fix imports hard

etna/libs/ts2vec/dilated_conv.py

@@ -23,10 +23,11 @@
 """
 # Note: Copied from ts2vec repository (https://github.com/yuezhihan/ts2vec/tree/main)
 
-import torch
-from torch import nn
-import torch.nn.functional as F
-import numpy as np
+from etna import SETTINGS
+
+if SETTINGS.torch_required:
+    from torch import nn
+    import torch.nn.functional as F
 
 
 class SamePadConv(nn.Module):

etna/libs/ts2vec/encoder.py

@@ -23,12 +23,15 @@
 """
 # Note: Copied from ts2vec repository (https://github.com/yuezhihan/ts2vec/tree/main)
 
-import torch
-from torch import nn
-import torch.nn.functional as F
 import numpy as np
 from etna.libs.ts2vec.dilated_conv import DilatedConvEncoder
 
+from etna import SETTINGS
+
+if SETTINGS.torch_required:
+    import torch
+    from torch import nn
+
 
 def generate_continuous_mask(B, T, n=5, l=0.1):
     res = torch.full((B, T), True, dtype=torch.bool)

etna/libs/ts2vec/losses.py

@@ -22,10 +22,11 @@
 SOFTWARE.
 """
 # Note: Copied from ts2vec repository (https://github.com/yuezhihan/ts2vec/tree/main)
+from etna import SETTINGS
 
-import torch
-from torch import nn
-import torch.nn.functional as F
+if SETTINGS.torch_required:
+    import torch
+    import torch.nn.functional as F
 
 
 def hierarchical_contrastive_loss(z1, z2, alpha=0.5, temporal_unit=0):

etna/libs/ts2vec/ts2vec.py

@@ -25,15 +25,18 @@
 # Removed skipping training loop when model is already pretrained. Removed "multiscale" encode option.
 # Move lr parameter to fit method
 
-import torch
-import torch.nn.functional as F
-from torch.utils.data import TensorDataset, DataLoader
 import numpy as np
 from etna.libs.ts2vec.encoder import TSEncoder
-from etna.loggers import tslogger, ConsoleLogger
+from etna.loggers import tslogger
 from etna.libs.ts2vec.losses import  hierarchical_contrastive_loss
 from etna.libs.ts2vec.utils import take_per_row, split_with_nan, centerize_vary_length_series, torch_pad_nan, AveragedModel
-import math
+
+from etna import SETTINGS
+
+if SETTINGS.torch_required:
+    import torch
+    import torch.nn.functional as F
+    from torch.utils.data import TensorDataset, DataLoader
 
 
 class TS2Vec:

etna/libs/ts2vec/utils.py

@@ -24,12 +24,13 @@
 # Note: Copied from ts2vec repository (https://github.com/yuezhihan/ts2vec/tree/main)
 
 import numpy as np
-import pickle
-import torch
-import random
-from datetime import datetime
 from copy import deepcopy
 
+from etna import SETTINGS
+
+if SETTINGS.torch_required:
+    import torch
+
 
 def torch_pad_nan(arr, left=0, right=0, dim=0):
     if left > 0:

etna/libs/tstcc/attention.py

@@ -23,10 +23,13 @@
 """
 # Note: Copied from ts-tcc repository (https://github.com/emadeldeen24/TS-TCC/tree/main)
 
-import torch
-import torch.nn as nn
-import torch.nn.functional as F
-from einops import rearrange, repeat
+from etna import SETTINGS
+
+if SETTINGS.torch_required:
+    import torch
+    import torch.nn as nn
+    import torch.nn.functional as F
+    from einops import rearrange, repeat
 
 
 class Residual(nn.Module):

etna/libs/tstcc/augmentations.py

@@ -25,7 +25,11 @@
 # Fix numpy warning in `permutation` function
 
 import numpy as np
-import torch
+
+from etna import SETTINGS
+
+if SETTINGS.torch_required:
+    import torch
 
 
 def DataTransform(sample, jitter_scale_ratio, max_seg, jitter_ratio):

etna/libs/tstcc/dataloader.py

@@ -23,11 +23,13 @@
 """
 # Note: Copied from ts-tcc repository (https://github.com/emadeldeen24/TS-TCC/tree/main)
 
-import torch
-from torch.utils.data import Dataset
-
 from etna.libs.tstcc.augmentations import DataTransform
 
+from etna import SETTINGS
+
+if SETTINGS.torch_required:
+    import torch
+    from torch.utils.data import Dataset
 
 class Load_Dataset(Dataset):
     # Initialize your data, download, etc.

etna/libs/tstcc/encoder.py

@@ -27,7 +27,10 @@
 # Added ignoring warning about even kernel lengths and odd dilation in nn.Conv1d blocks.
 import warnings
 
-from torch import nn
+from etna import SETTINGS
+
+if SETTINGS.torch_required:
+    from torch import nn
 
 
 class ConvEncoder(nn.Module):

etna/libs/tstcc/loss.py

@@ -23,9 +23,13 @@
 """
 # Note: Copied from ts-tcc repository (https://github.com/emadeldeen24/TS-TCC/tree/main)
 
-import torch
 import numpy as np
 
+from etna import SETTINGS
+
+if SETTINGS.torch_required:
+    import torch
+
 
 class NTXentLoss(torch.nn.Module):
 

etna/libs/tstcc/tc.py

@@ -26,10 +26,13 @@
 
 import warnings
 
-import torch
-import torch.nn as nn
 import numpy as np
 from etna.libs.tstcc.attention import Seq_Transformer
+from etna import SETTINGS
+
+if SETTINGS.torch_required:
+    import torch
+    import torch.nn as nn
 
 
 class TC(nn.Module):

etna/libs/tstcc/tstcc.py

@@ -30,10 +30,13 @@
 from etna.libs.tstcc.dataloader import Load_Dataset
 from etna.libs.tstcc.loss import NTXentLoss
 from etna.loggers import tslogger
-import numpy as np
-import torch
-import torch.nn.functional as F
-from torch.utils.data import DataLoader
+
+from etna import SETTINGS
+
+if SETTINGS.torch_required:
+    import torch
+    import torch.nn.functional as F
+    from torch.utils.data import DataLoader
 
 
 class TSTCC:

etna/transforms/embeddings/models/ts2vec.py

@@ -6,11 +6,8 @@
 
 import numpy as np
 
-from etna import SETTINGS
 from etna.transforms.embeddings.models import BaseEmbeddingModel
-
-if SETTINGS.torch_required:
-    from etna.libs.ts2vec import TS2Vec
+from etna.libs.ts2vec import TS2Vec
 
 
 class TS2VecEmbeddingModel(BaseEmbeddingModel):

etna/transforms/embeddings/models/tstcc.py

@@ -5,11 +5,9 @@
 
 import numpy as np
 
-from etna import SETTINGS
 from etna.transforms.embeddings.models import BaseEmbeddingModel
 
-if SETTINGS.torch_required:
-    from etna.libs.tstcc import TSTCC
+from etna.libs.tstcc import TSTCC
 
 
 class TSTCCEmbeddingModel(BaseEmbeddingModel):