tf.raw_ops.LRNGrad
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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 .
|
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Last updated 2024-04-26 UTC.
[null,null,["Last updated 2024-04-26 UTC."],[],[],null,["# tf.raw_ops.LRNGrad\n\n\u003cbr /\u003e\n\nGradients for Local Response Normalization.\n\n#### View aliases\n\n\n**Compat aliases for migration**\n\nSee\n[Migration guide](https://www.tensorflow.org/guide/migrate) for\nmore details.\n\n[`tf.compat.v1.raw_ops.LRNGrad`](https://www.tensorflow.org/api_docs/python/tf/raw_ops/LRNGrad)\n\n\u003cbr /\u003e\n\n tf.raw_ops.LRNGrad(\n input_grads,\n input_image,\n output_image,\n depth_radius=5,\n bias=1,\n alpha=1,\n beta=0.5,\n name=None\n )\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|----------------|-----------------------------------------------------------------------------------------------------------------------------------|\n| `input_grads` | A `Tensor`. Must be one of the following types: `half`, `bfloat16`, `float32`. 4-D with shape `[batch, height, width, channels]`. |\n| `input_image` | A `Tensor`. Must have the same type as `input_grads`. 4-D with shape `[batch, height, width, channels]`. |\n| `output_image` | A `Tensor`. Must have the same type as `input_grads`. 4-D with shape `[batch, height, width, channels]`. |\n| `depth_radius` | An optional `int`. Defaults to `5`. A depth radius. |\n| `bias` | An optional `float`. Defaults to `1`. An offset (usually \\\u003e 0 to avoid dividing by 0). |\n| `alpha` | An optional `float`. Defaults to `1`. A scale factor, usually positive. |\n| `beta` | An optional `float`. Defaults to `0.5`. An exponent. |\n| `name` | A name for the operation (optional). |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|---|---|\n| A `Tensor`. Has the same type as `input_grads`. ||\n\n\u003cbr /\u003e"]]