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tf.compat.v1.squeeze

Removes dimensions of size 1 from the shape of a tensor. (deprecated arguments)

Given a tensor input, this operation returns a tensor of the same type with all dimensions of size 1 removed. If you don't want to remove all size 1 dimensions, you can remove specific size 1 dimensions by specifying axis.

For example:

# 't' is a tensor of shape [1, 2, 1, 3, 1, 1]
t = tf.ones([1, 2, 1, 3, 1, 1])
print(tf.shape(tf.squeeze(t)).numpy())
[2 3]

Or, to remove specific size 1 dimensions:

# 't' is a tensor of shape [1, 2, 1, 3, 1, 1]
t = tf.ones([1, 2, 1, 3, 1, 1])
print(tf.shape(tf.squeeze(t, [2, 4])).numpy())
[1 2 3 1]
Note: if input is a tf.RaggedTensor, then this operation takes O(N) time, where N is the number of elements in the squeezed dimensions.
Args
input A Tensor. The input to squeeze.
axis An optional list of ints. Defaults to []. If specified, only squeezes the dimensions listed. The dimension index starts at 0. It is an error to squeeze a dimension that is not 1. Must be in the range [-rank(input), rank(input)). Must be specified if input is a RaggedTensor.
name A name for the operation (optional).
squeeze_dims Deprecated keyword argument that is now axis.
Returns
A Tensor. Has the same type as input. Contains the same data as input, but has one or more dimensions of size 1 removed.
Raises
ValueError When both squeeze_dims and axis are specified.

© 2020 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.3/api_docs/python/tf/compat/v1/squeeze