FakeQuantWithMinMaxVarsPerChannelGradient

public final class FakeQuantWithMinMaxVarsPerChannelGradient

Compute gradients for a FakeQuantWithMinMaxVarsPerChannel operation.

Nested Classes

class

FakeQuantWithMinMaxVarsPerChannelGradient.Options

Optional attributes for FakeQuantWithMinMaxVarsPerChannelGradient

Constants

String

OP_NAME

The name of this op, as known by TensorFlow core engine

Public Methods

Output<TFloat32>	backpropWrtMax() Backpropagated gradients w.r.t.
Output<TFloat32>	backpropWrtMin() Backpropagated gradients w.r.t.
Output<TFloat32>	backpropsWrtInput() Backpropagated gradients w.r.t.
static FakeQuantWithMinMaxVarsPerChannelGradient	create(Scope scope, Operand<TFloat32> gradients, Operand<TFloat32> inputs, Operand<TFloat32> min, Operand<TFloat32> max, Options... options) Factory method to create a class wrapping a new FakeQuantWithMinMaxVarsPerChannelGradient operation.
static FakeQuantWithMinMaxVarsPerChannelGradient.Options	narrowRange(Boolean narrowRange)
static FakeQuantWithMinMaxVarsPerChannelGradient.Options	numBits(Long numBits)

Inherited Methods

From class org.tensorflow.op.RawOp

final boolean	equals(Object obj)
final int	hashCode()
Operation	op() Return this unit of computation as a single Operation.
final String	toString()

From class java.lang.Object

boolean	equals(Object arg0)
final Class<?>	getClass()
int	hashCode()
final void	notify()
final void	notifyAll()
String	toString()
final void	wait(long arg0, int arg1)
final void	wait(long arg0)
final void	wait()

From interface org.tensorflow.op.Op

abstract ExecutionEnvironment	env() Return the execution environment this op was created in.
abstract Operation	op() Return this unit of computation as a single Operation.

Constants

public static final String OP_NAME

The name of this op, as known by TensorFlow core engine

Constant Value: "FakeQuantWithMinMaxVarsPerChannelGradient"

Public Methods

public Output<TFloat32> backpropWrtMax ()

Backpropagated gradients w.r.t. max parameter, shape `[d]`: `sum_per_d(gradients * (inputs > max))`.

public Output<TFloat32> backpropWrtMin ()

Backpropagated gradients w.r.t. min parameter, shape `[d]`: `sum_per_d(gradients * (inputs < min))`.

public Output<TFloat32> backpropsWrtInput ()

Backpropagated gradients w.r.t. inputs, shape same as `inputs`: `gradients * (inputs >= min && inputs <= max)`.

public static FakeQuantWithMinMaxVarsPerChannelGradient create (Scope scope, Operand<TFloat32> gradients, Operand<TFloat32> inputs, Operand<TFloat32> min, Operand<TFloat32> max, Options... options)

Factory method to create a class wrapping a new FakeQuantWithMinMaxVarsPerChannelGradient operation.

Parameters

scope	current scope
gradients	Backpropagated gradients above the FakeQuantWithMinMaxVars operation, shape one of: `[d]`, `[b, d]`, `[b, h, w, d]`.
inputs	Values passed as inputs to the FakeQuantWithMinMaxVars operation, shape same as `gradients`. min, max: Quantization interval, floats of shape `[d]`.
options	carries optional attributes values

Returns

• a new instance of FakeQuantWithMinMaxVarsPerChannelGradient

public static FakeQuantWithMinMaxVarsPerChannelGradient.Options narrowRange (Boolean narrowRange)

Parameters

narrowRange	Whether to quantize into 2^num_bits - 1 distinct values.

public static FakeQuantWithMinMaxVarsPerChannelGradient.Options numBits (Long numBits)

Parameters

numBits	The bitwidth of the quantization; between 2 and 16, inclusive.