42:19 +0200 Subject: [PATCH 30/92] total n fsps in reshape --- src/partiqlegan/pipelines/data_science/qgnn.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/partiqlegan/pipelines/data_science/qgnn.py b/src/partiqlegan/pipelines/data_science/qgnn.py index 122cee7..78e1e46 100644 --- a/src/partiqlegan/pipelines/data_science/qgnn.py +++ b/src/partiqlegan/pipelines/data_science/qgnn.py @@ -615,7 +615,7 @@ def get_all_shots(result, out_shape): x, (batch, 2**self.total_n_fsps-1) ) - x = x.reshape(batch, 1, 2**n_leaves-1).repeat( + x = x.reshape(batch, 1, 2**self.total_n_fsps-1).repeat( 1, n_leaves, 1 ) # x = x.permute(0, 2, 1) # (b, c, l, l) -> split the leaves From a70ca0c9ac4ec40e42d9ab8fc03c4883129b3f72 Mon Sep 17 00:00:00 2001 From: lc3267 Date: Mon, 17 Oct 2022 23:03:00 +0200 Subject: [PATCH 31/92] reduced number of epochs and increased learning rate and disabled data reupload --- conf/base/parameters/data_science.yml | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/conf/base/parameters/data_science.yml b/conf/base/parameters/data_science.yml index 9e68909..d30c012 100644 --- a/conf/base/parameters/data_science.yml +++ b/conf/base/parameters/data_science.yml @@ -5,7 +5,7 @@ post_model_sel: "pqgnn" # only for split training n_momenta: 4 # Classical -epochs: 20 +epochs: 10 normalize: "smartone" # one, smartone, zmuv normalize_individually: False zero_mean: False @@ -15,7 +15,7 @@ batchnorm: True dropout_rate: 0.2 dropout_rate_range: [0.1, 1.0, "linear"] -learning_rate: 0.001 +learning_rate: 0.01 learning_rate_range: [1e-5, 1e-1, "log"] learning_rate_decay: 100 learning_rate_decay_range: [1, 1000, "log"] @@ -42,7 +42,7 @@ embedding_dims: -1 # no effect if tokenization not enabled symmetrize: True # Quantum -data_reupload: True +data_reupload: False data_reupload_range: [True, False] add_rot_gates: True add_rot_gates_range: [True, False] From b4df762d6c61877f3da89c9ababafdc51d8c48f8 Mon Sep 17 00:00:00 2001 From: stroblme Date: Tue, 18 Oct 2022 09:49:43 +0200 Subject: [PATCH 32/92] enabled data reupload again --- conf/base/parameters/data_science.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/conf/base/parameters/data_science.yml b/conf/base/parameters/data_science.yml index d30c012..a91012e 100644 --- a/conf/base/parameters/data_science.yml +++ b/conf/base/parameters/data_science.yml @@ -42,7 +42,7 @@ embedding_dims: -1 # no effect if tokenization not enabled symmetrize: True # Quantum -data_reupload: False +data_reupload: True data_reupload_range: [True, False] add_rot_gates: True add_rot_gates_range: [True, False] From 636088e075ebdf50bc3b4bd7c373f47fe21b28f5 Mon Sep 17 00:00:00 2001 From: stroblme Date: Tue, 18 Oct 2022 09:51:55 +0200 Subject: [PATCH 33/92] increased epochs to 20 --- conf/base/parameters/data_science.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/conf/base/parameters/data_science.yml b/conf/base/parameters/data_science.yml index a91012e..0d15a2a 100644 --- a/conf/base/parameters/data_science.yml +++ b/conf/base/parameters/data_science.yml @@ -5,7 +5,7 @@ post_model_sel: "pqgnn" # only for split training n_momenta: 4 # Classical -epochs: 10 +epochs: 20 normalize: "smartone" # one, smartone, zmuv normalize_individually: False zero_mean: False From 8f15721054f764a83b2167b5403bdac00807f91f Mon Sep 17 00:00:00 2001 From: stroblme Date: Tue, 18 Oct 2022 09:58:25 +0200 Subject: [PATCH 34/92] enabled padding dropout --- conf/base/parameters/data_science.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/conf/base/parameters/data_science.yml b/conf/base/parameters/data_science.yml index 0d15a2a..a292a35 100644 --- a/conf/base/parameters/data_science.yml +++ b/conf/base/parameters/data_science.yml @@ -48,7 +48,7 @@ add_rot_gates: True add_rot_gates_range: [True, False] n_layers_vqc: 3 n_layers_vqc_range: [1, 5, "linear"] -padding_dropout: False +padding_dropout: True mutually_exclusive_meas: False #TODO specify when available redis_host: "localhost" From 5e08ca24110c61713e42b704629c61b62b687c8f Mon Sep 17 00:00:00 2001 From: lc3267 Date: Tue, 18 Oct 2022 16:17:05 +0200 Subject: [PATCH 35/92] enabled validation-only-mode --- .vscode/launch.json | 10 ++ conf/base/parameters/data_science.yml | 3 + src/partiqlegan/pipeline_registry.py | 2 + .../pipelines/data_science/instructor.py | 4 +- .../pipelines/data_science/nodes.py | 5 +- .../pipelines/data_science/pipeline.py | 92 ++++++++++++++++++- 6 files changed, 109 insertions(+), 7 deletions(-) diff --git a/.vscode/launch.json b/.vscode/launch.json index 3fb1f1b..bec3777 100644 --- a/.vscode/launch.json +++ b/.vscode/launch.json @@ -85,6 +85,16 @@ // Any other arguments should be passed as a comma-seperated-list // e.g "args": ["run", "--pipeline", "pipeline_name"] }, + { + "name": "KR: - validation", + "type": "python", + "request": "launch", + "console": "integratedTerminal", + "module": "kedro", + "args": ["run", "--pipeline", "validation_qgnn_pipeline"] + // Any other arguments should be passed as a comma-seperated-list + // e.g "args": ["run", "--pipeline", "pipeline_name"] + }, { "name": "KR: - training Optuna", "type": "python", diff --git a/conf/base/parameters/data_science.yml b/conf/base/parameters/data_science.yml index a292a35..16c9fc3 100644 --- a/conf/base/parameters/data_science.yml +++ b/conf/base/parameters/data_science.yml @@ -3,6 +3,8 @@ model_sel: "qgnn" # qmlp, qftgnn, qgnn post_model_sel: "pqgnn" # only for split training n_momenta: 4 +default_modes: ["train", "val"] +validation_mode: ["val"] # Classical epochs: 20 @@ -50,6 +52,7 @@ n_layers_vqc: 3 n_layers_vqc_range: [1, 5, "linear"] padding_dropout: True mutually_exclusive_meas: False +backend: "aer_simulator_statevector" #TODO specify when available redis_host: "localhost" redis_port: 6379 diff --git a/src/partiqlegan/pipeline_registry.py b/src/partiqlegan/pipeline_registry.py index bfd1734..d82836f 100644 --- a/src/partiqlegan/pipeline_registry.py +++ b/src/partiqlegan/pipeline_registry.py @@ -23,6 +23,7 @@ def register_pipelines() -> Dict[str, Pipeline]: training_qgnn_pipeline = ds.create_training_qgnn_pipeline() resume_training_qgnn_pipeline = ds.create_resume_training_qgnn_pipeline() + validation_qgnn_pipeline = ds.create_validation_qgnn_pipeline() debug_training_qgnn_pipeline = ds.create_debug_training_qgnn_pipeline() debug_training_optuna_pipeline = ds.create_debug_training_optuna_pipeline() @@ -44,6 +45,7 @@ def register_pipelines() -> Dict[str, Pipeline]: # "data_processing_belleII_pipeline": data_processing_belleII_pipeline, "training_qgnn_pipeline": training_qgnn_pipeline, "resume_training_qgnn_pipeline": resume_training_qgnn_pipeline, + "validation_qgnn_pipeline": validation_qgnn_pipeline, "debug_training_qgnn_pipeline": debug_training_qgnn_pipeline, "debug_training_optuna_pipeline": debug_training_optuna_pipeline, # "split_training_qgnn_pipeline": split_training_qgnn_pipeline, diff --git a/src/partiqlegan/pipelines/data_science/instructor.py b/src/partiqlegan/pipelines/data_science/instructor.py index 7ebfa79..df74404 100644 --- a/src/partiqlegan/pipelines/data_science/instructor.py +++ b/src/partiqlegan/pipelines/data_science/instructor.py @@ -233,7 +233,7 @@ def __init__( ) self.detectAnomaly = detectAnomaly # TODO: introduce as parameter if helpful - def train(self, start_epoch=1): + def train(self, start_epoch=1, enabled_modes=["train", "val"]): if self.detectAnomaly: log.info(f"Anomaly detection enabled") t.autograd.set_detect_anomaly(True) @@ -248,7 +248,7 @@ def train(self, start_epoch=1): for epoch in range(start_epoch, 1 + self.epochs): logits_for_plotting = [] labels_for_plotting = [] - for mode in ["train", "val"]: + for mode in enabled_modes: data_batch = DataLoader( DataWrapper(self.data[mode], normalize=self.normalize, normalize_individually=self.normalize_individually, zero_mean=self.zero_mean), batch_size=self.batch_size, diff --git a/src/partiqlegan/pipelines/data_science/nodes.py b/src/partiqlegan/pipelines/data_science/nodes.py index 0a682c9..50391fe 100644 --- a/src/partiqlegan/pipelines/data_science/nodes.py +++ b/src/partiqlegan/pipelines/data_science/nodes.py @@ -313,10 +313,11 @@ def create_instructor( return {"instructor": instructor} -def train(instructor: Instructor, start_epoch=1): +def train(instructor: Instructor, start_epoch=1, enabled_modes=["train", "val"]): result = instructor.train( - start_epoch + start_epoch=start_epoch, + enabled_modes=enabled_modes ) # returns a dict of e.g. the model, checkpoints and the gradients return result diff --git a/src/partiqlegan/pipelines/data_science/pipeline.py b/src/partiqlegan/pipelines/data_science/pipeline.py index f3baafe..d78731b 100644 --- a/src/partiqlegan/pipelines/data_science/pipeline.py +++ b/src/partiqlegan/pipelines/data_science/pipeline.py @@ -98,7 +98,7 @@ def create_training_qgnn_pipeline(**kwargs) -> Pipeline: ), node( func=train, - inputs={"instructor": "instructor"}, + inputs={"instructor": "instructor", "enabled_modes":"params:default_modes"}, outputs={ "trained_model": "trained_quantum_model", "checkpoint": "checkpoint", @@ -245,7 +245,7 @@ def create_resume_training_qgnn_pipeline(**kwargs) -> Pipeline: ), node( func=train, - inputs={"instructor": "instructor", "start_epoch": "start_epoch"}, + inputs={"instructor": "instructor", "start_epoch": "start_epoch", "enabled_modes":"params:default_modes"}, outputs={ "trained_model": "trained_quantum_model", "checkpoint": "checkpoint_out", @@ -256,7 +256,93 @@ def create_resume_training_qgnn_pipeline(**kwargs) -> Pipeline: ] ) - +def create_validation_qgnn_pipeline(**kwargs) -> Pipeline: + return pipeline( + [ + *create_metadata_nodes(**kwargs), + node( + func=unpack_checkpoint, + inputs={ + "checkpoint": "checkpoint", + }, + outputs={ + "model_state_dict": "model_state_dict", + "optimizer_state_dict": "optimizer_state_dict", + "start_epoch": "start_epoch", + }, + name="unpack_checkpoint", + tags="split_run", + ), + node( + func=create_model, + inputs={ + "n_classes": "n_classes", + "n_momenta": "params:n_momenta", + "model_sel": "params:model_sel", + "n_blocks": "params:n_blocks", + "dim_feedforward": "params:dim_feedforward", + "n_layers_mlp": "params:n_layers_mlp", + "n_additional_mlp_layers": "params:n_additional_mlp_layers", + "n_final_mlp_layers": "params:n_final_mlp_layers", + "skip_block": "params:skip_block", + "skip_global": "params:skip_global", + "dropout_rate": "params:dropout_rate", + "factor": "params:factor", + "tokenize": "params:tokenize", + "embedding_dims": "params:embedding_dims", + "batchnorm": "params:batchnorm", + "symmetrize": "params:symmetrize", + "data_reupload": "params:data_reupload", + "add_rot_gates": "params:add_rot_gates", + "n_layers_vqc": "params:n_layers_vqc", + "padding_dropout": "params:padding_dropout", + "mutually_exclusive_meas": "params:mutually_exclusive_meas", + "n_fsps": "n_fsps", + "device": "params:device", + }, + outputs={"nri_model": "nri_model"}, + name="create_model", + ), + node( + func=create_instructor, + inputs={ + "model": "nri_model", + "dataset_lca_and_leaves": "dataset_lca_and_leaves", + "learning_rate": "params:learning_rate", + "learning_rate_decay": "params:learning_rate_decay", + "gamma": "params:gamma", + "batch_size": "params:batch_size", + "epochs": "params:epochs", + "normalize": "params:normalize", + "normalize_individually": "params:normalize_individually", + "zero_mean": "params:zero_mean", + "plot_mode": "params:plot_mode", + "plotting_rows": "params:plotting_rows", + "log_gradients": "params:log_gradients", + "device": "params:device", + "n_fsps": "n_fsps", + "n_classes": "n_classes", + "gradients_clamp": "params:gradients_clamp", + "gradients_spreader": "params:gradients_spreader", + "detectAnomaly": "params:detect_anomaly", + "model_state_dict": "model_state_dict", + "optimizer_state_dict": "optimizer_state_dict", + }, + outputs={"instructor": "instructor"}, + name="create_instructor", + ), + node( + func=train, + inputs={"instructor": "instructor", "enabled_modes":"params:validation_mode"}, + outputs={ + "trained_model": "trained_quantum_model", + "checkpoint": "checkpoint_out", + "gradients": "gradients", + }, + name="train_qgnn", + ), + ] + ) # additional pipeline just to add it as an exception in kedro def create_debug_training_qgnn_pipeline(**kwargs) -> Pipeline: return create_training_qgnn_pipeline(**kwargs) From ebc81a916622e48b3be41b7fb985018041ebb1e0 Mon Sep 17 00:00:00 2001 From: lc3267 Date: Tue, 18 Oct 2022 16:17:21 +0200 Subject: [PATCH 36/92] improved logging info --- src/partiqlegan/pipelines/data_science/instructor.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/partiqlegan/pipelines/data_science/instructor.py b/src/partiqlegan/pipelines/data_science/instructor.py index df74404..0eb95d9 100644 --- a/src/partiqlegan/pipelines/data_science/instructor.py +++ b/src/partiqlegan/pipelines/data_science/instructor.py @@ -238,7 +238,7 @@ def train(self, start_epoch=1, enabled_modes=["train", "val"]): log.info(f"Anomaly detection enabled") t.autograd.set_detect_anomaly(True) - log.info(f"Training started with a batch size of {self.batch_size}") + log.info(f"Starting loops from epoch {start_epoch} using modes {enabled_modes}.") result = None best_acc = 0 all_grads = [] From 85ef26ebb8100f719d4641b0652c9f2d4d255b3c Mon Sep 17 00:00:00 2001 From: lc3267 Date: Tue, 18 Oct 2022 16:22:21 +0200 Subject: [PATCH 37/92] added real backend option --- src/partiqlegan/pipelines/data_science/.gitignore | 1 + src/partiqlegan/pipelines/data_science/nodes.py | 2 ++ .../pipelines/data_science/pipeline.py | 3 +++ src/partiqlegan/pipelines/data_science/qgnn.py | 15 ++++++++++++++- 4 files changed, 20 insertions(+), 1 deletion(-) create mode 100644 src/partiqlegan/pipelines/data_science/.gitignore diff --git a/src/partiqlegan/pipelines/data_science/.gitignore b/src/partiqlegan/pipelines/data_science/.gitignore new file mode 100644 index 0000000..41688ee --- /dev/null +++ b/src/partiqlegan/pipelines/data_science/.gitignore @@ -0,0 +1 @@ +ibmq_access.py \ No newline at end of file diff --git a/src/partiqlegan/pipelines/data_science/nodes.py b/src/partiqlegan/pipelines/data_science/nodes.py index 50391fe..05206aa 100644 --- a/src/partiqlegan/pipelines/data_science/nodes.py +++ b/src/partiqlegan/pipelines/data_science/nodes.py @@ -223,6 +223,7 @@ def create_model( n_layers_vqc: bool, padding_dropout: bool, mutually_exclusive_meas: bool, + backend: str, pre_trained_model: DataParallel = None, **kwargs, ) -> DataParallel: @@ -250,6 +251,7 @@ def create_model( n_layers_vqc=n_layers_vqc, padding_dropout=padding_dropout, mutually_exclusive_meas=mutually_exclusive_meas, + backend=backend, pre_trained_model=pre_trained_model, **kwargs, ) diff --git a/src/partiqlegan/pipelines/data_science/pipeline.py b/src/partiqlegan/pipelines/data_science/pipeline.py index d78731b..6c76b46 100644 --- a/src/partiqlegan/pipelines/data_science/pipeline.py +++ b/src/partiqlegan/pipelines/data_science/pipeline.py @@ -64,6 +64,7 @@ def create_training_qgnn_pipeline(**kwargs) -> Pipeline: "n_layers_vqc": "params:n_layers_vqc", "padding_dropout": "params:padding_dropout", "mutually_exclusive_meas": "params:mutually_exclusive_meas", + "backend": "params:backend", "n_fsps": "n_fsps", "device": "params:device", }, @@ -209,6 +210,7 @@ def create_resume_training_qgnn_pipeline(**kwargs) -> Pipeline: "n_layers_vqc": "params:n_layers_vqc", "padding_dropout": "params:padding_dropout", "mutually_exclusive_meas": "params:mutually_exclusive_meas", + "backend": "params:backend", "n_fsps": "n_fsps", "device": "params:device", }, @@ -297,6 +299,7 @@ def create_validation_qgnn_pipeline(**kwargs) -> Pipeline: "n_layers_vqc": "params:n_layers_vqc", "padding_dropout": "params:padding_dropout", "mutually_exclusive_meas": "params:mutually_exclusive_meas", + "backend": "params:backend", "n_fsps": "n_fsps", "device": "params:device", }, diff --git a/src/partiqlegan/pipelines/data_science/qgnn.py b/src/partiqlegan/pipelines/data_science/qgnn.py index 78e1e46..1d3e2ea 100644 --- a/src/partiqlegan/pipelines/data_science/qgnn.py +++ b/src/partiqlegan/pipelines/data_science/qgnn.py @@ -111,6 +111,7 @@ def __init__( add_rot_gates=True, padding_dropout=True, mutually_exclusive_meas=True, + backend="aer_simulator_statevector", **kwargs, ): super(qgnn, self).__init__() @@ -130,8 +131,20 @@ def __init__( self.padding_dropout = padding_dropout self.mutually_exclusive_meas = mutually_exclusive_meas + if backend != "aer_simulator_statevector": + import ibmq_access + self.provider = q.IBMQ.enable_account( + token=ibmq_access.token, + hub=ibmq_access.hub, + group=ibmq_access.group, + project=ibmq_access.project, + ) + self.backend = self.provider.get_backend(backend) + else: + self.backend = q.Aer.get_backend(backend) + self.qi = q.utils.QuantumInstance( - q.Aer.get_backend("aer_simulator_statevector") + self.backend ) self.enc_params = [] From 2974bd3dd39e4e10984fc4a56e9be808ef561912 Mon Sep 17 00:00:00 2001 From: lc3267 Date: Tue, 18 Oct 2022 17:09:24 +0200 Subject: [PATCH 38/92] implemented backend loading --- src/partiqlegan/pipelines/data_science/qgnn.py | 14 +++++++++----- 1 file changed, 9 insertions(+), 5 deletions(-) diff --git a/src/partiqlegan/pipelines/data_science/qgnn.py b/src/partiqlegan/pipelines/data_science/qgnn.py index 1d3e2ea..4337590 100644 --- a/src/partiqlegan/pipelines/data_science/qgnn.py +++ b/src/partiqlegan/pipelines/data_science/qgnn.py @@ -132,15 +132,17 @@ def __init__( self.mutually_exclusive_meas = mutually_exclusive_meas if backend != "aer_simulator_statevector": - import ibmq_access + from .ibmq_access import token, hub, group, project + log.info(f"Searching for backend {backend} on IBMQ using token {token[:10]}****, hub {hub}, group {group} and project {project}") self.provider = q.IBMQ.enable_account( - token=ibmq_access.token, - hub=ibmq_access.hub, - group=ibmq_access.group, - project=ibmq_access.project, + token=token, + hub=hub, + group=group, + project=project, ) self.backend = self.provider.get_backend(backend) else: + log.info(f"Using simulator backend {backend}") self.backend = q.Aer.get_backend(backend) self.qi = q.utils.QuantumInstance( @@ -253,6 +255,8 @@ def circuit_builder(qc, n_qubits, n_hidden): log.info( f"Building Quantum Circuit with {self.layers} layers and {n_fsps} qubits" ) + # assert self.backend.configuration().num_qubits <= n_fsps + self.qc = q.QuantumCircuit(n_fsps) circuit_builder(self.qc, n_fsps, self.layers) From 08b3258eea65bd9e9976b90ac17b4d52127a3581 Mon Sep 17 00:00:00 2001 From: lc3267 Date: Tue, 18 Oct 2022 20:36:15 +0200 Subject: [PATCH 39/92] comment describing valid option --- conf/base/parameters/data_science.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/conf/base/parameters/data_science.yml b/conf/base/parameters/data_science.yml index 16c9fc3..4cf25fa 100644 --- a/conf/base/parameters/data_science.yml +++ b/conf/base/parameters/data_science.yml @@ -52,7 +52,7 @@ n_layers_vqc: 3 n_layers_vqc_range: [1, 5, "linear"] padding_dropout: True mutually_exclusive_meas: False -backend: "aer_simulator_statevector" +backend: "aer_simulator_statevector" # aer_simulator_statevector, perth #TODO specify when available redis_host: "localhost" redis_port: 6379 From e500f37a812676aa647045e50e9f1b4e141fa969 Mon Sep 17 00:00:00 2001 From: lc3267 Date: Tue, 18 Oct 2022 23:11:35 +0200 Subject: [PATCH 40/92] added improved measurement interpretation --- conf/base/parameters/data_science.yml | 3 +- .../pipelines/data_science/qgnn.py | 56 ++++++++++++++++--- 2 files changed, 51 insertions(+), 8 deletions(-) diff --git a/conf/base/parameters/data_science.yml b/conf/base/parameters/data_science.yml index 4cf25fa..0b3b648 100644 --- a/conf/base/parameters/data_science.yml +++ b/conf/base/parameters/data_science.yml @@ -7,7 +7,7 @@ default_modes: ["train", "val"] validation_mode: ["val"] # Classical -epochs: 20 +epochs: 10 normalize: "smartone" # one, smartone, zmuv normalize_individually: False zero_mean: False @@ -52,6 +52,7 @@ n_layers_vqc: 3 n_layers_vqc_range: [1, 5, "linear"] padding_dropout: True mutually_exclusive_meas: False +measurement: "entangled" # mutually_exclusive, all, entangled backend: "aer_simulator_statevector" # aer_simulator_statevector, perth #TODO specify when available redis_host: "localhost" diff --git a/src/partiqlegan/pipelines/data_science/qgnn.py b/src/partiqlegan/pipelines/data_science/qgnn.py index 4337590..e3221ef 100644 --- a/src/partiqlegan/pipelines/data_science/qgnn.py +++ b/src/partiqlegan/pipelines/data_science/qgnn.py @@ -327,8 +327,11 @@ def interpreter(x): MLP(1, dim_feedforward, dim_feedforward, dropout_rate, batchnorm) ] else: + # initial_mlp = [ + # MLP(2**self.total_n_fsps, dim_feedforward, dim_feedforward, dropout_rate, batchnorm) + # ] initial_mlp = [ - MLP(2**self.total_n_fsps-1, dim_feedforward, dim_feedforward, dropout_rate, batchnorm) + MLP(2**(self.total_n_fsps-1)+1, dim_feedforward, dim_feedforward, dropout_rate, batchnorm) ] # Add any additional layers as per request initial_mlp.extend( @@ -595,6 +598,23 @@ def build_binary_permutation_indices(digits): assert len(permutations_indices) == digits return permutations_indices + def build_related_permutation_indices(digits): + """ + Generate the binary permutation indices. + :param digits: + :return: + """ + permutations_indices = [] + for d in range(digits): + permutations_indices.append([]) + for i in range(0, 2**digits): + if bin(i).count("1") == 0: + permutations_indices[d].append(i) + elif len(bin(i))-2 >= d: + if bin(i)[-d-1] == "1": + permutations_indices[d].append(i) + return permutations_indices + def get_binary_shots(result, permutations_indices, out_shape): """ Generate the binary shots. @@ -617,10 +637,28 @@ def get_all_shots(result, out_shape): lcag = lcag.to(result.device) for i in range(out_shape[0]): lcag[i] = result[ - i, out_shape[1] + i, out_shape[1]-1 ] return lcag + def get_related_shots(result, permutations_indices, out_shape): + """ + Generate the binary shots. + :param result: + :param permutations_indices: + :param out_shape: + :return: + """ + lcag = t.zeros(out_shape) + lcag = lcag.to(result.device) + for i in range(out_shape[0]): # iterate batches + lcag[i] = t.stack([result[ + i, permutations_indices[j] + ] for j in range(out_shape[1])]) + # lcag[:, np.tril_indices_from(lcag[:], k=-1)] = result[:, permutations_indices] + return lcag + + if self.mutually_exclusive_meas: x = get_binary_shots( x, build_binary_permutation_indices(n_leaves), (batch, n_leaves) @@ -628,13 +666,17 @@ def get_all_shots(result, out_shape): x = x.reshape(batch, n_leaves, 1) else: - x = get_all_shots( - x, (batch, 2**self.total_n_fsps-1) - ) + # x = get_all_shots( + # x, (batch, 2**self.total_n_fsps) + # ) - x = x.reshape(batch, 1, 2**self.total_n_fsps-1).repeat( - 1, n_leaves, 1 + x = get_related_shots( + x, build_related_permutation_indices(self.total_n_fsps), (batch, n_leaves, 2**(self.total_n_fsps-1)+1) ) + + # x = x.reshape(batch, 1, 2**self.total_n_fsps).repeat( + # 1, n_leaves, 1 + # ) # x = x.permute(0, 2, 1) # (b, c, l, l) -> split the leaves From f759578d36639e9021ef1493ef42743897b76b1c Mon Sep 17 00:00:00 2001 From: lc3267 Date: Wed, 19 Oct 2022 11:16:26 +0200 Subject: [PATCH 41/92] propagated measurement setting as parameter --- conf/base/parameters/data_science.yml | 3 +- .../pipelines/data_science/nodes.py | 4 +- .../pipelines/data_science/pipeline.py | 6 +-- .../pipelines/data_science/qgnn.py | 41 ++++++++++--------- 4 files changed, 28 insertions(+), 26 deletions(-) diff --git a/conf/base/parameters/data_science.yml b/conf/base/parameters/data_science.yml index 0b3b648..29812de 100644 --- a/conf/base/parameters/data_science.yml +++ b/conf/base/parameters/data_science.yml @@ -51,8 +51,7 @@ add_rot_gates_range: [True, False] n_layers_vqc: 3 n_layers_vqc_range: [1, 5, "linear"] padding_dropout: True -mutually_exclusive_meas: False -measurement: "entangled" # mutually_exclusive, all, entangled +measurement: "all" # mutually_exclusive, all, entangled backend: "aer_simulator_statevector" # aer_simulator_statevector, perth #TODO specify when available redis_host: "localhost" diff --git a/src/partiqlegan/pipelines/data_science/nodes.py b/src/partiqlegan/pipelines/data_science/nodes.py index 05206aa..e46d110 100644 --- a/src/partiqlegan/pipelines/data_science/nodes.py +++ b/src/partiqlegan/pipelines/data_science/nodes.py @@ -222,7 +222,7 @@ def create_model( add_rot_gates: bool, n_layers_vqc: bool, padding_dropout: bool, - mutually_exclusive_meas: bool, + measurement: str, backend: str, pre_trained_model: DataParallel = None, **kwargs, @@ -250,7 +250,7 @@ def create_model( add_rot_gates=add_rot_gates, n_layers_vqc=n_layers_vqc, padding_dropout=padding_dropout, - mutually_exclusive_meas=mutually_exclusive_meas, + measurement=measurement, backend=backend, pre_trained_model=pre_trained_model, **kwargs, diff --git a/src/partiqlegan/pipelines/data_science/pipeline.py b/src/partiqlegan/pipelines/data_science/pipeline.py index 6c76b46..59a5c0f 100644 --- a/src/partiqlegan/pipelines/data_science/pipeline.py +++ b/src/partiqlegan/pipelines/data_science/pipeline.py @@ -63,7 +63,7 @@ def create_training_qgnn_pipeline(**kwargs) -> Pipeline: "add_rot_gates": "params:add_rot_gates", "n_layers_vqc": "params:n_layers_vqc", "padding_dropout": "params:padding_dropout", - "mutually_exclusive_meas": "params:mutually_exclusive_meas", + "measurement": "params:measurement", "backend": "params:backend", "n_fsps": "n_fsps", "device": "params:device", @@ -209,7 +209,7 @@ def create_resume_training_qgnn_pipeline(**kwargs) -> Pipeline: "add_rot_gates": "params:add_rot_gates", "n_layers_vqc": "params:n_layers_vqc", "padding_dropout": "params:padding_dropout", - "mutually_exclusive_meas": "params:mutually_exclusive_meas", + "measurement": "params:measurement", "backend": "params:backend", "n_fsps": "n_fsps", "device": "params:device", @@ -298,7 +298,7 @@ def create_validation_qgnn_pipeline(**kwargs) -> Pipeline: "add_rot_gates": "params:add_rot_gates", "n_layers_vqc": "params:n_layers_vqc", "padding_dropout": "params:padding_dropout", - "mutually_exclusive_meas": "params:mutually_exclusive_meas", + "measurement": "params:measurement", "backend": "params:backend", "n_fsps": "n_fsps", "device": "params:device", diff --git a/src/partiqlegan/pipelines/data_science/qgnn.py b/src/partiqlegan/pipelines/data_science/qgnn.py index e3221ef..f54b58c 100644 --- a/src/partiqlegan/pipelines/data_science/qgnn.py +++ b/src/partiqlegan/pipelines/data_science/qgnn.py @@ -110,7 +110,7 @@ def __init__( data_reupload=True, add_rot_gates=True, padding_dropout=True, - mutually_exclusive_meas=True, + measurement="entangled", backend="aer_simulator_statevector", **kwargs, ): @@ -129,7 +129,7 @@ def __init__( self.skip_global = skip_global # self.max_leaves = max_leaves self.padding_dropout = padding_dropout - self.mutually_exclusive_meas = mutually_exclusive_meas + self.measurement = measurement if backend != "aer_simulator_statevector": from .ibmq_access import token, hub, group, project @@ -322,17 +322,20 @@ def interpreter(x): # initial_mlp = [ # MLP(n_momenta, dim_feedforward, dim_feedforward, dropout_rate, batchnorm) # ] - if self.mutually_exclusive_meas: + if self.measurement == "mutually_exclusive_meas": initial_mlp = [ MLP(1, dim_feedforward, dim_feedforward, dropout_rate, batchnorm) ] - else: - # initial_mlp = [ - # MLP(2**self.total_n_fsps, dim_feedforward, dim_feedforward, dropout_rate, batchnorm) - # ] + elif self.measurement == "all": + initial_mlp = [ + MLP(2**self.total_n_fsps, dim_feedforward, dim_feedforward, dropout_rate, batchnorm) + ] + elif self.measurement == "entangled": initial_mlp = [ MLP(2**(self.total_n_fsps-1)+1, dim_feedforward, dim_feedforward, dropout_rate, batchnorm) ] + else: + raise ValueError("Invalid measurement specified") # Add any additional layers as per request initial_mlp.extend( [ @@ -659,27 +662,27 @@ def get_related_shots(result, permutations_indices, out_shape): return lcag - if self.mutually_exclusive_meas: + if self.measurement == "mutually_exclusive_meas": x = get_binary_shots( x, build_binary_permutation_indices(n_leaves), (batch, n_leaves) ) x = x.reshape(batch, n_leaves, 1) - else: - # x = get_all_shots( - # x, (batch, 2**self.total_n_fsps) - # ) + elif self.measurement == "all": + x = get_all_shots( + x, (batch, 2**self.total_n_fsps) + ) + x = x.reshape(batch, 1, 2**self.total_n_fsps).repeat( + 1, n_leaves, 1 + ) + # x = x.permute(0, 2, 1) # (b, c, l, l) -> split the leaves + elif self.measurement == "entangled": x = get_related_shots( x, build_related_permutation_indices(self.total_n_fsps), (batch, n_leaves, 2**(self.total_n_fsps-1)+1) ) - - # x = x.reshape(batch, 1, 2**self.total_n_fsps).repeat( - # 1, n_leaves, 1 - # ) - # x = x.permute(0, 2, 1) # (b, c, l, l) -> split the leaves - - + else: + raise ValueError("Invalid measurement specified") # Initial set of linear layers # (b, l, 1) -> (b, l, d) x = self.initial_mlp( From 3a4f595b9a4d483f89910764fed012b27aa9a315 Mon Sep 17 00:00:00 2001 From: lc3267 Date: Wed, 19 Oct 2022 12:04:01 +0200 Subject: [PATCH 42/92] added circuit_19 as pqc --- .../pipelines/data_science/qgnn.py | 34 ++++++++++++++++++- 1 file changed, 33 insertions(+), 1 deletion(-) diff --git a/src/partiqlegan/pipelines/data_science/qgnn.py b/src/partiqlegan/pipelines/data_science/qgnn.py index f54b58c..9699d6b 100644 --- a/src/partiqlegan/pipelines/data_science/qgnn.py +++ b/src/partiqlegan/pipelines/data_science/qgnn.py @@ -110,6 +110,7 @@ def __init__( data_reupload=True, add_rot_gates=True, padding_dropout=True, + predefined_vqc="", measurement="entangled", backend="aer_simulator_statevector", **kwargs, @@ -130,6 +131,7 @@ def __init__( # self.max_leaves = max_leaves self.padding_dropout = padding_dropout self.measurement = measurement + self.predefined_vqc = predefined_vqc if backend != "aer_simulator_statevector": from .ibmq_access import token, hub, group, project @@ -243,13 +245,43 @@ def variational(qc, n_qubits, identifier): f"{identifier}_crz_{n_qubits - i - 1}_{n_qubits - i}", ) + def build_circuit_19(qc, n_qubits, identifier): + for i in range(n_qubits): + qc.rx( + q.circuit.Parameter(f"{identifier}_rx_0_{i}"), + i, + f"{identifier}_rx_0_{i}", + ) + qc.rz(q.circuit.Parameter(f"{identifier}_rz_1_{i}"), i) + + for i in range(n_qubits - 1): + if i == 0: + qc.crx( + q.circuit.Parameter(f"{identifier}_crx_{i+1}_{i}"), + i, + n_qubits - 1, + f"{identifier}_crx_{i+1}_{i}", + ) + else: + qc.crx( + q.circuit.Parameter(f"{identifier}_crx_{i+1}_{i}"), + n_qubits - i, + n_qubits - i - 1, + f"{identifier}_crx_{i+1}_{i}", + ) + def circuit_builder(qc, n_qubits, n_hidden): enc_params = gen_encoding_params(n_qubits, f"enc") for i in range(n_hidden): if data_reupload or i == 0: encoding(qc, n_qubits, enc_params, f"enc_{i}") qc.barrier() - variational(qc, n_qubits, f"var_{i}") + if self.predefined_vqc == "": + variational(qc, n_qubits, f"var_{i}") + elif self.predefined_vqc == "circuit_19": + build_circuit_19(qc, n_qubits, f"var_{i}") + else: + raise ValueError("Invalid circuit specified") qc.barrier() log.info( From de6c753739cb58bedd5166ca9451e40527164902 Mon Sep 17 00:00:00 2001 From: lc3267 Date: Wed, 19 Oct 2022 12:04:10 +0200 Subject: [PATCH 43/92] predefined pqc option --- conf/base/parameters/data_science.yml | 1 + src/partiqlegan/pipelines/data_science/nodes.py | 2 ++ src/partiqlegan/pipelines/data_science/pipeline.py | 3 +++ 3 files changed, 6 insertions(+) diff --git a/conf/base/parameters/data_science.yml b/conf/base/parameters/data_science.yml index 29812de..43f4079 100644 --- a/conf/base/parameters/data_science.yml +++ b/conf/base/parameters/data_science.yml @@ -51,6 +51,7 @@ add_rot_gates_range: [True, False] n_layers_vqc: 3 n_layers_vqc_range: [1, 5, "linear"] padding_dropout: True +predefined_vqc: "circuit_19" # "", "circuit_10", .. tba. measurement: "all" # mutually_exclusive, all, entangled backend: "aer_simulator_statevector" # aer_simulator_statevector, perth #TODO specify when available diff --git a/src/partiqlegan/pipelines/data_science/nodes.py b/src/partiqlegan/pipelines/data_science/nodes.py index e46d110..9e363a9 100644 --- a/src/partiqlegan/pipelines/data_science/nodes.py +++ b/src/partiqlegan/pipelines/data_science/nodes.py @@ -222,6 +222,7 @@ def create_model( add_rot_gates: bool, n_layers_vqc: bool, padding_dropout: bool, + predefined_vqc: str, measurement: str, backend: str, pre_trained_model: DataParallel = None, @@ -250,6 +251,7 @@ def create_model( add_rot_gates=add_rot_gates, n_layers_vqc=n_layers_vqc, padding_dropout=padding_dropout, + predefined_vqc=predefined_vqc, measurement=measurement, backend=backend, pre_trained_model=pre_trained_model, diff --git a/src/partiqlegan/pipelines/data_science/pipeline.py b/src/partiqlegan/pipelines/data_science/pipeline.py index 59a5c0f..98f7b06 100644 --- a/src/partiqlegan/pipelines/data_science/pipeline.py +++ b/src/partiqlegan/pipelines/data_science/pipeline.py @@ -63,6 +63,7 @@ def create_training_qgnn_pipeline(**kwargs) -> Pipeline: "add_rot_gates": "params:add_rot_gates", "n_layers_vqc": "params:n_layers_vqc", "padding_dropout": "params:padding_dropout", + "predefined_vqc": "params:predefined_vqc", "measurement": "params:measurement", "backend": "params:backend", "n_fsps": "n_fsps", @@ -209,6 +210,7 @@ def create_resume_training_qgnn_pipeline(**kwargs) -> Pipeline: "add_rot_gates": "params:add_rot_gates", "n_layers_vqc": "params:n_layers_vqc", "padding_dropout": "params:padding_dropout", + "predefined_vqc": "params:predefined_vqc", "measurement": "params:measurement", "backend": "params:backend", "n_fsps": "n_fsps", @@ -298,6 +300,7 @@ def create_validation_qgnn_pipeline(**kwargs) -> Pipeline: "add_rot_gates": "params:add_rot_gates", "n_layers_vqc": "params:n_layers_vqc", "padding_dropout": "params:padding_dropout", + "predefined_vqc": "params:predefined_vqc", "measurement": "params:measurement", "backend": "params:backend", "n_fsps": "n_fsps", From 99e213dd163f80462a71fafeeb3fb24e9a979089 Mon Sep 17 00:00:00 2001 From: lc3267 Date: Wed, 19 Oct 2022 12:04:44 +0200 Subject: [PATCH 44/92] back to entangled --- conf/base/parameters/data_science.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/conf/base/parameters/data_science.yml b/conf/base/parameters/data_science.yml index 43f4079..afca398 100644 --- a/conf/base/parameters/data_science.yml +++ b/conf/base/parameters/data_science.yml @@ -52,7 +52,7 @@ n_layers_vqc: 3 n_layers_vqc_range: [1, 5, "linear"] padding_dropout: True predefined_vqc: "circuit_19" # "", "circuit_10", .. tba. -measurement: "all" # mutually_exclusive, all, entangled +measurement: "entangled" # mutually_exclusive, all, entangled backend: "aer_simulator_statevector" # aer_simulator_statevector, perth #TODO specify when available redis_host: "localhost" From 6bac45d03b60d75580c0cad4407cda2da6496a09 Mon Sep 17 00:00:00 2001 From: lc3267 Date: Wed, 19 Oct 2022 22:32:04 +0200 Subject: [PATCH 45/92] tuned dff and lrd --- conf/base/parameters/data_science.yml | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/conf/base/parameters/data_science.yml b/conf/base/parameters/data_science.yml index afca398..ba4ff05 100644 --- a/conf/base/parameters/data_science.yml +++ b/conf/base/parameters/data_science.yml @@ -11,7 +11,7 @@ epochs: 10 normalize: "smartone" # one, smartone, zmuv normalize_individually: False zero_mean: False -dim_feedforward: 32 +dim_feedforward: 64 dim_feedforward_range: [4, 2048, "log"] batchnorm: True @@ -19,7 +19,7 @@ dropout_rate: 0.2 dropout_rate_range: [0.1, 1.0, "linear"] learning_rate: 0.01 learning_rate_range: [1e-5, 1e-1, "log"] -learning_rate_decay: 100 +learning_rate_decay: 200 learning_rate_decay_range: [1, 1000, "log"] gamma: 0.5 batch_size: 8 From 7a31b5108c09d10a9296d66b5dc32e02af3b1f48 Mon Sep 17 00:00:00 2001 From: lc3267 Date: Wed, 19 Oct 2022 22:32:30 +0200 Subject: [PATCH 46/92] increased epochs --- conf/base/parameters/data_science.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/conf/base/parameters/data_science.yml b/conf/base/parameters/data_science.yml index ba4ff05..a4f6e2a 100644 --- a/conf/base/parameters/data_science.yml +++ b/conf/base/parameters/data_science.yml @@ -7,7 +7,7 @@ default_modes: ["train", "val"] validation_mode: ["val"] # Classical -epochs: 10 +epochs: 20 normalize: "smartone" # one, smartone, zmuv normalize_individually: False zero_mean: False From 8f4f66fbce193ccce50b7a1488d0ad2e307a5b6f Mon Sep 17 00:00:00 2001 From: lc3267 Date: Thu, 20 Oct 2022 10:13:40 +0200 Subject: [PATCH 47/92] adapted to settings from run ecc74ac0312340b48d157667da192a45 --- conf/base/parameters/data_science.yml | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/conf/base/parameters/data_science.yml b/conf/base/parameters/data_science.yml index a4f6e2a..be2f2da 100644 --- a/conf/base/parameters/data_science.yml +++ b/conf/base/parameters/data_science.yml @@ -7,11 +7,11 @@ default_modes: ["train", "val"] validation_mode: ["val"] # Classical -epochs: 20 +epochs: 10 normalize: "smartone" # one, smartone, zmuv normalize_individually: False zero_mean: False -dim_feedforward: 64 +dim_feedforward: 32 dim_feedforward_range: [4, 2048, "log"] batchnorm: True @@ -50,7 +50,7 @@ add_rot_gates: True add_rot_gates_range: [True, False] n_layers_vqc: 3 n_layers_vqc_range: [1, 5, "linear"] -padding_dropout: True +padding_dropout: False predefined_vqc: "circuit_19" # "", "circuit_10", .. tba. measurement: "entangled" # mutually_exclusive, all, entangled backend: "aer_simulator_statevector" # aer_simulator_statevector, perth From 28a6847235cdd86a132589c29ed46fa6c865d326 Mon Sep 17 00:00:00 2001 From: lc3267 Date: Thu, 20 Oct 2022 10:22:37 +0200 Subject: [PATCH 48/92] enabled gradient logging --- conf/base/parameters/data_science.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/conf/base/parameters/data_science.yml b/conf/base/parameters/data_science.yml index be2f2da..1140216 100644 --- a/conf/base/parameters/data_science.yml +++ b/conf/base/parameters/data_science.yml @@ -67,5 +67,5 @@ device: 'cpu' # anything but 'cpu' to use cuda devices instead # MLFLOW plot_mode: "val" plotting_rows: 4 -log_gradients: False # set false when using models where the quantum layer is not the first one +log_gradients: True # set false when using models where the quantum layer is not the first one git_hash_identifier: "git_hash" \ No newline at end of file From 4578894c09989a569746c42e00111ba2a05ba756 Mon Sep 17 00:00:00 2001 From: stroblme Date: Thu, 20 Oct 2022 10:23:51 +0200 Subject: [PATCH 49/92] reduced learning rate and back to mutually exclusive meas --- conf/base/parameters/data_science.yml | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/conf/base/parameters/data_science.yml b/conf/base/parameters/data_science.yml index be2f2da..0c12246 100644 --- a/conf/base/parameters/data_science.yml +++ b/conf/base/parameters/data_science.yml @@ -17,9 +17,9 @@ batchnorm: True dropout_rate: 0.2 dropout_rate_range: [0.1, 1.0, "linear"] -learning_rate: 0.01 +learning_rate: 0.001 learning_rate_range: [1e-5, 1e-1, "log"] -learning_rate_decay: 200 +learning_rate_decay: 100 learning_rate_decay_range: [1, 1000, "log"] gamma: 0.5 batch_size: 8 @@ -52,7 +52,7 @@ n_layers_vqc: 3 n_layers_vqc_range: [1, 5, "linear"] padding_dropout: False predefined_vqc: "circuit_19" # "", "circuit_10", .. tba. -measurement: "entangled" # mutually_exclusive, all, entangled +measurement: "mutually_exclusive" # mutually_exclusive, all, entangled backend: "aer_simulator_statevector" # aer_simulator_statevector, perth #TODO specify when available redis_host: "localhost" @@ -67,5 +67,5 @@ device: 'cpu' # anything but 'cpu' to use cuda devices instead # MLFLOW plot_mode: "val" plotting_rows: 4 -log_gradients: False # set false when using models where the quantum layer is not the first one +log_gradients: True # set false when using models where the quantum layer is not the first one git_hash_identifier: "git_hash" \ No newline at end of file From 76118f477551ed385300c9eca3220930f5b96aeb Mon Sep 17 00:00:00 2001 From: stroblme Date: Thu, 20 Oct 2022 10:33:37 +0200 Subject: [PATCH 50/92] fixed meas naming --- src/partiqlegan/pipelines/data_science/qgnn.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/src/partiqlegan/pipelines/data_science/qgnn.py b/src/partiqlegan/pipelines/data_science/qgnn.py index 9699d6b..55222b3 100644 --- a/src/partiqlegan/pipelines/data_science/qgnn.py +++ b/src/partiqlegan/pipelines/data_science/qgnn.py @@ -354,7 +354,7 @@ def interpreter(x): # initial_mlp = [ # MLP(n_momenta, dim_feedforward, dim_feedforward, dropout_rate, batchnorm) # ] - if self.measurement == "mutually_exclusive_meas": + if self.measurement == "mutually_exclusive": initial_mlp = [ MLP(1, dim_feedforward, dim_feedforward, dropout_rate, batchnorm) ] @@ -694,7 +694,7 @@ def get_related_shots(result, permutations_indices, out_shape): return lcag - if self.measurement == "mutually_exclusive_meas": + if self.measurement == "mutually_exclusive": x = get_binary_shots( x, build_binary_permutation_indices(n_leaves), (batch, n_leaves) ) From ecea46d3357f765d92a0502fddd4e320cb302132 Mon Sep 17 00:00:00 2001 From: lc3267 Date: Thu, 20 Oct 2022 15:03:41 +0200 Subject: [PATCH 51/92] restricted epochs to 1 if only validation --- src/partiqlegan/pipelines/data_science/instructor.py | 3 +++ 1 file changed, 3 insertions(+) diff --git a/src/partiqlegan/pipelines/data_science/instructor.py b/src/partiqlegan/pipelines/data_science/instructor.py index 0eb95d9..5c20664 100644 --- a/src/partiqlegan/pipelines/data_science/instructor.py +++ b/src/partiqlegan/pipelines/data_science/instructor.py @@ -244,6 +244,9 @@ def train(self, start_epoch=1, enabled_modes=["train", "val"]): all_grads = [] checkpoint = None + if enabled_modes == ["val"]: + self.epochs = 1 + try: # catch things like gradient nan exceptions for epoch in range(start_epoch, 1 + self.epochs): logits_for_plotting = [] From a6085382e0e8a3b854175a25696ce3c3007e346b Mon Sep 17 00:00:00 2001 From: lc3267 Date: Thu, 20 Oct 2022 15:10:59 +0200 Subject: [PATCH 52/92] perth backend and adapted config to 3723457a837e4df9a5a2caef6a0574a8 --- conf/base/parameters/data_science.yml | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/conf/base/parameters/data_science.yml b/conf/base/parameters/data_science.yml index 0c12246..0681bfd 100644 --- a/conf/base/parameters/data_science.yml +++ b/conf/base/parameters/data_science.yml @@ -17,9 +17,9 @@ batchnorm: True dropout_rate: 0.2 dropout_rate_range: [0.1, 1.0, "linear"] -learning_rate: 0.001 +learning_rate: 0.01 learning_rate_range: [1e-5, 1e-1, "log"] -learning_rate_decay: 100 +learning_rate_decay: 200 learning_rate_decay_range: [1, 1000, "log"] gamma: 0.5 batch_size: 8 @@ -52,8 +52,8 @@ n_layers_vqc: 3 n_layers_vqc_range: [1, 5, "linear"] padding_dropout: False predefined_vqc: "circuit_19" # "", "circuit_10", .. tba. -measurement: "mutually_exclusive" # mutually_exclusive, all, entangled -backend: "aer_simulator_statevector" # aer_simulator_statevector, perth +measurement: "entangled" # mutually_exclusive, all, entangled +backend: "perth" # aer_simulator_statevector, perth #TODO specify when available redis_host: "localhost" redis_port: 6379 From 226922306a9e519941c526c6a305f19cf0170945 Mon Sep 17 00:00:00 2001 From: lc3267 Date: Thu, 20 Oct 2022 15:11:47 +0200 Subject: [PATCH 53/92] backend name fix --- conf/base/parameters/data_science.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/conf/base/parameters/data_science.yml b/conf/base/parameters/data_science.yml index 0681bfd..d7ee209 100644 --- a/conf/base/parameters/data_science.yml +++ b/conf/base/parameters/data_science.yml @@ -53,7 +53,7 @@ n_layers_vqc_range: [1, 5, "linear"] padding_dropout: False predefined_vqc: "circuit_19" # "", "circuit_10", .. tba. measurement: "entangled" # mutually_exclusive, all, entangled -backend: "perth" # aer_simulator_statevector, perth +backend: "ibm_perth" # aer_simulator_statevector, perth #TODO specify when available redis_host: "localhost" redis_port: 6379 From a61d74aa9eaf8e83a10927a9e9d64ee98af170fd Mon Sep 17 00:00:00 2001 From: lc3267 Date: Thu, 20 Oct 2022 17:13:22 +0200 Subject: [PATCH 54/92] some mlflow handling and plotting stuff --- create_checkpoint_from_mlflow.py | 29 ++++++++++++++++++ create_plots_from_metrics.py | 51 ++++++++++++++++++++++++++++++++ 2 files changed, 80 insertions(+) create mode 100644 create_checkpoint_from_mlflow.py create mode 100644 create_plots_from_metrics.py diff --git a/create_checkpoint_from_mlflow.py b/create_checkpoint_from_mlflow.py new file mode 100644 index 0000000..66a3e2c --- /dev/null +++ b/create_checkpoint_from_mlflow.py @@ -0,0 +1,29 @@ +import os +import yaml +import pickle +import mlflow +import datetime + +#ecc74ac0312340b48d157667da192a45 +id = str(input("Enter experiment id: \t")) +run = mlflow.get_run(id) +start_time = datetime.datetime.utcfromtimestamp(run.info.start_time/1000).strftime('%Y-%m-%d %H:%M:%S') +input(f"Found a run from {start_time} at git hash {run.data.tags['git_hash'][:6]}. Continue?") +artifact_uri = run.info.artifact_uri + +with open(os.path.join(artifact_uri[7:], "model.yml"), "r") as f: + model_state_dict = yaml.unsafe_load(f) + +with open(os.path.join(artifact_uri[7:], "optimizer.yml"), "r") as f: + optimizer_state_dict = yaml.unsafe_load(f) + +start_epoch = 1 + +checkpoint = { + "start_epoch": start_epoch, + "model_state_dict": model_state_dict, + "optimizer_state_dict": optimizer_state_dict, + } + +with open(os.path.join(artifact_uri[7:], "checkpoint.pickle"), "wb") as f: + pickle.dump(checkpoint, f, protocol=pickle.HIGHEST_PROTOCOL) diff --git a/create_plots_from_metrics.py b/create_plots_from_metrics.py new file mode 100644 index 0000000..5371d4d --- /dev/null +++ b/create_plots_from_metrics.py @@ -0,0 +1,51 @@ +import mlflow +import datetime +import matplotlib as mpl +import matplotlib.pyplot as plt + +id="ecc74ac0312340b48d157667da192a45" +# id = str(input("Enter experiment id: \t")) +run = mlflow.get_run(id) +start_time = datetime.datetime.utcfromtimestamp(run.info.start_time/1000).strftime('%Y-%m-%d %H:%M:%S') +input(f"Found a run from {start_time} at git hash {run.data.tags['git_hash'][:6]}. Continue?") + +client = mlflow.tracking.MlflowClient() + +metrics = ["train_loss", "val_loss", "train_accuracy", "val_accuracy", "train_logic_accuracy", "val_logic_accuracy", "train_perfect_lcag", "val_perfect_lcag"] + +metric_histories = dict() +for metric in metrics: + metric_history = client.get_metric_history(id, metric) + metric_histories[metric] = ([], []) + for metric_step in metric_history: + metric_histories[metric][0].append(metric_step.step) + metric_histories[metric][1].append(metric_step.value) + + +fig = plt.figure(figsize=(12,6)) +ax = plt.gca() + +cmap = mpl.cm.get_cmap('Dark2_r') + +for i, metric in enumerate(metrics): + if "loss" in metric: + best = min(metric_histories[metric][1]) + elif "perfect" or "accuracy" in metric: + best = max(metric_histories[metric][1]) + + ax.plot(*metric_histories[metric], color=cmap(i), label=metric) + ax.set_xticks(metric_histories[metric][0]) + plt.axhline(y=best, color=cmap(i), linestyle=':', label=f"best_{metric}") + +# Shrink current axis by 20% +box = ax.get_position() +ax.set_position([box.x0, box.y0, box.width * 0.7, box.height]) +ax.set_facecolor("#FAFAFA") +fig.patch.set_facecolor("#FAFAFA") +# Put a legend to the right of the current axis +ax.legend(loc='center left', bbox_to_anchor=(1, 0.5), facecolor="#FAFAFA", framealpha=1) +title = input("Gimme a catchy title: \t") +plt.title(title) +plt.savefig("test.png", bbox_inches='tight') + + From 7af9bee5c26219fe047b8db70806998406c5d043 Mon Sep 17 00:00:00 2001 From: lc3267 Date: Thu, 20 Oct 2022 17:20:32 +0200 Subject: [PATCH 55/92] back to simulator and one more vqc layer --- conf/base/parameters/data_science.yml | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/conf/base/parameters/data_science.yml b/conf/base/parameters/data_science.yml index d7ee209..bd244ce 100644 --- a/conf/base/parameters/data_science.yml +++ b/conf/base/parameters/data_science.yml @@ -48,12 +48,12 @@ data_reupload: True data_reupload_range: [True, False] add_rot_gates: True add_rot_gates_range: [True, False] -n_layers_vqc: 3 +n_layers_vqc: 4 n_layers_vqc_range: [1, 5, "linear"] padding_dropout: False predefined_vqc: "circuit_19" # "", "circuit_10", .. tba. measurement: "entangled" # mutually_exclusive, all, entangled -backend: "ibm_perth" # aer_simulator_statevector, perth +backend: "aer_simulator_statevector" # aer_simulator_statevector, perth #TODO specify when available redis_host: "localhost" redis_port: 6379 From b8b0cde522df51a6d4ce721f4ea0f6a7173b7712 Mon Sep 17 00:00:00 2001 From: lc3267 Date: Fri, 21 Oct 2022 09:28:05 +0200 Subject: [PATCH 56/92] reduced number of vqcs and old circuit --- conf/base/parameters/data_science.yml | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/conf/base/parameters/data_science.yml b/conf/base/parameters/data_science.yml index bd244ce..3b6372b 100644 --- a/conf/base/parameters/data_science.yml +++ b/conf/base/parameters/data_science.yml @@ -48,10 +48,10 @@ data_reupload: True data_reupload_range: [True, False] add_rot_gates: True add_rot_gates_range: [True, False] -n_layers_vqc: 4 +n_layers_vqc: 3 n_layers_vqc_range: [1, 5, "linear"] padding_dropout: False -predefined_vqc: "circuit_19" # "", "circuit_10", .. tba. +predefined_vqc: "" # "", "circuit_10", .. tba. measurement: "entangled" # mutually_exclusive, all, entangled backend: "aer_simulator_statevector" # aer_simulator_statevector, perth #TODO specify when available From e6cfbf88b5133e1ee4d11ed596947cdf0566f61b Mon Sep 17 00:00:00 2001 From: lc3267 Date: Fri, 21 Oct 2022 11:45:07 +0200 Subject: [PATCH 57/92] lot of fixes on the plotting of losses --- create_plots_from_metrics.py | 19 +++++++++++++++---- 1 file changed, 15 insertions(+), 4 deletions(-) diff --git a/create_plots_from_metrics.py b/create_plots_from_metrics.py index 5371d4d..c3e4673 100644 --- a/create_plots_from_metrics.py +++ b/create_plots_from_metrics.py @@ -2,9 +2,10 @@ import datetime import matplotlib as mpl import matplotlib.pyplot as plt +import numpy as np -id="ecc74ac0312340b48d157667da192a45" -# id = str(input("Enter experiment id: \t")) +# id="2d3aff6fc96c49f28c74dc9f057fecee" +id = str(input("Enter experiment id: \t")) run = mlflow.get_run(id) start_time = datetime.datetime.utcfromtimestamp(run.info.start_time/1000).strftime('%Y-%m-%d %H:%M:%S') input(f"Found a run from {start_time} at git hash {run.data.tags['git_hash'][:6]}. Continue?") @@ -30,18 +31,28 @@ for i, metric in enumerate(metrics): if "loss" in metric: best = min(metric_histories[metric][1]) + best_idx = np.argmin(metric_histories[metric][1]) elif "perfect" or "accuracy" in metric: best = max(metric_histories[metric][1]) + best_idx = np.argmax(metric_histories[metric][1]) ax.plot(*metric_histories[metric], color=cmap(i), label=metric) - ax.set_xticks(metric_histories[metric][0]) - plt.axhline(y=best, color=cmap(i), linestyle=':', label=f"best_{metric}") + ax.set_xticks(metric_histories[metric][0][1::(len(metric_histories[metric][0])//10)]) # we start counting at 1, so it looks better if we have the max epoch shown + plt.axhline(y=best, xmin=1/len(metric_histories[metric][0]), xmax=(1+best_idx)/(len(metric_histories[metric][0])+1), color=cmap(i), linewidth=0.7, linestyle=':', label=f"best_{metric}") # Shrink current axis by 20% box = ax.get_position() ax.set_position([box.x0, box.y0, box.width * 0.7, box.height]) ax.set_facecolor("#FAFAFA") +ax.spines['top'].set_visible(False) +ax.spines['right'].set_visible(False) +ax.spines['bottom'].set_visible(False) +ax.spines['left'].set_visible(False) +plt.axvline(x=1, color="#666666", linewidth=0.7) +ax.tick_params(axis=u'both', which=u'both',length=0) fig.patch.set_facecolor("#FAFAFA") +plt.grid(color="#F1F1F1") + # Put a legend to the right of the current axis ax.legend(loc='center left', bbox_to_anchor=(1, 0.5), facecolor="#FAFAFA", framealpha=1) title = input("Gimme a catchy title: \t") From a307c6b483ee537b471e266c497666fa857becd8 Mon Sep 17 00:00:00 2001 From: stroblme Date: Fri, 21 Oct 2022 13:15:15 +0200 Subject: [PATCH 58/92] some more reporting in checkpoint creation --- create_checkpoint_from_mlflow.py | 4 ++++ 1 file changed, 4 insertions(+) diff --git a/create_checkpoint_from_mlflow.py b/create_checkpoint_from_mlflow.py index 66a3e2c..d04b324 100644 --- a/create_checkpoint_from_mlflow.py +++ b/create_checkpoint_from_mlflow.py @@ -25,5 +25,9 @@ "optimizer_state_dict": optimizer_state_dict, } +print(f"Checkpoint opened, writing to file at {os.path.join(artifact_uri[7:], 'checkpoint.pickle')}") + with open(os.path.join(artifact_uri[7:], "checkpoint.pickle"), "wb") as f: pickle.dump(checkpoint, f, protocol=pickle.HIGHEST_PROTOCOL) + +print("Done. You'll need to overwrite the checkpoint.pickle file in /data/08_reporting in order to use it.") \ No newline at end of file From 6aecfefca85eba98bb031234f3d43e9f0d10b6d6 Mon Sep 17 00:00:00 2001 From: stroblme Date: Fri, 21 Oct 2022 13:25:27 +0200 Subject: [PATCH 59/92] enabled direkt export to reporting --- create_checkpoint_from_mlflow.py | 8 ++++++-- 1 file changed, 6 insertions(+), 2 deletions(-) diff --git a/create_checkpoint_from_mlflow.py b/create_checkpoint_from_mlflow.py index d04b324..4c02e19 100644 --- a/create_checkpoint_from_mlflow.py +++ b/create_checkpoint_from_mlflow.py @@ -11,6 +11,7 @@ input(f"Found a run from {start_time} at git hash {run.data.tags['git_hash'][:6]}. Continue?") artifact_uri = run.info.artifact_uri +print(f"Opening Checkpoint for model.yml and optimizer.yml ...") with open(os.path.join(artifact_uri[7:], "model.yml"), "r") as f: model_state_dict = yaml.unsafe_load(f) @@ -25,9 +26,12 @@ "optimizer_state_dict": optimizer_state_dict, } -print(f"Checkpoint opened, writing to file at {os.path.join(artifact_uri[7:], 'checkpoint.pickle')}") +print(f"Checkpoint opened, writing to file at {os.path.join(artifact_uri[7:], 'checkpoint.pickle')} ...") with open(os.path.join(artifact_uri[7:], "checkpoint.pickle"), "wb") as f: pickle.dump(checkpoint, f, protocol=pickle.HIGHEST_PROTOCOL) -print("Done. You'll need to overwrite the checkpoint.pickle file in /data/08_reporting in order to use it.") \ No newline at end of file +input("Done. Press any key to write the checkpoint to /data/08_reporting as well.") + +with open(os.path.join("./data/08_reporting", "checkpoint.pickle"), "wb") as f: + pickle.dump(checkpoint, f, protocol=pickle.HIGHEST_PROTOCOL) \ No newline at end of file From d4054b10deefca80c6f7f9f820499b6b27b6a269 Mon Sep 17 00:00:00 2001 From: stroblme Date: Fri, 21 Oct 2022 13:25:46 +0200 Subject: [PATCH 60/92] circuit 19 for validation with exp 3723457a837e4df9a5a2caef6a0574a8 --- conf/base/parameters/data_science.