experiments/STT-tensorflow
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Use tf.function's default autograph=True in saved_model/integration_test.

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There is currently no demonstrable need to do something non-obvious here.

PiperOrigin-RevId: 259782705
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A. Unique TensorFlower 2019-07-24 11:36:35 -07:00 committed by TensorFlower Gardener
parent 7251a1efe4
commit d0eeef269d
2 changed files with 2 additions and 2 deletions
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2
tensorflow/examples/saved_model/integration_tests/export_mnist_cnn.py
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@ -117,7 +117,7 @@ def wrap_keras_model_for_export(model, batch_input_shape,
# the desired argspec. # the desired argspec.
def wrapped(*args, **kwargs): # TODO(arnoegw): Can we use call_fn itself? def wrapped(*args, **kwargs): # TODO(arnoegw): Can we use call_fn itself?
return call_fn(*args, **kwargs) return call_fn(*args, **kwargs)
traced_call_fn = tf.function(autograph=False)( traced_call_fn = tf.function(
tf_decorator.make_decorator(call_fn, wrapped, decorator_argspec=argspec)) tf_decorator.make_decorator(call_fn, wrapped, decorator_argspec=argspec))
# Now we need to trigger traces for all supported combinations of the # Now we need to trigger traces for all supported combinations of the

2
tensorflow/examples/saved_model/integration_tests/export_rnn_cell.py
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@ -37,7 +37,7 @@ def main(argv):
root.rnn_cell = tf.keras.layers.LSTMCell(units=10, recurrent_initializer=None) root.rnn_cell = tf.keras.layers.LSTMCell(units=10, recurrent_initializer=None)
# Wrap the rnn_cell.__call__ function and assign to next_state. # Wrap the rnn_cell.__call__ function and assign to next_state.
root.next_state = tf.function(root.rnn_cell.__call__, autograph=False) root.next_state = tf.function(root.rnn_cell.__call__)
# Wrap the rnn_cell.get_initial_function using a decorator and assign to an # Wrap the rnn_cell.get_initial_function using a decorator and assign to an
# attribute with the same name. # attribute with the same name.