python–tensorlow . math . nextafter()
哎哎哎:# t0]https://www . geeksforgeeks . org/python-tensorlow-math-nextafter/
TensorFlow 是谷歌为开发机器学习模型和深度学习神经网络而设计的开源 python 库。 nextafter() 用于在 x2 方向上寻找元素 wisenext 的 x1 可表示值。
语法: tf.math.nextafter(x1，x2，name)
参数:
- x1: 是输入张量。这个张量允许的数据类型是 float64，float32。
- x2: 是与 x1 相同数据类型的输入张量。
- 名称(可选):定义操作的名称。
返回: 它返回一个数据类型为 x1 的张量。
例 1:
Python 3
# Importing the library
import tensorflow as tf
# Initializing the input tensor
x1 = tf.constant([1, 2, -3, -4], dtype = tf.float64)
x2 = tf.constant([5, -7, 3, -8], dtype = tf.float64)
# Printing the input tensor
print('x1: ', x1)
print('x2: ', x2)
# Calculating result
res = tf.math.nextafter(x1, x2)
# Printing the result
print('Result: ', res)
输出:
x1: tf.Tensor([ 1\. 2\. -3\. -4.], shape=(4, ), dtype=float64)
x2: tf.Tensor([ 5\. -7\. 3\. -8.], shape=(4, ), dtype=float64)
Result: tf.Tensor([ 1\. 2\. -3\. -4.], shape=(4, ), dtype=float64)
示例 2: 本示例对 x1 和 x2 使用不同的数据类型。它将引发无效的文档恐怖。
Python 3
# importing the library
import tensorflow as tf
# Initializing the input tensor
x1 = tf.constant([1, 2, -3, -4], dtype = tf.float64)
x2 = tf.constant([5, -7, 3, -8], dtype = tf.float32)
# Printing the input tensor
print('x1: ', x1)
print('x2: ', x2)
# Calculating result
res = tf.math.nextafter(x1, x2)
# Printing the result
print('Result: ', res)
输出:
x1: tf.Tensor([ 1\. 2\. -3\. -4.], shape=(4, ), dtype=float64)
x2: tf.Tensor([ 5\. -7\. 3\. -8.], shape=(4, ), dtype=float32)
---------------------------------------------------------------------------
InvalidArgumentError Traceback (most recent call last)
in ()
8
9 # Calculating result
---> 10 res = tf.math.nextafter(x1, x2)
11
12 # Printing the result
2 frames
/usr/local/lib/python3.6/dist-packages/six.py in raise_from(value, from_value)
InvalidArgumentError: cannot compute NextAfter as input #1(zero-based) was expected to be a double tensor but is a float tensor [Op:NextAfter]
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