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Do not clip gradient if gradient is None #349

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Do not clip gradient if gradient is None #349

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2 changes: 1 addition & 1 deletion seq2seq/models/seq2seq_model.py
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Original file line number Diff line number Diff line change
Expand Up @@ -74,7 +74,7 @@ def _clip_gradients(self, grads_and_vars):
clipped_gradients = []
variables = []
for gradient, variable in grads_and_vars:
if "embedding" in variable.name:
if "embedding" in variable.name and gradient != None:
tmp = tf.clip_by_norm(
gradient.values, self.params["optimizer.clip_embed_gradients"])
gradient = tf.IndexedSlices(tmp, gradient.indices, gradient.dense_shape)
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