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Added support for TF 2.3.0 #42

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Added support for TF 2.3.0 #42

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6 changes: 3 additions & 3 deletions model_training_utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -236,7 +236,7 @@ def train_steps(iterator, steps):
'retracing.')

for _ in tf.range(steps):
strategy.experimental_run_v2(_replicated_step, args=(next(iterator),))
strategy.run(_replicated_step, args=(next(iterator),))

def train_single_step(iterator):
"""Performs a distributed training step.
Expand All @@ -247,7 +247,7 @@ def train_single_step(iterator):
Raises:
ValueError: Any of the arguments or tensor shapes are invalid.
"""
strategy.experimental_run_v2(_replicated_step, args=(next(iterator),))
strategy.run(_replicated_step, args=(next(iterator),))

def test_step(iterator):
"""Calculates evaluation metrics on distributed devices."""
Expand All @@ -260,7 +260,7 @@ def _test_step_fn(inputs):
for metric in eval_metrics:
metric.update_state(labels, model_outputs)

strategy.experimental_run_v2(_test_step_fn, args=(next(iterator),))
strategy.run(_replicated_step, args=(next(iterator),))

if not run_eagerly:
train_single_step = tf.function(train_single_step)
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