tf.squeeze用法
- 作用
tf.squeeze的作用是移除给定的tensor中大小为1的维度。
源码是:
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:
# '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]
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))`.
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.
"""
if squeeze_dims is not None:
if axis is not None:
raise ValueError("Cannot specify both 'squeeze_dims' and 'axis'")
axis = squeeze_dims
if np.isscalar(axis):
axis = [axis]
return gen_array_ops.squeeze(input, axis, name)
举例说明用法:
import tensorflow as tf
a = tf.ones(shape=[3,1,4,1,2,1,5])
b = tf.squeeze(a)
sess = tf.InteractiveSession()
print(a.shape)
print(b)
输出为:
(3, 1, 4, 1, 2, 1, 5)
Tensor("Squeeze:0", shape=(3, 4, 2, 5), dtype=float32)