Python| TensorFlow acosh() 方法
Tensorflow 是谷歌开发的开源机器学习库。它的应用之一是开发深度神经网络。
模块tensorflow.math为许多基本的数学运算提供支持。函数tf.acosh() [别名 tf.math.acosh] 为 Tensorflow 中的反双曲余弦函数提供支持。它期望输入在 [1, ∞) 范围内，并为超出此范围的任何输入返回nan 。输入类型是张量，如果输入包含多个元素，则计算元素级反双曲余弦。
Syntax: tf.acosh(x, name=None) or tf.math.acosh(x, name=None)
Parameters:
x: A tensor of any of the following types: float16, float32, float64, complex64, or complex128.
name (optional): The name for the operation.
Return type: A tensor with the same type as that of x.
代码#1：
Python3
# Importing the Tensorflow library
import tensorflow as tf
# A constant vector of size 6
a = tf.constant([1.0, 0.5, 3.4, -2.1, 0.0, 6.5],
dtype = tf.float32)
# Applying the acosh function and
# storing the result in 'b'
b = tf.acosh(a, name ='acosh')
# Initiating a Tensorflow session
with tf.Session() as sess:
print('Input type:', a)
print('Input:', sess.run(a))
print('Return type:', b)
print('Output:', sess.run(b))Python3
# Importing the Tensorflow library
import tensorflow as tf
# Importing the NumPy library
import numpy as np
# Importing the matplotlib.pyplot function
import matplotlib.pyplot as plt
# A vector of size 15 with values from 1 to 10
a = np.linspace(1, 10, 15)
# Applying the inverse hyperbolic cosine
# function and storing the result in 'b'
b = tf.acosh(a, name ='acosh')
# Initiating a Tensorflow session
with tf.Session() as sess:
print('Input:', a)
print('Output:', sess.run(b))
plt.plot(a, sess.run(b), color = 'red', marker = "o")
plt.title("tensorflow.acosh")
plt.xlabel("X")
plt.ylabel("Y")
plt.show()输出：
Input type: Tensor("Const:0", shape=(6, ), dtype=float32)
Input: [ 1. 0.5 3.4 -2.1 0. 6.5]
Return type: Tensor("acosh:0", shape=(6, ), dtype=float32)
Output: [0. nan 1.894559 nan nan 2.558979]
代码 #2：可视化
Python3
# Importing the Tensorflow library
import tensorflow as tf
# Importing the NumPy library
import numpy as np
# Importing the matplotlib.pyplot function
import matplotlib.pyplot as plt
# A vector of size 15 with values from 1 to 10
a = np.linspace(1, 10, 15)
# Applying the inverse hyperbolic cosine
# function and storing the result in 'b'
b = tf.acosh(a, name ='acosh')
# Initiating a Tensorflow session
with tf.Session() as sess:
print('Input:', a)
print('Output:', sess.run(b))
plt.plot(a, sess.run(b), color = 'red', marker = "o")
plt.title("tensorflow.acosh")
plt.xlabel("X")
plt.ylabel("Y")
plt.show()
输出：
Input: [ 1. 1.64285714 2.28571429 2.92857143 3.57142857 4.21428571
4.85714286 5.5 6.14285714 6.78571429 7.42857143 8.07142857
8.71428571 9.35714286 10. ]
Output: [0. 1.08055227 1.46812101 1.73714862 1.94591015 2.11724401
2.26282815 2.38952643 2.50174512 2.60249262 2.69391933 2.77761797
2.85480239 2.92641956 2.99322285]_method_0.png)