TensorFlow是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。
grad_pass_through()用于创建grad-pass-through操作，并按函数传递正向行为。
Syntax: tensorflow.grad_passs_through( f )
参数：
- f: It is a function which returns a Tensor or nested structure of Tensor.
Returns: It returns a function h(x) which returns the same values as f(x) and whose gradients are the same as those of an identity function.
范例1：
Python3
# Importing the library
import tensorflow as tf
# Initiaizing the Tensor
x = tf.Variable(2.0, name ="x")
z = tf.Variable(4.0, name ="z")
with tf.GradientTape() as gfg:
# y will evaluate to 16.0 i.e 4**2
y = tf.grad_pass_through(x.assign)(z**2)
# res will evaluate to 8.0
res = gfg.gradient(y, z)
# Printing result
print("y:", y)
print("res:", res)输出：
y: tf.Tensor(16.0, shape=(), dtype=float32) res: tf.Tensor(8.0, shape=(), dtype=float32)
范例2：
Python3
# Importing the library
import tensorflow as tf
# Initiaizing the Tensor
x = tf.Variable(3.0, name ="x")
with tf.GradientTape() as gfg:
# y will evaluate to 9.0 i.e 3**2
y = tf.grad_pass_through(x.assign)(x**2)
# res will evaluate to 6.0
res = gfg.gradient(y, x)
# Printing result
print("y:", y)
print("res:", res)输出：
y: tf.Tensor(9.0, shape=(), dtype=float32) res: tf.Tensor(6.0, shape=(), dtype=float32)
相关用法
注：本文由纯净天空筛选整理自aman neekhara大神的英文原创作品 Python – tesnsorflow.grad_pass_through()。非经特殊声明，原始代码版权归原作者所有，本译文未经允许或授权，请勿转载或复制。