# tf.squeeze

https://www.w3cschool.cn/tensorflow_python/tensorflow_python-1yed2mih.html

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

# '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.
Note：如果input是一个RaggedTensor，那么这个操作会花费O(N)的时间。

Args:
input: A Tensor. The input to squeeze.
intput：一个Tensor。

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.


axis：可选，ints，默认[]。如果指定了，就仅压缩指定维度。维度从0开始。如果尝试压缩维度不为1的的维度会出错。如果是RaggedTensor，一定要指定。

name: A name for the operation (optional).
squeeze_dims: Deprecated keyword argument that is now axis.


squeeze_dims：已废弃。现在建议使用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.

"""

posted @ 2020-07-31 17:10  ZH奶酪  阅读(44)  评论(0编辑  收藏