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bindsnet/datasets/preprocess.py | 2 +- bindsnet/datasets/torchvision_wrapper.py | 9 ++------- bindsnet/learning/learning.py | 2 +- examples/benchmark/sparse_vs_dense_tensors.py | 1 - examples/mnist/MCC_reservoir.py | 1 - 5 files changed, 4 insertions(+), 11 deletions(-) diff --git a/bindsnet/datasets/preprocess.py b/bindsnet/datasets/preprocess.py index 9948ac18..37ce1dc5 100644 --- a/bindsnet/datasets/preprocess.py +++ b/bindsnet/datasets/preprocess.py @@ -151,7 +151,7 @@ def crop_sample(sample): opts = {} image, bb = sample["image"], sample["bb"] orig_bbox = BoundingBox(bb[0], bb[1], bb[2], bb[3]) - (output_image, pad_image_location, edge_spacing_x, edge_spacing_y) = cropPadImage( + output_image, pad_image_location, edge_spacing_x, edge_spacing_y = cropPadImage( orig_bbox, image ) new_bbox = BoundingBox(0, 0, 0, 0) diff --git a/bindsnet/datasets/torchvision_wrapper.py b/bindsnet/datasets/torchvision_wrapper.py index 23960a04..b1e36519 100644 --- a/bindsnet/datasets/torchvision_wrapper.py +++ b/bindsnet/datasets/torchvision_wrapper.py @@ -16,18 +16,13 @@ def create_torchvision_dataset_wrapper(ds_type): ds_type = getattr(torchDB, ds_type) class TorchvisionDatasetWrapper(ds_type): - __doc__ = ( - """BindsNET torchvision dataset wrapper for: + __doc__ = """BindsNET torchvision dataset wrapper for: The core difference is the output of __getitem__ is no longer (image, label) rather a dictionary containing the image, label, and their encoded versions if encoders were provided. - \n\n""" - + str(ds_type) - if ds_type.__doc__ is None - else ds_type.__doc__ - ) + \n\n""" + str(ds_type) if ds_type.__doc__ is None else ds_type.__doc__ def __init__( self, diff --git a/bindsnet/learning/learning.py b/bindsnet/learning/learning.py index b7ad0927..0ffad89c 100644 --- a/bindsnet/learning/learning.py +++ b/bindsnet/learning/learning.py @@ -877,7 +877,7 @@ def _conv1d_connection_update(self, **kwargs) -> None: ``AbstractConnection`` class. """ # Get convolutional layer parameters. - (out_channels, in_channels, kernel_size) = self.connection.w.size() + out_channels, in_channels, kernel_size = self.connection.w.size() padding, stride = self.connection.padding, self.connection.stride batch_size = self.source.batch_size diff --git a/examples/benchmark/sparse_vs_dense_tensors.py b/examples/benchmark/sparse_vs_dense_tensors.py index db5a34b7..228fdc4a 100644 --- a/examples/benchmark/sparse_vs_dense_tensors.py +++ b/examples/benchmark/sparse_vs_dense_tensors.py @@ -4,7 +4,6 @@ from bindsnet.evaluation import all_activity, assign_labels, proportion_weighting - parser = argparse.ArgumentParser() parser.add_argument("--benchmark_type", choices=["memory", "runtime"], default="memory") args = parser.parse_args() diff --git a/examples/mnist/MCC_reservoir.py b/examples/mnist/MCC_reservoir.py index 89145d6f..ff91876f 100644 --- a/examples/mnist/MCC_reservoir.py +++ b/examples/mnist/MCC_reservoir.py @@ -26,7 +26,6 @@ from 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