Merge pull request #17 from HHousen/deepsource-fix-9408a52c

Remove blank lines after docstring
HHousen · Jul 7, 2021 · fb5421e · fb5421e
2 parents afd3842 + 39c1d5e
commit fb5421e
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diff --git a/lecture2notes/end_to_end/text_detection.py b/lecture2notes/end_to_end/text_detection.py
@@ -40,7 +40,6 @@ def get_text_bounding_boxes(
  Returns:
  list: The coordinates of bounding boxes containing text.
  """
-
  if type(net) is str:
  net = load_east(net)
 

diff --git a/lecture2notes/end_to_end/transcribe/transcribe_main.py b/lecture2notes/end_to_end/transcribe/transcribe_main.py
@@ -410,7 +410,6 @@ def resolve_deepspeech_models(dir_name):
  Returns:
  tuple: a tuple containing each of the model files (pb, scorer)
  """
-
  pb = glob.glob(dir_name + "/*.pbmm")[0]
  logging.debug("Found model: %s", pb)
 

diff --git a/lecture2notes/models/slide_classifier/grad_cam.py b/lecture2notes/models/slide_classifier/grad_cam.py
@@ -171,7 +171,6 @@ def occlusion_sensitivity(
  "Visualizing and Understanding Convolutional Networks"
  https://arxiv.org/abs/1311.2901
  """
-
  torch.set_grad_enabled(False)
  model.eval()
  mean = mean if mean else 0
@@ -293,7 +292,6 @@ def main(args):
  """
  Visualize model responses given multiple images
  """
-
  device = get_device(not args.cpu)
 
  from slide_classifier_pytorch import SlideClassifier

diff --git a/lecture2notes/models/slide_classifier/lr_finder.py b/lecture2notes/models/slide_classifier/lr_finder.py
@@ -219,7 +219,6 @@ def plot(self, skip_start=10, skip_end=5, log_lr=True):
  scale; otherwise, plotted in a linear scale. Default: True.
 
  """
-
  if skip_start < 0:
  raise ValueError("skip_start cannot be negative")
  if skip_end < 0:

diff --git a/lecture2notes/models/slide_classifier/slide-classifier-pytorch-old.py b/lecture2notes/models/slide_classifier/slide-classifier-pytorch-old.py
@@ -880,8 +880,6 @@ def plot_confusion_matrix(
  Normalization can be applied by setting `normalize=True`
  https://scikit-learn.org/stable/auto_examples/model_selection/plot_confusion_matrix.html#sphx-glr-auto-examples-model-selection-plot-confusion-matrix-py.
  """
-
- # Compute confusion matrix
  cm = confusion_matrix(y_true, y_pred)
  # Only use the labels that appear in the data
  # classes = classes[unique_labels(y_true, y_pred)]

diff --git a/lecture2notes/models/slide_classifier/slide_classifier_helpers.py b/lecture2notes/models/slide_classifier/slide_classifier_helpers.py
@@ -29,8 +29,6 @@ def plot_confusion_matrix(
  Normalization can be applied by setting `normalize=True`
  https://scikit-learn.org/stable/auto_examples/model_selection/plot_confusion_matrix.html#sphx-glr-auto-examples-model-selection-plot-confusion-matrix-py.
  """
-
- # Compute confusion matrix
  cm = confusion_matrix(y_true, y_pred)
  # Only use the labels that appear in the data
  # classes = classes[unique_labels(y_true, y_pred)]