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@@ -341,7 +341,7 @@ def loss_fun(logits, labels):
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# Calculate the cross entropy between labels and predictions
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labels = tf.cast(labels, tf.int64)
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cross_entropy = tf.nn.sparse_softmax_cross_entropy_with_logits(
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- logits, labels, name='cross_entropy_per_example')
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+ logits=logits, labels=labels, name='cross_entropy_per_example')
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# Calculate the average cross entropy loss across the batch.
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cross_entropy_mean = tf.reduce_mean(cross_entropy, name='cross_entropy')
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