Python| TensorFlow exp() 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.exp() [别名 tf.math.exp] 为 Tensorflow 中的指数函数提供支持。它期望复数形式的输入为_method_0.png "由 QuickLaTeX.com 渲染")
或浮点数。输入类型是张量，如果输入包含多个元素，则计算元素指数值， _method_1.png "由 QuickLaTeX.com 渲染")
.
Syntax: tf.exp(x, name=None) or tf.math.exp(x, name=None)
Parameters:
x: A Tensor of type bfloat16, half, float32, float64, complex64 or complex128.
name (optional): The name for the operation.
Return type: A Tensor with the same size and type as that of x.
代码#1：
Python3
# Importing the Tensorflow library
import tensorflow as tf
# A constant vector of size 5
a = tf.constant([-0.5, -0.1, 0, 0.1, 0.5], dtype = tf.float32)
# Applying the exp function and
# storing the result in 'b'
b = tf.exp(a, name ='exp')
# 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 21 with values from -10 to 10
a = np.linspace(-10, 10, 21)
# Applying the exponential function and
# storing the result in 'b'
b = tf.exp(a, name ='exp')
# 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.abs")
plt.xlabel("X")
plt.ylabel("Y")
plt.show()输出：
Input type: Tensor("Const:0", shape=(5, ), dtype=float32)
Input: [-0.5 -0.1 0. 0.1 0.5]
Return type: Tensor("exp:0", shape=(5, ), dtype=float32)
Output: [0.60653067 0.9048374 1. 1.105171 1.6487212 ]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 21 with values from -10 to 10
a = np.linspace(-10, 10, 21)
# Applying the exponential function and
# storing the result in 'b'
b = tf.exp(a, name ='exp')
# 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.abs")
plt.xlabel("X")
plt.ylabel("Y")
plt.show()
输出：
Input: [-10. -9. -8. -7. -6. -5. -4. -3. -2. -1. 0. 1. 2. 3.
4. 5. 6. 7. 8. 9. 10.]
Output: [4.53999298e-05 1.23409804e-04 3.35462628e-04 9.11881966e-04
2.47875218e-03 6.73794700e-03 1.83156389e-02 4.97870684e-02
1.35335283e-01 3.67879441e-01 1.00000000e+00 2.71828183e+00
7.38905610e+00 2.00855369e+01 5.45981500e+01 1.48413159e+02
4.03428793e+02 1.09663316e+03 2.98095799e+03 8.10308393e+03
2.20264658e+04]_method_2.png)