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/conf/base/parameters/data_science.yml b/conf/base/parameters/data_science.yml index 3b6372b..5296dcd 100644 --- a/conf/base/parameters/data_science.yml +++ b/conf/base/parameters/data_science.yml @@ -51,7 +51,7 @@ add_rot_gates_range: [True, False] n_layers_vqc: 3 n_layers_vqc_range: [1, 5, "linear"] padding_dropout: False -predefined_vqc: "" # "", "circuit_10", .. tba. +predefined_vqc: "circuit_19" # "", "circuit_19", .. tba. measurement: "entangled" # mutually_exclusive, all, entangled backend: "aer_simulator_statevector" # aer_simulator_statevector, perth #TODO specify when available From bec3a4664b2c9116d935666a61163d4d6129b9b4 Mon Sep 17 00:00:00 2001 From: stroblme Date: Fri, 21 Oct 2022 13:32:37 +0200 Subject: [PATCH 61/92] ibm perth for exp with 3723457a837e4df9a5a2caef6a0574a8 --- conf/base/parameters/data_science.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/conf/base/parameters/data_science.yml b/conf/base/parameters/data_science.yml index 5296dcd..530cc62 100644 --- a/conf/base/parameters/data_science.yml +++ b/conf/base/parameters/data_science.yml @@ -53,7 +53,7 @@ n_layers_vqc_range: [1, 5, "linear"] padding_dropout: False predefined_vqc: "circuit_19" # "", "circuit_19", .. tba. measurement: "entangled" # mutually_exclusive, all, entangled -backend: "aer_simulator_statevector" # aer_simulator_statevector, perth +backend: "ibm_perth" # aer_simulator_statevector, ibm_perth #TODO specify when available redis_host: "localhost" redis_port: 6379 From 703fce61767f1289d8d32eca9b91a18bd70545a9 Mon Sep 17 00:00:00 2001 From: lc3267 Date: Fri, 21 Oct 2022 16:50:47 +0200 Subject: [PATCH 62/92] some more plot tuning --- create_plots_from_metrics.py | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/create_plots_from_metrics.py b/create_plots_from_metrics.py index c3e4673..abb6483 100644 --- a/create_plots_from_metrics.py +++ b/create_plots_from_metrics.py @@ -28,6 +28,8 @@ cmap = mpl.cm.get_cmap('Dark2_r') +hline_offset=0.5 + for i, metric in enumerate(metrics): if "loss" in metric: best = min(metric_histories[metric][1]) @@ -38,7 +40,7 @@ ax.plot(*metric_histories[metric], color=cmap(i), label=metric) ax.set_xticks(metric_histories[metric][0][1::(len(metric_histories[metric][0])//10)]) # we start counting at 1, so it looks better if we have the max epoch shown - plt.axhline(y=best, xmin=1/len(metric_histories[metric][0]), xmax=(1+best_idx)/(len(metric_histories[metric][0])+1), color=cmap(i), linewidth=0.7, linestyle=':', label=f"best_{metric}") + plt.axhline(y=best, xmin=hline_offset/(len(metric_histories[metric][0])), xmax=(best_idx+hline_offset)/(len(metric_histories[metric][0])), color=cmap(i), linewidth=0.8, linestyle=':', label=f"best_{metric}") # Shrink current axis by 20% box = ax.get_position() @@ -54,7 +56,7 @@ plt.grid(color="#F1F1F1") # Put a legend to the right of the current axis -ax.legend(loc='center left', bbox_to_anchor=(1, 0.5), facecolor="#FAFAFA", framealpha=1) +ax.legend(loc='center left', bbox_to_anchor=(1, 0.5), facecolor="#FAFAFA", framealpha=0.3) title = input("Gimme a catchy title: \t") plt.title(title) plt.savefig("test.png", bbox_inches='tight') From c41a534766a3513ac72bcdad8cbe7e593d07be83 Mon Sep 17 00:00:00 2001 From: lc3267 Date: Fri, 21 Oct 2022 21:21:24 +0200 Subject: [PATCH 63/92] rm *z --- .../pipelines/data_science/qgnn.py | 32 +++++++++---------- 1 file changed, 16 insertions(+), 16 deletions(-) diff --git a/src/partiqlegan/pipelines/data_science/qgnn.py b/src/partiqlegan/pipelines/data_science/qgnn.py index 55222b3..bcf3672 100644 --- a/src/partiqlegan/pipelines/data_science/qgnn.py +++ b/src/partiqlegan/pipelines/data_science/qgnn.py @@ -202,10 +202,10 @@ def variational(qc, n_qubits, identifier): i, f"{identifier}_ry_{i}", ) - qc.rz( - q.circuit.Parameter(f"{identifier}_rz_0_{i}"), - i, - ) + # qc.rz( + # q.circuit.Parameter(f"{identifier}_rz_0_{i}"), + # i, + # ) if i == 0: qc.crx( q.circuit.Parameter(f"{identifier}_crx_{n_qubits - 1}_{i}"), @@ -219,12 +219,12 @@ def variational(qc, n_qubits, identifier): n_qubits - 1, f"{identifier}_cry_{n_qubits - 1}_{i}", ) - qc.crz( - q.circuit.Parameter(f"{identifier}_crz_{n_qubits - 1}_{i}"), - i, - n_qubits - 1, - f"{identifier}_crz_{n_qubits - 1}_{i}", - ) + # qc.crz( + # q.circuit.Parameter(f"{identifier}_crz_{n_qubits - 1}_{i}"), + # i, + # n_qubits - 1, + # f"{identifier}_crz_{n_qubits - 1}_{i}", + # ) else: qc.crx( q.circuit.Parameter(f"{identifier}_crx_{n_qubits - i - 1}_{n_qubits - i}"), @@ -238,12 +238,12 @@ def variational(qc, n_qubits, identifier): n_qubits - i - 1, f"{identifier}_cry_{n_qubits - i - 1}_{n_qubits - i}", ) - qc.crz( - q.circuit.Parameter(f"{identifier}_crz_{n_qubits - i - 1}_{n_qubits - i}"), - n_qubits - i, - n_qubits - i - 1, - f"{identifier}_crz_{n_qubits - i - 1}_{n_qubits - i}", - ) + # qc.crz( + # q.circuit.Parameter(f"{identifier}_crz_{n_qubits - i - 1}_{n_qubits - i}"), + # n_qubits - i, + # n_qubits - i - 1, + # f"{identifier}_crz_{n_qubits - i - 1}_{n_qubits - i}", + # ) def build_circuit_19(qc, n_qubits, identifier): for i in range(n_qubits): From 7cfe3712085a717a878ed934f1172c732eb79783 Mon Sep 17 00:00:00 2001 From: lc3267 Date: Fri, 21 Oct 2022 21:21:39 +0200 Subject: [PATCH 64/92] back to initial circuit --- conf/base/parameters/data_science.yml | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/conf/base/parameters/data_science.yml b/conf/base/parameters/data_science.yml index 530cc62..dade247 100644 --- a/conf/base/parameters/data_science.yml +++ b/conf/base/parameters/data_science.yml @@ -51,9 +51,9 @@ add_rot_gates_range: [True, False] n_layers_vqc: 3 n_layers_vqc_range: [1, 5, "linear"] padding_dropout: False -predefined_vqc: "circuit_19" # "", "circuit_19", .. tba. +predefined_vqc: "" # "", "circuit_19", .. tba. measurement: "entangled" # mutually_exclusive, all, entangled -backend: "ibm_perth" # aer_simulator_statevector, ibm_perth +backend: "aer_simulator_statevector" # aer_simulator_statevector, ibm_perth #TODO specify when available redis_host: "localhost" redis_port: 6379 From 0b47d709e22d1f46ae8f338d023afa3bbbdb7f5e Mon Sep 17 00:00:00 2001 From: lc3267 Date: Sat, 22 Oct 2022 11:53:42 +0200 Subject: [PATCH 65/92] decreased learning rate --- conf/base/parameters/data_science.yml | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/conf/base/parameters/data_science.yml b/conf/base/parameters/data_science.yml index dade247..61677a4 100644 --- a/conf/base/parameters/data_science.yml +++ b/conf/base/parameters/data_science.yml @@ -17,9 +17,9 @@ batchnorm: True dropout_rate: 0.2 dropout_rate_range: [0.1, 1.0, "linear"] -learning_rate: 0.01 +learning_rate: 0.001 learning_rate_range: [1e-5, 1e-1, "log"] -learning_rate_decay: 200 +learning_rate_decay: 100 learning_rate_decay_range: [1, 1000, "log"] gamma: 0.5 batch_size: 8 From 91723b3d5e8de830800abc33592a821c26e14ab9 Mon Sep 17 00:00:00 2001 From: lc3267 Date: Sat, 22 Oct 2022 11:54:04 +0200 Subject: [PATCH 66/92] 20 epochs --- conf/base/parameters/data_science.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/conf/base/parameters/data_science.yml b/conf/base/parameters/data_science.yml index 61677a4..8f3173b 100644 --- a/conf/base/parameters/data_science.yml +++ b/conf/base/parameters/data_science.yml @@ -7,7 +7,7 @@ default_modes: ["train", "val"] validation_mode: ["val"] # Classical -epochs: 10 +epochs: 20 normalize: "smartone" # one, smartone, zmuv normalize_individually: False zero_mean: False From 86a720c7b3b2bf803ec9dd354948c7141c87628e Mon Sep 17 00:00:00 2001 From: lc3267 Date: Sun, 23 Oct 2022 23:09:50 +0200 Subject: [PATCH 67/92] added rz gates again --- src/partiqlegan/pipelines/data_science/qgnn.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/src/partiqlegan/pipelines/data_science/qgnn.py b/src/partiqlegan/pipelines/data_science/qgnn.py index bcf3672..b55ed29 100644 --- a/src/partiqlegan/pipelines/data_science/qgnn.py +++ b/src/partiqlegan/pipelines/data_science/qgnn.py @@ -202,10 +202,10 @@ def variational(qc, n_qubits, identifier): i, f"{identifier}_ry_{i}", ) - # qc.rz( - # q.circuit.Parameter(f"{identifier}_rz_0_{i}"), - # i, - # ) + qc.rz( + q.circuit.Parameter(f"{identifier}_rz_0_{i}"), + i, + ) if i == 0: qc.crx( q.circuit.Parameter(f"{identifier}_crx_{n_qubits - 1}_{i}"), From 53c7e7edc59d2f77f1a28af8e9c99c88c177dcfd Mon Sep 17 00:00:00 2001 From: lc3267 Date: Sun, 23 Oct 2022 23:10:07 +0200 Subject: [PATCH 68/92] red epochs inc lr --- conf/base/parameters/data_science.yml | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/conf/base/parameters/data_science.yml b/conf/base/parameters/data_science.yml index 8f3173b..8e02c75 100644 --- a/conf/base/parameters/data_science.yml +++ b/conf/base/parameters/data_science.yml @@ -7,7 +7,7 @@ default_modes: ["train", "val"] validation_mode: ["val"] # Classical -epochs: 20 +epochs: 10 normalize: "smartone" # one, smartone, zmuv normalize_individually: False zero_mean: False @@ -17,7 +17,7 @@ batchnorm: True dropout_rate: 0.2 dropout_rate_range: [0.1, 1.0, "linear"] -learning_rate: 0.001 +learning_rate: 0.01 learning_rate_range: [1e-5, 1e-1, "log"] learning_rate_decay: 100 learning_rate_decay_range: [1, 1000, "log"] From 84d16e37b54a75be4c2219f006c67924660bd3c9 Mon Sep 17 00:00:00 2001 From: lc3267 Date: Mon, 24 Oct 2022 22:59:34 +0200 Subject: [PATCH 69/92] rm rz again --- src/partiqlegan/pipelines/data_science/qgnn.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/src/partiqlegan/pipelines/data_science/qgnn.py b/src/partiqlegan/pipelines/data_science/qgnn.py index b55ed29..bcf3672 100644 --- a/src/partiqlegan/pipelines/data_science/qgnn.py +++ b/src/partiqlegan/pipelines/data_science/qgnn.py @@ -202,10 +202,10 @@ def variational(qc, n_qubits, identifier): i, f"{identifier}_ry_{i}", ) - qc.rz( - q.circuit.Parameter(f"{identifier}_rz_0_{i}"), - i, - ) + # qc.rz( + # q.circuit.Parameter(f"{identifier}_rz_0_{i}"), + # i, + # ) if i == 0: qc.crx( q.circuit.Parameter(f"{identifier}_crx_{n_qubits - 1}_{i}"), From 502b2e1b87838f97f2dbb8b4cdf1dab82bf9b7d3 Mon Sep 17 00:00:00 2001 From: lc3267 Date: Mon, 24 Oct 2022 22:59:43 +0200 Subject: [PATCH 70/92] inc lr decay --- conf/base/parameters/data_science.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/conf/base/parameters/data_science.yml b/conf/base/parameters/data_science.yml index 8e02c75..dade247 100644 --- a/conf/base/parameters/data_science.yml +++ b/conf/base/parameters/data_science.yml @@ -19,7 +19,7 @@ dropout_rate: 0.2 dropout_rate_range: [0.1, 1.0, "linear"] learning_rate: 0.01 learning_rate_range: [1e-5, 1e-1, "log"] -learning_rate_decay: 100 +learning_rate_decay: 200 learning_rate_decay_range: [1, 1000, "log"] gamma: 0.5 batch_size: 8 From a5e9ab18b19ef0772c24a1e1b35f7b78b730fee2 Mon Sep 17 00:00:00 2001 From: lc3267 Date: Mon, 24 Oct 2022 23:00:30 +0200 Subject: [PATCH 71/92] inc epochs --- conf/base/parameters/data_science.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/conf/base/parameters/data_science.yml b/conf/base/parameters/data_science.yml index dade247..3a48ae9 100644 --- a/conf/base/parameters/data_science.yml +++ b/conf/base/parameters/data_science.yml @@ -7,7 +7,7 @@ default_modes: ["train", "val"] validation_mode: ["val"] # Classical -epochs: 10 +epochs: 20 normalize: "smartone" # one, smartone, zmuv normalize_individually: False zero_mean: False From 33bea17c7d0ff9197a000c8a09307deb23b87a32 Mon Sep 17 00:00:00 2001 From: lc3267 Date: Sat, 19 Nov 2022 09:21:11 +0100 Subject: [PATCH 72/92] circuit_19 --- conf/base/parameters/data_science.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/conf/base/parameters/data_science.yml b/conf/base/parameters/data_science.yml index 3a48ae9..46ab08d 100644 --- a/conf/base/parameters/data_science.yml +++ b/conf/base/parameters/data_science.yml @@ -51,7 +51,7 @@ add_rot_gates_range: [True, False] n_layers_vqc: 3 n_layers_vqc_range: [1, 5, "linear"] padding_dropout: False -predefined_vqc: "" # "", "circuit_19", .. tba. +predefined_vqc: "circuit_19" # "", "circuit_19", .. tba. measurement: "entangled" # mutually_exclusive, all, entangled backend: "aer_simulator_statevector" # aer_simulator_statevector, ibm_perth #TODO specify when available From 267dedba78493e2ad02429903ad47fafbded203f Mon Sep 17 00:00:00 2001 From: lc3267 Date: Sat, 19 Nov 2022 20:55:35 +0100 Subject: [PATCH 73/92] reduced lr --- conf/base/parameters/data_science.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/conf/base/parameters/data_science.yml b/conf/base/parameters/data_science.yml index 46ab08d..7e3ab67 100644 --- a/conf/base/parameters/data_science.yml +++ b/conf/base/parameters/data_science.yml @@ -17,7 +17,7 @@ batchnorm: True dropout_rate: 0.2 dropout_rate_range: [0.1, 1.0, "linear"] -learning_rate: 0.01 +learning_rate: 0.001 learning_rate_range: [1e-5, 1e-1, "log"] learning_rate_decay: 200 learning_rate_decay_range: [1, 1000, "log"] From 97346c6ced0fb241fea33f8cbf85ae2f953441a6 Mon Sep 17 00:00:00 2001 From: lc3267 Date: Sun, 20 Nov 2022 23:33:38 +0100 Subject: [PATCH 74/92] circuit19 fix --- src/partiqlegan/pipelines/data_science/qgnn.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/src/partiqlegan/pipelines/data_science/qgnn.py b/src/partiqlegan/pipelines/data_science/qgnn.py index bcf3672..9170cb8 100644 --- a/src/partiqlegan/pipelines/data_science/qgnn.py +++ b/src/partiqlegan/pipelines/data_science/qgnn.py @@ -254,19 +254,19 @@ def build_circuit_19(qc, n_qubits, identifier): ) qc.rz(q.circuit.Parameter(f"{identifier}_rz_1_{i}"), i) - for i in range(n_qubits - 1): + for i in range(n_qubits): if i == 0: qc.crx( q.circuit.Parameter(f"{identifier}_crx_{i+1}_{i}"), - i, n_qubits - 1, + i, f"{identifier}_crx_{i+1}_{i}", ) else: qc.crx( q.circuit.Parameter(f"{identifier}_crx_{i+1}_{i}"), - n_qubits - i, n_qubits - i - 1, + n_qubits - i, f"{identifier}_crx_{i+1}_{i}", ) From 75ba7ddc63ba67515b1e3c649b8170f2afe7a6e8 Mon Sep 17 00:00:00 2001 From: lc3267 Date: Sat, 10 Dec 2022 22:37:53 +0100 Subject: [PATCH 75/92] added standard design --- mkdocs.yml | 51 +++++++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 51 insertions(+) create mode 100644 mkdocs.yml diff --git a/mkdocs.yml b/mkdocs.yml new file mode 100644 index 0000000..02cc189 --- /dev/null +++ b/mkdocs.yml @@ -0,0 +1,51 @@ +site_name: partiqleDTR +theme: + name: material + highlightjs: true + palette: + # Palette toggle for light mode + - media: "(prefers-color-scheme: light)" + scheme: default + primary: teal + accent: cyan + toggle: + icon: material/brightness-7 + name: Switch to dark mode + # Palette toggle for dark mode + - media: "(prefers-color-scheme: dark)" + scheme: slate + primary: teal + accent: cyan + toggle: + icon: material/brightness-4 + name: Switch to light mode +plugins: + - search + - mkdocstrings: + handlers: + # See: https://mkdocstrings.github.io/python/usage/ + python: + paths: ["src"] + options: + docstring_style: sphinx +markdown_extensions: + - markdown_include.include: + base_path: . + - toc: + permalink: "#" + baselevel: 1 + separator: "_" + - pymdownx.emoji: + emoji_index: !!python/name:materialx.emoji.twemoji + emoji_generator: 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["lc3267 "] readme = "README.md" [tool.poetry.dependencies] -python = "^3.8" +python = ">=3.8.1,<3.11" qiskit = "^0.38.0" pytorch = "^1.0.2" black = "^22.6.0" @@ -38,6 +38,16 @@ kedro-viz = "^5.1.1" kedro-mlflow = "^0.11.3" formattex = "^0.0.3" +[tool.poetry.group.dev.dependencies] +pytest = "^7.2.0" +pre-commit = "^2.20.0" +black = "^22.10.0" +flake8 = "^6.0.0" +mkdocs = "^1.4.2" +mkdocstrings = "^0.19.0" +markdown-include = "^0.8.0" +mkdocs-material = "^8.5.11" +mkdocstrings-python = "^0.8.2" [build-system] requires = ["poetry-core"] From 38bfc97002dc541fcd287e751e3986bc626d6cae Mon Sep 17 00:00:00 2001 From: lc3267 Date: Sat, 10 Dec 2022 22:38:08 +0100 Subject: [PATCH 77/92] added mkdocs dependencies --- .vscode/setup.sh | 2 ++ .vscode/setup_dev.sh | 6 ++++++ 2 files changed, 8 insertions(+) create mode 100755 .vscode/setup.sh create mode 100755 .vscode/setup_dev.sh diff --git a/.vscode/setup.sh b/.vscode/setup.sh new file mode 100755 index 0000000..a3ee031 --- /dev/null +++ b/.vscode/setup.sh @@ -0,0 +1,2 @@ +poetry install --without dev +poetry run kedro mlflow init \ No newline at end of file diff --git a/.vscode/setup_dev.sh b/.vscode/setup_dev.sh new file mode 100755 index 0000000..a31ca23 --- /dev/null +++ b/.vscode/setup_dev.sh @@ -0,0 +1,6 @@ +poetry install +poetry run pre-commit autoupdate +poetry run pre-commit install +poetry run kedro mlflow init +poetry run pytest +poetry run mkdocs build \ No newline at end of file From 76d8cab5a2c4b78cf9d664c06c68bc7ce66bb477 Mon Sep 17 00:00:00 2001 From: lc3267 Date: Sat, 10 Dec 2022 22:38:15 +0100 Subject: [PATCH 78/92] added mkdocs tasks --- .vscode/tasks.json | 95 ++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 95 insertions(+) create mode 100644 .vscode/tasks.json diff --git a/.vscode/tasks.json b/.vscode/tasks.json new file mode 100644 index 0000000..35f0cb3 --- /dev/null +++ b/.vscode/tasks.json @@ -0,0 +1,95 @@ +{ + "version": "2.0.0", + "tasks": [ + + { + "label": "Setup", + "type": "shell", + "command": ".vscode/setup.sh", + "group": "none", + "presentation": { + "reveal": "never", + "panel": "new" + }, + "problemMatcher": [] + }, + { + "label": "Kedro Test", + "type": "shell", + "command": "poetry", + "args": ["run", "pytest"], + "group": "none", + "presentation": { + "reveal": "never", + "panel": "dedicated" + }, + "problemMatcher": [] + }, + { + "label": "Kedro Viz", + "type": "shell", + "command": "poetry", + "args": ["run", "kedro", "viz", "--autoreload"], + "group": "none", + "presentation": { + "reveal": "never", + "panel": "new" + }, + "runOptions": { + "runOn": "folderOpen" + }, + "problemMatcher": [] + }, + { + "label": "MLFlow Dashboard", + "type": "shell", + "command": "poetry", + "args": ["run", "mlflow", "ui"], + "group": "none", + "presentation": { + "reveal": "never", + "panel": "new" + }, + "runOptions": { + "runOn": "folderOpen" + }, + "problemMatcher": [] + }, + { + "label": "MkDocs Build", + "type": "shell", + "command": "poetry", + "args": ["run", "mkdocs", "build"], + "group": "none", + "presentation": { + "reveal": "never", + "panel": "dedicated" + }, + "problemMatcher": [] + }, + { + "label": "MkDocs Serve", + "type": "shell", + "command": "poetry", + "args": ["run", "mkdocs", "serve"], + "group": "none", + "presentation": { + "reveal": "never", + "panel": "dedicated" + }, + "problemMatcher": [] + }, + { + "label": "MkDocs Deploy", + "type": "shell", + "command": "poetry", + "args": ["run", "mkdocs", "gh-deploy"], + "group": "none", + "presentation": { + "reveal": "never", + "panel": "dedicated" + }, + "problemMatcher": [] + }, + ] + } \ No newline at end of file From 9df6e82de1544aa8829c6b61bda2672a17c3d38f Mon Sep 17 00:00:00 2001 From: lc3267 Date: Sat, 10 Dec 2022 22:38:24 +0100 Subject: [PATCH 79/92] some dummy main page --- docs/index.md | 26 ++++++++++++++++++++++++++ 1 file changed, 26 insertions(+) create mode 100644 docs/index.md diff --git a/docs/index.md b/docs/index.md new file mode 100644 index 0000000..3edeec2 --- /dev/null +++ b/docs/index.md @@ -0,0 +1,26 @@ +# Documentation + +Attempt to solve the particle decay tree reconstruction problem using hybrid quantum machine learning architectures. + +## Setup + +Assuming [poetry](https://python-poetry.org/) is installed, simply run the VSCode task "Setup" or manually: + +```bash +.vscode/setup.sh +``` + +If you use VSCode, you can run mlflow and kedro-viz as tasks. +There are also launch configurations for the kedro experiments. + + +## Project layout + +This project uses [kedro](https://kedro.org) and [mlflow](https://mlflow.org) as framework and for experiment tracking purposes. +Below are some of the main files and folders: + + .vscode/setup.sh # Starting point on a freshly cloned repo + .vscode/setup_dev.sh # Includes development modules and runs default build steps + src/partiqlegan # Kedro pipelines and nodes + src/tests # Stuff for testing + data # Kedro data folders From 56743de23e2b2a83579da7a6f71e7d9cacc501f3 Mon Sep 17 00:00:00 2001 From: lc3267 Date: Sat, 10 Dec 2022 22:39:45 +0100 Subject: [PATCH 80/92] dummy todo page --- docs/results.md | 3 +++ 1 file changed, 3 insertions(+) create mode 100644 docs/results.md diff --git a/docs/results.md b/docs/results.md new file mode 100644 index 0000000..db92953 --- /dev/null +++ b/docs/results.md @@ -0,0 +1,3 @@ +# Results + +Todo.. \ No newline at end of file From 8dd14f7c55aa9e7b486b78c40bed8bc38a70a767 Mon Sep 17 00:00:00 2001 From: lc3267 Date: Sat, 10 Dec 2022 22:45:38 +0100 Subject: [PATCH 81/92] updated repo --- mkdocs.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/mkdocs.yml b/mkdocs.yml index 02cc189..91db482 100644 --- a/mkdocs.yml +++ b/mkdocs.yml @@ -44,7 +44,7 @@ extra: link: https://www.researchgate.net/profile/Melvin-Strobl name: Researchgate - icon: fontawesome/brands/github - link: https://github.com/stroblme/easee + link: https://github.com/stroblme/partiqleDTR name: Github - icon: fontawesome/solid/section link: https://stroblme.de/index.php/legal-notice/ From fd47cc8900b6b69e65b12333c5621ce248545cc9 Mon Sep 17 00:00:00 2001 From: lc3267 Date: Sat, 10 Dec 2022 22:45:45 +0100 Subject: [PATCH 82/92] refactoring --- docs/source/conf.py | 2 +- pyproject.toml | 8 ++++---- src/{partiqlegan => partiqleDTR}/__init__.py | 0 src/{partiqlegan => partiqleDTR}/__main__.py | 0 src/{partiqlegan => partiqleDTR}/hooks.py | 0 src/{partiqlegan => partiqleDTR}/pipeline_registry.py | 6 +++--- src/{partiqlegan => partiqleDTR}/pipelines/__init__.py | 0 .../pipelines/data_generation/README.md | 0 .../pipelines/data_generation/__init__.py | 0 .../pipelines/data_generation/nodes.py | 0 .../pipelines/data_generation/pipeline.py | 0 .../pipelines/data_processing/README.md | 0 .../pipelines/data_processing/__init__.py | 0 .../pipelines/data_processing/nodes.py | 0 .../pipelines/data_processing/pipeline.py | 0 .../pipelines/data_science/.gitignore | 0 .../pipelines/data_science/README.md | 0 .../pipelines/data_science/__init__.py | 0 .../pipelines/data_science/dgnn.py | 0 .../pipelines/data_science/dqgnn.py | 0 .../pipelines/data_science/gnn.py | 0 .../pipelines/data_science/gradients_visualization.py | 0 .../pipelines/data_science/graph_visualization.py | 0 .../pipelines/data_science/hyperparam_optimizer.py | 0 .../pipelines/data_science/instructor.py | 0 .../pipelines/data_science/mlp.py | 0 .../pipelines/data_science/nodes.py | 0 .../pipelines/data_science/pipeline.py | 0 .../pipelines/data_science/pqgnn.py | 0 .../pipelines/data_science/qftgnn.py | 0 .../pipelines/data_science/qgnn.py | 0 .../pipelines/data_science/qgnn_bckp.py | 0 .../pipelines/data_science/qgnn_new.py | 0 .../pipelines/data_science/qmlp.py | 0 .../pipelines/data_science/quantum_mlp.py | 0 .../pipelines/data_science/sgnn.py | 0 .../pipelines/data_science/sqgnn.py | 0 .../pipelines/data_science/utils.py | 0 src/{partiqlegan => partiqleDTR}/settings.py | 2 +- 39 files changed, 9 insertions(+), 9 deletions(-) rename src/{partiqlegan => partiqleDTR}/__init__.py (100%) rename src/{partiqlegan => partiqleDTR}/__main__.py (100%) rename src/{partiqlegan => partiqleDTR}/hooks.py (100%) rename src/{partiqlegan => partiqleDTR}/pipeline_registry.py (93%) rename src/{partiqlegan => partiqleDTR}/pipelines/__init__.py (100%) rename src/{partiqlegan => partiqleDTR}/pipelines/data_generation/README.md (100%) rename src/{partiqlegan => partiqleDTR}/pipelines/data_generation/__init__.py (100%) rename src/{partiqlegan => partiqleDTR}/pipelines/data_generation/nodes.py (100%) rename src/{partiqlegan => partiqleDTR}/pipelines/data_generation/pipeline.py (100%) rename src/{partiqlegan => partiqleDTR}/pipelines/data_processing/README.md (100%) rename src/{partiqlegan => partiqleDTR}/pipelines/data_processing/__init__.py (100%) rename src/{partiqlegan => partiqleDTR}/pipelines/data_processing/nodes.py (100%) rename src/{partiqlegan => partiqleDTR}/pipelines/data_processing/pipeline.py (100%) rename src/{partiqlegan => partiqleDTR}/pipelines/data_science/.gitignore (100%) rename src/{partiqlegan => partiqleDTR}/pipelines/data_science/README.md (100%) rename src/{partiqlegan => partiqleDTR}/pipelines/data_science/__init__.py (100%) rename src/{partiqlegan => partiqleDTR}/pipelines/data_science/dgnn.py (100%) rename src/{partiqlegan => partiqleDTR}/pipelines/data_science/dqgnn.py (100%) rename src/{partiqlegan => partiqleDTR}/pipelines/data_science/gnn.py (100%) rename src/{partiqlegan => partiqleDTR}/pipelines/data_science/gradients_visualization.py (100%) rename src/{partiqlegan => partiqleDTR}/pipelines/data_science/graph_visualization.py (100%) rename src/{partiqlegan => partiqleDTR}/pipelines/data_science/hyperparam_optimizer.py (100%) rename src/{partiqlegan => partiqleDTR}/pipelines/data_science/instructor.py (100%) rename src/{partiqlegan => partiqleDTR}/pipelines/data_science/mlp.py (100%) rename src/{partiqlegan => partiqleDTR}/pipelines/data_science/nodes.py (100%) rename