# tf.squeeze(input, axis=None, name=None, squeeze_dims=None)

### tf.squeeze(input, axis=None, name=None, squeeze_dims=None)

See the guide: Tensor Transformations > Shapes and Shaping

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:

# 't' is a tensor of shape [1, 2, 1, 3, 1, 1]
shape(squeeze(t)) ==> [2, 3]


Or, to remove specific size 1 dimensions:

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

Defined in tensorflow/python/ops/array_ops.py.