Python| TensorFlow tan() 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.tan() [别名tf.math.tan ] 为 Tensorflow 中的正切函数提供支持。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，则计算元素切线。

Syntax: tf.tan(x, name=None) or tf.math.tan(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 tan function and
# storing the result in 'b'
b = tf.tan(a, name ='tan')
  
# 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 tangent function and
# storing the result in 'b'
b = tf.tan(a, name ='tan')
  
# 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.tan") 
    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("tan:0", shape=(6, ), dtype=float32)
Output: [ 1.5574077 -0.5463025  0.264317   1.7098469  0.        -0.2202772]

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 tangent function and
# storing the result in 'b'
b = tf.tan(a, name ='tan')
  
# 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.tan") 
    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: [-1.55740772 -1.15486601 -0.86700822 -0.64298589 -0.45689311 -0.29375136
 -0.14383696  0.          0.14383696  0.29375136  0.45689311  0.64298589
  0.86700822  1.15486601  1.55740772]