Python – tensorflow.math.erfinv()
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。
erfinv()用于计算元素级逆误差函数。
Syntax: tensorflow.math.erfinv( x, name)
Parameters:
- x: It’s the input tensor. Allowed dtypes are bfloat16, half, float32, float64.
- name(optional): It defines the 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([.1, .2, .3, .4, .5], dtype = tf.float64)
# Printing the input tensor
print('Input: ', a)
# Calculating inverse error
res = tf.math.erfinv(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 inverse error
res = tf.math.erfinv(x = a)
# Plotting the graph
plt.plot(a, res, color ='green')
plt.title('tensorflow.math.erfinv')
plt.xlabel('Input')
plt.ylabel('Result')
plt.show()
输出:
Input: tf.Tensor([0.1 0.2 0.3 0.4 0.5], shape=(5, ), dtype=float64)
Result: tf.Tensor([0.08885599 0.17914345 0.27246271 0.37080716 0.47693628], 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 inverse error
res = tf.math.erfinv(x = a)
# Plotting the graph
plt.plot(a, res, color ='green')
plt.title('tensorflow.math.erfinv')
plt.xlabel('Input')
plt.ylabel('Result')
plt.show()
输出: