[pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

setup.py

@@ -6,6 +6,7 @@
     PyScaffold helps you to put up the scaffold of your new Python project.
     Learn more under: https://pyscaffold.org/
 """
+
 from setuptools import setup
 
 if __name__ == "__main__":

src/grelu/data/dataset.py

@@ -4,6 +4,7 @@
 All dataset classes produce either one-hot encoded sequences of shape (4, L)
 or sequence-label pairs of shape (4, L) and (T, L).
 """
+
 import os
 from typing import Callable, List, Optional, Sequence, Tuple, Union
 

src/grelu/data/preprocess.py

@@ -1,6 +1,7 @@
 """
 Functions to preprocess genomic datasets.
 """
+
 import os
 import subprocess
 import tempfile

src/grelu/data/utils.py

@@ -1,6 +1,7 @@
 """
 Dataset-related utility functions.
 """
+
 from typing import List, Union
 
 import pandas as pd

src/grelu/interpret/score.py

@@ -1,6 +1,7 @@
 """
 Functions related to scoring the importance of individual DNA bases.
 """
+
 import os
 import warnings
 from typing import Callable, List, Optional, Union

src/grelu/io/__init__.py

@@ -78,38 +78,38 @@ def update_ckpt(ckpt_file: str, out_file: Optional[str] = None) -> None:
     }
 
     for i in range(6):
-        keys_dict[
-            f"model.conv_tower.{i}.0.0"
-        ] = f"model.embedding.conv_tower.blocks.{i+1}.0.norm.layer"
-        keys_dict[
-            f"model.conv_tower.{i}.0.2"
-        ] = f"model.embedding.conv_tower.blocks.{i+1}.0.conv"
-        keys_dict[
-            f"model.conv_tower.{i}.1.fn.0"
-        ] = f"model.embedding.conv_tower.blocks.{i+1}.1.norm.layer"
-        keys_dict[
-            f"model.conv_tower.{i}.1.fn.2"
-        ] = f"model.embedding.conv_tower.blocks.{i+1}.1.conv"
-        keys_dict[
-            f"model.conv_tower.{i}.2"
-        ] = f"model.embedding.conv_tower.blocks.{i+1}.1.pool.layer"
+        keys_dict[f"model.conv_tower.{i}.0.0"] = (
+            f"model.embedding.conv_tower.blocks.{i+1}.0.norm.layer"
+        )
+        keys_dict[f"model.conv_tower.{i}.0.2"] = (
+            f"model.embedding.conv_tower.blocks.{i+1}.0.conv"
+        )
+        keys_dict[f"model.conv_tower.{i}.1.fn.0"] = (
+            f"model.embedding.conv_tower.blocks.{i+1}.1.norm.layer"
+        )
+        keys_dict[f"model.conv_tower.{i}.1.fn.2"] = (
+            f"model.embedding.conv_tower.blocks.{i+1}.1.conv"
+        )
+        keys_dict[f"model.conv_tower.{i}.2"] = (
+            f"model.embedding.conv_tower.blocks.{i+1}.1.pool.layer"
+        )
 
     for i in range(ckpt["hyper_parameters"]["model_params"]["n_transformers"]):
-        keys_dict[
-            f"model.transformer.{i}.0.fn.0"
-        ] = f"model.embedding.transformer_tower.blocks.{i}.norm.layer"
-        keys_dict[
-            f"model.transformer.{i}.0.fn.1"
-        ] = f"model.embedding.transformer_tower.blocks.{i}.mha"
-        keys_dict[
-            f"model.transformer.{i}.1.fn.0"
-        ] = f"model.embedding.transformer_tower.blocks.{i}.ffn.dense1.norm.layer"
-        keys_dict[
-            f"model.transformer.{i}.1.fn.1"
-        ] = f"model.embedding.transformer_tower.blocks.{i}.ffn.dense1.linear"
-        keys_dict[
-            f"model.transformer.{i}.1.fn.4"
-        ] = f"model.embedding.transformer_tower.blocks.{i}.ffn.dense2.linear"
+        keys_dict[f"model.transformer.{i}.0.fn.0"] = (
+            f"model.embedding.transformer_tower.blocks.{i}.norm.layer"
+        )
+        keys_dict[f"model.transformer.{i}.0.fn.1"] = (
+            f"model.embedding.transformer_tower.blocks.{i}.mha"
+        )
+        keys_dict[f"model.transformer.{i}.1.fn.0"] = (
+            f"model.embedding.transformer_tower.blocks.{i}.ffn.dense1.norm.layer"
+        )
+        keys_dict[f"model.transformer.{i}.1.fn.1"] = (
+            f"model.embedding.transformer_tower.blocks.{i}.ffn.dense1.linear"
+        )
+        keys_dict[f"model.transformer.{i}.1.fn.4"] = (
+            f"model.embedding.transformer_tower.blocks.{i}.ffn.dense2.linear"
+        )
 
     # Make new state dict in which old names are replaced by new ones
     new_state_dict = OrderedDict()

src/grelu/io/fasta.py

@@ -1,6 +1,7 @@
 """
 Functions related to reading and writing FASTA files
 """
+
 import gzip
 import os
 from typing import List

src/grelu/io/genome.py

@@ -1,6 +1,7 @@
 """
 Functions for loading genomes and related annotation files
 """
+
 import os
 from typing import List, Optional, Union
 

src/grelu/io/meme.py

@@ -1,6 +1,7 @@
 """
 Functions related to reading and writing MEME files
 """
+
 import os
 from typing import List, Optional
 

src/grelu/lightning/losses.py

@@ -1,6 +1,7 @@
 """
 Custom loss functions
 """
+
 import torch
 import torch.nn.functional as F
 from torch import Tensor, nn

src/grelu/model/layers.py

@@ -1,6 +1,7 @@
 """
 Commonly used layers to build deep learning models.
 """
+
 from typing import Optional
 
 import torch

src/grelu/model/position.py

@@ -1,6 +1,7 @@
 """
 Functions to generate positional encodings.
 """
+
 import math
 
 import numpy as np

src/grelu/model/trunks/borzoi.py

@@ -1,6 +1,7 @@
 """
 The Borzoi model architecture and its required classes.
 """
+
 from enformer_pytorch.modeling_enformer import exponential_linspace_int
 from torch import Tensor, nn
 

src/grelu/model/trunks/enformer.py

@@ -1,6 +1,7 @@
 """
 The Enformer model architecture and its required classes
 """
+
 import torch
 from einops import rearrange
 from enformer_pytorch.modeling_enformer import Attention, exponential_linspace_int

src/grelu/sequence/metrics.py

@@ -1,6 +1,7 @@
 """
 Functions to calculate metrics based on the content of a sequence
 """
+
 from typing import List, Optional, Union
 
 import numpy as np

src/grelu/sequence/mutate.py

@@ -1,6 +1,7 @@
 """
 Functions to mutate or alter DNA sequences in various ways.
 """
+
 from typing import List, Optional, Union
 
 import numpy as np

src/grelu/transforms/label_transforms.py

@@ -3,6 +3,7 @@
 
 The input to the forward method is assumed to be a numpy array of shape (N, T, L)
 """
+
 from typing import Callable, Optional, Union
 
 import numpy as np

src/grelu/utils.py

@@ -1,6 +1,7 @@
 """
 General utility functions
 """
+
 from typing import Callable, Optional, Sequence, Union
 
 import numpy as np

src/grelu/variant.py

@@ -1,6 +1,7 @@
 """
 This module provides functions to filter and process genetic variants.
 """
+
 import warnings
 from typing import Callable, List, Optional, Tuple, Union