From 333c06794cd03cb8c2127b3a3590657135c939d5 Mon Sep 17 00:00:00 2001 From: Olivier Sprangers Date: Mon, 22 Apr 2024 09:50:27 +0200 Subject: [PATCH] remove_multivariate --- action_files/test_models/src/evaluation.py | 2 +- action_files/test_models/src/models.py | 5 ----- 2 files changed, 1 insertion(+), 6 deletions(-) diff --git a/action_files/test_models/src/evaluation.py b/action_files/test_models/src/evaluation.py index f6b0a9db6..cbe4e35c6 100644 --- a/action_files/test_models/src/evaluation.py +++ b/action_files/test_models/src/evaluation.py @@ -43,7 +43,7 @@ def evaluate(model: str, dataset: str, group: str): groups = ['Monthly'] models = ['AutoDilatedRNN', 'RNN', 'TCN', 'DeepAR', 'NHITS', 'TFT', 'AutoMLP', 'DLinear', 'VanillaTransformer', - 'BiTCN', 'TiDE', 'TSMixer', 'iTransformer'] + 'BiTCN', 'TiDE'] datasets = ['M3'] evaluation = [evaluate(model, dataset, group) for model, group in product(models, groups) for dataset in datasets] evaluation = [eval_ for eval_ in evaluation if eval_ is not None] diff --git a/action_files/test_models/src/models.py b/action_files/test_models/src/models.py index ab715672a..583613bdb 100644 --- a/action_files/test_models/src/models.py +++ b/action_files/test_models/src/models.py @@ -26,8 +26,6 @@ # from neuralforecast.models.autoformer import Autoformer # from neuralforecast.models.patchtst import PatchTST from neuralforecast.models.dlinear import DLinear -from neuralforecast.models.tsmixer import TSMixer -from neuralforecast.models.itransformer import iTransformer from neuralforecast.models.bitcn import BiTCN from neuralforecast.models.tide import TiDE @@ -66,7 +64,6 @@ def main(dataset: str = 'M3', group: str = 'Monthly') -> None: "val_check_steps": 100, "random_seed": tune.choice([1, 2, 3, 4, 5, 6, 7, 8, 9, 10]),} - n_series = train['unique_id'].nunique() models = [ AutoDilatedRNN(h=horizon, loss=MAE(), config=config_drnn, num_samples=2, cpus=1), RNN(h=horizon, input_size=2 * horizon, encoder_hidden_size=50, max_steps=300), @@ -79,8 +76,6 @@ def main(dataset: str = 'M3', group: str = 'Monthly') -> None: DeepAR(h=horizon, input_size=2 * horizon, scaler_type='minmax1', max_steps=1000), BiTCN(h=horizon, input_size=2 * horizon, loss=MAE(), dropout=0.0, max_steps=1000, val_check_steps=500), TiDE(h=horizon, input_size=2 * horizon, loss=MAE(), max_steps=1000, val_check_steps=500), - TSMixer(h=horizon, input_size=2 * horizon, n_series=n_series, loss=MAE(), max_steps=1000, val_check_steps=500), - iTransformer(h=horizon, input_size=2 * horizon, n_series=n_series, loss=MAE(), max_steps=1000, val_check_steps=500), ] # Models