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]
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.
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