src/{partiqlegan => partiqleDTR}/pipelines/data_science/pipeline.py (100%) rename src/{partiqlegan => partiqleDTR}/pipelines/data_science/pqgnn.py (100%) rename src/{partiqlegan => partiqleDTR}/pipelines/data_science/qftgnn.py (100%) rename src/{partiqlegan => partiqleDTR}/pipelines/data_science/qgnn.py (100%) rename src/{partiqlegan => partiqleDTR}/pipelines/data_science/qgnn_bckp.py (100%) rename src/{partiqlegan => partiqleDTR}/pipelines/data_science/qgnn_new.py (100%) rename src/{partiqlegan => partiqleDTR}/pipelines/data_science/qmlp.py (100%) rename src/{partiqlegan => partiqleDTR}/pipelines/data_science/quantum_mlp.py (100%) rename src/{partiqlegan => partiqleDTR}/pipelines/data_science/sgnn.py (100%) rename src/{partiqlegan => partiqleDTR}/pipelines/data_science/sqgnn.py (100%) rename src/{partiqlegan => partiqleDTR}/pipelines/data_science/utils.py (100%) rename src/{partiqlegan => partiqleDTR}/settings.py (94%) diff --git a/docs/source/conf.py b/docs/source/conf.py index d21063d..b642b45 100644 --- a/docs/source/conf.py +++ b/docs/source/conf.py @@ -22,7 +22,7 @@ from kedro.framework.cli.utils import find_stylesheets from recommonmark.transform import AutoStructify -from partiqlegan import __version__ as release +from partiqleDTR import __version__ as release # -- Project information ----------------------------------------------------- diff --git a/pyproject.toml b/pyproject.toml index d35d299..ea995f1 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,6 +1,6 @@ [tool.kedro] -package_name = "partiqlegan" -project_name = "partiqlegan" +package_name = "partiqleDTR" +project_name = "partiqleDTR" project_version = "0.18.1" [tool.isort] @@ -14,7 +14,7 @@ known_third_party = "kedro" [tool.pytest.ini_options] addopts = """ --cov-report term-missing \ ---cov src/partiqlegan -ra""" +--cov src/partiqleDTR -ra""" [tool.coverage.report] fail_under = 0 @@ -22,7 +22,7 @@ show_missing = true exclude_lines = ["pragma: no cover", "raise NotImplementedError"] [tool.poetry] -name = "partiqlegan" +name = "partiqleDTR" version = "0.1.0" description = "" authors = ["lc3267 "] diff --git a/src/partiqlegan/__init__.py b/src/partiqleDTR/__init__.py similarity index 100% rename from src/partiqlegan/__init__.py rename to src/partiqleDTR/__init__.py diff --git a/src/partiqlegan/__main__.py b/src/partiqleDTR/__main__.py similarity index 100% rename from src/partiqlegan/__main__.py rename to src/partiqleDTR/__main__.py diff --git a/src/partiqlegan/hooks.py b/src/partiqleDTR/hooks.py similarity index 100% rename from src/partiqlegan/hooks.py rename to src/partiqleDTR/hooks.py diff --git a/src/partiqlegan/pipeline_registry.py b/src/partiqleDTR/pipeline_registry.py similarity index 93% rename from src/partiqlegan/pipeline_registry.py rename to src/partiqleDTR/pipeline_registry.py index d82836f..fb794c7 100644 --- a/src/partiqlegan/pipeline_registry.py +++ b/src/partiqleDTR/pipeline_registry.py @@ -3,9 +3,9 @@ from kedro.pipeline import Pipeline, pipeline -from partiqlegan.pipelines import data_generation as dg -from partiqlegan.pipelines import data_processing as dp -from partiqlegan.pipelines import data_science as ds +from partiqleDTR.pipelines import data_generation as dg +from partiqleDTR.pipelines import data_processing as dp +from partiqleDTR.pipelines import data_science as ds def register_pipelines() -> Dict[str, Pipeline]: diff --git a/src/partiqlegan/pipelines/__init__.py b/src/partiqleDTR/pipelines/__init__.py similarity index 100% rename from src/partiqlegan/pipelines/__init__.py rename to src/partiqleDTR/pipelines/__init__.py diff --git a/src/partiqlegan/pipelines/data_generation/README.md b/src/partiqleDTR/pipelines/data_generation/README.md similarity index 100% rename from src/partiqlegan/pipelines/data_generation/README.md rename to src/partiqleDTR/pipelines/data_generation/README.md diff --git a/src/partiqlegan/pipelines/data_generation/__init__.py b/src/partiqleDTR/pipelines/data_generation/__init__.py similarity index 100% rename from src/partiqlegan/pipelines/data_generation/__init__.py rename to src/partiqleDTR/pipelines/data_generation/__init__.py diff --git a/src/partiqlegan/pipelines/data_generation/nodes.py b/src/partiqleDTR/pipelines/data_generation/nodes.py similarity index 100% rename from src/partiqlegan/pipelines/data_generation/nodes.py rename to src/partiqleDTR/pipelines/data_generation/nodes.py diff --git a/src/partiqlegan/pipelines/data_generation/pipeline.py b/src/partiqleDTR/pipelines/data_generation/pipeline.py similarity index 100% rename from src/partiqlegan/pipelines/data_generation/pipeline.py rename to src/partiqleDTR/pipelines/data_generation/pipeline.py diff --git a/src/partiqlegan/pipelines/data_processing/README.md b/src/partiqleDTR/pipelines/data_processing/README.md similarity index 100% rename from src/partiqlegan/pipelines/data_processing/README.md rename to src/partiqleDTR/pipelines/data_processing/README.md diff --git a/src/partiqlegan/pipelines/data_processing/__init__.py b/src/partiqleDTR/pipelines/data_processing/__init__.py similarity index 100% rename from src/partiqlegan/pipelines/data_processing/__init__.py rename to src/partiqleDTR/pipelines/data_processing/__init__.py diff --git a/src/partiqlegan/pipelines/data_processing/nodes.py b/src/partiqleDTR/pipelines/data_processing/nodes.py similarity index 100% rename from src/partiqlegan/pipelines/data_processing/nodes.py rename to src/partiqleDTR/pipelines/data_processing/nodes.py diff --git a/src/partiqlegan/pipelines/data_processing/pipeline.py b/src/partiqleDTR/pipelines/data_processing/pipeline.py similarity index 100% rename from src/partiqlegan/pipelines/data_processing/pipeline.py rename to src/partiqleDTR/pipelines/data_processing/pipeline.py diff --git a/src/partiqlegan/pipelines/data_science/.gitignore b/src/partiqleDTR/pipelines/data_science/.gitignore similarity index 100% rename from src/partiqlegan/pipelines/data_science/.gitignore rename to src/partiqleDTR/pipelines/data_science/.gitignore diff --git a/src/partiqlegan/pipelines/data_science/README.md b/src/partiqleDTR/pipelines/data_science/README.md similarity index 100% rename from src/partiqlegan/pipelines/data_science/README.md rename to src/partiqleDTR/pipelines/data_science/README.md diff --git a/src/partiqlegan/pipelines/data_science/__init__.py b/src/partiqleDTR/pipelines/data_science/__init__.py similarity index 100% rename from src/partiqlegan/pipelines/data_science/__init__.py rename to src/partiqleDTR/pipelines/data_science/__init__.py diff --git a/src/partiqlegan/pipelines/data_science/dgnn.py b/src/partiqleDTR/pipelines/data_science/dgnn.py similarity index 100% rename from src/partiqlegan/pipelines/data_science/dgnn.py rename to src/partiqleDTR/pipelines/data_science/dgnn.py diff --git a/src/partiqlegan/pipelines/data_science/dqgnn.py b/src/partiqleDTR/pipelines/data_science/dqgnn.py similarity index 100% rename from src/partiqlegan/pipelines/data_science/dqgnn.py rename to src/partiqleDTR/pipelines/data_science/dqgnn.py diff --git a/src/partiqlegan/pipelines/data_science/gnn.py b/src/partiqleDTR/pipelines/data_science/gnn.py similarity index 100% rename from src/partiqlegan/pipelines/data_science/gnn.py rename to src/partiqleDTR/pipelines/data_science/gnn.py diff --git a/src/partiqlegan/pipelines/data_science/gradients_visualization.py b/src/partiqleDTR/pipelines/data_science/gradients_visualization.py similarity index 100% rename from src/partiqlegan/pipelines/data_science/gradients_visualization.py rename to src/partiqleDTR/pipelines/data_science/gradients_visualization.py diff --git a/src/partiqlegan/pipelines/data_science/graph_visualization.py b/src/partiqleDTR/pipelines/data_science/graph_visualization.py similarity index 100% rename from src/partiqlegan/pipelines/data_science/graph_visualization.py rename to src/partiqleDTR/pipelines/data_science/graph_visualization.py diff --git a/src/partiqlegan/pipelines/data_science/hyperparam_optimizer.py b/src/partiqleDTR/pipelines/data_science/hyperparam_optimizer.py similarity index 100% rename from src/partiqlegan/pipelines/data_science/hyperparam_optimizer.py rename to src/partiqleDTR/pipelines/data_science/hyperparam_optimizer.py diff --git a/src/partiqlegan/pipelines/data_science/instructor.py b/src/partiqleDTR/pipelines/data_science/instructor.py similarity index 100% rename from src/partiqlegan/pipelines/data_science/instructor.py rename to src/partiqleDTR/pipelines/data_science/instructor.py diff --git a/src/partiqlegan/pipelines/data_science/mlp.py b/src/partiqleDTR/pipelines/data_science/mlp.py similarity index 100% rename from src/partiqlegan/pipelines/data_science/mlp.py rename to src/partiqleDTR/pipelines/data_science/mlp.py diff --git a/src/partiqlegan/pipelines/data_science/nodes.py b/src/partiqleDTR/pipelines/data_science/nodes.py similarity index 100% rename from src/partiqlegan/pipelines/data_science/nodes.py rename to src/partiqleDTR/pipelines/data_science/nodes.py diff --git a/src/partiqlegan/pipelines/data_science/pipeline.py b/src/partiqleDTR/pipelines/data_science/pipeline.py similarity index 100% rename from src/partiqlegan/pipelines/data_science/pipeline.py rename to src/partiqleDTR/pipelines/data_science/pipeline.py diff --git a/src/partiqlegan/pipelines/data_science/pqgnn.py b/src/partiqleDTR/pipelines/data_science/pqgnn.py similarity index 100% rename from src/partiqlegan/pipelines/data_science/pqgnn.py rename to src/partiqleDTR/pipelines/data_science/pqgnn.py diff --git a/src/partiqlegan/pipelines/data_science/qftgnn.py b/src/partiqleDTR/pipelines/data_science/qftgnn.py similarity index 100% rename from src/partiqlegan/pipelines/data_science/qftgnn.py rename to src/partiqleDTR/pipelines/data_science/qftgnn.py diff --git a/src/partiqlegan/pipelines/data_science/qgnn.py b/src/partiqleDTR/pipelines/data_science/qgnn.py similarity index 100% rename from src/partiqlegan/pipelines/data_science/qgnn.py rename to src/partiqleDTR/pipelines/data_science/qgnn.py diff --git a/src/partiqlegan/pipelines/data_science/qgnn_bckp.py b/src/partiqleDTR/pipelines/data_science/qgnn_bckp.py similarity index 100% rename from src/partiqlegan/pipelines/data_science/qgnn_bckp.py rename to src/partiqleDTR/pipelines/data_science/qgnn_bckp.py diff --git a/src/partiqlegan/pipelines/data_science/qgnn_new.py b/src/partiqleDTR/pipelines/data_science/qgnn_new.py similarity index 100% rename from src/partiqlegan/pipelines/data_science/qgnn_new.py rename to src/partiqleDTR/pipelines/data_science/qgnn_new.py diff --git a/src/partiqlegan/pipelines/data_science/qmlp.py b/src/partiqleDTR/pipelines/data_science/qmlp.py similarity index 100% rename from src/partiqlegan/pipelines/data_science/qmlp.py rename to src/partiqleDTR/pipelines/data_science/qmlp.py diff --git a/src/partiqlegan/pipelines/data_science/quantum_mlp.py b/src/partiqleDTR/pipelines/data_science/quantum_mlp.py similarity index 100% rename from src/partiqlegan/pipelines/data_science/quantum_mlp.py rename to src/partiqleDTR/pipelines/data_science/quantum_mlp.py diff --git a/src/partiqlegan/pipelines/data_science/sgnn.py b/src/partiqleDTR/pipelines/data_science/sgnn.py similarity index 100% rename from src/partiqlegan/pipelines/data_science/sgnn.py rename to src/partiqleDTR/pipelines/data_science/sgnn.py diff --git a/src/partiqlegan/pipelines/data_science/sqgnn.py b/src/partiqleDTR/pipelines/data_science/sqgnn.py similarity index 100% rename from src/partiqlegan/pipelines/data_science/sqgnn.py rename to src/partiqleDTR/pipelines/data_science/sqgnn.py diff --git a/src/partiqlegan/pipelines/data_science/utils.py b/src/partiqleDTR/pipelines/data_science/utils.py similarity index 100% rename from src/partiqlegan/pipelines/data_science/utils.py rename to src/partiqleDTR/pipelines/data_science/utils.py diff --git a/src/partiqlegan/settings.py b/src/partiqleDTR/settings.py similarity index 94% rename from src/partiqlegan/settings.py rename to src/partiqleDTR/settings.py index 6f3c38e..8b9a766 100644 --- a/src/partiqlegan/settings.py +++ b/src/partiqleDTR/settings.py @@ -1,5 +1,5 @@ """Project settings.""" -from partiqlegan.hooks import ProjectHooks +from partiqleDTR.hooks import ProjectHooks # Instantiate and list your project hooks here HOOKS = (ProjectHooks(),) From ce51b2be81bbfbe6f21332056ba0df301c912437 Mon Sep 17 00:00:00 2001 From: lc3267 Date: Tue, 28 Feb 2023 16:08:18 +0100 Subject: [PATCH 83/92] fixed naming --- src/partiqleDTR/__init__.py | 2 +- src/partiqleDTR/__main__.py | 4 ++-- 2 files changed, 3 insertions(+), 3 deletions(-) diff --git a/src/partiqleDTR/__init__.py b/src/partiqleDTR/__init__.py index 4186287..5d1b51b 100644 --- a/src/partiqleDTR/__init__.py +++ b/src/partiqleDTR/__init__.py @@ -1,4 +1,4 @@ -"""partiqlegan +"""partiqleDTR """ __version__ = "0.1" diff --git a/src/partiqleDTR/__main__.py b/src/partiqleDTR/__main__.py index cc48aaf..eeac8ce 100644 --- a/src/partiqleDTR/__main__.py +++ b/src/partiqleDTR/__main__.py @@ -1,5 +1,5 @@ -"""partiqlegan file for ensuring the package is executable -as `partiqlegan` and `python -m partiqlegan` +"""partiqleDTR file for ensuring the package is executable +as `partiqleDTR` and `python -m partiqleDTR` """ import importlib from pathlib import Path From eca8ec9087f3381bf19c19aa248592b447aca3aa Mon Sep 17 00:00:00 2001 From: lc3267 Date: Wed, 1 Mar 2023 21:52:43 +0100 Subject: [PATCH 84/92] added flipped circuit_19 --- poetry.lock | 2729 ++++++++++++----- pyproject.toml | 7 +- .../pipelines/data_science/qgnn.py | 27 + 3 files changed, 1914 insertions(+), 849 deletions(-) diff --git a/poetry.lock b/poetry.lock index e9b1b70..04521a6 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,14 +1,22 @@ +[[package]] +name = "absl-py" +version = "1.4.0" +description = "Abseil Python Common Libraries, see https://github.com/abseil/abseil-py." +category = "main" +optional = false +python-versions = ">=3.6" + [[package]] name = "aiofiles" -version = "0.6.0" +version = "22.1.0" description = "File support for asyncio." category = "main" optional = false -python-versions = "*" +python-versions = ">=3.7,<4.0" [[package]] name = "alembic" -version = "1.8.1" +version = "1.9.2" description = "A database migration tool for SQLAlchemy." category = "main" optional = false @@ -59,14 +67,6 @@ doc = ["packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme"] test = ["contextlib2", "coverage[toml] (>=4.5)", "hypothesis (>=4.0)", "mock (>=4)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (<0.15)", "uvloop (>=0.15)"] trio = ["trio (>=0.16,<0.22)"] -[[package]] -name = "appdirs" -version = "1.4.4" -description = "A small Python module for determining appropriate platform-specific dirs, e.g. a \"user data dir\"." -category = "main" -optional = false -python-versions = "*" - [[package]] name = "appnope" version = "0.1.3" @@ -87,29 +87,45 @@ python-versions = ">=3.6" python-dateutil = ">=2.7.0" [[package]] -name = "asgiref" -version = "3.5.2" -description = "ASGI specs, helper code, and adapters" +name = "asttokens" +version = "2.2.1" +description = "Annotate AST trees with source code positions" category = "main" optional = false -python-versions = ">=3.7" +python-versions = "*" + +[package.dependencies] +six = "*" [package.extras] -tests = ["mypy (>=0.800)", "pytest", "pytest-asyncio"] +test = ["astroid", "pytest"] + +[[package]] +name = "astunparse" +version = "1.6.3" +description = "An AST unparser for Python" +category = "main" +optional = false +python-versions = "*" + +[package.dependencies] +six = ">=1.6.1,<2.0" +wheel = ">=0.23.0,<1.0" [[package]] name = "attrs" -version = "22.1.0" +version = "22.2.0" description = "Classes Without Boilerplate" category = "main" optional = false -python-versions = ">=3.5" +python-versions = ">=3.6" [package.extras] -dev = ["cloudpickle", "coverage[toml] (>=5.0.2)", "furo", "hypothesis", "mypy (>=0.900,!=0.940)", "pre-commit", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "sphinx", "sphinx-notfound-page", "zope.interface"] -docs = ["furo", "sphinx", "sphinx-notfound-page", "zope.interface"] -tests = ["cloudpickle", "coverage[toml] (>=5.0.2)", "hypothesis", "mypy (>=0.900,!=0.940)", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "zope.interface"] -tests_no_zope = ["cloudpickle", "coverage[toml] (>=5.0.2)", "hypothesis", "mypy (>=0.900,!=0.940)", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins"] +cov = ["attrs[tests]", "coverage-enable-subprocess", "coverage[toml] (>=5.3)"] +dev = ["attrs[docs,tests]"] +docs = ["furo", "myst-parser", "sphinx", "sphinx-notfound-page", "sphinxcontrib-towncrier", "towncrier", "zope.interface"] +tests = ["attrs[tests-no-zope]", "zope.interface"] +tests-no-zope = ["cloudpickle", "cloudpickle", "hypothesis", "hypothesis", "mypy (>=0.971,<0.990)", "mypy (>=0.971,<0.990)", "pympler", "pympler", "pytest (>=4.3.0)", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-mypy-plugins", "pytest-xdist[psutil]", "pytest-xdist[psutil]"] [[package]] name = "backcall" @@ -132,7 +148,7 @@ chardet = ">=3.0.2" [[package]] name = "black" -version = "22.10.0" +version = "22.12.0" description = "The uncompromising code formatter." category = "main" optional = false @@ -154,22 +170,22 @@ uvloop = ["uvloop (>=0.15.2)"] [[package]] name = "build" -version = "0.9.0" -description = "A simple, correct PEP 517 build frontend" +version = "0.10.0" +description = "A simple, correct Python build frontend" category = "main" optional = false -python-versions = ">=3.6" +python-versions = ">= 3.7" [package.dependencies] colorama = {version = "*", markers = "os_name == \"nt\""} packaging = ">=19.0" -pep517 = ">=0.9.1" -tomli = {version = ">=1.0.0", markers = "python_version < \"3.11\""} +pyproject_hooks = "*" +tomli = {version = ">=1.1.0", markers = "python_version < \"3.11\""} [package.extras] docs = ["furo (>=2021.08.31)", "sphinx (>=4.0,<5.0)", "sphinx-argparse-cli (>=1.5)", "sphinx-autodoc-typehints (>=1.10)"] test = ["filelock (>=3)", "pytest (>=6.2.4)", "pytest-cov (>=2.12)", "pytest-mock (>=2)", "pytest-rerunfailures (>=9.1)", "pytest-xdist (>=1.34)", "setuptools (>=42.0.0)", "setuptools (>=56.0.0)", "toml (>=0.10.0)", "wheel (>=0.36.0)"] -typing = ["importlib-metadata (>=4.6.4)", "mypy (==0.950)", "typing-extensions (>=3.7.4.3)"] +typing = ["importlib-metadata (>=5.1)", "mypy (==0.991)", "tomli", "typing-extensions (>=3.7.4.3)"] virtualenv = ["virtualenv (>=20.0.35)"] [[package]] @@ -217,14 +233,11 @@ python-versions = ">=3.7" [[package]] name = "charset-normalizer" -version = "2.1.1" +version = "3.0.1" description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet." category = "main" optional = false -python-versions = ">=3.6.0" - -[package.extras] -unicode_backport = ["unicodedata2"] +python-versions = "*" [[package]] name = "click" @@ -239,7 +252,7 @@ colorama = {version = "*", markers = "platform_system == \"Windows\""} [[package]] name = "cloudpickle" -version = "2.2.0" +version = "2.2.1" description = "Extended pickling support for Python objects" category = "main" optional = false @@ -283,7 +296,7 @@ requests = ">=2.23.0" [[package]] name = "cryptography" -version = "38.0.4" +version = "39.0.0" description = "cryptography is a package which provides cryptographic recipes and primitives to Python developers." category = "main" optional = false @@ -293,9 +306,9 @@ python-versions = ">=3.6" cffi = ">=1.12" [package.extras] -docs = ["sphinx (>=1.6.5,!=1.8.0,!=3.1.0,!=3.1.1)", "sphinx-rtd-theme"] +docs = ["sphinx (>=1.6.5,!=1.8.0,!=3.1.0,!=3.1.1,!=5.2.0,!=5.2.0.post0)", "sphinx-rtd-theme"] docstest = ["pyenchant (>=1.6.11)", "sphinxcontrib-spelling (>=4.0.1)", "twine (>=1.12.0)"] -pep8test = ["black", "flake8", "flake8-import-order", "pep8-naming"] +pep8test = ["black", "ruff"] sdist = ["setuptools-rust (>=0.11.4)"] ssh = ["bcrypt (>=3.1.5)"] test = ["hypothesis (>=1.11.4,!=3.79.2)", "iso8601", "pretend", "pytest (>=6.2.0)", "pytest-benchmark", "pytest-cov", "pytest-subtests", "pytest-xdist", "pytz"] @@ -326,11 +339,11 @@ python-versions = ">=3.5" [[package]] name = "dill" -version = "0.3.6" +version = "0.3.5.1" description = "serialize all of python" category = "main" optional = false -python-versions = ">=3.7" +python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*, !=3.6.*" [package.extras] graph = ["objgraph (>=1.7.2)"] @@ -343,6 +356,14 @@ category = "dev" optional = false python-versions = "*" +[[package]] +name = "dm-tree" +version = "0.1.8" +description = "Tree is a library for working with nested data structures." +category = "main" +optional = false +python-versions = "*" + [[package]] name = "docker" version = "6.0.1" @@ -389,7 +410,7 @@ python-versions = ">=3.6" [[package]] name = "exceptiongroup" -version = "1.0.4" +version = "1.1.0" description = "Backport of PEP 654 (exception groups)" category = "dev" optional = false @@ -398,35 +419,57 @@ python-versions = ">=3.7" [package.extras] test = ["pytest (>=6)"] +[[package]] +name = "executing" +version = "1.2.0" +description = "Get the currently executing AST node of a frame, and other information" +category = "main" +optional = false +python-versions = "*" + +[package.extras] +tests = ["asttokens", "littleutils", "pytest", "rich"] + [[package]] name = "fastapi" -version = "0.66.1" +version = "0.85.2" description = "FastAPI framework, high performance, easy to learn, fast to code, ready for production" category = "main" optional = false -python-versions = ">=3.6" +python-versions = ">=3.7" [package.dependencies] pydantic = ">=1.6.2,<1.7 || >1.7,<1.7.1 || >1.7.1,<1.7.2 || >1.7.2,<1.7.3 || >1.7.3,<1.8 || >1.8,<1.8.1 || >1.8.1,<2.0.0" -starlette = "0.14.2" +starlette = "0.20.4" [package.extras] -all = ["aiofiles (>=0.5.0,<0.6.0)", "async_exit_stack (>=1.0.1,<2.0.0)", "async_generator (>=1.10,<2.0.0)", "email_validator (>=1.1.1,<2.0.0)", "graphene (>=2.1.8,<3.0.0)", "itsdangerous (>=1.1.0,<2.0.0)", "jinja2 (>=2.11.2,<3.0.0)", "orjson (>=3.2.1,<4.0.0)", "python-multipart (>=0.0.5,<0.0.6)", "pyyaml (>=5.3.1,<6.0.0)", "requests (>=2.24.0,<3.0.0)", "ujson (>=4.0.1,<5.0.0)", "uvicorn[standard] (>=0.12.0,<0.14.0)"] -dev = ["autoflake (>=1.3.1,<2.0.0)", "flake8 (>=3.8.3,<4.0.0)", "graphene (>=2.1.8,<3.0.0)", "passlib[bcrypt] (>=1.7.2,<2.0.0)", "python-jose[cryptography] (>=3.3.0,<4.0.0)", "uvicorn[standard] (>=0.12.0,<0.14.0)"] -doc = ["markdown-include (>=0.6.0,<0.7.0)", "mkdocs (>=1.1.2,<2.0.0)", "mkdocs-markdownextradata-plugin (>=0.1.7,<0.2.0)", "mkdocs-material (>=7.1.9,<8.0.0)", "pyyaml (>=5.3.1,<6.0.0)", "typer-cli (>=0.0.12,<0.0.13)"] -test = ["aiofiles (>=0.5.0,<0.6.0)", "async_exit_stack (>=1.0.1,<2.0.0)", "async_generator (>=1.10,<2.0.0)", "black (==20.8b1)", "databases[sqlite] (>=0.3.2,<0.4.0)", "email_validator (>=1.1.1,<2.0.0)", "flake8 (>=3.8.3,<4.0.0)", "flask (>=1.1.2,<2.0.0)", "httpx (>=0.14.0,<0.15.0)", "isort (>=5.0.6,<6.0.0)", "mypy (==0.812)", "orjson (>=3.2.1,<4.0.0)", "peewee (>=3.13.3,<4.0.0)", "pytest (>=6.2.4,<7.0.0)", "pytest-asyncio (>=0.14.0,<0.15.0)", "pytest-cov (>=2.12.0,<3.0.0)", "python-multipart (>=0.0.5,<0.0.6)", "requests (>=2.24.0,<3.0.0)", "sqlalchemy (>=1.3.18,<1.4.0)", "ujson (>=4.0.1,<5.0.0)"] +all = ["email-validator (>=1.1.1,<2.0.0)", "itsdangerous (>=1.1.0,<3.0.0)", "jinja2 (>=2.11.2,<4.0.0)", "orjson (>=3.2.1,<4.0.0)", "python-multipart (>=0.0.5,<0.0.6)", "pyyaml (>=5.3.1,<7.0.0)", "requests (>=2.24.0,<3.0.0)", "ujson (>=4.0.1,!=4.0.2,!=4.1.0,!=4.2.0,!=4.3.0,!=5.0.0,!=5.1.0,<6.0.0)", "uvicorn[standard] (>=0.12.0,<0.19.0)"] +dev = ["autoflake (>=1.4.0,<2.0.0)", "flake8 (>=3.8.3,<6.0.0)", "pre-commit (>=2.17.0,<3.0.0)", "uvicorn[standard] (>=0.12.0,<0.19.0)"] +doc = ["mdx-include (>=1.4.1,<2.0.0)", "mkdocs (>=1.1.2,<2.0.0)", "mkdocs-markdownextradata-plugin (>=0.1.7,<0.3.0)", "mkdocs-material (>=8.1.4,<9.0.0)", "pyyaml (>=5.3.1,<7.0.0)", "typer[all] (>=0.6.1,<0.7.0)"] +test = ["anyio[trio] (>=3.2.1,<4.0.0)", "black (==22.8.0)", "databases[sqlite] (>=0.3.2,<0.7.0)", "email-validator (>=1.1.1,<2.0.0)", "flake8 (>=3.8.3,<6.0.0)", "flask (>=1.1.2,<3.0.0)", "httpx (>=0.23.0,<0.24.0)", "isort (>=5.0.6,<6.0.0)", "mypy (==0.982)", "orjson (>=3.2.1,<4.0.0)", "passlib[bcrypt] (>=1.7.2,<2.0.0)", "peewee (>=3.13.3,<4.0.0)", "pytest (>=7.1.3,<8.0.0)", "pytest-cov (>=2.12.0,<5.0.0)", "python-jose[cryptography] (>=3.3.0,<4.0.0)", "python-multipart (>=0.0.5,<0.0.6)", "pyyaml (>=5.3.1,<7.0.0)", "requests (>=2.24.0,<3.0.0)", "sqlalchemy (>=1.3.18,<=1.4.41)", "types-orjson (==3.6.2)", "types-ujson (==5.5.0)", "ujson (>=4.0.1,!=4.0.2,!=4.1.0,!=4.2.0,!=4.3.0,!=5.0.0,!