压缩值为1的维度

numpy自带有np.squeeze()
tensorflow自带有tf.squeeze()
其反向操作 增加维度是：tf.expand_dims(input, axis=None, name=None, dim=None)

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

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:

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

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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.

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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.

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Raises:

• ValueError: When both

  squeeze_dims

  and

  axis

  are specified.