Python中的 tensorflow.math.special.expint()函数

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。

expint()函数

expint()用于计算 x 的逐元素指数积分。它被定义为 exp(t) / t 从 -inf 到 x 的积分，定义域为所有正实数。

Syntax: tensorflow.math.special.expint( x, name)

Parameter:

• x: It’s a Tensor or Sparse Tensor. Allowed dtypes are float32 and float64.
• name(optional): It defines name for the operation.

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

示例 1：

Python3

# importing the library
import tensorflow as tf
 
# Initializing the input tensor
a = tf.constant([ [-5, -7],[ 2, 0]], dtype=tf.float64)
 
# Printing the input tensor
print('a: ', a)
 
# Calculating result
res = tf.math.special.expint(a)
 
# Printing the result
print('Result: ', res)

输出：

a:  tf.Tensor(
[[-5. -7.]
 [ 2.  0.]], shape=(2, 2), dtype=float64)
Result:  tf.Tensor(
[[       nan        nan]
 [4.95423436       -inf]], shape=(2, 2), dtype=float64)

示例 2：

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('a: ', a)
 
# Calculating result
res = tf.math.special.expint(a)
 
# Printing the result
print('Result: ', res)

输出：

a:  tf.Tensor([1. 2. 3. 4. 5.], shape=(5,), dtype=float64) 
Result:  tf.Tensor([ 1.89511782  4.95423436  9.93383257 19.63087447 40.18527536], shape=(5,), dtype=float64)