Clean mnist comment, add Linear layer
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2 changed files with 20 additions and 11 deletions
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@ -9,13 +9,13 @@ def load_image_file(path: str, magic_number: int = 2051, flatten: bool = False)
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"""Load MNIST image file"""
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images = []
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with open(path, 'rb') as data_file:
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header_data = data_file.read(16) ## 4 * int32 = 16 bytes
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header_data = data_file.read(16) # 4 * int32 = 16 bytes
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data_magic, data_count, rows, cols = struct.unpack('>iiii', header_data)
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if data_magic != magic_number:
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raise RuntimeError(
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f'MNIST image file doesn\'t have correct mmagic number: {data_magic} instead of {magic_number}')
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image_data_size = rows * cols
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image_chunk = 1000 ## loading by chunk for faster IO
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image_chunk = 1000 # loading by chunk for faster IO
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for _ in range(data_count // image_chunk):
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data = data_file.read(image_data_size * image_chunk)
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data = struct.unpack('B' * image_data_size * image_chunk, data)
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@ -32,12 +32,12 @@ def load_label_file(path: str, magic_number: int = 2049) -> np.ndarray:
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"""Load MNIST label file"""
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labels = []
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with open(path, 'rb') as data_file:
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header_data = data_file.read(8) ## 2 * int32 = 8 bytes
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header_data = data_file.read(8) # 2 * int32 = 8 bytes
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data_magic, data_count = struct.unpack('>ii', header_data)
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if data_magic != magic_number:
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raise RuntimeError(
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f'MNIST label file doesn\'t have correct mmagic number: {data_magic} instead of {magic_number}')
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label_chunk = 1000 ## loading by chunk for faster IO
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label_chunk = 1000 # loading by chunk for faster IO
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for _ in range(data_count // label_chunk):
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data = data_file.read(label_chunk)
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data = struct.unpack('B' * label_chunk, data)
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