tf.squeeze

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

Aliases:

  • tf.compat.v2.squeeze
tf.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.

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