Python – tensorflow.math.reduce_euclidean_norm()

TensorFlow 是由 Google 设计的开源Python库，用于开发机器学习模型和深度学习神经网络。

reduce_euclidean_norm()用于计算跨张量维度的元素的欧几里得范数。

Syntax: tensorflow.math.reduce_euclidean_norm( input_tensor, axis, keepdims, name)

Parameters:

• input_tensor: It is numeric tensor to reduce.
• axis(optional): It represent the dimensions to  reduce. It’s value should be in range [-rank(input_tensor), rank(input_tensor)). If no value is given for this all dimensions are reduced.
• keepdims(optional): It’s default value is False. If it’s set to True it will retain the reduced dimension with length 1.
• name(optional): It defines the name for the operation.

Returns: It returns a tensor.

示例 1：

Python3

# importing the library
import tensorflow as tf
 
# Initializing the input tensor
a = tf.constant([1, 2, 3, 4], dtype = tf.float64)
 
# Printing the input tensor
print('Input: ', a)
 
# Calculating result
res = tf.math.reduce_euclidean_norm(a)
 
# Printing the result
print('Result: ', res)

输出：

Input:  tf.Tensor([1. 2. 3. 4.], shape=(4, ), dtype=float64)
Result:  tf.Tensor(5.477225575051661, shape=(), dtype=float64)

示例 2：

Python3

# importing the library
import tensorflow as tf
 
# Initializing the input tensor
a = tf.constant([[1, 2], [3, 4]], dtype = tf.float64)
 
# Printing the input tensor
print('Input: ', a)
 
# Calculating result
res = tf.math.reduce_euclidean_norm(a, axis = 1, keepdims = True)
 
# Printing the result
print('Result: ', res)

输出：

Input:  tf.Tensor(
[[1. 2.]
 [3. 4.]], shape=(2, 2), dtype=float64)
Result:  tf.Tensor(
[[2.23606798]
 [5.        ]], shape=(2, 1), dtype=float64)