/TensorFlow 1.15


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Updates the shape of a tensor and checks at runtime that the shape holds.

For example:

x = tf.compat.v1.placeholder(tf.int32)
==> TensorShape(None)
y = x * 2
==> TensorShape(None)

y = tf.ensure_shape(y, (None, 3, 3))
==> TensorShape([Dimension(None), Dimension(3), Dimension(3)])

with tf.compat.v1.Session() as sess:
  # Raises tf.errors.InvalidArgumentError, because the shape (3,) is not
  # compatible with the shape (None, 3, 3)
  sess.run(y, feed_dict={x: [1, 2, 3]})

Note: This differs from Tensor.set_shape in that it sets the static shape of the resulting tensor and enforces it at runtime, raising an error if the tensor's runtime shape is incompatible with the specified shape. Tensor.set_shape sets the static shape of the tensor without enforcing it at runtime, which may result in inconsistencies between the statically-known shape of tensors and the runtime value of tensors.
x A Tensor.
shape A TensorShape representing the shape of this tensor, a TensorShapeProto, a list, a tuple, or None.
name A name for this operation (optional). Defaults to "EnsureShape".
A Tensor. Has the same type and contents as x. At runtime, raises a tf.errors.InvalidArgumentError if shape is incompatible with the shape of x.

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Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.