=5.1.0,<6.0.0)"] + +[[package]] +name = "fastdtw" +version = "0.3.4" +description = "Dynamic Time Warping (DTW) algorithm with an O(N) time and memory complexity." +category = "main" +optional = false +python-versions = "*" + +[package.dependencies] +numpy = "*" [[package]] name = "filelock" -version = "3.8.2" +version = "3.9.0" description = "A platform independent file lock." category = "dev" optional = false python-versions = ">=3.7" [package.extras] -docs = ["furo (>=2022.9.29)", "sphinx (>=5.3)", "sphinx-autodoc-typehints (>=1.19.5)"] -testing = ["covdefaults (>=2.2.2)", "coverage (>=6.5)", "pytest (>=7.2)", "pytest-cov (>=4)", "pytest-timeout (>=2.1)"] +docs = ["furo (>=2022.12.7)", "sphinx (>=5.3)", "sphinx-autodoc-typehints (>=1.19.5)"] +testing = ["covdefaults (>=2.2.2)", "coverage (>=7.0.1)", "pytest (>=7.2)", "pytest-cov (>=4)", "pytest-timeout (>=2.1)"] [[package]] name = "flake8" @@ -442,7 +485,7 @@ pycodestyle = ">=2.10.0,<2.11.0" pyflakes = ">=3.0.0,<3.1.0" [[package]] -name = "Flask" +name = "flask" version = "2.2.2" description = "A simple framework for building complex web applications." category = "main" @@ -460,6 +503,14 @@ Werkzeug = ">=2.2.2" async = ["asgiref (>=3.2)"] dotenv = ["python-dotenv"] +[[package]] +name = "flatbuffers" +version = "23.1.21" +description = "The FlatBuffers serialization format for Python" +category = "main" +optional = false +python-versions = "*" + [[package]] name = "formattex" version = "0.0.3" @@ -507,6 +558,14 @@ smb = ["smbprotocol"] ssh = ["paramiko"] tqdm = ["tqdm"] +[[package]] +name = "gast" +version = "0.5.3" +description = "Python AST that abstracts the underlying Python version" +category = "main" +optional = false +python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*" + [[package]] name = "ghp-import" version = "2.1.0" @@ -533,8 +592,8 @@ python-versions = ">=3.7" smmap = ">=3.0.1,<6" [[package]] -name = "GitPython" -version = "3.1.29" +name = "gitpython" +version = "3.1.30" description = "GitPython is a python library used to interact with Git repositories" category = "main" optional = false @@ -543,6 +602,53 @@ python-versions = ">=3.7" [package.dependencies] gitdb = ">=4.0.1,<5" +[[package]] +name = "google-auth" +version = "2.16.1" +description = "Google Authentication Library" +category = "main" +optional = false +python-versions = ">=2.7,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*" + +[package.dependencies] +cachetools = ">=2.0.0,<6.0" +pyasn1-modules = ">=0.2.1" +rsa = {version = ">=3.1.4,<5", markers = "python_version >= \"3.6\""} +six = ">=1.9.0" + +[package.extras] +aiohttp = ["aiohttp (>=3.6.2,<4.0.0dev)", "requests (>=2.20.0,<3.0.0dev)"] +enterprise-cert = ["cryptography (==36.0.2)", "pyopenssl (==22.0.0)"] +pyopenssl = ["cryptography (>=38.0.3)", "pyopenssl (>=20.0.0)"] +reauth = ["pyu2f (>=0.1.5)"] +requests = ["requests (>=2.20.0,<3.0.0dev)"] + +[[package]] +name = "google-auth-oauthlib" +version = "0.4.6" +description = "Google Authentication Library" +category = "main" +optional = false +python-versions = ">=3.6" + +[package.dependencies] +google-auth = ">=1.0.0" +requests-oauthlib = ">=0.7.0" + +[package.extras] +tool = ["click (>=6.0.0)"] + +[[package]] +name = "google-pasta" +version = "0.2.0" +description = "pasta is an AST-based Python refactoring library" +category = "main" +optional = false +python-versions = "*" + +[package.dependencies] +six = "*" + [[package]] name = "graphql-core" version = "3.2.3" @@ -553,7 +659,7 @@ python-versions = ">=3.6,<4" [[package]] name = "greenlet" -version = "2.0.1" +version = "2.0.2" description = "Lightweight in-process concurrent programming" category = "main" optional = false @@ -561,11 +667,11 @@ python-versions = ">=2.7,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*" [package.extras] docs = ["Sphinx", "docutils (<0.18)"] -test = ["faulthandler", "objgraph", "psutil"] +test = ["objgraph", "psutil"] [[package]] name = "griffe" -version = "0.24.1" +version = "0.25.4" description = "Signatures for entire Python programs. Extract the structure, the frame, the skeleton of your project, to generate API documentation or find breaking changes in your API." category = "dev" optional = false @@ -577,6 +683,17 @@ colorama = ">=0.4" [package.extras] async = ["aiofiles (>=0.7,<1.0)"] +[[package]] +name = "grpcio" +version = "1.51.3" +description = "HTTP/2-based RPC framework" +category = "main" +optional = false +python-versions = ">=3.7" + +[package.extras] +protobuf = ["grpcio-tools (>=1.51.3)"] + [[package]] name = "gunicorn" version = "20.1.0" @@ -602,6 +719,17 @@ category = "main" optional = false python-versions = ">=3.7" +[[package]] +name = "h5py" +version = "3.8.0" +description = "Read and write HDF5 files from Python" +category = "main" +optional = false +python-versions = ">=3.7" + +[package.dependencies] +numpy = ">=1.14.5" + [[package]] name = "httptools" version = "0.5.0" @@ -615,7 +743,7 @@ test = ["Cython (>=0.29.24,<0.30.0)"] [[package]] name = "identify" -version = "2.5.9" +version = "2.5.17" description = "File identification library for Python" category = "dev" optional = false @@ -634,7 +762,7 @@ python-versions = ">=3.5" [[package]] name = "importlib-metadata" -version = "5.1.0" +version = "6.0.0" description = "Read metadata from Python packages" category = "main" optional = false @@ -644,13 +772,13 @@ python-versions = ">=3.7" zipp = ">=0.5" [package.extras] -docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)"] +docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"] perf = ["ipython"] testing = ["flake8 (<5)", "flufl.flake8", "importlib-resources (>=1.3)", "packaging", "pyfakefs", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-flake8", "pytest-mypy (>=0.9.1)", "pytest-perf (>=0.9.2)"] [[package]] name = "importlib-resources" -version = "5.10.1" +version = "5.10.2" description = "Read resources from Python packages" category = "main" optional = false @@ -660,24 +788,24 @@ python-versions = ">=3.7" zipp = {version = ">=3.1.0", markers = "python_version < \"3.10\""} [package.extras] -docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)"] +docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"] testing = ["flake8 (<5)", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-flake8", "pytest-mypy (>=0.9.1)"] [[package]] name = "iniconfig" -version = "1.1.1" -description = "iniconfig: brain-dead simple config-ini parsing" +version = "2.0.0" +description = "brain-dead simple config-ini parsing" category = "dev" optional = false -python-versions = "*" +python-versions = ">=3.7" [[package]] name = "ipython" -version = "7.34.0" +version = "8.9.0" description = "IPython: Productive Interactive Computing" category = "main" optional = false -python-versions = ">=3.7" +python-versions = ">=3.8" [package.dependencies] appnope = {version = "*", markers = "sys_platform == \"darwin\""} @@ -688,21 +816,23 @@ jedi = ">=0.16" matplotlib-inline = "*" pexpect = {version = ">4.3", markers = "sys_platform != \"win32\""} pickleshare = "*" -prompt-toolkit = ">=2.0.0,<3.0.0 || >3.0.0,<3.0.1 || >3.0.1,<3.1.0" -pygments = "*" -setuptools = ">=18.5" -traitlets = ">=4.2" +prompt-toolkit = ">=3.0.30,<3.1.0" +pygments = ">=2.4.0" +stack-data = "*" +traitlets = ">=5" [package.extras] -all = ["Sphinx (>=1.3)", "ipykernel", "ipyparallel", "ipywidgets", "nbconvert", "nbformat", "nose (>=0.10.1)", "notebook", "numpy (>=1.17)", "pygments", "qtconsole", "requests", "testpath"] -doc = ["Sphinx (>=1.3)"] +all = ["black", "curio", "docrepr", "ipykernel", "ipyparallel", "ipywidgets", "matplotlib", "matplotlib (!=3.2.0)", "nbconvert", "nbformat", "notebook", "numpy (>=1.20)", "pandas", "pytest (<7)", "pytest (<7.1)", "pytest-asyncio", "qtconsole", "setuptools (>=18.5)", "sphinx (>=1.3)", "sphinx-rtd-theme", "stack-data", "testpath", "trio", "typing-extensions"] +black = ["black"] +doc = ["docrepr", "ipykernel", "matplotlib", "pytest (<7)", "pytest (<7.1)", "pytest-asyncio", "setuptools (>=18.5)", "sphinx (>=1.3)", "sphinx-rtd-theme", "stack-data", "testpath", "typing-extensions"] kernel = ["ipykernel"] nbconvert = ["nbconvert"] nbformat = ["nbformat"] notebook = ["ipywidgets", "notebook"] parallel = ["ipyparallel"] qtconsole = ["qtconsole"] -test = ["ipykernel", "nbformat", "nose (>=0.10.1)", "numpy (>=1.17)", "pygments", "requests", "testpath"] +test = ["pytest (<7.1)", "pytest-asyncio", "testpath"] +test-extra = ["curio", "matplotlib (!=3.2.0)", "nbformat", "numpy (>=1.20)", "pandas", "pytest (<7.1)", "pytest-asyncio", "testpath", "trio"] [[package]] name = "itsdangerous" @@ -729,7 +859,7 @@ qa = ["flake8 (==3.8.3)", "mypy (==0.782)"] testing = ["Django (<3.1)", "attrs", "colorama", "docopt", "pytest (<7.0.0)"] [[package]] -name = "Jinja2" +name = "jinja2" version = "3.1.2" description = "A very fast and expressive template engine." category = "main" @@ -762,6 +892,14 @@ category = "main" optional = false python-versions = ">=2.6, !=3.0.*, !=3.1.*, !=3.2.*" +[[package]] +name = "joblib" +version = "1.2.0" +description = "Lightweight pipelining with Python functions" +category = "main" +optional = false +python-versions = ">=3.7" + [[package]] name = "kedro" version = "0.18.4" @@ -794,58 +932,58 @@ toposort = ">=1.7,<2.0" [package.extras] all = ["Jinja2 (<3.1.0)", "Pillow (>=9.0,<10.0)", "PyYAML (>=4.2,<7.0)", "SQLAlchemy (>=1.2,<2.0)", "biopython (>=1.73,<2.0)", "compress-pickle[lz4] (>=2.1.0,<2.2.0)", "dask[complete] (>=2021.10,<2022.0)", "delta-spark (>=1.0,<3.0)", "docutils (==0.16)", "geopandas (>=0.6.0,<1.0)", "hdfs (>=2.5.8,<3.0)", "holoviews (>=1.13.0,<1.14.0)", "ipykernel (>=5.3,<7.0)", "lxml (>=4.6,<5.0)", "matplotlib (>=3.0.3,<4.0)", "myst-parser (>=0.17.2,<0.18.0)", "nbsphinx (==0.8.1)", "nbstripout (>=0.4,<1.0)", "networkx (>=2.4,<3.0)", "opencv-python (>=4.5.5.64,<4.6.0.0)", "openpyxl (>=3.0.6,<4.0)", "pandas (>=1.3,<2.0)", "pandas-gbq (>=0.12.0,<0.18.0)", "plotly (>=4.8.0,<6.0)", "pyarrow (>=1.0,<7.0)", "pyproj (>=3.0,<4.0)", "pyspark (>=2.2,<4.0)", "redis (>=4.1,<5.0)", "requests (>=2.20,<3.0)", "s3fs (>=0.3.0,<0.5)", "scikit-learn (>=1.0.2,<1.1.0)", "scipy (>=1.7.3,<1.8.0)", "sphinx (>=3.4.3,<3.5.0)", "sphinx-autodoc-typehints (==1.11.1)", "sphinx-copybutton (==0.3.1)", "sphinx-rtd-theme (==1.1.1)", "sphinxcontrib-mermaid (>=0.7.1,<0.8.0)", "tables (>=3.6,<4.0)", "tables (>=3.6.0,<3.7.0)", "tensorflow (>=2.0,<3.0)", "triad (>=0.6.7,<1.0)"] api = ["requests (>=2.20,<3.0)"] -"api.apidataset" = ["requests (>=2.20,<3.0)"] +api-apidataset = ["requests (>=2.20,<3.0)"] biosequence = ["biopython (>=1.73,<2.0)"] -"biosequence.biosequencedataset" = ["biopython (>=1.73,<2.0)"] +biosequence-biosequencedataset = ["biopython (>=1.73,<2.0)"] dask = ["dask[complete] (>=2021.10,<2022.0)", "triad (>=0.6.7,<1.0)"] -"dask.parquetdataset" = ["dask[complete] (>=2021.10,<2022.0)", "triad (>=0.6.7,<1.0)"] +dask-parquetdataset = ["dask[complete] (>=2021.10,<2022.0)", "triad (>=0.6.7,<1.0)"] docs = ["Jinja2 (<3.1.0)", "docutils (==0.16)", "ipykernel (>=5.3,<7.0)", "myst-parser (>=0.17.2,<0.18.0)", "nbsphinx (==0.8.1)", "nbstripout (>=0.4,<1.0)", "sphinx (>=3.4.3,<3.5.0)", "sphinx-autodoc-typehints (==1.11.1)", "sphinx-copybutton (==0.3.1)", "sphinx-rtd-theme (==1.1.1)", "sphinxcontrib-mermaid (>=0.7.1,<0.8.0)"] geopandas = ["geopandas (>=0.6.0,<1.0)", "pyproj (>=3.0,<4.0)"] -"geopandas.geojsondataset" = ["geopandas (>=0.6.0,<1.0)", "pyproj (>=3.0,<4.0)"] +geopandas-geojsondataset = ["geopandas (>=0.6.0,<1.0)", "pyproj (>=3.0,<4.0)"] holoviews = ["holoviews (>=1.13.0,<1.14.0)"] -"holoviews.holoviewswriter" = ["holoviews (>=1.13.0,<1.14.0)"] +holoviews-holoviewswriter = ["holoviews (>=1.13.0,<1.14.0)"] matplotlib = ["matplotlib (>=3.0.3,<4.0)"] -"matplotlib.matplotlibwriter" = ["matplotlib (>=3.0.3,<4.0)"] +matplotlib-matplotlibwriter = ["matplotlib (>=3.0.3,<4.0)"] networkx = ["networkx (>=2.4,<3.0)"] -"networkx.networkxdataset" = ["networkx (>=2.4,<3.0)"] +networkx-networkxdataset = ["networkx (>=2.4,<3.0)"] pandas = ["SQLAlchemy (>=1.2,<2.0)", "lxml (>=4.6,<5.0)", "openpyxl (>=3.0.6,<4.0)", "pandas (>=1.3,<2.0)", "pandas-gbq (>=0.12.0,<0.18.0)", "pyarrow (>=1.0,<7.0)", "tables (>=3.6,<4.0)", "tables (>=3.6.0,<3.7.0)"] -"pandas.csvdataset" = ["pandas (>=1.3,<2.0)"] -"pandas.exceldataset" = ["openpyxl (>=3.0.6,<4.0)", "pandas (>=1.3,<2.0)"] -"pandas.featherdataset" = ["pandas (>=1.3,<2.0)"] -"pandas.gbqquerydataset" = ["pandas (>=1.3,<2.0)", "pandas-gbq (>=0.12.0,<0.18.0)"] -"pandas.gbqtabledataset" = ["pandas (>=1.3,<2.0)", "pandas-gbq (>=0.12.0,<0.18.0)"] -"pandas.genericdataset" = ["pandas (>=1.3,<2.0)"] -"pandas.hdfdataset" = ["pandas (>=1.3,<2.0)", "tables (>=3.6,<4.0)", "tables (>=3.6.0,<3.7.0)"] -"pandas.jsondataset" = ["pandas (>=1.3,<2.0)"] -"pandas.parquetdataset" = ["pandas (>=1.3,<2.0)", "pyarrow (>=1.0,<7.0)"] -"pandas.sqlquerydataset" = ["SQLAlchemy (>=1.2,<2.0)", "pandas (>=1.3,<2.0)"] -"pandas.sqltabledataset" = ["SQLAlchemy (>=1.2,<2.0)", "pandas (>=1.3,<2.0)"] -"pandas.xmldataset" = ["lxml (>=4.6,<5.0)", "pandas (>=1.3,<2.0)"] +pandas-csvdataset = ["pandas (>=1.3,<2.0)"] +pandas-exceldataset = ["openpyxl (>=3.0.6,<4.0)", "pandas (>=1.3,<2.0)"] +pandas-featherdataset = ["pandas (>=1.3,<2.0)"] +pandas-gbqquerydataset = ["pandas (>=1.3,<2.0)", "pandas-gbq (>=0.12.0,<0.18.0)"] +pandas-gbqtabledataset = ["pandas (>=1.3,<2.0)", "pandas-gbq (>=0.12.0,<0.18.0)"] +pandas-genericdataset = ["pandas (>=1.3,<2.0)"] +pandas-hdfdataset = ["pandas (>=1.3,<2.0)", "tables (>=3.6,<4.0)", "tables (>=3.6.0,<3.7.0)"] +pandas-jsondataset = ["pandas (>=1.3,<2.0)"] +pandas-parquetdataset = ["pandas (>=1.3,<2.0)", "pyarrow (>=1.0,<7.0)"] +pandas-sqlquerydataset = ["SQLAlchemy (>=1.2,<2.0)", "pandas (>=1.3,<2.0)"] +pandas-sqltabledataset = ["SQLAlchemy (>=1.2,<2.0)", "pandas (>=1.3,<2.0)"] +pandas-xmldataset = ["lxml (>=4.6,<5.0)", "pandas (>=1.3,<2.0)"] pickle = ["compress-pickle[lz4] (>=2.1.0,<2.2.0)"] -"pickle.pickledataset" = ["compress-pickle[lz4] (>=2.1.0,<2.2.0)"] +pickle-pickledataset = ["compress-pickle[lz4] (>=2.1.0,<2.2.0)"] pillow = ["Pillow (>=9.0,<10.0)"] -"pillow.imagedataset" = ["Pillow (>=9.0,<10.0)"] +pillow-imagedataset = ["Pillow (>=9.0,<10.0)"] plotly = ["pandas (>=1.3,<2.0)", "plotly (>=4.8.0,<6.0)"] -"plotly.jsondataset" = ["plotly (>=4.8.0,<6.0)"] -"plotly.plotlydataset" = ["pandas (>=1.3,<2.0)", "plotly (>=4.8.0,<6.0)"] +plotly-jsondataset = ["plotly (>=4.8.0,<6.0)"] +plotly-plotlydataset = ["pandas (>=1.3,<2.0)", "plotly (>=4.8.0,<6.0)"] redis = ["redis (>=4.1,<5.0)"] spark = ["delta-spark (>=1.0,<3.0)", "hdfs (>=2.5.8,<3.0)", "pyspark (>=2.2,<4.0)", "s3fs (>=0.3.0,<0.5)"] -"spark.deltatabledataset" = ["delta-spark (>=1.0,<3.0)", "hdfs (>=2.5.8,<3.0)", "pyspark (>=2.2,<4.0)", "s3fs (>=0.3.0,<0.5)"] -"spark.sparkdataset" = ["hdfs (>=2.5.8,<3.0)", "pyspark (>=2.2,<4.0)", "s3fs (>=0.3.0,<0.5)"] -"spark.sparkhivedataset" = ["hdfs (>=2.5.8,<3.0)", "pyspark (>=2.2,<4.0)", "s3fs (>=0.3.0,<0.5)"] -"spark.sparkjdbcdataset" = ["hdfs (>=2.5.8,<3.0)", "pyspark (>=2.2,<4.0)", "s3fs (>=0.3.0,<0.5)"] +spark-deltatabledataset = ["delta-spark (>=1.0,<3.0)", "hdfs (>=2.5.8,<3.0)", "pyspark (>=2.2,<4.0)", "s3fs (>=0.3.0,<0.5)"] +spark-sparkdataset = ["hdfs (>=2.5.8,<3.0)", "pyspark (>=2.2,<4.0)", "s3fs (>=0.3.0,<0.5)"] +spark-sparkhivedataset = ["hdfs (>=2.5.8,<3.0)", "pyspark (>=2.2,<4.0)", "s3fs (>=0.3.0,<0.5)"] +spark-sparkjdbcdataset = ["hdfs (>=2.5.8,<3.0)", "pyspark (>=2.2,<4.0)", "s3fs (>=0.3.0,<0.5)"] svmlight = ["scikit-learn (>=1.0.2,<1.1.0)", "scipy (>=1.7.3,<1.8.0)"] -"svmlight.svmlightdataset" = ["scikit-learn (>=1.0.2,<1.1.0)", "scipy (>=1.7.3,<1.8.0)"] +svmlight-svmlightdataset = ["scikit-learn (>=1.0.2,<1.1.0)", "scipy (>=1.7.3,<1.8.0)"] tensorflow = ["tensorflow (>=2.0,<3.0)"] -"tensorflow.tensorflowmodeldataset" = ["tensorflow (>=2.0,<3.0)"] +tensorflow-tensorflowmodeldataset = ["tensorflow (>=2.0,<3.0)"] video = ["opencv-python (>=4.5.5.64,<4.6.0.0)"] -"video.videodataset" = ["opencv-python (>=4.5.5.64,<4.6.0.0)"] +video-videodataset = ["opencv-python (>=4.5.5.64,<4.6.0.0)"] yaml = ["PyYAML (>=4.2,<7.0)", "pandas (>=1.3,<2.0)"] -"yaml.yamldataset" = ["PyYAML (>=4.2,<7.0)", "pandas (>=1.3,<2.0)"] +yaml-yamldataset = ["PyYAML (>=4.2,<7.0)", "pandas (>=1.3,<2.0)"] [[package]] name = "kedro-mlflow" -version = "0.11.4" +version = "0.11.7" description = "A kedro-plugin to use mlflow in your kedro projects" category = "main" optional = false @@ -858,34 +996,67 @@ pydantic = ">=1.0.0,<2.0.0" [package.extras] dev = ["jupyter (>=1.0.0,<2.0.0)", "pre-commit (>=2.0.0,<3.0.0)"] -doc = ["myst-parser (>=0.17.2,<0.19.0)", "sphinx (>=4.5.0,<6.0.0)", "sphinx-click (>=3.1,<4.4)", "sphinx-markdown-tables (>=0.0.15,<0.1.0)", "sphinx_copybutton (>=0.5.0,<0.6.0)", "sphinx_rtd_theme (>=1.0.0,<1.1.0)"] -extras = ["notebook (>=6.0.0)"] -test = ["black (==22.8.0)", "flake8 (==5.0.4)", "isort (==5.10.1)", "pytest (>=5.4.0,<8.0.0)", "pytest-cov (>=2.8.0,<4.0.0)", "pytest-lazy-fixture (>=0.6.0,<1.0.0)", "pytest-mock (>=3.1.0,<4.0.0)", "scikit-learn (>=0.23.0,<1.2.0)"] +doc = ["myst-parser (>=0.17.2,<0.19.0)", "sphinx (>=4.5.0,<7.0.0)", "sphinx-click (>=3.1,<4.5)", "sphinx-markdown-tables (>=0.0.15,<0.1.0)", "sphinx_copybutton (>=0.5.0,<0.6.0)", "sphinx_rtd_theme (>=1.0,<1.2)"] +test = ["black (==22.12.0)", "flake8 (==5.0.4)", "isort (==5.11.4)", "pytest (>=5.4.0,<8.0.0)", "pytest-cov (>=2.8.0,<5.0.0)", "pytest-lazy-fixture (>=0.6.0,<1.0.0)", "pytest-mock (>=3.1.0,<4.0.0)", "scikit-learn (>=0.23.0,<1.3.0)"] [[package]] name = "kedro-viz" -version = "5.1.1" +version = "5.2.1" description = "Kedro-Viz helps visualise Kedro data and analytics pipelines" category = "main" optional = false python-versions = ">=3.7, <3.11" [package.dependencies] -aiofiles = "0.6.0" -fastapi = ">=0.63.0,<0.67.0" -ipython = ">=7.0.0,<8.0" +aiofiles = "22.1.0" +fastapi = ">=0.73.0,<0.86.0" +ipython = ">=7.0.0,<9.0" kedro = ">=0.17.0" networkx = ">=1.0" +orjson = ">=3.8,<4.0" pandas = ">=0.24" plotly = ">=4.0" -semver = ">=2.10,<3.0" -sqlalchemy = ">=1.2,<2.0" -strawberry-graphql = ">=0.99.0,<=0.127.0" -uvicorn = {version = ">=0.17.0,<0.18.0", extras = ["standard"]} -watchgod = ">=0.8.0,<0.9.0" +semver = ">=2.13,<3.0" +sqlalchemy = ">=1.4,<2.0" +strawberry-graphql = ">=0.99.0,<1.0" +uvicorn = {version = ">=0.20.0,<0.21.0", extras = ["standard"]} +watchgod = ">=0.8.2,<0.9.0" + +[[package]] +name = "keras" +version = "2.8.0" +description = "Deep learning for humans." +category = "main" +optional = false +python-versions = "*" + +[[package]] +name = "keras-preprocessing" +version = "1.1.2" +description = "Easy data preprocessing and data augmentation for deep learning models" +category = "main" +optional = false +python-versions = "*" + +[package.dependencies] +numpy = ">=1.9.1" +six = ">=1.9.0" + +[package.extras] +image = ["Pillow (>=5.2.0)", "scipy (>=0.14)"] +pep8 = ["flake8"] +tests = ["Pillow", "keras", "pandas", "pytest", "pytest-cov", "pytest-xdist", "tensorflow"] [[package]] -name = "Mako" +name = "libclang" +version = "15.0.6.1" +description = "Clang Python Bindings, mirrored from the official LLVM repo: https://github.com/llvm/llvm-project/tree/main/clang/bindings/python, to make the installation process easier." +category = "main" +optional = false +python-versions = "*" + +[[package]] +name = "mako" version = "1.2.4" description = "A super-fast templating language that borrows the best ideas from the existing templating languages." category = "main" @@ -901,10 +1072,10 @@ lingua = ["lingua"] testing = ["pytest"] [[package]] -name = "Markdown" +name = "markdown" version = "3.3.7" description = "Python implementation of Markdown." -category = "dev" +category = "main" optional = false python-versions = ">=3.6" @@ -929,8 +1100,8 @@ markdown = ">=3.0" tests = ["pytest"] [[package]] -name = "MarkupSafe" -version = "2.1.1" +name = "markupsafe" +version = "2.1.2" description = "Safely add untrusted strings to HTML/XML markup." category = "main" optional = false @@ -1027,7 +1198,7 @@ python-versions = ">=3.7" [[package]] name = "mkdocstrings" -version = "0.19.0" +version = "0.19.1" description = "Automatic documentation from sources, for MkDocs." category = "dev" optional = false @@ -1048,7 +1219,7 @@ python-legacy = ["mkdocstrings-python-legacy (>=0.2.1)"] [[package]] name = "mkdocstrings-python" -version = "0.8.2" +version = "0.8.3" description = "A Python handler for mkdocstrings." category = "dev" optional = false @@ -1119,17 +1290,17 @@ python-versions = "*" [[package]] name = "networkx" -version = "2.8.8" +version = "3.0" description = "Python package for creating and manipulating graphs and networks" category = "main" optional = false python-versions = ">=3.8" [package.extras] -default = ["matplotlib (>=3.4)", "numpy (>=1.19)", "pandas (>=1.3)", "scipy (>=1.8)"] -developer = ["mypy (>=0.982)", "pre-commit (>=2.20)"] -doc = ["nb2plots (>=0.6)", "numpydoc (>=1.5)", "pillow (>=9.2)", "pydata-sphinx-theme (>=0.11)", "sphinx (>=5.2)", "sphinx-gallery (>=0.11)", "texext (>=0.6.6)"] -extra = ["lxml (>=4.6)", "pydot (>=1.4.2)", "pygraphviz (>=1.9)", "sympy (>=1.10)"] +default = ["matplotlib (>=3.4)", "numpy (>=1.20)", "pandas (>=1.3)", "scipy (>=1.8)"] +developer = ["mypy (>=0.991)", "pre-commit (>=2.20)"] +doc = ["nb2plots (>=0.6)", "numpydoc (>=1.5)", "pillow (>=9.2)", "pydata-sphinx-theme (>=0.11)", "sphinx (==5.2.3)", "sphinx-gallery (>=0.11)", "texext (>=0.6.7)"] +extra = ["lxml (>=4.6)", "pydot (>=1.4.2)", "pygraphviz (>=1.10)", "sympy (>=1.10)"] test = ["codecov (>=2.1)", "pytest (>=7.2)", "pytest-cov (>=4.0)"] [[package]] @@ -1162,6 +1333,54 @@ category = "main" optional = false python-versions = ">=3.8" +[[package]] +name = "nvidia-cublas-cu11" +version = "11.10.3.66" +description = "CUBLAS native runtime libraries" +category = "main" +optional = false +python-versions = ">=3" + +[package.dependencies] +setuptools = "*" +wheel = "*" + +[[package]] +name = "nvidia-cuda-nvrtc-cu11" +version = "11.7.99" +description = "NVRTC native runtime libraries" +category = "main" +optional = false +python-versions = ">=3" + +[package.dependencies] +setuptools = "*" +wheel = "*" + +[[package]] +name = "nvidia-cuda-runtime-cu11" +version = "11.7.99" +description = "CUDA Runtime native Libraries" +category = "main" +optional = false +python-versions = ">=3" + +[package.dependencies] +setuptools = "*" +wheel = "*" + +[[package]] +name = "nvidia-cudnn-cu11" +version = "8.5.0.96" +description = "cuDNN runtime libraries" +category = "main" +optional = false +python-versions = ">=3" + +[package.dependencies] +setuptools = "*" +wheel = "*" + [[package]] name = "oauthlib" version = "3.2.2" @@ -1175,9 +1394,32 @@ rsa = ["cryptography (>=3.0.0)"] signals = ["blinker (>=1.4.0)"] signedtoken = ["cryptography (>=3.0.0)", "pyjwt (>=2.0.0,<3)"] +[[package]] +name = "opt-einsum" +version = "3.3.0" +description = "Optimizing numpys einsum function" +category = "main" +optional = false +python-versions = ">=3.5" + +[package.dependencies] +numpy = ">=1.7" + +[package.extras] +docs = ["numpydoc", "sphinx (==1.2.3)", "sphinx-rtd-theme", "sphinxcontrib-napoleon"] +tests = ["pytest", "pytest-cov", "pytest-pep8"] + +[[package]] +name = "orjson" +version = "3.8.5" +description = "Fast, correct Python JSON library supporting dataclasses, datetimes, and numpy" +category = "main" +optional = false +python-versions = ">=3.7" + [[package]] name = "packaging" -version = "22.0" +version = "23.0" description = "Core utilities for Python packages" category = "main" optional = false @@ -1185,7 +1427,7 @@ python-versions = ">=3.7" [[package]] name = "pandas" -version = "1.5.2" +version = "1.5.3" description = "Powerful data structures for data analysis, time series, and statistics" category = "main" optional = false @@ -1216,7 +1458,7 @@ testing = ["docopt", "pytest (<6.0.0)"] [[package]] name = "pathspec" -version = "0.10.2" +version = "0.11.0" description = "Utility library for gitignore style pattern matching of file paths." category = "main" optional = false @@ -1224,33 +1466,42 @@ python-versions = ">=3.7" [[package]] name = "pbr" -version = "5.11.0" +version = "5.11.1" description = "Python Build Reasonableness" category = "main" optional = false python-versions = ">=2.6" [[package]] -name = "pep517" -version = "0.13.0" -description = "Wrappers to build Python packages using PEP 517 hooks" +name = "pexpect" +version = "4.8.0" +description = "Pexpect allows easy control of interactive console applications." category = "main" optional = false -python-versions = ">=3.6" +python-versions = "*" [package.dependencies] -tomli = {version = ">=1.1.0", markers = "python_version < \"3.11\""} +ptyprocess = ">=0.5" [[package]] -name = "pexpect" -version = "4.8.0" -description = "Pexpect allows easy control of interactive console applications." +name = "phasespace" +version = "1.8.0" +description = "TensorFlow implementation of the Raubold and Lynch method for n-body events" category = "main" optional = false -python-versions = "*" +python-versions = ">=3.7" [package.dependencies] -ptyprocess = ">=0.5" +tensorflow = ">=2.7" +tensorflow-probability = ">=0.15,<=0.18" + +[package.extras] +dev = ["Sphinx", "awkward (>=1.0,<2.0)", "bumpversion", "coverage", "decaylanguage (>=0.12.0)", "flaky", "graphviz", "jupyter-sphinx", "matplotlib", "myst-nb", "nbval", "numpy", "particle (>=0.16.0)", "pre-commit", "pytest", "pytest-cov", "pytest-xdist", "scipy", "sphinx-bootstrap-theme", "sphinx-math-dollar", "twine", "uproot (>=4.0,<5.0)", "watchdog", "wget", "zfit (>=0.10.0)", "zfit-physics (>=0.3)"] +doc = ["Sphinx", "decaylanguage (>=0.12.0)", "graphviz", "jupyter-sphinx", "myst-nb", "particle (>=0.16.0)", "sphinx-bootstrap-theme", "sphinx-math-dollar", "zfit (>=0.10.0)", "zfit-physics (>=0.3)"] +fromdecay = ["decaylanguage (>=0.12.0)", "particle (>=0.16.0)", "zfit (>=0.10.0)", "zfit-physics (>=0.3)"] +tensorflow = ["tensorflow", "tensorflow-probability"] +test = ["awkward (>=1.0,<2.0)", "coverage", "decaylanguage (>=0.12.0)", "flaky", "matplotlib", "nbval", "numpy", "particle (>=0.16.0)", "pytest", "pytest-cov", "pytest-xdist", "scipy", "uproot (>=4.0,<5.0)", "wget", "zfit (>=0.10.0)", "zfit-physics (>=0.3)"] +tf = ["tensorflow", "tensorflow-probability"] [[package]] name = "pickleshare" @@ -1262,7 +1513,7 @@ python-versions = "*" [[package]] name = "pip" -version = "22.3.1" +version = "23.0" description = "The PyPA recommended tool for installing Python packages." category = "main" optional = false @@ -1270,7 +1521,7 @@ python-versions = ">=3.7" [[package]] name = "pip-tools" -version = "6.11.0" +version = "6.12.2" description = "pip-tools keeps your pinned dependencies fresh." category = "main" optional = false @@ -1285,23 +1536,23 @@ wheel = "*" [package.extras] coverage = ["pytest-cov"] -testing = ["flit-core (>=2,<4)", "poetry-core (>=1.0.0)", "pytest", "pytest-rerunfailures", "pytest-xdist"] +testing = ["flit-core (>=2,<4)", "poetry-core (>=1.0.0)", "pytest (>=7.2.0)", "pytest-rerunfailures", "pytest-xdist"] [[package]] name = "platformdirs" -version = "2.6.0" +version = "2.6.2" description = "A small Python package for determining appropriate platform-specific dirs, e.g. a \"user data dir\"." category = "main" optional = false python-versions = ">=3.7" [package.extras] -docs = ["furo (>=2022.9.29)", "proselint (>=0.13)", "sphinx (>=5.3)", "sphinx-autodoc-typehints (>=1.19.4)"] -test = ["appdirs (==1.4.4)", "pytest (>=7.2)", "pytest-cov (>=4)", "pytest-mock (>=3.10)"] +docs = ["furo (>=2022.12.7)", "proselint (>=0.13)", "sphinx (>=5.3)", "sphinx-autodoc-typehints (>=1.19.5)"] +test = ["appdirs (==1.4.4)", "covdefaults (>=2.2.2)", "pytest (>=7.2)", "pytest-cov (>=4)", "pytest-mock (>=3.10)"] [[package]] name = "plotly" -version = "5.11.0" +version = "5.13.0" description = "An open-source, interactive data visualization library for Python" category = "main" optional = false @@ -1332,7 +1583,7 @@ python-versions = "*" [[package]] name = "pre-commit" -version = "2.20.0" +version = "2.21.0" description = "A framework for managing and maintaining multi-language pre-commit hooks." category = "dev" optional = false @@ -1343,12 +1594,11 @@ cfgv = ">=2.0.0" identify = ">=1.0.0" nodeenv = ">=0.11.1" pyyaml = ">=5.1" -toml = "*" -virtualenv = ">=20.0.8" +virtualenv = ">=20.10.0" [[package]] name = "prometheus-client" -version = "0.15.0" +version = "0.16.0" description = "Python client for the Prometheus monitoring system." category = "main" optional = false @@ -1382,7 +1632,7 @@ wcwidth = "*" [[package]] name = "protobuf" -version = "4.21.11" +version = "4.21.12" description = "" category = "main" optional = false @@ -1407,6 +1657,36 @@ category = "main" optional = false python-versions = "*" +[[package]] +name = "pure-eval" +version = "0.2.2" +description = "Safely evaluate AST nodes without side effects" +category = "main" +optional = false +python-versions = "*" + +[package.extras] +tests = ["pytest"] + +[[package]] +name = "pyasn1" +version = "0.4.8" +description = "ASN.1 types and codecs" +category = "main" +optional = false +python-versions = "*" + +[[package]] +name = "pyasn1-modules" +version = "0.2.8" +description = "A collection of ASN.1-based protocols modules." +category = "main" +optional = false +python-versions = "*" + +[package.dependencies] +pyasn1 = ">=0.4.6,<0.5.0" + [[package]] name = "pycodestyle" version = "2.10.0" @@ -1425,14 +1705,14 @@ python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*" [[package]] name = "pydantic" -version = "1.10.2" +version = "1.10.4" description = "Data validation and settings management using python type hints" category = "main" optional = false python-versions = ">=3.7" [package.dependencies] -typing-extensions = ">=4.1.0" +typing-extensions = ">=4.2.0" [package.extras] dotenv = ["python-dotenv (>=0.10.4)"] @@ -1447,8 +1727,8 @@ optional = false python-versions = ">=3.6" [[package]] -name = "Pygments" -version = "2.13.0" +name = "pygments" +version = "2.14.0" description = "Pygments is a syntax highlighting package written in Python." category = "main" optional = false @@ -1458,7 +1738,7 @@ python-versions = ">=3.6" plugins = ["importlib-metadata"] [[package]] -name = "PyJWT" +name = "pyjwt" version = "2.6.0" description = "JSON Web Token implementation in Python" category = "main" @@ -1473,7 +1753,7 @@ tests = ["coverage[toml] (==5.0.4)", "pytest (>=6.0.0,<7.0.0)"] [[package]] name = "pymdown-extensions" -version = "9.9" +version = "9.9.2" description = "Extension pack for Python Markdown." category = "dev" optional = false @@ -1482,9 +1762,20 @@ python-versions = ">=3.7" [package.dependencies] markdown = ">=3.2" +[[package]] +name = "pyproject-hooks" +version = "1.0.0" +description = "Wrappers to call pyproject.toml-based build backend hooks." +category = "main" +optional = false +python-versions = ">=3.7" + +[package.dependencies] +tomli = {version = ">=1.1.0", markers = "python_version < \"3.11\""} + [[package]] name = "pytest" -version = "7.2.0" +version = "7.2.1" description = "pytest: simple powerful testing with Python" category = "dev" optional = false @@ -1515,7 +1806,7 @@ six = ">=1.5" [[package]] name = "python-dotenv" -version = "0.21.0" +version = "0.21.1" description = "Read key-value pairs from a .env file and set them as environment variables" category = "main" optional = false @@ -1525,19 +1816,16 @@ python-versions = ">=3.7" cli = ["click (>=5.0)"] [[package]] -name = "python-multipart" -version = "0.0.5" -description = "A streaming multipart parser for Python" +name = "python-json-logger" +version = "2.0.7" +description = "A python library adding a json log formatter" category = "main" optional = false -python-versions = "*" - -[package.dependencies] -six = ">=1.4.0" +python-versions = ">=3.6" [[package]] name = "python-slugify" -version = "7.0.0" +version = "8.0.0" description = "A Python slugify application that also handles Unicode" category = "main" optional = false @@ -1551,34 +1839,26 @@ unidecode = ["Unidecode (>=1.1.1)"] [[package]] name = "pytoolconfig" -version = "1.2.2" +version = "1.2.5" description = "Python tool configuration" category = "main" optional = false python-versions = ">=3.7" [package.dependencies] -appdirs = {version = ">=1.4.4", optional = true, markers = "extra == \"global\""} -packaging = ">=21.3" -tomli = {version = ">=2.0", markers = "python_version < \"3.11\""} +packaging = ">=22.0" +platformdirs = {version = ">=1.4.4", optional = true, markers = "extra == \"global\""} +tomli = {version = ">=2.0.1", markers = "python_version < \"3.11\""} [package.extras] doc = ["sphinx (>=4.5.0)", "tabulate (>=0.8.9)"] -gen_docs = ["pytoolconfig[doc]", "sphinx (>=4.5.0)", "sphinx-autodoc-typehints (>=1.18.1)", "sphinx-rtd-theme (>=1.0.0)"] -global = ["appdirs (>=1.4.4)"] +gendocs = ["pytoolconfig[doc]", "sphinx (>=4.5.0)", "sphinx-autodoc-typehints (>=1.18.1)", "sphinx-rtd-theme (>=1.0.0)"] +global = ["platformdirs (>=1.4.4)"] validation = ["pydantic (>=1.7.4)"] -[[package]] -name = "pytorch" -version = "1.0.2" -description = "" -category = "main" -optional = false -python-versions = "*" - [[package]] name = "pytz" -version = "2022.6" +version = "2022.7.1" description = "World timezone definitions, modern and historical" category = "main" optional = false @@ -1593,7 +1873,7 @@ optional = false python-versions = "*" [[package]] -name = "PyYAML" +name = "pyyaml" version = "6.0" description = "YAML parser and emitter for Python" category = "main" @@ -1601,7 +1881,7 @@ optional = false python-versions = ">=3.6" [[package]] -name = "pyyaml_env_tag" +name = "pyyaml-env-tag" version = "0.1" description = "A custom YAML tag for referencing environment variables in YAML files. " category = "dev" @@ -1613,16 +1893,16 @@ pyyaml = "*" [[package]] name = "qiskit" -version = "0.38.0" +version = "0.41.1" description = "Software for developing quantum computing programs" category = "main" optional = false python-versions = ">=3.7" [package.dependencies] -qiskit-aer = "0.11.0" -qiskit-ibmq-provider = "0.19.2" -qiskit-terra = "0.21.2" +qiskit-aer = "0.11.2" +qiskit-ibmq-provider = "0.20.1" +qiskit-terra = "0.23.2" [package.extras] all = ["ipywidgets (>=7.3.0)", "matplotlib (>=2.1)", "pillow (>=4.2.1)", "pydot", "pygments (>=2.4)", "pylatexenc (>=1.4)", "qiskit-experiments (>=0.2.0)", "qiskit-finance (>=0.3.3)", "qiskit-machine-learning (>=0.4.0)", "qiskit-nature (>=0.4.1)", "qiskit-optimization (>=0.4.0)", "seaborn (>=0.9.0)"] @@ -1635,7 +1915,7 @@ visualization = ["ipywidgets (>=7.3.0)", "matplotlib (>=2.1)", "pillow (>=4.2.1) [[package]] name = "qiskit-aer" -version = "0.11.0" +version = "0.11.2" description = "Qiskit Aer - High performance simulators for Qiskit" category = "main" optional = false @@ -1651,28 +1931,50 @@ dask = ["dask", "distributed"] [[package]] name = "qiskit-ibmq-provider" -version = "0.19.2" +version = "0.20.1" description = "Qiskit provider for accessing the quantum devices and simulators at IBMQ" category = "main" optional = false python-versions = ">=3.7" [package.dependencies] -numpy = ">=1.13" -python-dateutil = ">=2.8.0" -qiskit-terra = ">=0.18.0" -requests = ">=2.19" -requests-ntlm = ">=1.1.0" -urllib3 = ">=1.21.1" -websocket-client = ">=1.0.1" -websockets = {version = ">=10.0", markers = "python_version >= \"3.7\""} +numpy = "<1.24" +python-dateutil = ">=2.8.0,<2.9.0" +qiskit-terra = ">=0.23.0,<0.24.0" +requests = ">=2.28.0,<2.29.0" +requests-ntlm = ">=1.1.0,<1.2.0" +urllib3 = ">=1.26.0,<1.27.0" +websocket-client = ">=1.5.1,<1.6.0" +websockets = {version = ">=10.0,<11.0", markers = "python_version >= \"3.7\""} [package.extras] -visualization = ["ipython (>=5.0.0)", "ipyvue (>=1.4.1)", "ipyvuetify (>=1.1)", "ipywidgets (>=7.3.0)", "matplotlib (>=2.1)", "plotly (>=4.4)", "pyperclip (>=1.7)", "seaborn (>=0.9.0)", "traitlets (!=5.0.5)"] +visualization = ["ipython (>=5.0.0)", "ipyvue (>=1.4.1)", "ipyvuetify (>=1.1)", "ipywidgets (<=7.7.2)", "matplotlib (>=2.1)", "plotly (>=4.4)", "pyperclip (>=1.7)", "seaborn (>=0.9.0)", "traitlets (!=5.0.5)"] + +[[package]] +name = "qiskit-machine-learning" +version = "0.5.0" +description = "Qiskit Machine Learning: A library of quantum computing machine learning experiments" +category = "main" +optional = false +python-versions = ">=3.7" + +[package.dependencies] +dill = ">=0.3.4,<0.3.6" +fastdtw = "*" +numpy = ">=1.17" +psutil = ">=5" +qiskit-terra = ">=0.22" +scikit-learn = ">=0.20.0" +scipy = ">=1.4" +setuptools = ">=40.1.0" + +[package.extras] +sparse = ["sparse"] +torch = ["torch"] [[package]] name = "qiskit-terra" -version = "0.21.2" +version = "0.23.2" description = "Software for developing quantum computing programs" category = "main" optional = false @@ -1684,19 +1986,19 @@ numpy = ">=1.17" ply = ">=3.10" psutil = ">=5" python-dateutil = ">=2.8.0" -retworkx = ">=0.11.0" +rustworkx = ">=0.12.0" scipy = ">=1.5" stevedore = ">=3.0.0" symengine = {version = ">=0.9", markers = "platform_machine == \"x86_64\" or platform_machine == \"aarch64\" or platform_machine == \"ppc64le\" or platform_machine == \"amd64\" or platform_machine == \"arm64\""} sympy = ">=1.3" -tweedledum = ">=1.1,<2.0" [package.extras] -all = ["ipywidgets (>=7.3.0)", "matplotlib (>=3.3)", "pillow (>=4.2.1)", "pydot", "pygments (>=2.4)", "pylatexenc (>=1.4)", "python-constraint (>=1.4)", "seaborn (>=0.9.0)", "z3-solver (>=4.7)"] +all = ["ipywidgets (>=7.3.0)", "matplotlib (>=3.3)", "pillow (>=4.2.1)", "pydot", "pygments (>=2.4)", "pylatexenc (>=1.4)", "python-constraint (>=1.4)", "qiskit-qasm3-import (>=0.1.0)", "seaborn (>=0.9.0)", "z3-solver (>=4.7)"] bip-mapper = ["cplex", "docplex"] crosstalk-pass = ["z3-solver (>=4.7)"] csp-layout-pass = ["python-constraint (>=1.4)"] -toqm = ["qiskit-toqm (>=0.0.4)"] +qasm3-import = ["qiskit-qasm3-import (>=0.1.0)"] +toqm = ["qiskit-toqm (>=0.1.0)"] visualization = ["ipywidgets (>=7.3.0)", "matplotlib (>=3.3)", "pillow (>=4.2.1)", "pydot", "pygments (>=2.4)", "pylatexenc (>=1.4)", "seaborn (>=0.9.0)"] [[package]] @@ -1712,7 +2014,7 @@ six = "*" [[package]] name = "requests" -version = "2.28.1" +version = "2.28.2" description = "Python HTTP for Humans." category = "main" optional = false @@ -1720,16 +2022,16 @@ python-versions = ">=3.7, <4" [package.dependencies] certifi = ">=2017.4.17" -charset-normalizer = ">=2,<3" +charset-normalizer = ">=2,<4" idna = ">=2.5,<4" urllib3 = ">=1.21.1,<1.27" [package.extras] socks = ["PySocks (>=1.5.6,!=1.5.7)"] -use_chardet_on_py3 = ["chardet (>=3.0.2,<6)"] +use-chardet-on-py3 = ["chardet (>=3.0.2,<6)"] [[package]] -name = "requests_ntlm" +name = "requests-ntlm" version = "1.1.0" description = "This package allows for HTTP NTLM authentication using the requests library." category = "main" @@ -1742,21 +2044,19 @@ ntlm-auth = ">=1.0.2" requests = ">=2.0.0" [[package]] -name = "retworkx" -version = "0.12.1" -description = "A python graph library implemented in Rust" +name = "requests-oauthlib" +version = "1.3.1" +description = "OAuthlib authentication support for Requests." category = "main" optional = false -python-versions = ">=3.7" +python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*" [package.dependencies] -numpy = ">=1.16.0" -rustworkx = "0.12.1" +oauthlib = ">=3.0.0" +requests = ">=2.0.0" [package.extras] -all = ["matplotlib (>=3.0)", "pillow (>=5.4)"] -graphviz = ["pillow (>=5.4)"] -mpl = ["matplotlib (>=3.0)"] +rsa = ["oauthlib[signedtoken] (>=3.0.0)"] [[package]] name = "rich" @@ -1789,6 +2089,17 @@ pytoolconfig = {version = ">=1.2.2", extras = ["global"]} dev = ["build (>=0.7.0)", "pytest (>=7.0.1)", "pytest-timeout (>=2.1.0)"] doc = ["pytoolconfig[doc]", "sphinx (>=4.5.0)", "sphinx-autodoc-typehints (>=1.18.1)", "sphinx-rtd-theme (>=1.0.0)"] +[[package]] +name = "rsa" +version = "4.9" +description = "Pure-Python RSA implementation" +category = "main" +optional = false +python-versions = ">=3.6,<4" + +[package.dependencies] +pyasn1 = ">=0.1.3" + [[package]] name = "rustworkx" version = "0.12.1" @@ -1805,21 +2116,41 @@ all = ["matplotlib (>=3.0)", "pillow (>=5.4)"] graphviz = ["pillow (>=5.4)"] mpl = ["matplotlib (>=3.0)"] +[[package]] +name = "scikit-learn" +version = "1.2.1" +description = "A set of python modules for machine learning and data mining" +category = "main" +optional = false +python-versions = ">=3.8" + +[package.dependencies] +joblib = ">=1.1.1" +numpy = ">=1.17.3" +scipy = ">=1.3.2" +threadpoolctl = ">=2.0.0" + +[package.extras] +benchmark = ["matplotlib (>=3.1.3)", "memory-profiler (>=0.57.0)", "pandas (>=1.0.5)"] +docs = ["Pillow (>=7.1.2)", "matplotlib (>=3.1.3)", "memory-profiler (>=0.57.0)", "numpydoc (>=1.2.0)", "pandas (>=1.0.5)", "plotly (>=5.10.0)", "pooch (>=1.6.0)", "scikit-image (>=0.16.2)", "seaborn (>=0.9.0)", "sphinx (>=4.0.1)", "sphinx-gallery (>=0.7.0)", "sphinx-prompt (>=1.3.0)", "sphinxext-opengraph (>=0.4.2)"] +examples = ["matplotlib (>=3.1.3)", "pandas (>=1.0.5)", "plotly (>=5.10.0)", "pooch (>=1.6.0)", "scikit-image (>=0.16.2)", "seaborn (>=0.9.0)"] +tests = ["black (>=22.3.0)", "flake8 (>=3.8.2)", "matplotlib (>=3.1.3)", "mypy (>=0.961)", "numpydoc (>=1.2.0)", "pandas (>=1.0.5)", "pooch (>=1.6.0)", "pyamg (>=4.0.0)", "pytest (>=5.3.1)", "pytest-cov (>=2.9.0)", "scikit-image (>=0.16.2)"] + [[package]] name = "scipy" -version = "1.9.3" +version = "1.10.0" description = "Fundamental algorithms for scientific computing in Python" category = "main" optional = false -python-versions = ">=3.8" +python-versions = "<3.12,>=3.8" [package.dependencies] -numpy = ">=1.18.5,<1.26.0" +numpy = ">=1.19.5,<1.27.0" [package.extras] -dev = ["flake8", "mypy", "pycodestyle", "typing_extensions"] -doc = ["matplotlib (>2)", "numpydoc", "pydata-sphinx-theme (==0.9.0)", "sphinx (!=4.1.0)", "sphinx-panels (>=0.5.2)", "sphinx-tabs"] -test = ["asv", "gmpy2", "mpmath", "pytest", "pytest-cov", "pytest-xdist", "scikit-umfpack", "threadpoolctl"] +dev = ["click", "doit (>=0.36.0)", "flake8", "mypy", "pycodestyle", "pydevtool", "rich-click", "typing_extensions"] +doc = ["matplotlib (>2)", "numpydoc", "pydata-sphinx-theme (==0.9.0)", "sphinx (!=4.1.0)", "sphinx-design (>=0.2.0)"] +test = ["asv", "gmpy2", "mpmath", "pooch", "pytest", "pytest-cov", "pytest-timeout", "pytest-xdist", "scikit-umfpack", "threadpoolctl"] [[package]] name = "semver" @@ -1831,14 +2162,14 @@ python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*" [[package]] name = "setuptools" -version = "65.6.3" +version = "67.1.0" description = "Easily download, build, install, upgrade, and uninstall Python packages" category = "main" optional = false python-versions = ">=3.7" [package.extras] -docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "pygments-github-lexers (==0.0.5)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-favicon", "sphinx-hoverxref (<2)", "sphinx-inline-tabs", "sphinx-notfound-page (==0.8.3)", "sphinx-reredirects", "sphinxcontrib-towncrier"] +docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "pygments-github-lexers (==0.0.5)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-favicon", "sphinx-hoverxref (<2)", "sphinx-inline-tabs", "sphinx-lint", "sphinx-notfound-page (==0.8.3)", "sphinx-reredirects", "sphinxcontrib-towncrier"] testing = ["build[virtualenv]", "filelock (>=3.4.0)", "flake8 (<5)", "flake8-2020", "ini2toml[lite] (>=0.9)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "pip (>=19.1)", "pip-run (>=8.8)", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-flake8", "pytest-mypy (>=0.9.1)", "pytest-perf", "pytest-timeout", "pytest-xdist", "tomli-w (>=1.0.0)", "virtualenv (>=13.0.0)", "wheel"] testing-integration = ["build[virtualenv]", "filelock (>=3.4.0)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "pytest", "pytest-enabler", "pytest-xdist", "tomli", "virtualenv (>=13.0.0)", "wheel"] @@ -1867,8 +2198,8 @@ optional = false python-versions = ">=3.7" [[package]] -name = "SQLAlchemy" -version = "1.4.44" +name = "sqlalchemy" +version = "1.4.46" description = "Database Abstraction Library" category = "main" optional = false @@ -1882,19 +2213,19 @@ aiomysql = ["aiomysql", "greenlet (!=0.4.17)"] aiosqlite = ["aiosqlite", "greenlet (!=0.4.17)", "typing_extensions (!=3.10.0.1)"] asyncio = ["greenlet (!=0.4.17)"] asyncmy = ["asyncmy (>=0.2.3,!=0.2.4)", "greenlet (!=0.4.17)"] -mariadb_connector = ["mariadb (>=1.0.1,!=1.1.2)"] +mariadb-connector = ["mariadb (>=1.0.1,!=1.1.2)"] mssql = ["pyodbc"] -mssql_pymssql = ["pymssql"] -mssql_pyodbc = ["pyodbc"] +mssql-pymssql = ["pymssql"] +mssql-pyodbc = ["pyodbc"] mypy = ["mypy (>=0.910)", "sqlalchemy2-stubs"] mysql = ["mysqlclient (>=1.4.0)", "mysqlclient (>=1.4.0,<2)"] -mysql_connector = ["mysql-connector-python"] +mysql-connector = ["mysql-connector-python"] oracle = ["cx_oracle (>=7)", "cx_oracle (>=7,<8)"] postgresql = ["psycopg2 (>=2.7)"] -postgresql_asyncpg = ["asyncpg", "greenlet (!=0.4.17)"] -postgresql_pg8000 = ["pg8000 (>=1.16.6,!=1.29.0)"] -postgresql_psycopg2binary = ["psycopg2-binary"] -postgresql_psycopg2cffi = ["psycopg2cffi"] +postgresql-asyncpg = ["asyncpg", "greenlet (!=0.4.17)"] +postgresql-pg8000 = ["pg8000 (>=1.16.6,!=1.29.0)"] +postgresql-psycopg2binary = ["psycopg2-binary"] +postgresql-psycopg2cffi = ["psycopg2cffi"] pymysql = ["pymysql", "pymysql (<1)"] sqlcipher = ["sqlcipher3_binary"] @@ -1906,16 +2237,36 @@ category = "main" optional = false python-versions = ">=3.5" +[[package]] +name = "stack-data" +version = "0.6.2" +description = "Extract data from python stack frames and tracebacks for informative displays" +category = "main" +optional = false +python-versions = "*" + +[package.dependencies] +asttokens = ">=2.1.0" +executing = ">=1.2.0" +pure-eval = "*" + +[package.extras] +tests = ["cython", "littleutils", "pygments", "pytest", "typeguard"] + [[package]] name = "starlette" -version = "0.14.2" +version = "0.20.4" description = "The little ASGI library that shines." category = "main" optional = false -python-versions = ">=3.6" +python-versions = ">=3.7" + +[package.dependencies] +anyio = ">=3.4.0,<5" +typing-extensions = {version = ">=3.10.0", markers = "python_version < \"3.10\""} [package.extras] -full = ["aiofiles", "graphene", "itsdangerous", "jinja2", "python-multipart", "pyyaml", "requests"] +full = ["itsdangerous", "jinja2", "python-multipart", "pyyaml", "requests"] [[package]] name = "stevedore" @@ -1930,32 +2281,31 @@ pbr = ">=2.0.0,<2.1.0 || >2.1.0" [[package]] name = "strawberry-graphql" -version = "0.127.0" +version = "0.155.3" description = "A library for creating GraphQL APIs" category = "main" optional = false python-versions = ">=3.7,<4.0" [package.dependencies] -click = ">=7.0,<9.0" graphql-core = ">=3.2.0,<3.3.0" -pygments = ">=2.3,<3.0" python-dateutil = ">=2.7.0,<3.0.0" -python-multipart = ">=0.0.5,<0.0.6" typing_extensions = ">=3.7.4,<5.0.0" [package.extras] aiohttp = ["aiohttp (>=3.7.4.post0,<4.0.0)"] -asgi = ["starlette (>=0.13.6)"] +asgi = ["python-multipart (>=0.0.5,<0.0.6)", "starlette (>=0.13.6)"] chalice = ["chalice (>=1.22,<2.0)"] channels = ["asgiref (>=3.2,<4.0)", "channels (>=3.0.5)"] -debug-server = ["starlette (>=0.13.6)", "uvicorn (>=0.11.6,<0.19.0)"] +cli = ["click (>=7.0,<9.0)", "libcst (>=0.4.7)", "pygments (>=2.3,<3.0)", "rich (>=12.0.0)"] +debug = ["libcst (>=0.4.7)", "rich (>=12.0.0)"] +debug-server = ["click (>=7.0,<9.0)", "libcst (>=0.4.7)", "pygments (>=2.3,<3.0)", "python-multipart (>=0.0.5,<0.0.6)", "rich (>=12.0.0)", "starlette (>=0.13.6)", "uvicorn (>=0.11.6,<0.21.0)"] django = ["Django (>=3.2)", "asgiref (>=3.2,<4.0)"] -fastapi = ["fastapi (>=0.65.2)"] +fastapi = ["fastapi (>=0.65.2)", "python-multipart (>=0.0.5,<0.0.6)"] flask = ["flask (>=1.1)"] opentelemetry = ["opentelemetry-api (<2)", "opentelemetry-sdk (<2)"] pydantic = ["pydantic (<2)"] -sanic = ["sanic (>=20.12.2,<22.0.0)"] +sanic = ["sanic (>=20.12.2)"] [[package]] name = "symengine" @@ -1999,7 +2349,132 @@ python-versions = ">=3.6" doc = ["reno", "sphinx", "tornado (>=4.5)"] [[package]] -name = "TexSoup" +name = "tensorboard" +version = "2.8.0" +description = "TensorBoard lets you watch Tensors Flow" +category = "main" +optional = false +python-versions = ">=3.6" + +[package.dependencies] +absl-py = ">=0.4" +google-auth = ">=1.6.3,<3" +google-auth-oauthlib = ">=0.4.1,<0.5" +grpcio = ">=1.24.3" +markdown = ">=2.6.8" +numpy = ">=1.12.0" +protobuf = ">=3.6.0" +requests = ">=2.21.0,<3" +setuptools = ">=41.0.0" +tensorboard-data-server = ">=0.6.0,<0.7.0" +tensorboard-plugin-wit = ">=1.6.0" +werkzeug = ">=0.11.15" +wheel = ">=0.26" + +[[package]] +name = "tensorboard-data-server" +version = "0.6.1" +description = "Fast data loading for TensorBoard" +category = "main" +optional = false +python-versions = ">=3.6" + +[[package]] +name = "tensorboard-plugin-wit" +version = "1.8.1" +description = "What-If Tool TensorBoard plugin." +category = "main" +optional = false +python-versions = "*" + +[[package]] +name = "tensorflow" +version = "2.8.1" +description = "TensorFlow is an open source machine learning framework for everyone." +category = "main" +optional = false +python-versions = "*" + +[package.dependencies] +absl-py = ">=0.4.0" +astunparse = ">=1.6.0" +flatbuffers = ">=1.12" +gast = ">=0.2.1" +google-pasta = ">=0.1.1" +grpcio = ">=1.24.3,<2.0" +h5py = ">=2.9.0" +keras = ">=2.8.0rc0,<2.9" +keras-preprocessing = ">=1.1.1" +libclang = ">=9.0.1" +numpy = ">=1.20" +opt-einsum = ">=2.3.2" +protobuf = ">=3.9.2" +setuptools = "*" +six = ">=1.12.0" +tensorboard = ">=2.8,<2.9" +tensorflow-estimator = ">=2.8,<2.9" +tensorflow-io-gcs-filesystem = ">=0.23.1" +termcolor = ">=1.1.0" +typing-extensions = ">=3.6.6" +wrapt = ">=1.11.0" + +[[package]] +name = "tensorflow-estimator" +version = "2.8.0" +description = "TensorFlow Estimator." +category = "main" +optional = false +python-versions = "*" + +[[package]] +name = "tensorflow-io-gcs-filesystem" +version = "0.31.0" +description = "TensorFlow IO" +category = "main" +optional = false +python-versions = ">=3.7, <3.12" + +[package.extras] +tensorflow = ["tensorflow (>=2.11.0,<2.12.0)"] +tensorflow-aarch64 = ["tensorflow-aarch64 (>=2.11.0,<2.12.0)"] +tensorflow-cpu = ["tensorflow-cpu (>=2.11.0,<2.12.0)"] +tensorflow-gpu = ["tensorflow-gpu (>=2.11.0,<2.12.0)"] +tensorflow-rocm = ["tensorflow-rocm (>=2.11.0,<2.12.0)"] + +[[package]] +name = "tensorflow-probability" +version = "0.18.0" +description = "Probabilistic modeling and statistical inference in TensorFlow" +category = "main" +optional = false +python-versions = "*" + +[package.dependencies] +absl-py = "*" +cloudpickle = ">=1.3" +decorator = "*" +dm-tree = "*" +gast = ">=0.3.2" +numpy = ">=1.13.3" +six = ">=1.10.0" + +[package.extras] +jax = ["jax", "jaxlib"] +tfds = ["tensorflow-datasets (>=2.2.0)"] + +[[package]] +name = "termcolor" +version = "2.2.0" +description = "ANSI color formatting for output in terminal" +category = "main" +optional = false +python-versions = ">=3.7" + +[package.extras] +tests = ["pytest", "pytest-cov"] + +[[package]] +name = "texsoup" version = "0.3.1" description = "parses valid LaTeX and provides variety of Beautiful-Soup-esque methods and Pythonic idioms for iterating over and searching the parse tree" category = "main" @@ -2014,6 +2489,14 @@ category = "main" optional = false python-versions = "*" +[[package]] +name = "threadpoolctl" +version = "3.1.0" +description = "threadpoolctl" +category = "main" +optional = false +python-versions = ">=3.6" + [[package]] name = "toml" version = "0.10.2" @@ -2032,31 +2515,41 @@ python-versions = ">=3.7" [[package]] name = "toposort" -version = "1.7" -description = "\"Implements a topological sort algorithm.