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@@ -5,8 +5,8 @@ def load_training_samples():
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"""
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Return np_images, np_expected
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where
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- np_impages is a np.array of 60 000 x 784
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- np_expected is a np.array of 60 000 x 10
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+ np_impages is a np.array of 784 x 60 000
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+ np_expected is a np.array of 10 x 60 000
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"""
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mndata = MNIST('../../resources/download')
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@@ -25,4 +25,4 @@ def load_training_samples():
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for k, label in enumerate(labels):
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np_expected[k][label] = 1.0
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- return np_images, np_expected
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+ return np.transpose(np_images), np.transpose(np_expected)
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