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@ -15,39 +15,24 @@ def __mnist_reader_creator__(data, target):
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return reader
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class MNIST(object):
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"""
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mnist dataset reader. The `train_reader` and `test_reader` method returns
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a iterator of each sample. Each sample is combined by 784-dim float and a
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one-dim label
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"""
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TEST_SIZE = 10000
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def __init__(self, random_state=0, test_size=10000, **options):
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data = sklearn.datasets.mldata.fetch_mldata(
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"MNIST original", data_home=DATA_HOME)
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self.X_train, self.X_test, self.y_train, self.y_test = sklearn.model_selection.train_test_split(
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data.data,
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data.target,
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test_size=test_size,
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random_state=random_state,
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**options)
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data = sklearn.datasets.mldata.fetch_mldata(
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"MNIST original", data_home=DATA_HOME)
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X_train, X_test, y_train, y_test = sklearn.model_selection.train_test_split(
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data.data, data.target, test_size=TEST_SIZE, random_state=0)
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def train_creator(self):
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return __mnist_reader_creator__(self.X_train, self.y_train)
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def test_creator(self):
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return __mnist_reader_creator__(self.X_test, self.y_test)
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def train_creator():
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return __mnist_reader_creator__(X_train, y_train)
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__default_instance__ = MNIST()
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train_creator = __default_instance__.train_creator
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test_creator = __default_instance__.test_creator
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def test_creator():
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return __mnist_reader_creator__(X_test, y_test)
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def unittest():
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size = 12045
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mnist = MNIST(test_size=size)
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assert len(list(mnist.test_creator()())) == size
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assert len(list(test_creator()())) == TEST_SIZE
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if __name__ == '__main__':
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