Python – tensorflow.raw_ops.Exp()

TensorFlow 是由 Google 设计的开源Python库，用于开发机器学习模型和深度学习神经网络。 TensorFlow raw_ops 提供对所有 TensorFlow 操作的低级访问。 Exp()用于查找 x 的元素指数。

For complex numbers
e^(x+iy) = e^x * e^iy = e^x * (cos y + i sin y)

Syntax: tf.raw_ops.Exp(x, name)

Parameters: 

• x: It’s the input tensor. Allowed dtype for this tensor are bfloat16, half, float32, float64, complex64, complex128. 
• name(optional): It’s defines the name for the operation.
   

Returns:  It returns a tensor of same dtype as x.
 

注意：它只接受关键字参数。

示例 1：

Python3

# Importing the library
import tensorflow as tf
  
# Initializing the input tensor
a = tf.constant([1, 2, 3, 4, 5], dtype = tf.float64)
  
# Printing the input tensor
print('Input: ', a)
  
# Calculating exponential
res = tf.raw_ops.Exp(x = a)
  
# Printing the result
print('Result: ', res)

输出：

Input:  tf.Tensor([1. 2. 3. 4. 5.], shape=(5, ), dtype=float64)
Result:  tf.Tensor([  2.71828183   7.3890561   20.08553692  54.59815003 148.4131591 ], shape=(5, ), dtype=float64)

示例 2：可视化

Python3

# importing the library
import tensorflow as tf
import matplotlib.pyplot as plt
  
# Initializing the input tensor
a = tf.constant([1, 2, 3, 4, 5], dtype = tf.float64)
  
# Calculating exponential
res = tf.raw_ops.Exp(x = a)
  
# Plotting the graph
plt.plot(a, res, color ='green')
plt.title('tensorflow.raw_ops.Exp')
plt.xlabel('Input')
plt.ylabel('Result')
plt.show()

输出：