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Add migration block for tf.compat.v1.placeholder

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PiperOrigin-RevId: 381158940
Change-Id: I64aeae4cf3e0a3459c6d284e2a90c04b216b5984
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A. Unique TensorFlower 2021-06-23 18:40:48 -07:00 committed by TensorFlower Gardener
parent ade35c112e
commit a3b7535ec5
1 changed files with 14 additions and 4 deletions
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18
tensorflow/python/ops/array_ops.py
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@ -3251,10 +3251,6 @@ def placeholder(dtype, shape=None, name=None):
print(sess.run(y, feed_dict={x: rand_array})) # Will succeed.
```
@compatibility(eager)
Placeholders are not compatible with eager execution.
@end_compatibility
Args:
dtype: The type of elements in the tensor to be fed.
shape: The shape of the tensor to be fed (optional). If the shape is not
@ -3267,6 +3263,20 @@ def placeholder(dtype, shape=None, name=None):
Raises:
RuntimeError: if eager execution is enabled
@compatibility(TF2)
This API is not compatible with eager execution and `tf.function`. To migrate
to TF2, rewrite the code to be compatible with eager execution. Check the
[migration
guide](https://www.tensorflow.org/guide/migrate#1_replace_v1sessionrun_calls)
on replacing `Session.run` calls. In TF2, you can just pass tensors directly
into ops and layers. If you want to explicitly set up your inputs, also see
[Keras functional API](https://www.tensorflow.org/guide/keras/functional) on
how to use `tf.keras.Input` to replace `tf.compat.v1.placeholder`.
`tf.function` arguments also do the job of `tf.compat.v1.placeholder`.
For more details please read [Better
performance with tf.function](https://www.tensorflow.org/guide/function).
@end_compatibility
"""
if context.executing_eagerly():
raise RuntimeError("tf.placeholder() is not compatible with "