Python – tensorflow.math.multiply_no_nan()
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。 multiply_no_nan()用于逐元素查找 x*y。它支持广播,如果 y 为 0,甚至 x 为无限或 NaN,则返回 0。
Syntax: tf.math.multiply_no_nan(x, y, name)
Parameter:
- x: It’s the input tensor. Allowed dtype for this tensor are bfloat16, half, float32, float64, uint8, int8, uint16, int16, int32, int64, complex64, complex128.
- y: It’s the input tensor of same dtype as x.
- name(optional): It’s 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([.2, .5, .7, 1], dtype = tf.float64)
b = tf.constant([.1, .3, 1, 5], dtype = tf.float64)
# Printing the input tensor
print('a: ', a)
print('b: ', b)
# Calculating result
res = tf.math.multiply_no_nan(x = a, y = b)
# Printing the result
print('Result: ', res)
Python3
# importing the library
import tensorflow as tf
import numpy as np
# Initializing the input tensor
a = tf.constant([-2, -5, np.inf, np.nan], dtype = tf.float64)
b = tf.constant([-1, -6, 0, 0], dtype = tf.float64)
# Printing the input tensor
print('a: ', a)
print('b: ', b)
# Calculating result
res = tf.math.multiply_no_nan(x = a, y = b)
# Printing the result
print('Result: ', res)
输出:
a: tf.Tensor([0.2 0.5 0.7 1. ], shape=(4, ), dtype=float64)
b: tf.Tensor([0.1 0.3 1. 5. ], shape=(4, ), dtype=float64)
Result: tf.Tensor([0.02 0.15 0.7 5. ], shape=(4, ), dtype=float64)
示例 2:复数乘法
Python3
# importing the library
import tensorflow as tf
import numpy as np
# Initializing the input tensor
a = tf.constant([-2, -5, np.inf, np.nan], dtype = tf.float64)
b = tf.constant([-1, -6, 0, 0], dtype = tf.float64)
# Printing the input tensor
print('a: ', a)
print('b: ', b)
# Calculating result
res = tf.math.multiply_no_nan(x = a, y = b)
# Printing the result
print('Result: ', res)
输出:
a: tf.Tensor([-2. -5. inf nan], shape=(4, ), dtype=float64)
b: tf.Tensor([-1. -6. 0. 0.], shape=(4, ), dtype=float64)
Result: tf.Tensor([ 2. 30. 0. 0.], shape=(4, ), dtype=float64)