Python – tensorflow.math.erfc()


Python – tensorflow.math.erfc()

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。

erfc()用于计算元素方式的互补高斯误差函数。

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 complementary Gauss error
res = tf.math.erfc(x = 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([1, 2, 3, 4, 5], dtype = tf.float64)
  
# Calculating complementary Gauss error
res = tf.math.erfc(x = a)
  
# Plotting the graph
plt.plot(a, res, color ='green')
plt.title('tensorflow.math.erfc')
plt.xlabel('Input')
plt.ylabel('Result')
plt.show()


输出:

Input:  tf.Tensor([1. 2. 3. 4. 5.], shape=(5, ), dtype=float64)
Result:  tf.Tensor(
[1.57299207e-01 4.67773498e-03 2.20904970e-05 1.54172579e-08
 1.53745979e-12], 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 complementary Gauss error
res = tf.math.erfc(x = a)
  
# Plotting the graph
plt.plot(a, res, color ='green')
plt.title('tensorflow.math.erfc')
plt.xlabel('Input')
plt.ylabel('Result')
plt.show()

输出:


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