Python - tensorflow.math.subtract()
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。
减法()用于计算元素明智(xy)。
Syntax: tensorflow.math.subtract(x, y, name)
Parameters:
- x: It’s a tensor. Allowed dtypes are bfloat16, half, float32, float64, complex64, complex128.
- y: It’s a tensor of same dtype as x.
- 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, 2, 5, 7], dtype = tf.float64)
b = tf.constant([ 1, 3, 9, 4, 7], dtype = tf.float64)
# Printing the input tensor
print('a: ', a)
print('b: ', b)
# Calculating result
res = tf.math.subtract(a, b)
# Printing the result
print('Result: ', res)
Python3
# importing the library
import tensorflow as tf
# Initializing the input tensor
a = tf.constant([ -5 + 3j, -7-2j, 2 + 1j, 5-7j, 7 + 3j], dtype = tf.complex128)
b = tf.constant([ 1 + 5j, 3 + 1j, 9-5j, 4 + 3j, 7-6j], dtype = tf.complex128)
# Printing the input tensor
print('a: ', a)
print('b: ', b)
# Calculating result
res = tf.math.subtract(a, b)
# Printing the result
print('Result: ', res)
输出:
a: tf.Tensor([-5. -7. 2. 5. 7.], shape=(5, ), dtype=float64)
b: tf.Tensor([1. 3. 9. 4. 7.], shape=(5, ), dtype=float64)
Result: tf.Tensor([ -6. -10. -7. 1. 0.], shape=(5, ), dtype=float64)
示例 2:采用复杂输入
Python3
# importing the library
import tensorflow as tf
# Initializing the input tensor
a = tf.constant([ -5 + 3j, -7-2j, 2 + 1j, 5-7j, 7 + 3j], dtype = tf.complex128)
b = tf.constant([ 1 + 5j, 3 + 1j, 9-5j, 4 + 3j, 7-6j], dtype = tf.complex128)
# Printing the input tensor
print('a: ', a)
print('b: ', b)
# Calculating result
res = tf.math.subtract(a, b)
# Printing the result
print('Result: ', res)
输出:
a: tf.Tensor([-5.+3.j -7.-2.j 2.+1.j 5.-7.j 7.+3.j], shape=(5, ), dtype=complex128)
b: tf.Tensor([1.+5.j 3.+1.j 9.-5.j 4.+3.j 7.-6.j], shape=(5, ), dtype=complex128)
Result: tf.Tensor([ -6. -2.j -10. -3.j -7. +6.j 1.-10.j 0. +9.j], shape=(5, ), dtype=complex128)