Gradients for Local Response Normalization.
tf.raw_ops.LRNGrad(
input_grads,
input_image,
output_image,
depth_radius=5,
bias=1,
alpha=1,
beta=0.5,
name=None
)
| Args | |
|---|---|
input_grads | A Tensor. Must be one of the following types: half, bfloat16, float32. 4-D with shape [batch, height, width, channels]. |
input_image | A Tensor. Must have the same type as input_grads. 4-D with shape [batch, height, width, channels]. |
output_image | A Tensor. Must have the same type as input_grads. 4-D with shape [batch, height, width, channels]. |
depth_radius | An optional int. Defaults to 5. A depth radius. |
bias | An optional float. Defaults to 1. An offset (usually > 0 to avoid dividing by 0). |
alpha | An optional float. Defaults to 1. A scale factor, usually positive. |
beta | An optional float. Defaults to 0.5. An exponent. |
name | A name for the operation (optional). |
| Returns | |
|---|---|
A Tensor. Has the same type as input_grads. |
© 2022 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 4.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.9/api_docs/python/tf/raw_ops/LRNGrad