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fixed dimension compatibility
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tutorials/image/cifar10/cifar10.py

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@@ -240,7 +240,7 @@ def inference(images):
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# local3
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with tf.variable_scope('local3') as scope:
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# Move everything into depth so we can perform a single matrix multiply.
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reshape = tf.reshape(pool2, [images.get_shape()[0], -1])
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reshape = tf.reshape(pool2, [images.get_shape().as_list()[0], -1])
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dim = reshape.get_shape()[1].value
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weights = _variable_with_weight_decay('weights', shape=[dim, 384],
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stddev=0.04, wd=0.004)

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