tf.quantization.fake_quant_with_min_max_vars_gradient

Compute gradients for a FakeQuantWithMinMaxVars operation.

Compat aliases for migration

tf.quantization.fake_quant_with_min_max_vars_gradient(
    gradients, inputs, min, max, num_bits=8, narrow_range=False, name=None
)

Args
`gradients`	A `Tensor` of type `float32`. Backpropagated gradients above the FakeQuantWithMinMaxVars operation.
`inputs`	A `Tensor` of type `float32`. Values passed as inputs to the FakeQuantWithMinMaxVars operation. min, max: Quantization interval, scalar floats.
`min`	A `Tensor` of type `float32`.
`max`	A `Tensor` of type `float32`.
`num_bits`	An optional `int`. Defaults to `8`. The bitwidth of the quantization; between 2 and 8, inclusive.
`narrow_range`	An optional `bool`. Defaults to `False`. Whether to quantize into 2^num_bits - 1 distinct values.
`name`	A name for the operation (optional).

Returns
A tuple of `Tensor` objects (backprops_wrt_input, backprop_wrt_min, backprop_wrt_max).
`backprops_wrt_input`	A `Tensor` of type `float32`.
`backprop_wrt_min`	A `Tensor` of type `float32`.
`backprop_wrt_max`	A `Tensor` of type `float32`.

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 2021-02-18 UTC.

Args