TensorFlow. tf.reduce_mean

tf.reduce_mean

tf.reduce_mean(input_tensor,reduction_indices=None,keep_dims=False,name=None)

Computes the mean of elements across dimensions of a tensor.

按某一维度(reduction_indices)计算一个张量的个元素的平均值。

Reduces input_tensor along the dimensions given in reduction_indices. Unless keep_dims is true, the rank of the tensor is reduced by 1 for each entry in reduction_indices.

If keep_dims is true, the reduced dimensions are retained with length 1.

沿着reduction_indices给出的维度方向降维。如果keep_dims等于true，则按reduction_indices给出的降维的尺寸保留为1维，如果是False，则降维到1维。

If reduction_indices has no entries, all dimensions are reduced, and a tensor with a single element is returned.

如果reduction_indices没有指定，则所有维度都要降维，返回一个含有单个元素的张量。

举例：

import tensorflow as tf

sess = tf.InteractiveSession()

x = tf.constant(value=[[1.,2.,3.],[4.,5.,6.],[7.,8.,9.]],dtype=tf.float32,shape=[3,3],name=”x”)

print sess.run(x)

print x

mean1 = tf.reduce_mean(input_tensor=x, reduction_indices=None, keep_dims=False)

mean1 = tf.reduce_mean(input_tensor=x, reduction_indices=None, keep_dims=False)

mean2 = tf.reduce_mean(input_tensor=x, reduction_indices=0, keep_dims=False)

mean3 = tf.reduce_mean(input_tensor=x, reduction_indices=1, keep_dims=False)

mean4 = tf.reduce_mean(input_tensor=x, reduction_indices=0, keep_dims=True)

mean5 = tf.reduce_mean(input_tensor=x, reduction_indices=1, keep_dims=True)

mean6 = tf.reduce_mean(input_tensor=x, reduction_indices=None, keep_dims=True)

print sess.run(mean1)

print mean1

print sess.run(mean2)

print mean2

print sess.run(mean3)

print mean3

print sess.run(mean4)

print mean4

print sess.run(mean5)

print mean5

print sess.run(mean6)

print mean6

输出：

[[ 1. 2. 3.]

[ 4. 5. 6.]

[ 7. 8. 9.]]

Tensor(“x:0”, shape=(3, 3), dtype=float32)

5.0

Tensor(“Mean_2:0”, shape=(), dtype=float32)

[ 4. 5. 6.]

Tensor(“Mean_3:0”, shape=(3,), dtype=float32)

[ 2. 5. 8.]

Tensor(“Mean_4:0”, shape=(3,), dtype=float32)

[[ 4. 5. 6.]]

Tensor(“Mean_5:0”, shape=(1, 3), dtype=float32)

[[ 2.]

[ 5.]

[ 8.]]

Tensor(“Mean_6:0”, shape=(3, 1), dtype=float32)

[[ 5.]]

Tensor(“Mean_1:0”, shape=(1, 1), dtype=float32)

Args:

input_tensor: The tensor to reduce. Should have numeric type.

reduction_indices: The dimensions to reduce. If None (the default), reduces all dimensions.

keep_dims: If true, retains reduced dimensions with length 1.

name: A name for the operation (optional).

Returns:

The reduced tensor.

参数说明：

Input_tensor：被降维的张量必须其数据类型必须被预先指定。

reduction_indices：降维的维度如果为None(default)，则所有维度都要降维。

keep_dims：如果keep_dims为true，则降维的尺寸将保留为1

name：降维操作的名字。

返回一个降维后的张量。

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