Python – tensorflow.math.softplus()
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。
softplus()用于计算元素级 log(exp(features) + 1)。
Syntax: tensorflow.math.softplus(features, name)
Parameters:
- features: It’s a tensor. Allowed dtypes are half, bfloat16, float32, float64.
- name(optional): It defines the name for the operation.
Returns: It returns a tensor.
示例 1:
Python3
# importing the library
import tensorflow as tf
# Initializing the input tensor
a = tf.constant([ 5, 7, 9, 15], dtype = tf.float64)
# Printing the input tensor
print('a: ', a)
# Calculating result
res = tf.math.softplus(a)
# Printing the result
print('Result: ', res)
Python3
# Importing the library
import tensorflow as tf
import matplotlib.pyplot as plt
# Initializing the input tensor
a = tf.constant([ 5, 7, 9, 15], dtype = tf.float64)
# Calculating tangent
res = tf.math.softplus(a)
# Plotting the graph
plt.plot(a, res, color ='green')
plt.title('tensorflow.math.softplus')
plt.xlabel('Input')
plt.ylabel('Result')
plt.show()
输出:
a: tf.Tensor([ 5. 7. 9. 15.], shape=(4, ), dtype=float64)
Result: tf.Tensor([ 5.00671535 7.00091147 9.0001234 15.00000031], shape=(4, ), 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([ 5, 7, 9, 15], dtype = tf.float64)
# Calculating tangent
res = tf.math.softplus(a)
# Plotting the graph
plt.plot(a, res, color ='green')
plt.title('tensorflow.math.softplus')
plt.xlabel('Input')
plt.ylabel('Result')
plt.show()
输出: