chore: start fixing mypy errors

src/gt4sd/algorithms/core.py

@@ -25,7 +25,7 @@
 
 from __future__ import annotations
 
-import collections
+from collections.abc import Hashable
 import logging
 import os
 import shutil
@@ -233,7 +233,7 @@ def sample(self, number_of_items: int = 100) -> Iterator[S]:
  try:
  valid_item = self.configuration.validate_item(item)
  # check if sample is hashable
- if not isinstance(item, collections.Hashable):
+ if not isinstance(item, Hashable):
  yield valid_item
  item_set.add(str(index))
  else:
@@ -623,9 +623,11 @@ def save_version_from_training_pipeline_arguments(
  target_version,
  )
  filepaths_mapping = {
- filename: source_filepath
- if os.path.exists(source_filepath)
- else os.path.join(source_missing_path, filename)
+ filename: (
+ source_filepath
+ if os.path.exists(source_filepath)
+ else os.path.join(source_missing_path, filename)
+ )
  for filename, source_filepath in filepaths_mapping.items()
  }
  logger.info(f"Saving artifacts into {target_path}...")
@@ -713,9 +715,11 @@ def upload_version_from_training_pipeline_arguments(
 
  # mapping between filenames and paths for a version.
  filepaths_mapping = {
- filename: source_filepath
- if os.path.exists(source_filepath)
- else os.path.join(source_missing_path, filename)
+ filename: (
+ source_filepath
+ if os.path.exists(source_filepath)
+ else os.path.join(source_missing_path, filename)
+ )
  for filename, source_filepath in filepaths_mapping.items()
  }
 

src/gt4sd/frameworks/cgcnn/data.py

@@ -31,7 +31,7 @@
 import logging
 import os
 import random
-from typing import Any, Callable, List, Tuple, Union
+from typing import Any, Callable, List, Tuple, Union, Optional
 
 import numpy as np
 import torch
@@ -49,7 +49,7 @@ def get_train_val_test_loader(
  dataset: torch.utils.data.Dataset,
  collate_fn: Callable[[List[Any]], Any] = default_collate,
  batch_size: int = 64,
- train_ratio: float = None,
+ train_ratio: Optional[float] = None,
  val_ratio: float = 0.1,
  test_ratio: float = 0.1,
  return_test: bool = False,
@@ -241,9 +241,7 @@ def expand(self, distances: np.ndarray) -> np.ndarray:
  Expanded distance matrix with the last dimension of length
  len(self.filter).
  """
- return np.exp(
- -((distances[..., np.newaxis] - self.filter) ** 2) / self.var**2
- )
+ return np.exp(-((distances[..., np.newaxis] - self.filter) ** 2) / self.var**2)
 
 
 class AtomInitializer: