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Merge pull request #40808 from geetachavan1/cherrypicks_X2P52 

[CherryPick:r2.3] Allow tf.distribute.TPUStrategy to be used with TPUEmbedding API and ensure that LossScaleOptimizer properly rejects it.
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Goldie Gadde 2020-06-25 21:39:08 -07:00 committed by GitHub
parent fbaa6d4346 b878ae3918
commit 9cc469ac21
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2 changed files with 4 additions and 2 deletions
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3
tensorflow/python/keras/mixed_precision/experimental/loss_scale_optimizer.py
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@ -440,7 +440,8 @@ class LossScaleOptimizer(_DelegatingTrackableMixin, optimizer_v2.OptimizerV2):
if not strategy_supports_loss_scaling():
strategy = distribution_strategy_context.get_strategy()
if isinstance(strategy,
(tpu_strategy.TPUStrategy, tpu_strategy.TPUStrategyV1)):
(tpu_strategy.TPUStrategy, tpu_strategy.TPUStrategyV1,
tpu_strategy.TPUStrategyV2)):
raise ValueError(
'Loss scaling is not supported with TPUStrategy. Loss scaling is '
'unnecessary with TPUs, since they support bfloat16 instead of '

3
tensorflow/python/tpu/tpu_embedding_v2.py
View File

@ -265,7 +265,8 @@ class TPUEmbedding(tracking.AutoTrackable):
Adam or Adagrad).
"""
self._strategy = distribution_strategy_context.get_strategy()
self._using_tpu = isinstance(self._strategy, tpu_strategy.TPUStrategy)
self._using_tpu = isinstance(self._strategy, (tpu_strategy.TPUStrategy,
tpu_strategy.TPUStrategyV2))
self._pipeline_execution_with_tensor_core = (
pipeline_execution_with_tensor_core)