\"" +version = "1.9" +description = "Implements a topological sort algorithm." category = "main" optional = false python-versions = "*" [[package]] -name = "traitlets" -version = "5.6.0" -description = "Traitlets Python configuration system" +name = "torch" +version = "1.13.1" +description = "Tensors and Dynamic neural networks in Python with strong GPU acceleration" category = "main" optional = false -python-versions = ">=3.7" +python-versions = ">=3.7.0" + +[package.dependencies] +nvidia-cublas-cu11 = {version = "11.10.3.66", markers = "platform_system == \"Linux\""} +nvidia-cuda-nvrtc-cu11 = {version = "11.7.99", markers = "platform_system == \"Linux\""} +nvidia-cuda-runtime-cu11 = {version = "11.7.99", markers = "platform_system == \"Linux\""} +nvidia-cudnn-cu11 = {version = "8.5.0.96", markers = "platform_system == \"Linux\""} +typing-extensions = "*" [package.extras] -docs = ["myst-parser", "pydata-sphinx-theme", "sphinx"] -test = ["pre-commit", "pytest"] +opt-einsum = 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a/pyproject.toml b/pyproject.toml index ea995f1..745fcc8 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -30,13 +30,16 @@ readme = "README.md" [tool.poetry.dependencies] python = ">=3.8.1,<3.11" -qiskit = "^0.38.0" -pytorch = "^1.0.2" +torch = "^1.12.1+cpu" black = "^22.6.0" kedro = "^0.18.3" kedro-viz = "^5.1.1" kedro-mlflow = "^0.11.3" formattex = "^0.0.3" +qiskit-machine-learning = "^0.5.0" +qiskit = "^0.41.1" #"^0.38.0" +python-json-logger = "^2.0.7" +phasespace = "^1.8.0" [tool.poetry.group.dev.dependencies] pytest = "^7.2.0" diff --git a/src/partiqleDTR/pipelines/data_science/qgnn.py b/src/partiqleDTR/pipelines/data_science/qgnn.py index 9170cb8..b185eaa 100644 --- a/src/partiqleDTR/pipelines/data_science/qgnn.py +++ b/src/partiqleDTR/pipelines/data_science/qgnn.py @@ -245,6 +245,31 @@ def variational(qc, n_qubits, identifier): # f"{identifier}_crz_{n_qubits - i - 1}_{n_qubits - i}", # ) + def build_circuit_19_flipped(qc, n_qubits, identifier): + for i in range(n_qubits): + qc.rx( + q.circuit.Parameter(f"{identifier}_rx_0_{i}"), + i, + f"{identifier}_rx_0_{i}", + ) + qc.rz(q.circuit.Parameter(f"{identifier}_rz_1_{i}"), i) + + for i in range(n_qubits): + if i == 0: + qc.crx( + q.circuit.Parameter(f"{identifier}_crx_{i+1}_{i}"), + i, + n_qubits - 1, + f"{identifier}_crx_{i+1}_{i}", + ) + else: + qc.crx( + q.circuit.Parameter(f"{identifier}_crx_{i+1}_{i}"), + n_qubits - i, + n_qubits - i - 1, + f"{identifier}_crx_{i+1}_{i}", + ) + def build_circuit_19(qc, n_qubits, identifier): for i in range(n_qubits): qc.rx( @@ -280,6 +305,8 @@ def circuit_builder(qc, n_qubits, n_hidden): variational(qc, n_qubits, f"var_{i}") elif self.predefined_vqc == "circuit_19": build_circuit_19(qc, n_qubits, f"var_{i}") + elif self.predefined_vqc == "circuit_19_flipped": + build_circuit_19_flipped(qc, n_qubits, f"var_{i}") else: raise ValueError("Invalid circuit specified") qc.barrier() From 25293d450e57853138c08e68cf1ddc952a8c1a69 Mon Sep 17 00:00:00 2001 From: lc3267 Date: Fri, 17 Mar 2023 16:31:01 +0100 Subject: [PATCH 85/92] added mlruns bkcp --- .gitignore | 1 + .vscode/mlflow_cleanup.py | 34 ++++++++++++++++++++++++++++++++++ 2 files changed, 35 insertions(+) create mode 100644 .vscode/mlflow_cleanup.py diff --git a/.gitignore b/.gitignore index ee5b335..94c524b 100644 --- a/.gitignore +++ b/.gitignore @@ -1,5 +1,6 @@ venv mlruns +.mlruns_bckp *.pdf .ipython *.png diff --git a/.vscode/mlflow_cleanup.py b/.vscode/mlflow_cleanup.py new file mode 100644 index 0000000..55f2f3b --- /dev/null +++ b/.vscode/mlflow_cleanup.py @@ -0,0 +1,34 @@ +import glob +import os +import yaml +import shutil + +mlflow_path = "./mlruns/1" +backup_dir = "./.mlruns_bckp" + +cut_after = 1 # 1670237437014 + +runs = glob.glob(os.path.join(mlflow_path, "*")) + +for r in runs: + mark_for_deletion = False + mark_for_deprecation = False + if not os.path.isdir(r): + continue + with open(os.path.join(r, "meta.yaml"), "r") as f: + try: + content = yaml.safe_load(f) + except yaml.YAMLError as exc: + print(exc) + + if content["status"] != 3: + mark_for_deletion = True + elif int(content["end_time"]) < cut_after: + mark_for_deprecation = True + content["lifecycle_stage"] = "deleted" + + if mark_for_deletion: + shutil.move(r, os.path.join(backup_dir, os.path.basename(r))) + elif mark_for_deprecation: + with open(os.path.join(r, "meta.yaml"), "w") as f: + yaml.safe_dump(content, f) From 42699f9335b200fe0ff65b9b661c2014bb441837 Mon Sep 17 00:00:00 2001 From: lc3267 Date: Fri, 17 Mar 2023 16:31:20 +0100 Subject: [PATCH 86/92] proceedings plotting settings --- create_plots_from_metrics.py | 66 ++++++++++++++++++++++++++++++------ 1 file changed, 55 insertions(+), 11 deletions(-) diff --git a/create_plots_from_metrics.py b/create_plots_from_metrics.py index abb6483..b72fe95 100644 --- a/create_plots_from_metrics.py +++ b/create_plots_from_metrics.py @@ -23,13 +23,30 @@ metric_histories[metric][1].append(metric_step.value) -fig = plt.figure(figsize=(12,6)) +fig = plt.figure(figsize=(12,7)) ax = plt.gca() -cmap = mpl.cm.get_cmap('Dark2_r') +SMALL_SIZE = 12 +MEDIUM_SIZE = 14 +BIGGER_SIZE = 16 + +plt.rc('font', size=SMALL_SIZE) # controls default text sizes +plt.rc('axes', titlesize=MEDIUM_SIZE) # fontsize of the axes title +plt.rc('axes', labelsize=MEDIUM_SIZE) # fontsize of the x and y labels +plt.rc('xtick', labelsize=SMALL_SIZE) # fontsize of the tick labels +plt.rc('ytick', labelsize=SMALL_SIZE) # fontsize of the tick labels +plt.rc('legend', fontsize=SMALL_SIZE) # legend fontsize +plt.rc('figure', titlesize=BIGGER_SIZE) # fontsize of the figure title +plt.rcParams.update({'font.size': 22}) +plt.rcParams.update({'axes.titlesize': 22}) + +cmap = mpl.cm.get_cmap('tab10') hline_offset=0.5 +handles = [] +labels = [] + for i, metric in enumerate(metrics): if "loss" in metric: best = min(metric_histories[metric][1]) @@ -40,25 +57,52 @@ ax.plot(*metric_histories[metric], color=cmap(i), label=metric) ax.set_xticks(metric_histories[metric][0][1::(len(metric_histories[metric][0])//10)]) # we start counting at 1, so it looks better if we have the max epoch shown - plt.axhline(y=best, xmin=hline_offset/(len(metric_histories[metric][0])), xmax=(best_idx+hline_offset)/(len(metric_histories[metric][0])), color=cmap(i), linewidth=0.8, linestyle=':', label=f"best_{metric}") + ax.tick_params(labelsize=SMALL_SIZE) + + # highlight the best line + # plt.axhline(y=best, xmin=hline_offset/(len(metric_histories[metric][0])), xmax=(best_idx+hline_offset)/(len(metric_histories[metric][0])), color=cmap(i), linewidth=0.8, linestyle=':', label=f"best_{metric}") + + handles.append(cmap(i)) + labels.append(f"best_{metric}") # Shrink current axis by 20% box = ax.get_position() ax.set_position([box.x0, box.y0, box.width * 0.7, box.height]) -ax.set_facecolor("#FAFAFA") +# ax.set_facecolor("#FAFAFA") +ax.set_facecolor("#FFFFFF") ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False) ax.spines['bottom'].set_visible(False) ax.spines['left'].set_visible(False) +ax.set_xlabel("Epoch", fontsize=MEDIUM_SIZE) +ax.set_ylabel("Metric", fontsize=MEDIUM_SIZE) +ax.set_ylim([0.0, 0.85]) + plt.axvline(x=1, color="#666666", linewidth=0.7) +plt.axhline(y=0, color="#666666", linewidth=0.7) ax.tick_params(axis=u'both', which=u'both',length=0) -fig.patch.set_facecolor("#FAFAFA") -plt.grid(color="#F1F1F1") - +# fig.patch.set_facecolor("#FAFAFA") +fig.patch.set_facecolor("#FFFFFF") +# plt.grid(color="#F1F1F1") +ax.grid(False) +# ax.xaxis.grid(True) # Put a legend to the right of the current axis -ax.legend(loc='center left', bbox_to_anchor=(1, 0.5), facecolor="#FAFAFA", framealpha=0.3) -title = input("Gimme a catchy title: \t") -plt.title(title) -plt.savefig("test.png", bbox_inches='tight') +# ax.legend(loc='center left', bbox_to_anchor=(1, 0.5), facecolor="#FAFAFA", framealpha=0.3) +legend = plt.legend(bbox_to_anchor=(1.04, 1), loc="lower left", ncol=len(labels)//2, framealpha=0.3, frameon=False) + +def export_legend(legend, filename): + leg_fig = legend.figure + leg_fig.canvas.draw() + bbox = legend.get_window_extent().transformed(leg_fig.dpi_scale_trans.inverted()) + leg_fig.savefig(filename, dpi="figure", bbox_inches=bbox) + +export_legend(legend, "legend.pdf") + +ax.get_legend().remove() + +# no title +# title = input("Gimme a catchy title: \t") +# plt.title(title, fontsize=BIGGER_SIZE) +plt.savefig("output.pdf", bbox_inches='tight') From 4e4f7f8a412b0aa37324e7ca307c40b2d0a5bbfa Mon Sep 17 00:00:00 2001 From: lc3267 Date: Fri, 17 Mar 2023 16:31:30 +0100 Subject: [PATCH 87/92] ran update --- poetry.lock | 1791 +++++++++++++++++++++++++++++++++++++++++------- pyproject.toml | 12 +- 2 files changed, 1572 insertions(+), 231 deletions(-) diff --git a/poetry.lock b/poetry.lock index 04521a6..b6de9e6 100644 --- a/poetry.lock +++ b/poetry.lock @@ -112,6 +112,14 @@ python-versions = "*" six = ">=1.6.1,<2.0" wheel = ">=0.23.0,<1.0" +[[package]] +name = "async-timeout" +version = "4.0.2" +description = "Timeout context manager for asyncio programs" +category = "main" +optional = false +python-versions = ">=3.6" + [[package]] name = "attrs" version = "22.2.0" @@ -168,6 +176,24 @@ d = ["aiohttp (>=3.7.4)"] jupyter = ["ipython (>=7.8.0)", "tokenize-rt (>=3.2.0)"] uvloop = ["uvloop (>=0.15.2)"] +[[package]] +name = "boost-histogram" +version = "1.3.2" +description = "The Boost::Histogram Python wrapper." +category = "main" +optional = false +python-versions = ">=3.6" + +[package.dependencies] +numpy = ">=1.13.3" + +[package.extras] +all = ["Sphinx (>=4.0)", "cloudpickle", "hypothesis (>=6.0)", "ipykernel", "matplotlib", "myst-parser (>=0.13)", "nbsphinx", "netCDF4", "numba", "pytest (>=6.0)", "pytest-benchmark", "sphinx-book-theme (>=0.0.33)", "sphinx-copybutton", "typer", "uproot3", "xarray", "xhistogram"] +dev = ["cloudpickle", "hypothesis (>=6.0)", "ipykernel", "pytest (>=6.0)", "pytest-benchmark", "typer"] +docs = ["Sphinx (>=4.0)", "myst-parser (>=0.13)", "nbsphinx", "sphinx-book-theme (>=0.0.33)", "sphinx-copybutton"] +examples = ["matplotlib", "netCDF4", "numba", "uproot3", "xarray", "xhistogram"] +test = ["cloudpickle", "hypothesis (>=6.0)", "pytest (>=6.0)", "pytest-benchmark"] + [[package]] name = "build" version = "0.10.0" @@ -258,6 +284,20 @@ category = "main" optional = false python-versions = ">=3.6" +[[package]] +name = "cmaes" +version = "0.9.1" +description = "Lightweight Covariance Matrix Adaptation Evolution Strategy (CMA-ES) implementation for Python 3." +category = "main" +optional = false +python-versions = ">=3.7" + +[package.dependencies] +numpy = "*" + +[package.extras] +cmawm = ["scipy"] + [[package]] name = "colorama" version = "0.4.6" @@ -266,6 +306,28 @@ category = "main" optional = false python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*,>=2.7" +[[package]] +name = "colored" +version = "1.4.4" +description = "Simple library for color and formatting to terminal" +category = 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"types-Pillow"] +test = ["Pillow", "matplotlib", "pytest"] +test-no-images = ["pytest"] + [[package]] name = "cookiecutter" version = "2.1.1" @@ -296,7 +376,7 @@ requests = ">=2.23.0" [[package]] name = "cryptography" -version = "39.0.0" +version = "39.0.2" description = "cryptography is a package which provides cryptographic recipes and primitives to Python developers." category = "main" optional = false @@ -306,12 +386,22 @@ python-versions = ">=3.6" cffi = ">=1.12" [package.extras] -docs = ["sphinx (>=1.6.5,!=1.8.0,!=3.1.0,!=3.1.1,!=5.2.0,!=5.2.0.post0)", "sphinx-rtd-theme"] +docs = ["sphinx (>=5.3.0)", "sphinx-rtd-theme (>=1.1.1)"] docstest = ["pyenchant (>=1.6.11)", "sphinxcontrib-spelling (>=4.0.1)", "twine (>=1.12.0)"] -pep8test = ["black", "ruff"] +pep8test = ["black", "check-manifest", "mypy", "ruff", "types-pytz", "types-requests"] sdist = ["setuptools-rust (>=0.11.4)"] ssh = ["bcrypt (>=3.1.5)"] -test = ["hypothesis (>=1.11.4,!=3.79.2)", "iso8601", "pretend", "pytest (>=6.2.0)", "pytest-benchmark", "pytest-cov", "pytest-subtests", "pytest-xdist", "pytz"] +test = ["hypothesis (>=1.11.4,!=3.79.2)", "iso8601", "pretend", "pytest (>=6.2.0)", "pytest-benchmark", "pytest-cov", "pytest-shard (>=0.1.2)", "pytest-subtests", "pytest-xdist", "pytz"] +test-randomorder = ["pytest-randomly"] +tox = ["tox"] + +[[package]] +name = "cycler" +version = "0.11.0" +description = "Composable style cycles" +category = "main" +optional = false +python-versions = ">=3.6" [[package]] name = "databricks-cli" @@ -329,6 +419,30 @@ requests = ">=2.17.3" six = ">=1.10.0" tabulate = ">=0.7.7" +[[package]] +name = "decaylanguage" +version = "0.15.1" +description = "A language to describe, manipulate and convert particle decays" +category = "main" +optional = false +python-versions = ">=3.7" + +[package.dependencies] +attrs = ">=19.2" +deprecated = "*" +graphviz = ">=0.12.0" +importlib-resources = {version = ">=2.0", markers = "python_version < \"3.9\""} +lark = ">=1.0.0" +numpy = ">=1.12" +pandas = ">=0.22" +particle = ">=0.21.0" +plumbum = ">=1.6.9" + +[package.extras] +dev = ["pytest (>=6)"] +docs = ["sphinx (>=4)", "sphinx-rtd-theme (>=0.5.0)"] +test = ["pytest (>=6)", "pytest-cov"] + [[package]] name = "decorator" version = "5.1.1" @@ -337,6 +451,20 @@ category = "main" optional = false python-versions = ">=3.5" +[[package]] +name = "deprecated" +version = "1.2.13" +description = "Python @deprecated decorator to deprecate old python classes, functions or methods." +category = "main" +optional = false +python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*" + +[package.dependencies] +wrapt = ">=1.10,<2" + +[package.extras] +dev = ["PyTest", "PyTest (<5)", "PyTest-Cov", "PyTest-Cov (<2.6)", "bump2version (<1)", "configparser (<5)", "importlib-metadata (<3)", "importlib-resources (<4)", "sphinx (<2)", "sphinxcontrib-websupport (<2)", "tox", "zipp (<2)"] + [[package]] name = "dill" version = "0.3.5.1" @@ -382,6 +510,14 @@ websocket-client = ">=0.32.0" [package.extras] ssh = ["paramiko (>=2.4.3)"] +[[package]] +name = "dotmap" +version = "1.3.30" +description = "ordered, dynamically-expandable dot-access dictionary" +category = "main" +optional = false +python-versions = "*" + [[package]] name = "dynaconf" version = "3.1.11" @@ -511,6 +647,28 @@ category = "main" optional = false python-versions = "*" +[[package]] +name = "fonttools" +version = "4.38.0" +description = "Tools to manipulate font files" +category = "main" +optional = false +python-versions = ">=3.7" + +[package.extras] +all = ["brotli (>=1.0.1)", "brotlicffi (>=0.8.0)", "fs (>=2.2.0,<3)", "lxml (>=4.0,<5)", "lz4 (>=1.7.4.2)", "matplotlib", "munkres", "scipy", "skia-pathops (>=0.5.0)", "sympy", "uharfbuzz (>=0.23.0)", "unicodedata2 (>=14.0.0)", "xattr", "zopfli (>=0.1.4)"] +graphite = ["lz4 (>=1.7.4.2)"] +interpolatable = ["munkres", "scipy"] +lxml = ["lxml (>=4.0,<5)"] +pathops = ["skia-pathops (>=0.5.0)"] +plot = ["matplotlib"] +repacker = ["uharfbuzz (>=0.23.0)"] +symfont = ["sympy"] +type1 = ["xattr"] +ufo = ["fs (>=2.2.0,<3)"] +unicode = ["unicodedata2 (>=14.0.0)"] +woff = ["brotli (>=1.0.1)", "brotlicffi (>=0.8.0)", "zopfli (>=0.1.4)"] + [[package]] name = "formattex" version = "0.0.3" @@ -560,7 +718,7 @@ tqdm = ["tqdm"] [[package]] name = "gast" -version = "0.5.3" +version = "0.4.0" description = "Python AST that abstracts the underlying Python version" category = "main" optional = false @@ -604,7 +762,7 @@ gitdb = ">=4.0.1,<5" [[package]] name = "google-auth" -version = "2.16.1" +version = "2.16.2" description = "Google Authentication Library" category = "main" optional = false @@ -657,6 +815,19 @@ category = "main" optional = false python-versions = ">=3.6,<4" +[[package]] +name = "graphviz" +version = "0.20.1" +description = "Simple Python interface for Graphviz" +category = "main" +optional = false +python-versions = ">=3.7" + +[package.extras] +dev = ["flake8", "pep8-naming", "tox (>=3)", "twine", "wheel"] +docs = ["sphinx (>=5)", "sphinx-autodoc-typehints", "sphinx-rtd-theme"] +test = ["coverage", "mock (>=4)", "pytest (>=7)", "pytest-cov", "pytest-mock (>=3)"] + [[package]] name = "greenlet" version = "2.0.2" @@ -730,6 +901,59 @@ python-versions = ">=3.7" [package.dependencies] numpy = ">=1.14.5" +[[package]] +name = "hepunits" +version = "2.3.1" +description = "Units and constants in the HEP system of units" +category = "main" +optional = false +python-versions = ">=3.7" + +[package.extras] +all = ["pytest (>=6)", "pytest-cov (>=2.8.0)"] +dev = ["pytest (>=6)", "pytest-cov (>=2.8.0)"] +test = ["pytest (>=6)", "pytest-cov (>=2.8.0)"] + +[[package]] +name = "hist" +version = "2.6.3" +description = "Hist classes and utilities" +category = "main" +optional = false +python-versions = ">=3.7" + +[package.dependencies] +boost-histogram = ">=1.3.1,<1.4.0" +histoprint = ">=2.2.0" +numpy = ">=1.14.5" + +[package.extras] +dask = ["dask-histogram (>=2023.1)", "dask[dataframe] (>=2022)"] +dev = ["dask-histogram (>=2023.1)", "dask[dataframe] (>=2022)", "iminuit (>=2)", "ipykernel", "matplotlib (>=3.0)", "mplhep (>=0.2.16)", "pytest (>=6)", "pytest-mpl (>=0.12)", "scipy (>=1.4)"] +docs = ["dask-histogram (>=2023.1)", "dask[dataframe] (>=2022)", "graphviz (>=0.20.1)", "iminuit (>=2)", "ipykernel", "ipython", "ipython-genutils", "matplotlib (>=3.0)", "mplhep (>=0.2.16)", "myst-parser (>=0.14)", "nbsphinx", "pillow", "pytest (>=6)", "pytest-mpl (>=0.12)", "scipy (>=1.4)", "sphinx (>=3.0.0)", "sphinx-book-theme (>=0.0.38)", "sphinx-copybutton", "sphinx-rtd-theme (>=0.5.0)", "uncertainties (>=3)"] +mpl = ["matplotlib (>=3.0)", "mplhep (>=0.2.16)"] +plot = ["iminuit (>=2)", "matplotlib (>=3.0)", "mplhep (>=0.2.16)", "scipy (>=1.4)"] +test = ["dask-histogram (>=2023.1)", "dask[dataframe] (>=2022)", "pytest (>=6)", "pytest-mpl (>=0.12)"] + +[[package]] +name = "histoprint" +version = "2.4.0" +description = "Pretty print of NumPy (and other) histograms to the console" +category = "main" +optional = false +python-versions = ">=3.6" + +[package.dependencies] +click = ">=7.0.0" +numpy = "*" +uhi = ">=0.2.1" + +[package.extras] +boost = ["boost-histogram (>=1.1)"] +rich = ["rich (>=12)"] +test = ["pytest (>=6.0)"] +uproot = ["awkward (>=1)", "uproot (>=4)"] + [[package]] name = "httptools" version = "0.5.0" @@ -760,6 +984,21 @@ category = "main" optional = false python-versions = ">=3.5" +[[package]] +name = "iminuit" +version = "2.20.0" +description = "Jupyter-friendly Python frontend for MINUIT2 in C++" +category = "main" +optional = false +python-versions = ">=3.8" + +[package.dependencies] +numpy = "*" + +[package.extras] +doc = ["ipykernel", "jax (>=0.4.1,<0.5.0)", "jaxlib (>=0.4.1,<0.5.0)", "jupyter-client", "nbconvert", "nbformat", "nbsphinx", "sphinx (>=5.3.0,<5.4.0)", "sphinx-rtd-theme"] +test = ["boost-histogram", "coverage", "cython", "ipywidgets", "jacobi", "joblib", "matplotlib", "numba", "numba-stats", "pytest", "resample (>=1.5)", "scipy", "tabulate"] + [[package]] name = "importlib-metadata" version = "6.0.0" @@ -842,6 +1081,22 @@ category = "main" optional = false python-versions = ">=3.7" +[[package]] +name = "jacobi" +version = "0.8.1" +description = "Compute numerical derivatives." +category = "main" +optional = false +python-versions = ">=3.6" + +[package.dependencies] +numpy = ">=1.10" + +[package.extras] +doc = ["ipykernel", "sphinx", "sphinx-rtd-theme"] +plot = ["matplotlib", "numdifftools"] +test = ["pytest", "pytest-benchmark", "types-setuptools"] + [[package]] name = "jedi" version = "0.18.2" @@ -1024,28 +1279,32 @@ watchgod = ">=0.8.2,<0.9.0" [[package]] name = "keras" -version = "2.8.0" +version = "2.11.0" description = "Deep learning for humans." category = "main" optional = false -python-versions = "*" +python-versions = ">=3.7" [[package]] -name = "keras-preprocessing" -version = "1.1.2" -description = "Easy data preprocessing and data augmentation for deep learning models" +name = "kiwisolver" +version = "1.4.4" +description = "A fast implementation of the Cassowary constraint solver" category = "main" optional = false -python-versions = "*" +python-versions = ">=3.7" -[package.dependencies] -numpy = ">=1.9.1" -six = ">=1.9.0" +[[package]] +name = "lark" +version = "1.1.5" +description = "a modern parsing library" +category = "main" +optional = false +python-versions = "*" [package.extras] -image = ["Pillow (>=5.2.0)", "scipy (>=0.14)"] -pep8 = ["flake8"] -tests = ["Pillow", "keras", "pandas", "pytest", "pytest-cov", "pytest-xdist", "tensorflow"] +atomic-cache = ["atomicwrites"] +nearley = ["js2py"] +regex = ["regex"] [[package]] name = "libclang" @@ -1107,6 +1366,27 @@ category = "main" optional = false python-versions = ">=3.7" +[[package]] +name = "matplotlib" +version = "3.7.0" +description = "Python plotting package" +category = "main" +optional = false +python-versions = ">=3.8" + +[package.dependencies] +contourpy = ">=1.0.1" +cycler = ">=0.10" +fonttools = ">=4.22.0" +importlib-resources = {version = ">=3.2.0", markers = "python_version < \"3.10\""} +kiwisolver = ">=1.0.1" +numpy = ">=1.20" +packaging = ">=20.0" +pillow = ">=6.2.0" +pyparsing = ">=2.3.1" +python-dateutil = ">=2.7" +setuptools_scm = ">=7" + [[package]] name = "matplotlib-inline" version = "0.1.6" @@ -1315,15 +1595,19 @@ python-versions = ">=2.7,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.* setuptools = "*" [[package]] -name = "ntlm-auth" -version = "1.5.0" -description = "Creates NTLM authentication structures" +name = "numdifftools" +version = "0.9.41" +description = "Solves automatic numerical differentiation problems in one or more variables." category = "main" optional = false -python-versions = ">=2.6,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*" +python-versions = "*" + +[package.dependencies] +numpy = ">=1.9" +scipy = ">=0.8" [package.extras] -cryptography = ["cryptography", "cryptography (<2.2)"] +build-sphinx = ["sphinx (>=1.3.1)"] [[package]] name = "numpy" @@ -1409,6 +1693,43 @@ numpy = ">=1.7" docs = ["numpydoc", "sphinx (==1.2.3)", "sphinx-rtd-theme", "sphinxcontrib-napoleon"] tests = ["pytest", "pytest-cov", "pytest-pep8"] +[[package]] +name = "optuna" +version = "3.1.0" +description = "A hyperparameter optimization framework" +category = "main" +optional = false +python-versions = ">=3.7" + +[package.dependencies] +alembic = ">=1.5.0" +cmaes = ">=0.9.1" +colorlog = "*" +numpy = "*" +packaging = ">=20.0" +PyYAML = "*" +sqlalchemy = ">=1.3.0" +tqdm = "*" + +[package.extras] +benchmark = ["asv (>=0.5.0)", "botorch", "cma", "scikit-optimize", "virtualenv"] +checking = ["black", "blackdoc", "hacking", "isort", "mypy", "types-PyYAML", "types-redis", "types-setuptools", "typing-extensions (>=3.10.0.0)"] +document = ["cma", "distributed", "fvcore", "lightgbm", "matplotlib (!=3.6.0)", "mlflow", "pandas", "pillow", "plotly (>=4.9.0)", "scikit-learn", "scikit-optimize", "sphinx (<6)", "sphinx-copybutton", "sphinx-gallery", "sphinx-plotly-directive", "sphinx-rtd-theme", "torch (==1.11.0)", "torchaudio (==0.11.0)", "torchvision (==0.12.0)"] +integration = ["allennlp (>=2.2.0)", "botorch (>=0.4.0,<0.8.0)", "cached-path (<=1.1.2)", "catalyst (>=21.3)", "catboost (>=0.26)", "chainer (>=5.0.0)", "cma", "distributed", "fastai", "lightgbm", "mlflow", "mpi4py", "mxnet", "pandas", "pytorch-ignite", "pytorch-lightning (>=1.5.0)", "scikit-learn (>=0.24.2)", "scikit-optimize", "shap", "skorch", "tensorflow", "tensorflow-datasets", "torch (==1.11.0)", "torchaudio (==0.11.0)", "torchvision (==0.12.0)", "wandb", "xgboost"] +optional = ["matplotlib (!=3.6.0)", "pandas", "plotly (>=4.9.0)", "redis", "scikit-learn (>=0.24.2)"] +test = ["codecov", "fakeredis[lua]", "kaleido", "pytest", "scipy (>=1.9.2)"] + +[[package]] +name = "ordered-set" +version = "4.1.0" +description = "An OrderedSet is a custom MutableSet that remembers its order, so that every" +category = "main" +optional = false +python-versions = ">=3.7" + +[package.extras] +dev = ["black", "mypy", "pytest"] + [[package]] name = "orjson" version = "3.8.5" @@ -1456,6 +1777,23 @@ python-versions = ">=3.6" qa = ["flake8 (==3.8.3)", "mypy (==0.782)"] testing = ["docopt", "pytest (<6.0.0)"] +[[package]] +name = "particle" +version = "0.21.2" +description = "Extended PDG particle data and MC identification codes" +category = "main" +optional = false +python-versions = ">=3.7" + +[package.dependencies] +attrs = ">=19.2" +hepunits = ">=2.0.0" +importlib-resources = {version = ">=2.0", markers = "python_version < \"3.9\""} + +[package.extras] +dev = ["pandas", "pytest (>=6)", "pytest-benchmark", "tabulate"] +test = ["pandas", "pytest (>=6)", "pytest-benchmark", "pytest-cov", "tabulate"] + [[package]] name = "pathspec" version = "0.11.0" @@ -1511,6 +1849,18 @@ category = "main" optional = false python-versions = "*" +[[package]] +name = "pillow" +version = "9.4.0" +description = "Python Imaging Library (Fork)" +category = "main" +optional = false +python-versions = ">=3.7" + +[package.extras] +docs = ["furo", "olefile", "sphinx (>=2.4)", "sphinx-copybutton", "sphinx-inline-tabs", "sphinx-issues (>=3.0.1)", "sphinx-removed-in", "sphinxext-opengraph"] +tests = ["check-manifest", "coverage", "defusedxml", "markdown2", "olefile", "packaging", "pyroma", "pytest", "pytest-cov", "pytest-timeout"] + [[package]] name = "pip" version = "23.0" @@ -1573,6 +1923,22 @@ python-versions = ">=3.6" dev = ["pre-commit", "tox"] testing = ["pytest", "pytest-benchmark"] +[[package]] +name = "plumbum" +version = "1.8.1" +description = "Plumbum: shell combinators library" +category = "main" +optional = false +python-versions = ">=3.6" + +[package.dependencies] +pywin32 = {version = "*", markers = "platform_system == \"Windows\" and platform_python_implementation != \"PyPy\""} + +[package.extras] +dev = ["paramiko", "psutil", "pytest (>=6.0)", "pytest-cov", "pytest-mock", "pytest-timeout"] +docs = ["sphinx (>=4.0.0)", "sphinx-rtd-theme (>=1.0.0)"] +ssh = ["paramiko"] + [[package]] name = "ply" version = "3.11" @@ -1632,11 +1998,11 @@ wcwidth = "*" [[package]] name = "protobuf" -version = "4.21.12" -description = "" +version = "3.19.6" +description = "Protocol Buffers" category = "main" optional = false -python-versions = ">=3.7" +python-versions = ">=3.5" [[package]] name = "psutil" @@ -1751,6 +2117,14 @@ dev = ["coverage[toml] (==5.0.4)", "cryptography (>=3.4.0)", "pre-commit", "pyte docs = ["sphinx (>=4.5.0,<5.0.0)", "sphinx-rtd-theme", "zope.interface"] tests = ["coverage[toml] (==5.0.4)", "pytest (>=6.0.0,<7.0.0)"] +[[package]] +name = "pylatexenc" +version = "2.10" +description = "Simple LaTeX parser providing latex-to-unicode and unicode-to-latex conversion" +category = "main" +optional = false +python-versions = "*" + [[package]] name = "pymdown-extensions" version = "9.9.2" @@ -1762,6 +2136,17 @@ python-versions = ">=3.7" [package.dependencies] markdown = ">=3.2" +[[package]] +name = "pyparsing" +version = "3.0.9" +description = "pyparsing module - Classes and methods to define and execute parsing grammars" +category = "main" +optional = false +python-versions = ">=3.6.8" + +[package.extras] +diagrams = ["jinja2", "railroad-diagrams"] + [[package]] name = "pyproject-hooks" version = "1.0.0" @@ -1773,6 +2158,21 @@ python-versions = ">=3.7" [package.dependencies] tomli = {version = ">=1.1.0", markers = "python_version < \"3.11\""} +[[package]] +name = "pyspnego" +version = "0.8.0" +description = "Windows Negotiate Authentication Client and Server" +category = "main" +optional = false +python-versions = ">=3.7" + +[package.dependencies] +cryptography = "*" + +[package.extras] +kerberos = ["gssapi (>=1.6.0)", "krb5 (>=0.3.0)"] +yaml = ["ruamel.yaml"] + [[package]] name = "pytest" version = "7.2.1" @@ -1893,16 +2293,16 @@ pyyaml = "*" [[package]] name = "qiskit" -version = "0.41.1" +version = "0.39.3" description = "Software for developing quantum computing programs" category = "main" optional = false python-versions = ">=3.7" [package.dependencies] -qiskit-aer = "0.11.2" -qiskit-ibmq-provider = "0.20.1" -qiskit-terra = "0.23.2" +qiskit-aer = "0.11.1" +qiskit-ibmq-provider = "0.19.2" +qiskit-terra = "0.22.3" [package.extras] all = ["ipywidgets (>=7.3.0)", "matplotlib (>=2.1)", "pillow (>=4.2.1)", "pydot", "pygments (>=2.4)", "pylatexenc (>=1.4)", "qiskit-experiments (>=0.2.0)", "qiskit-finance (>=0.3.3)", "qiskit-machine-learning (>=0.4.0)", "qiskit-nature (>=0.4.1)", "qiskit-optimization (>=0.4.0)", "seaborn (>=0.9.0)"] @@ -1915,7 +2315,7 @@ visualization = ["ipywidgets (>=7.3.0)", "matplotlib (>=2.1)", "pillow (>=4.2.1) [[package]] name = "qiskit-aer" -version = "0.11.2" +version = "0.11.1" description = "Qiskit Aer - High performance simulators for Qiskit" category = "main" optional = false @@ -1931,24 +2331,24 @@ dask = ["dask", "distributed"] [[package]] name = "qiskit-ibmq-provider" -version = "0.20.1" +version = "0.19.2" description = "Qiskit provider for accessing the quantum devices and simulators at IBMQ" category = "main" optional = false python-versions = ">=3.7" [package.dependencies] -numpy = "<1.24" -python-dateutil = ">=2.8.0,<2.9.0" -qiskit-terra = ">=0.23.0,<0.24.0" -requests = ">=2.28.0,<2.29.0" -requests-ntlm = ">=1.1.0,<1.2.0" -urllib3 = ">=1.26.0,<1.27.0" -websocket-client = ">=1.5.1,<1.6.0" -websockets = {version = ">=10.0,<11.0", markers = "python_version >= \"3.7\""} +numpy = ">=1.13" +python-dateutil = ">=2.8.0" +qiskit-terra = ">=0.18.0" +requests = ">=2.19" +requests-ntlm = ">=1.1.0" +urllib3 = ">=1.21.1" +websocket-client = ">=1.0.1" +websockets = {version = ">=10.0", markers = "python_version >= \"3.7\""} [package.extras] -visualization = ["ipython (>=5.0.0)", "ipyvue (>=1.4.1)", "ipyvuetify (>=1.1)", "ipywidgets (<=7.7.2)", "matplotlib (>=2.1)", "plotly (>=4.4)", "pyperclip (>=1.7)", "seaborn (>=0.9.0)", "traitlets (!=5.0.5)"] +visualization = ["ipython (>=5.0.0)", "ipyvue (>=1.4.1)", "ipyvuetify (>=1.1)", "ipywidgets (>=7.3.0)", "matplotlib (>=2.1)", "plotly (>=4.4)", "pyperclip (>=1.7)", "seaborn (>=0.9.0)", "traitlets (!