tf.raw_ops.QuantizeAndDequantizeV4Grad
Stay organized with collections
Save and categorize content based on your preferences.
Returns the gradient of QuantizeAndDequantizeV4
.
tf.raw_ops.QuantizeAndDequantizeV4Grad(
gradients, input, input_min, input_max, axis=-1, name=None
)
Returns a gradient of 1 for inputs that are within the quantization range,
or 0 otherwise.
Args |
gradients
|
A Tensor . Must be one of the following types: bfloat16 , half , float32 , float64 .
|
input
|
A Tensor . Must have the same type as gradients .
|
input_min
|
A Tensor . Must have the same type as gradients .
|
input_max
|
A Tensor . Must have the same type as gradients .
|
axis
|
An optional int . Defaults to -1 .
|
name
|
A name for the operation (optional).
|
Returns |
A tuple of Tensor objects (input_backprop, input_min_backprop, input_max_backprop).
|
input_backprop
|
A Tensor . Has the same type as gradients .
|
input_min_backprop
|
A Tensor . Has the same type as gradients .
|
input_max_backprop
|
A Tensor . Has the same type as gradients .
|
Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the Google Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates. Some content is licensed under the numpy license.
Last updated 2023-10-06 UTC.
[null,null,["Last updated 2023-10-06 UTC."],[],[],null,["# tf.raw_ops.QuantizeAndDequantizeV4Grad\n\n\u003cbr /\u003e\n\nReturns the gradient of `QuantizeAndDequantizeV4`.\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.QuantizeAndDequantizeV4Grad`](https://www.tensorflow.org/api_docs/python/tf/raw_ops/QuantizeAndDequantizeV4Grad)\n\n\u003cbr /\u003e\n\n tf.raw_ops.QuantizeAndDequantizeV4Grad(\n gradients, input, input_min, input_max, axis=-1, name=None\n )\n\nReturns a gradient of 1 for inputs that are within the quantization range,\nor 0 otherwise.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|-------------|-------------------------------------------------------------------------------------------|\n| `gradients` | A `Tensor`. Must be one of the following types: `bfloat16`, `half`, `float32`, `float64`. |\n| `input` | A `Tensor`. Must have the same type as `gradients`. |\n| `input_min` | A `Tensor`. Must have the same type as `gradients`. |\n| `input_max` | A `Tensor`. Must have the same type as `gradients`. |\n| `axis` | An optional `int`. Defaults to `-1`. |\n| `name` | A name for the operation (optional). |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|----------------------|-----------------------------------------------|\n| A tuple of `Tensor` objects (input_backprop, input_min_backprop, input_max_backprop). ||\n| `input_backprop` | A `Tensor`. Has the same type as `gradients`. |\n| `input_min_backprop` | A `Tensor`. Has the same type as `gradients`. |\n| `input_max_backprop` | A `Tensor`. Has the same type as `gradients`. |\n\n\u003cbr /\u003e"]]