📜  Python – tensorflow.clip_by_norm()

📅  最后修改于: 2022-05-13 01:54:40.152000             🧑  作者: Mango

Python – tensorflow.clip_by_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.

clip_by_norm()用于将张量值裁剪为最大 L2 范数。

示例 1:

Python3
# Importing the library
import tensorflow as tf
  
# Initializing the input tensor
t = tf.constant([1, 2, 3, 4], dtype = tf.float64)
clip_norm = .8
  
# Printing the input tensor
print('t: ', t)
print('clip_norm: ', clip_norm)
  
# Calculating tangent
res = tf.clip_by_norm(t, clip_norm)
  
# Printing the result
print('Result: ', res)


Python3
# Importing the library
import tensorflow as tf
  
# Initializing the input tensor
t = tf.constant([1, 2, 3, 4], dtype = tf.float64)
clip_norm = 5.2
  
  
# Printing the input tensor
print('t: ', t)
print('clip_norm: ', clip_norm)
  
# Calculating tangent
res = tf.clip_by_norm(t, clip_norm)
  
# Printing the result
print('Result: ', res)


输出:

t:  tf.Tensor([1. 2. 3. 4.], shape=(4, ), dtype=float64)
clip_norm:  0.8
Result:  tf.Tensor([0.14605935 0.2921187  0.43817805 0.58423739], shape=(4, ), dtype=float64)

示例 2:

Python3

# Importing the library
import tensorflow as tf
  
# Initializing the input tensor
t = tf.constant([1, 2, 3, 4], dtype = tf.float64)
clip_norm = 5.2
  
  
# Printing the input tensor
print('t: ', t)
print('clip_norm: ', clip_norm)
  
# Calculating tangent
res = tf.clip_by_norm(t, clip_norm)
  
# Printing the result
print('Result: ', res)

输出:

t:  tf.Tensor([1. 2. 3. 4.], shape=(4, ), dtype=float64)
clip_norm:  5.2
Result:  tf.Tensor([0.94938577 1.89877153 2.8481573  3.79754307], shape=(4, ), dtype=float64)