Python| TensorFlow cosh() 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.cosh() [别名 tf.math.cosh] 为 Tensorflow 中的双曲余弦函数提供支持。它期望以弧度形式输入。输入类型是张量，如果输入包含多个元素，则计算元素双曲余弦。

Syntax: tf.cosh(x, name=None) or tf.math.cosh(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.

编程需要懂一点英语

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 cosh function and
# storing the result in 'b'
b = tf.cosh(a, name ='cosh')
 
# 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 1
a = np.linspace(-1, 1, 15)
 
# Applying the hyperbolic cosine function and
# storing the result in 'b'
b = tf.cosh(a, name ='cosh')
 
# 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.cosh")
    plt.xlabel("X")
    plt.ylabel("Y")
 
    plt.show()

输出：

Input type: Tensor("Const_2:0", shape=(6, ), dtype=float32)
Input: [ 1.  -0.5  3.4 -2.1  0.  -6.5]
Return type: Tensor("cosh_1:0", shape=(6, ), dtype=float32)
Output: [  1.5430806   1.127626   14.998738    4.144313    1.        332.5716   ]

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 1
a = np.linspace(-1, 1, 15)
 
# Applying the hyperbolic cosine function and
# storing the result in 'b'
b = tf.cosh(a, name ='cosh')
 
# 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.cosh")
    plt.xlabel("X")
    plt.ylabel("Y")
 
    plt.show()

输出：

Input: [-1.         -0.85714286 -0.71428571 -0.57142857 -0.42857143 -0.28571429
 -0.14285714  0.          0.14285714  0.28571429  0.42857143  0.57142857
  0.71428571  0.85714286  1.        ]
Output: [1.54308063 1.39039564 1.26613436 1.16775654 1.09325103 1.04109475
 1.01022145 1.         1.01022145 1.04109475 1.09325103 1.16775654
 1.26613436 1.39039564 1.54308063]