=5.0.5)"] [[package]] name = "qiskit-machine-learning" @@ -1974,7 +2374,7 @@ torch = ["torch"] [[package]] name = "qiskit-terra" -version = "0.23.2" +version = "0.22.3" description = "Software for developing quantum computing programs" category = "main" optional = false @@ -1986,19 +2386,19 @@ numpy = ">=1.17" ply = ">=3.10" psutil = ">=5" python-dateutil = ">=2.8.0" -rustworkx = ">=0.12.0" +retworkx = ">=0.11.0" scipy = ">=1.5" stevedore = ">=3.0.0" symengine = {version = ">=0.9", markers = "platform_machine == \"x86_64\" or platform_machine == \"aarch64\" or platform_machine == \"ppc64le\" or platform_machine == \"amd64\" or platform_machine == \"arm64\""} sympy = ">=1.3" +tweedledum = {version = ">=1.1,<2.0", markers = "python_version < \"3.11\" and (platform_machine != \"arm64\" or sys_platform != \"darwin\")"} [package.extras] -all = ["ipywidgets (>=7.3.0)", "matplotlib (>=3.3)", "pillow (>=4.2.1)", "pydot", "pygments (>=2.4)", "pylatexenc (>=1.4)", "python-constraint (>=1.4)", "qiskit-qasm3-import (>=0.1.0)", "seaborn (>=0.9.0)", "z3-solver (>=4.7)"] +all = ["ipywidgets (>=7.3.0)", "matplotlib (>=3.3)", "pillow (>=4.2.1)", "pydot", "pygments (>=2.4)", "pylatexenc (>=1.4)", "python-constraint (>=1.4)", "seaborn (>=0.9.0)", "z3-solver (>=4.7)"] bip-mapper = ["cplex", "docplex"] crosstalk-pass = ["z3-solver (>=4.7)"] csp-layout-pass = ["python-constraint (>=1.4)"] -qasm3-import = ["qiskit-qasm3-import (>=0.1.0)"] -toqm = ["qiskit-toqm (>=0.1.0)"] +toqm = ["qiskit-toqm (>=0.0.4)"] visualization = ["ipywidgets (>=7.3.0)", "matplotlib (>=3.3)", "pillow (>=4.2.1)", "pydot", "pygments (>=2.4)", "pylatexenc (>=1.4)", "seaborn (>=0.9.0)"] [[package]] @@ -2012,6 +2412,21 @@ python-versions = "*" [package.dependencies] six = "*" +[[package]] +name = "redis" +version = "4.5.1" +description = "Python client for Redis database and key-value store" +category = "main" +optional = false +python-versions = ">=3.7" + +[package.dependencies] +async-timeout = ">=4.0.2" + +[package.extras] +hiredis = ["hiredis (>=1.0.0)"] +ocsp = ["cryptography (>=36.0.1)", "pyopenssl (==20.0.1)", "requests (>=2.26.0)"] + [[package]] name = "requests" version = "2.28.2" @@ -2032,15 +2447,15 @@ use-chardet-on-py3 = ["chardet (>=3.0.2,<6)"] [[package]] name = "requests-ntlm" -version = "1.1.0" +version = "1.2.0" description = "This package allows for HTTP NTLM authentication using the requests library." category = "main" optional = false -python-versions = "*" +python-versions = ">=3.7" [package.dependencies] cryptography = ">=1.3" -ntlm-auth = ">=1.0.2" +pyspnego = ">=0.1.6" requests = ">=2.0.0" [[package]] @@ -2058,6 +2473,23 @@ requests = ">=2.0.0" [package.extras] rsa = ["oauthlib[signedtoken] (>=3.0.0)"] +[[package]] +name = "retworkx" +version = "0.12.1" +description = "A python graph library implemented in Rust" +category = "main" +optional = false +python-versions = ">=3.7" + +[package.dependencies] +numpy = ">=1.16.0" +rustworkx = "0.12.1" + +[package.extras] +all = ["matplotlib (>=3.0)", "pillow (>=5.4)"] +graphviz = ["pillow (>=5.4)"] +mpl = ["matplotlib (>=3.0)"] + [[package]] name = "rich" version = "12.6.0" @@ -2173,6 +2605,24 @@ docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "pygments-g testing = ["build[virtualenv]", "filelock (>=3.4.0)", "flake8 (<5)", "flake8-2020", "ini2toml[lite] (>=0.9)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "pip (>=19.1)", "pip-run (>=8.8)", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-flake8", "pytest-mypy (>=0.9.1)", "pytest-perf", "pytest-timeout", "pytest-xdist", "tomli-w (>=1.0.0)", "virtualenv (>=13.0.0)", "wheel"] testing-integration = ["build[virtualenv]", "filelock (>=3.4.0)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "pytest", "pytest-enabler", "pytest-xdist", "tomli", "virtualenv (>=13.0.0)", "wheel"] +[[package]] +name = "setuptools-scm" +version = "7.1.0" +description = "the blessed package to manage your versions by scm tags" +category = "main" +optional = false +python-versions = ">=3.7" + +[package.dependencies] +packaging = ">=20.0" +setuptools = "*" +tomli = {version = ">=1.0.0", markers = "python_version < \"3.11\""} +typing-extensions = "*" + +[package.extras] +test = ["pytest (>=6.2)", "virtualenv (>20)"] +toml = ["setuptools (>=42)"] + [[package]] name = "six" version = "1.16.0" @@ -2350,11 +2800,11 @@ doc = ["reno", "sphinx", "tornado (>=4.5)"] [[package]] name = "tensorboard" -version = "2.8.0" +version = "2.11.2" description = "TensorBoard lets you watch Tensors Flow" category = "main" optional = false -python-versions = ">=3.6" +python-versions = ">=3.7" [package.dependencies] absl-py = ">=0.4" @@ -2363,12 +2813,12 @@ google-auth-oauthlib = ">=0.4.1,<0.5" grpcio = ">=1.24.3" markdown = ">=2.6.8" numpy = ">=1.12.0" -protobuf = ">=3.6.0" +protobuf = ">=3.9.2,<4" requests = ">=2.21.0,<3" setuptools = ">=41.0.0" tensorboard-data-server = ">=0.6.0,<0.7.0" tensorboard-plugin-wit = ">=1.6.0" -werkzeug = ">=0.11.15" +werkzeug = ">=1.0.1" wheel = ">=0.26" [[package]] @@ -2389,42 +2839,59 @@ python-versions = "*" [[package]] name = "tensorflow" -version = "2.8.1" +version = "2.11.0" description = "TensorFlow is an open source machine learning framework for everyone." category = "main" optional = false -python-versions = "*" +python-versions = ">=3.7" [package.dependencies] -absl-py = ">=0.4.0" +absl-py = ">=1.0.0" astunparse = ">=1.6.0" -flatbuffers = ">=1.12" -gast = ">=0.2.1" +flatbuffers = ">=2.0" +gast = ">=0.2.1,<=0.4.0" google-pasta = ">=0.1.1" grpcio = ">=1.24.3,<2.0" h5py = ">=2.9.0" -keras = ">=2.8.0rc0,<2.9" -keras-preprocessing = ">=1.1.1" -libclang = ">=9.0.1" +keras = ">=2.11.0,<2.12" +libclang = ">=13.0.0" numpy = ">=1.20" opt-einsum = ">=2.3.2" -protobuf = ">=3.9.2" +packaging = "*" +protobuf = ">=3.9.2,<3.20" setuptools = "*" six = ">=1.12.0" -tensorboard = ">=2.8,<2.9" -tensorflow-estimator = ">=2.8,<2.9" -tensorflow-io-gcs-filesystem = ">=0.23.1" +tensorboard = ">=2.11,<2.12" +tensorflow-estimator = ">=2.11.0,<2.12" +tensorflow-io-gcs-filesystem = {version = ">=0.23.1", markers = "platform_machine != \"arm64\" or platform_system != \"Darwin\""} termcolor = ">=1.1.0" typing-extensions = ">=3.6.6" wrapt = ">=1.11.0" +[[package]] +name = "tensorflow-addons" +version = "0.19.0" +description = "TensorFlow Addons." +category = "main" +optional = false +python-versions = "*" + +[package.dependencies] +packaging = "*" +typeguard = ">=2.7" + +[package.extras] +tensorflow = ["tensorflow (>=2.9.0,<2.12.0)"] +tensorflow-cpu = ["tensorflow-cpu (>=2.9.0,<2.12.0)"] +tensorflow-gpu = ["tensorflow-gpu (>=2.9.0,<2.12.0)"] + [[package]] name = "tensorflow-estimator" -version = "2.8.0" +version = "2.11.0" description = "TensorFlow Estimator." category = "main" optional = false -python-versions = "*" +python-versions = ">=3.7" [[package]] name = "tensorflow-io-gcs-filesystem" @@ -2489,6 +2956,28 @@ category = "main" optional = false python-versions = "*" +[[package]] +name = "texttable" +version = "1.6.7" +description = "module to create simple ASCII tables" +category = "main" +optional = false +python-versions = "*" + +[[package]] +name = "tf-quant-finance" +version = "0.0.1.dev34" +description = "High-performance TensorFlow library for quantitative finance." +category = "main" +optional = false +python-versions = "*" + +[package.dependencies] +attrs = ">=18.2.0" +numpy = ">=1.21" +protobuf = "*" +tensorflow-probability = ">=0.12.1" + [[package]] name = "threadpoolctl" version = "3.1.0" @@ -2539,6 +3028,49 @@ typing-extensions = "*" [package.extras] opt-einsum = ["opt-einsum (>=3.3)"] +[[package]] +name = "torchinfo" +version = "1.7.2" +description = "Model summary in PyTorch, based off of the original torchsummary." +category = "main" +optional = false +python-versions = ">=3.7" + +[[package]] +name = "torchvision" +version = "0.14.1" +description = "image and video datasets and models for torch deep learning" +category = "main" +optional = false +python-versions = ">=3.7" + +[package.dependencies] +numpy = "*" +pillow = ">=5.3.0,<8.3.0 || >=8.4.0" +requests = "*" +torch = "1.13.1" +typing-extensions = "*" + +[package.extras] +scipy = ["scipy"] + +[[package]] +name = "tqdm" +version = "4.64.1" +description = "Fast, Extensible Progress Meter" +category = "main" +optional = false +python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,>=2.7" + +[package.dependencies] +colorama = {version = "*", markers = "platform_system == \"Windows\""} + +[package.extras] +dev = ["py-make (>=0.1.0)", "twine", "wheel"] +notebook = ["ipywidgets (>=6)"] +slack = ["slack-sdk"] +telegram = ["requests"] + [[package]] name = "traitlets" version = "5.9.0" @@ -2551,6 +3083,26 @@ python-versions = ">=3.7" docs = ["myst-parser", "pydata-sphinx-theme", "sphinx"] test = ["argcomplete (>=2.0)", "pre-commit", "pytest", "pytest-mock"] +[[package]] +name = "tweedledum" +version = "1.1.1" +description = "A library for synthesizing and manipulating quantum circuits" +category = "main" +optional = false +python-versions = ">=3.6" + +[[package]] +name = "typeguard" +version = "2.13.3" +description = "Run-time type checker for Python" +category = "main" +optional = false +python-versions = ">=3.5.3" + +[package.extras] +doc = ["sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme"] +test = ["mypy", "pytest", "typing-extensions"] + [[package]] name = "typing-extensions" version = "4.4.0" @@ -2559,6 +3111,38 @@ category = "main" optional = false python-versions = ">=3.7" +[[package]] +name = "uhi" +version = "0.3.3" +description = "Unified Histogram Interface: tools to help library authors work with histograms" +category = "main" +optional = false +python-versions = ">=3.6" + +[package.dependencies] +numpy = ">=1.13.3" + +[package.extras] +docs = ["sphinx (>=4.0)", "sphinx-book-theme (>=0.0.40)", "sphinx-copybutton (>=0.3.1)"] +test = ["boost-histogram (>=1.0)", "importlib-metadata (>=1.0)", "pytest (>=6)"] + +[[package]] +name = "uproot" +version = "4.3.7" +description = "ROOT I/O in pure Python and NumPy." +category = "main" +optional = false +python-versions = ">=3.6" + +[package.dependencies] +numpy = "*" +setuptools = "*" + +[package.extras] +all = ["awkward (>=1.0.0,<2)", "boost-histogram (>=0.13)", "dask[array]", "flake8", "flake8-print (>=5)", "hist (>=1.2)", "lz4", "pandas", "pytest (>=4.6)", "requests", "scikit-hep-testdata", "xxhash"] +dev = ["awkward (>=1.0.0,<2)", "boost-histogram (>=0.13)", "hist (>=1.2)", "pandas"] +test = ["dask[array]", "flake8", "flake8-print (>=5)", "lz4", "pytest (>=4.6)", "requests", "scikit-hep-testdata", "xxhash"] + [[package]] name = "urllib3" version = "1.26.14" @@ -2731,6 +3315,91 @@ category = "main" optional = false python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,>=2.7" +[[package]] +name = "xxhash" +version = "3.2.0" +description = "Python binding for xxHash" +category = "main" +optional = false +python-versions = ">=3.6" + +[[package]] +name = "zfit" +version = "0.11.1" +description = "scalable pythonic model fitting for high energy physics" +category = "main" +optional = false +python-versions = ">=3.7" + +[package.dependencies] +boost-histogram = "*" +colorama = "*" +colored = "*" +colorlog = "*" +deprecated = "*" +dotmap = "*" +hist = "*" +iminuit = ">=2.3" +jacobi = "*" +numdifftools = "*" +numpy = ">=1.16" +ordered-set = "*" +pandas = "*" +pydantic = "*" +scipy = ">=1.2" +tabulate = "*" +tensorflow = ">=2.10,<2.12" +tensorflow-addons = "*" +tensorflow-probability = ">=0.18,<0.20" +texttable = "*" +tf-quant-finance = ">=v0.0.1-dev24" +uhi = "*" +uproot = ">=4,<5" +xxhash = "*" +zfit-interface = "*" + +[package.extras] +all = ["ipyopt (>=0.12)", "nlopt (>=2.7.1)"] +alldev = ["Jinja2", "Sphinx (>=3.5.4)", "bumpversion (>=0.5.3)", "check-manifest", "coverage (>=4.5.1)", "docformatter", "flake8 (>=3.5.0)", "ipyopt 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qiskit-machine-learning = "^0.5.0" -qiskit = "^0.41.1" #"^0.38.0" python-json-logger = "^2.0.7" phasespace = "^1.8.0" +particle = "^0.21.2" +decaylanguage = "^0.15.1" +zfit = "^0.11.1" +zfit-physics = "^0.5.0" +torchvision = "^0.14.1" +redis = "^4.5.1" +optuna = "^3.1.0" +matplotlib = "^3.7.0" +torchinfo = "^1.7.2" +pylatexenc = "^2.10" +qiskit = "0.39.3" [tool.poetry.group.dev.dependencies] pytest = "^7.2.0" From 35e6775a4ca419b905544c0fbc262c577927020b Mon Sep 17 00:00:00 2001 From: lc3267 Date: Fri, 17 Mar 2023 16:32:24 +0100 Subject: [PATCH 88/92] cleaned readme --- README.md | 134 +++++------------------------------------------------- 1 file changed, 12 insertions(+), 122 deletions(-) diff --git a/README.md b/README.md index b7419e2..244b130 100644 --- a/README.md +++ b/README.md @@ -18,6 +18,18 @@ pip compile torch_scatter needs gcc-c++ and python3-devel packages to build successfully. +with poetry you need to release the tensorflow-probability dependency from phasespace such that the line in ```.venv/lib/python3.10/site-packages/phasespace-1.8.0.dist-info/METADATA``` becomes +``` +Requires-Dist: tensorflow-probability (>=0.15) +``` +To achieve this, you may want to run +``` +poetry add phasespace +``` +prior to the installation of the other packages using +``` +poe + changed module dependencies in phasespace: before: @@ -44,125 +56,3 @@ run kedro mlflow init - - -## Overview - -This is your new Kedro project, which was generated using `Kedro 0.17.7`. - -Take a look at the [Kedro documentation](https://kedro.readthedocs.io) to get started. - -## Rules and guidelines - -In order to get the best out of the template: - -* Don't remove any lines from the `.gitignore` file we provide -* Make sure your results can be reproduced by following a [data engineering convention](https://kedro.readthedocs.io/en/stable/12_faq/01_faq.html#what-is-data-engineering-convention) -* Don't commit data to your repository -* Don't commit any credentials or your local configuration to your repository. Keep all your credentials and local configuration in `conf/local/` - -## How to install dependencies - -Declare any dependencies in `src/requirements.txt` for `pip` installation and `src/environment.yml` for `conda` installation. - -To install them, run: - -``` -kedro install -``` - -## How to run your Kedro pipeline - -You can run your Kedro project with: - -``` -kedro run -``` - -## How to test your Kedro project - -Have a look at the file `src/tests/test_run.py` for instructions on how to write your tests. You can run your tests as follows: - -``` -kedro test -``` - -To configure the coverage threshold, go to the `.coveragerc` file. - -## Project dependencies - -To generate or update the dependency requirements for your project: - -``` -kedro build-reqs -``` - -This will copy the contents of `src/requirements.txt` into a new file `src/requirements.in` which will be used as the source for `pip-compile`. You can see the output of the resolution by opening `src/requirements.txt`. - -After this, if you'd like to update your project requirements, please update `src/requirements.in` and re-run `kedro build-reqs`. - -[Further information about project dependencies](https://kedro.readthedocs.io/en/stable/04_kedro_project_setup/01_dependencies.html#project-specific-dependencies) - -## How to work with Kedro and notebooks - -> Note: Using `kedro jupyter` or `kedro ipython` to run your notebook provides these variables in scope: `context`, `catalog`, and `startup_error`. -> -> Jupyter, JupyterLab, and IPython are already included in the project requirements by default, so once you have run `kedro install` you will not need to take any extra steps before you use them. - -### Jupyter -To use Jupyter notebooks in your Kedro project, you need to install Jupyter: - -``` -pip install jupyter -``` - -After installing Jupyter, you can start a local notebook server: - -``` -kedro jupyter notebook -``` - -### JupyterLab -To use JupyterLab, you need to install it: - -``` -pip install jupyterlab -``` - -You can also start JupyterLab: - -``` -kedro jupyter lab -``` - -### IPython -And if you want to run an IPython session: - -``` -kedro ipython -``` - -### How to convert notebook cells to nodes in a Kedro project -You can move notebook code over into a Kedro project structure using a mixture of [cell tagging](https://jupyter-notebook.readthedocs.io/en/stable/changelog.html#release-5-0-0) and Kedro CLI commands. - -By adding the `node` tag to a cell and running the command below, the cell's source code will be copied over to a Python file within `src//nodes/`: - -``` -kedro jupyter convert -``` -> *Note:* The name of the Python file matches the name of the original notebook. - -Alternatively, you may want to transform all your notebooks in one go. Run the following command to convert all notebook files found in the project root directory and under any of its sub-folders: - -``` -kedro jupyter convert --all -``` - -### How to ignore notebook output cells in `git` -To automatically strip out all output cell contents before committing to `git`, you can run `kedro activate-nbstripout`. This will add a hook in `.git/config` which will run `nbstripout` before anything is committed to `git`. - -> *Note:* Your output cells will be retained locally. - -## Package your Kedro project - -[Further information about building project documentation and packaging your project](https://kedro.readthedocs.io/en/stable/03_tutorial/08_package_a_project.html) From e649ad7921a7113226bab9b3ca161f686b695739 Mon Sep 17 00:00:00 2001 From: lc3267 Date: Fri, 17 Mar 2023 16:32:36 +0100 Subject: [PATCH 89/92] debug flag --- .vscode/launch.json | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/.vscode/launch.json b/.vscode/launch.json index bec3777..ef27c14 100644 --- a/.vscode/launch.json +++ b/.vscode/launch.json @@ -124,7 +124,8 @@ "request": "launch", "console": "integratedTerminal", "module": "kedro", - "args": ["run"] + "args": ["run"], + // "justMyCode": false // Any other arguments should be passed as a comma-seperated-list // e.g "args": ["run", "--pipeline", "pipeline_name"] } From 10a5f899816500d595db765a922748feb4b52688 Mon Sep 17 00:00:00 2001 From: lc3267 Date: Fri, 17 Mar 2023 16:32:57 +0100 Subject: [PATCH 90/92] adj lr --- conf/base/parameters/data_science.yml | 7 ++++--- 1 file changed, 4 insertions(+), 3 deletions(-) diff --git a/conf/base/parameters/data_science.yml b/conf/base/parameters/data_science.yml index 7e3ab67..efa9e0d 100644 --- a/conf/base/parameters/data_science.yml +++ b/conf/base/parameters/data_science.yml @@ -17,7 +17,7 @@ batchnorm: True dropout_rate: 0.2 dropout_rate_range: [0.1, 1.0, "linear"] -learning_rate: 0.001 +learning_rate: 0.01 learning_rate_range: [1e-5, 1e-1, "log"] learning_rate_decay: 200 learning_rate_decay_range: [1, 1000, "log"] @@ -35,6 +35,7 @@ n_blocks_range: [1, 5, "linear"] n_layers_mlp: 2 # initial mlp layers before the blocks n_layers_mlp_range: [1, 5, "linear"] n_additional_mlp_layers: 0 # additional layers within a block + n_additional_mlp_layers_range: [1, 5, "linear"] n_final_mlp_layers: 2 # layers after the blocks n_final_mlp_layers_range: [1, 5, "linear"] @@ -51,9 +52,9 @@ add_rot_gates_range: [True, False] n_layers_vqc: 3 n_layers_vqc_range: [1, 5, "linear"] padding_dropout: False -predefined_vqc: "circuit_19" # "", "circuit_19", .. tba. +predefined_vqc: "circuit_18" # "", "circuit_19_missing", "circuit_19_flipped", "circuit_19", .. tba. measurement: "entangled" # mutually_exclusive, all, entangled -backend: "aer_simulator_statevector" # aer_simulator_statevector, ibm_perth +backend: "aer_simulator" # aer_simulator, aer_simulator_statevector, ibm_perth #TODO specify when available redis_host: "localhost" redis_port: 6379 From 6d87617c22c5d62cfc67d4303dfc35e3572b8974 Mon Sep 17 00:00:00 2001 From: lc3267 Date: Fri, 17 Mar 2023 16:33:20 +0100 Subject: [PATCH 91/92] backend evals --- .../pipelines/data_science/qgnn.py | 107 ++++++++++++++++-- 1 file changed, 95 insertions(+), 12 deletions(-) diff --git a/src/partiqleDTR/pipelines/data_science/qgnn.py b/src/partiqleDTR/pipelines/data_science/qgnn.py index b185eaa..e8931f4 100644 --- a/src/partiqleDTR/pipelines/data_science/qgnn.py +++ b/src/partiqleDTR/pipelines/data_science/qgnn.py @@ -12,7 +12,10 @@ import qiskit as q from qiskit import transpile, assemble from qiskit.visualization import * -from qiskit_machine_learning.neural_networks import CircuitQNN, TwoLayerQNN +from qiskit_machine_learning.neural_networks import CircuitQNN, TwoLayerQNN, SamplerQNN + +from qiskit.primitives import BackendSampler +from qiskit.providers.aer import QasmSimulator import logging @@ -119,6 +122,7 @@ def __init__( assert dim_feedforward % 2 == 0, "dim_feedforward must be an even number" + self.start=None self.num_classes = n_classes self.layers = n_layers_vqc # dim_feedforward//8 self.total_n_fsps = n_fsps # used for padding in forward path @@ -133,7 +137,7 @@ def __init__( self.measurement = measurement self.predefined_vqc = predefined_vqc - if backend != "aer_simulator_statevector": + if "simulator" not in backend: from .ibmq_access import token, hub, group, project log.info(f"Searching for backend {backend} on IBMQ using token {token[:10]}****, hub {hub}, group {group} and project {project}") self.provider = q.IBMQ.enable_account( @@ -146,10 +150,18 @@ def __init__( else: log.info(f"Using simulator backend {backend}") self.backend = q.Aer.get_backend(backend) - - self.qi = q.utils.QuantumInstance( - self.backend - ) + # # self.backend = QasmSimulator() + # self.bs = BackendSampler( + # self.backend, + # # options={ + # # "shots": 2048, + # # }, + # skip_transpilation=False, + # ) + + # self.qi = q.utils.QuantumInstance( + # self.backend + # ) self.enc_params = [] self.var_params = [] @@ -270,6 +282,31 @@ def build_circuit_19_flipped(qc, n_qubits, identifier): f"{identifier}_crx_{i+1}_{i}", ) + def build_circuit_19_missing(qc, n_qubits, identifier): + for i in range(n_qubits): + qc.rx( + q.circuit.Parameter(f"{identifier}_rx_0_{i}"), + i, + f"{identifier}_rx_0_{i}", + ) + qc.rz(q.circuit.Parameter(f"{identifier}_rz_1_{i}"), i) + + for i in range(n_qubits-1): + if i == 0: + qc.crx( + q.circuit.Parameter(f"{identifier}_crx_{i+1}_{i}"), + i, + n_qubits - 1, + f"{identifier}_crx_{i+1}_{i}", + ) + else: + qc.crx( + q.circuit.Parameter(f"{identifier}_crx_{i+1}_{i}"), + n_qubits - i, + n_qubits - i - 1, + f"{identifier}_crx_{i+1}_{i}", + ) + def build_circuit_19(qc, n_qubits, identifier): for i in range(n_qubits): qc.rx( @@ -295,6 +332,31 @@ def build_circuit_19(qc, n_qubits, identifier): f"{identifier}_crx_{i+1}_{i}", ) + def build_circuit_18(qc, n_qubits, identifier): + for i in range(n_qubits): + qc.rx( + q.circuit.Parameter(f"{identifier}_rx_0_{i}"), + i, + f"{identifier}_rx_0_{i}", + ) + qc.rz(q.circuit.Parameter(f"{identifier}_rz_1_{i}"), i) + + for i in range(n_qubits): + if i == 0: + qc.crz( + q.circuit.Parameter(f"{identifier}_crz_{i+1}_{i}"), + n_qubits - 1, + i, + f"{identifier}_crz_{i+1}_{i}", + ) + else: + qc.crz( + q.circuit.Parameter(f"{identifier}_crx_{i+1}_{i}"), + n_qubits - i - 1, + n_qubits - i, + f"{identifier}_crz_{i+1}_{i}", + ) + def circuit_builder(qc, n_qubits, n_hidden): enc_params = gen_encoding_params(n_qubits, f"enc") for i in range(n_hidden): @@ -307,6 +369,10 @@ def circuit_builder(qc, n_qubits, n_hidden): build_circuit_19(qc, n_qubits, f"var_{i}") elif self.predefined_vqc == "circuit_19_flipped": build_circuit_19_flipped(qc, n_qubits, f"var_{i}") + elif self.predefined_vqc == "circuit_18": + build_circuit_18(qc, n_qubits, f"var_{i}") + elif self.predefined_vqc == "circuit_19_missing": + build_circuit_19_missing(qc, n_qubits, f"var_{i}") else: raise ValueError("Invalid circuit specified") qc.barrier() @@ -335,20 +401,34 @@ def interpreter(x): return x start = time.time() - self.qnn = CircuitQNN( - self.qc, - self.enc_params, - self.var_params, - quantum_instance=self.qi, + # self.qnn = CircuitQNN( + # self.qc, + # self.enc_params, + # self.var_params, + # quantum_instance=self.qi, + # # interpret=interpreter, + # # output_shape=(n_fsps**2, n_classes), + # # sampling=True, + # input_gradients=True, + # ) + self.qnn = SamplerQNN( + circuit=self.qc, + # sampler=self.bs, + input_params=self.enc_params, + weight_params=self.var_params, + # quantum_instance=self.qi, # interpret=interpreter, # output_shape=(n_fsps**2, n_classes), # sampling=True, - input_gradients=True, + input_gradients=True, #set to true since we are using torch connector ) self.initial_weights = 0.1 * ( 2 * q.utils.algorithm_globals.random.random(self.qnn.num_weights) - 1 ) log.info(f"Transpilation took {time.time() - start}") + # self.quantum_layer = TorchConnector( + # self.qnn, initial_weights=self.initial_weights + # ) self.quantum_layer = TorchConnector( self.qnn, initial_weights=self.initial_weights ) @@ -645,6 +725,9 @@ def forward(self, inputs): x = self.quantum_layer(x) + if self.start is not None: + print(f"Duration: {time.time()-self.start}") + self.start = time.time() def build_binary_permutation_indices(digits): From 594fb8d83e93a70aeeb8483f17ab2bd5cdab19a6 Mon Sep 17 00:00:00 2001 From: lc3267 Date: Fri, 17 Mar 2023 16:33:43 +0100 Subject: [PATCH 92/92] started exporting circuits --- .../pipelines/data_science/circuits.py | 78 +++++++++++++++++++ 1 file changed, 78 insertions(+) create mode 100644 src/partiqleDTR/pipelines/data_science/circuits.py diff --git a/src/partiqleDTR/pipelines/data_science/circuits.py b/src/partiqleDTR/pipelines/data_science/circuits.py new file mode 100644 index 0000000..8fc05e1 --- /dev/null +++ b/src/partiqleDTR/pipelines/data_science/circuits.py @@ -0,0 +1,78 @@ +import qiskit as q + + +def build_circuit_19(qc, n_qubits, identifier): + for i in range(n_qubits): + qc.rx( + q.circuit.Parameter(f"{identifier}_rx_0_{i}"), + i, + f"{identifier}_rx_0_{i}", + ) + qc.rz(q.circuit.Parameter(f"{identifier}_rz_1_{i}"), i) + + for i in range(n_qubits): + if i == 0: + qc.crx( + q.circuit.Parameter(f"{identifier}_crx_{i+1}_{i}"), + n_qubits - 1, + i, + f"{identifier}_crx_{i+1}_{i}", + ) + else: + qc.crx( + q.circuit.Parameter(f"{identifier}_crx_{i+1}_{i}"), + n_qubits - i - 1, + n_qubits - i, + f"{identifier}_crx_{i+1}_{i}", + ) + +def build_circuit_19_missing(qc, n_qubits, identifier): + for i in range(n_qubits): + qc.rx( + q.circuit.Parameter(f"{identifier}_rx_0_{i}"), + i, + f"{identifier}_rx_0_{i}", + ) + qc.rz(q.circuit.Parameter(f"{identifier}_rz_1_{i}"), i) + + for i in range(n_qubits-1): + if i == 0: + qc.crx( + q.circuit.Parameter(f"{identifier}_crx_{i+1}_{i}"), + i, + n_qubits - 1, + f"{identifier}_crx_{i+1}_{i}", + ) + else: + qc.crx( + q.circuit.Parameter(f"{identifier}_crx_{i+1}_{i}"), + n_qubits - i, + n_qubits - i - 1, + f"{identifier}_crx_{i+1}_{i}", + ) + + +def build_circuit_19_flipped(qc, n_qubits, identifier): + for i in range(n_qubits): + qc.rx( + q.circuit.Parameter(f"{identifier}_rx_0_{i}"), + i, + f"{identifier}_rx_0_{i}", + ) + qc.rz(q.circuit.Parameter(f"{identifier}_rz_1_{i}"), i) + + for i in range(n_qubits): + if i == 0: + qc.crx( + q.circuit.Parameter(f"{identifier}_crx_{i+1}_{i}"), + i, + n_qubits - 1, + f"{identifier}_crx_{i+1}_{i}", + ) + else: + qc.crx( + q.circuit.Parameter(f"{identifier}_crx_{i+1}_{i}"), + n_qubits - i, + n_qubits - i - 1, + f"{identifier}_crx_{i+1}_{i}", + ) \ No newline at end of file