Tensorflow是Google開發的開源機器學習庫。它的應用之一是開發深度神經網絡。
模塊tensorflow.math
為許多基本的數學運算提供支持。函數tf.sinh()
[別名tf.math.sinh
]支持Tensorflow中的雙曲正弦函數。它期望以弧度形式輸入。輸入類型為張量,如果輸入包含多個元素,則將計算按元素的雙曲正弦值。
用法:tf.sinh(x, name=None) or tf.math.sinh(x, name=None)
參數:
x:以下任何類型的張量:float16,float32,float64,complex64或complex128。
name(可選):操作的名稱。
返回類型:與x具有相同類型的張量。
代碼1:
# 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 sinh function and
# storing the result in 'b'
b = tf.sinh(a, name ='sinh')
# 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))
輸出:
Input type:Tensor("Const_3:0", shape=(6, ), dtype=float32) Input:[ 1. -0.5 3.4 -2.1 0. -6.5] Return type:Tensor("sinh:0", shape=(6, ), dtype=float32) Output:[ 1.1752012 -0.5210953 14.965365 -4.0218563 0. -332.57004 ]
代碼2:可視化
# Importing the Tensorflow library
import tensorflow as tf
# Importing the NumPy library
import numpy as np
# Importing the matplotlib.pylot function
import matplotlib.pyplot as plt
# A vector of size 15 with values from -5 to 5
a = np.linspace(-5, 5, 15)
# Applying the hyperbolic sine function and
# storing the result in 'b'
b = tf.sinh(a, name ='sinh')
# 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.sinh")
plt.xlabel("X")
plt.ylabel("Y")
plt.show()
輸出:
Input:[-5. -4.28571429 -3.57142857 -2.85714286 -2.14285714 -1.42857143 -0.71428571 0. 0.71428571 1.42857143 2.14285714 2.85714286 3.57142857 4.28571429 5. ] Output:[-74.20321058 -36.32033021 -17.76962587 -8.67713772 -4.20321865 -1.96654142 -0.77659271 0. 0.77659271 1.96654142 4.20321865 8.67713772 17.76962587 36.32033021 74.20321058]
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注:本文由純淨天空篩選整理自vaibhav29498大神的英文原創作品 Python | Tensorflow sinh() method。非經特殊聲明,原始代碼版權歸原作者所有,本譯文未經允許或授權,請勿轉載或複製。