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.asin()
[別名tf.math.asin
]支持Tensorflow中的反正弦函數。它期望輸入在[-1,1]範圍內,並以弧度形式給出輸出。如果輸入不在[-1,1]範圍內,則返回nan。輸入類型為張量,如果輸入包含多個元素,則將計算按元素的反正弦值。
用法:tf.asin(x, name=None) or tf.math.asin(x, name=None)
參數:
x:以下任何類型的張量:bfloat16,half,float32,float64,int32,int64,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, 0.2, 0.0, -2],
dtype = tf.float32)
# Applying the asin function and
# storing the result in 'b'
b = tf.asin(a, name ='asin')
# 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_6:0", shape=(6, ), dtype=float32) Input:[ 1. -0.5 3.4 0.2 0. -2. ] Return type:Tensor("asin_2:0", shape=(6, ), dtype=float32) Output:[ 1.5707964 -0.5235988 nan 0.20135793 0. nan]
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 -1 to 1
a = np.linspace(-1, 1, 15)
# Applying the inverse sine function and
# storing the result in 'b'
b = tf.asin(a, name ='asin')
# 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.asin")
plt.xlabel("X")
plt.ylabel("Y")
plt.show()
輸出:
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:[-1.57079633 -1.0296968 -0.79560295 -0.60824558 -0.44291104 -0.2897517 -0.14334757 0. 0.14334757 0.2897517 0.44291104 0.60824558 0.79560295 1.0296968 1.57079633]
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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 asin() 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。