Renaming MNIST eval set to test set for consistency with slides.
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@ -139,7 +139,7 @@ class MNISTDataProvider(DataProvider):
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"""Create a new MNIST data provider object.
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"""Create a new MNIST data provider object.
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Args:
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Args:
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which_set: One of 'train', 'valid' or 'eval'. Determines which
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which_set: One of 'train', 'valid' or 'test'. Determines which
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portion of the MNIST data this object should provide.
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portion of the MNIST data this object should provide.
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batch_size (int): Number of data points to include in each batch.
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batch_size (int): Number of data points to include in each batch.
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max_num_batches (int): Maximum number of batches to iterate over
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max_num_batches (int): Maximum number of batches to iterate over
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@ -151,8 +151,8 @@ class MNISTDataProvider(DataProvider):
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rng (RandomState): A seeded random number generator.
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rng (RandomState): A seeded random number generator.
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"""
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"""
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# check a valid which_set was provided
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# check a valid which_set was provided
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assert which_set in ['train', 'valid', 'eval'], (
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assert which_set in ['train', 'valid', 'test'], (
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'Expected which_set to be either train, valid or eval. '
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'Expected which_set to be either train, valid or test. '
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'Got {0}'.format(which_set)
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'Got {0}'.format(which_set)
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)
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)
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self.which_set = which_set
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self.which_set = which_set
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@ -279,7 +279,7 @@ class CCPPDataProvider(DataProvider):
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'Got {0}'.format(which_set)
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'Got {0}'.format(which_set)
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)
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)
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# check input_dims are valid
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# check input_dims are valid
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if not input_dims is not None:
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if input_dims is not None:
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input_dims = set(input_dims)
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input_dims = set(input_dims)
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assert input_dims.issubset({0, 1, 2, 3}), (
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assert input_dims.issubset({0, 1, 2, 3}), (
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'input_dims should be a subset of {0, 1, 2, 3}'
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'input_dims should be a subset of {0, 1, 2, 3}'
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