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@@ -454,7 +454,7 @@ class VGSLImageModel(object):
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self.labels = tf.slice(self.labels, [0, 0], [-1, 1])
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self.labels = tf.reshape(self.labels, [-1])
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cross_entropy = tf.nn.sparse_softmax_cross_entropy_with_logits(
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- logits, self.labels, name='xent')
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+ logits=logits, labels=self.labels, name='xent')
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else:
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# TODO(rays) Labels need an extra dimension for logistic, so different
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# padding functions are needed, as well as a different loss function.
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