tf.compat.v2.squeeze

Removes dimensions of size 1 from the shape of a tensor.

tf.compat.v2.squeeze(
    input, axis=None, name=None
)

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]
tf.shape(tf.squeeze(t))  # [2, 3]

Or, to remove specific size 1 dimensions:

# 't' is a tensor of shape [1, 2, 1, 3, 1, 1]
tf.shape(tf.squeeze(t, [2, 4]))  # [1, 2, 3, 1]

Unlike the older op tf.compat.v1.squeeze, this op does not accept a deprecated squeeze_dims argument.

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).

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	The input cannot be converted to a tensor, or the specified axis cannot be squeezed.