Function squeeze

tensorflow/python/ops/array_ops.py:3605–3653

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

(input, axis=None, name=None, squeeze_dims=None)

@deprecation.deprecated_args(None, "Use the `axis` argument instead",
                             "squeeze_dims")
def squeeze(input, axis=None, name=None, squeeze_dims=None):
  # pylint: disable=redefined-builtin
  """Removes dimensions of size 1 from the shape of a tensor.

  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:

  ```python
  # '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:

  ```python
  # 't' is a tensor of shape [1, 2, 1, 3, 1, 1]
  tf.shape(tf.squeeze(t, [2, 4]))  # [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.
  """
  axis = deprecation.deprecated_argument_lookup("axis", axis, "squeeze_dims",
                                                squeeze_dims)
  if np.isscalar(axis):
    axis = [axis]
  return gen_array_ops.squeeze(input, axis, name)


@tf_export("squeeze", v1=[])