Fix import star (#9)

Image/PixelImage.py

@@ -1,4 +1,4 @@
-from pytti import *
+from pytti import DEVICE, named_rearrange, replace_grad, vram_usage_mode
 from pytti.Image import DifferentiableImage
 from pytti.LossAug import HSVLoss
 from pytti.ImageGuide import DirectImageGuide

Image/RGBImage.py

@@ -1,4 +1,4 @@
-from pytti import *
+from pytti import DEVICE, clamp_with_grad
 import torch
 from torch import nn
 from torchvision.transforms import functional as TF

Image/VQGANImage.py

@@ -8,7 +8,7 @@
   print("DEBUG: sys.path already contains ./taming transformers")
 from taming.models import cond_transformer, vqgan
 
-from pytti import *
+from pytti import DEVICE, replace_grad, clamp_with_grad, vram_usage_mode
 import torch
 from torch.nn import functional as F
 from pytti.Image import EMAImage

Image/__init__.py

@@ -2,7 +2,7 @@
 from torch import nn
 import numpy as np
 from PIL import Image
-from pytti import *
+from pytti import named_rearrange
 
 SUPPORTED_MODES = ['L','RGB','I','F']
 FORMAT_SAMPLES  = {'L':1, 'RGB':3, 'I':1, 'F':1}

ImageGuide.py

@@ -1,6 +1,6 @@
 from torch import optim, nn
 from pytti.Notebook import tqdm
-from pytti import *
+from pytti import format_input
 import pandas as pd
 import math
 

LossAug/LatentLoss.py

@@ -1,11 +1,10 @@
 from pytti.LossAug import MSELoss
 import gc, torch, os, math
-from pytti import DEVICE
 from torchvision.transforms import functional as TF
 from torch.nn import functional as F
 from PIL import Image
 import copy, re
-from pytti import *
+from pytti import DEVICE, fetch, parse, vram_usage_mode
 
 class LatentLoss(MSELoss):
   @torch.no_grad()

LossAug/MSELoss.py

@@ -4,7 +4,7 @@
 from torch.nn import functional as F
 from pytti.LossAug import Loss
 from pytti.Notebook import Rotoscoper
-from pytti import *
+from pytti import DEVICE, fetch, parse, vram_usage_mode
 import torch
 
 class MSELoss(Loss):

LossAug/__init__.py

@@ -2,7 +2,7 @@
 import torch
 from PIL import Image
 from torchvision.transforms import functional as TF
-from pytti import *
+from pytti import DEVICE, replace_grad, parametric_eval
 
 class Loss(nn.Module):
   def __init__(self, weight, stop, name):

Perceptor/Embedder.py

@@ -1,5 +1,5 @@
-from pytti import *
 import pytti
+from pytti import DEVICE, format_input, cat_with_pad, format_module, normalize
 
 import torch
 from torch import nn

Perceptor/Prompt.py

@@ -1,4 +1,4 @@
-from pytti import *
+from pytti import DEVICE, format_input, cat_with_pad, replace_grad, fetch, parse, parametric_eval, vram_usage_mode
 from pytti.Notebook import Rotoscoper
 import torch
 from torch import nn

Transforms.py

@@ -3,7 +3,7 @@
 import torch.nn.functional as F
 from PIL import Image, ImageFilter
 import numpy as np
-from pytti import *
+from pytti import DEVICE, parametric_eval
 from pytti.LossAug.DepthLoss import DepthLoss
 from infer import InferenceHelper
 

workhorse.py

@@ -48,7 +48,13 @@
 #  drive_mounted = False
 drive_mounted = False
 try:
-  from pytti.Notebook import *
+  from pytti.Notebook import (
+    is_notebook, change_tqdm_color, get_tqdm, get_last_file,
+    get_next_file, make_hbox, load_settings, write_settings, 
+    save_settings, save_batch, CLIP_MODEL_NAMES, load_clip, 
+    get_frames, build_loss, format_params, rotoscopers, 
+    clear_rotoscopers, update_rotoscopers, Rotoscoper
+  )
 except ModuleNotFoundError:
   if drive_mounted:
     #THIS IS NOT AN ERROR. This is the code that would
@@ -81,7 +87,7 @@
 from pytti.Perceptor.Prompt import parse_prompt
 from pytti.LossAug import TVLoss, HSVLoss, OpticalFlowLoss, TargetFlowLoss
 from pytti.Transforms import zoom_2d, zoom_3d, apply_flow
-from pytti import *
+from pytti import DEVICE, fetch, parametric_eval, set_t, vram_usage_mode, print_vram_usage, reset_vram_usage, freeze_vram_usage, vram_profiling
 from pytti.LossAug.DepthLoss import init_AdaBins
 logger.info("pytti loaded.")