Warning: This API is deprecated and will be removed in a future version of TensorFlow after the replacement is stable.

UniformQuantizedClipByValue

public final class UniformQuantizedClipByValue

Perform clip by value on the quantized Tensor `operand`.

Given quantized `operand` which was quantized using `scales` and `zero_points`, performs clip by value using `min` and `max` values. If quantization_axis is -1 (per-tensor quantized), the entire operand is clipped using scalar min, max. Otherwise (per-channel quantized), the clipping is also done per-channel.

Nested Classes

class UniformQuantizedClipByValue.Options Optional attributes for UniformQuantizedClipByValue

Public Methods

Output<T>	asOutput() Returns the symbolic handle of a tensor.
static <T> UniformQuantizedClipByValue<T>	create(Scope scope, Operand<T> operand, Operand<T> min, Operand<T> max, Operand<Float> scales, Operand<Integer> zeroPoints, Long quantizationMinVal, Long quantizationMaxVal, Options... options) Factory method to create a class wrapping a new UniformQuantizedClipByValue operation.
Output<T>	output() The output clipped Tensor of T, whose shape is same as operand.
static UniformQuantizedClipByValue.Options	quantizationAxis(Long quantizationAxis)

Inherited Methods

From class org.tensorflow.op.PrimitiveOp

final boolean	equals(Object obj)
final int	hashCode()
Operation	op() Returns the underlying `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.Operand

abstract Output<T>

asOutput()

Returns the symbolic handle of a tensor.

Public Methods

public Output<T> asOutput ()

Returns the symbolic handle of a tensor.

Inputs to TensorFlow operations are outputs of another TensorFlow operation. This method is used to obtain a symbolic handle that represents the computation of the input.

public static UniformQuantizedClipByValue<T> create (Scope scope, Operand<T> operand, Operand<T> min, Operand<T> max, Operand<Float> scales, Operand<Integer> zeroPoints, Long quantizationMinVal, Long quantizationMaxVal, Options... options)

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

Parameters

scope	current scope
operand	Must be a Tensor of T.
min	The min value(s) to clip operand. Must be a Tensor of T. Must be a scalar Tensor if quantization_axis is -1 (per-tensor quantization), otherwise 1D Tensor of size (operand.dim_size(quantization_axis),) (per-axis quantization).
max	The min value(s) to clip operand. Must be a Tensor of T. Must be a scalar Tensor if quantization_axis is -1 (per-tensor quantization), otherwise 1D Tensor of size (operand.dim_size(quantization_axis),) (per-axis quantization).
scales	The float value(s) used as scale(s) when quantizing `operand`, `min` and `max`. Must be a scalar Tensor if quantization_axis is -1 (per-tensor quantization), otherwise 1D Tensor of size (operand.dim_size(quantization_axis),) (per-axis quantization).
zeroPoints	The int32 value(s) used as zero_point(s) when quantizing `operand`, `min` and `max`. Same shape condition as scales.
quantizationMinVal	The quantization min value that was used when operand was quantized.
quantizationMaxVal	The quantization max value that was used when operand was quantized.
options	carries optional attributes values

Returns

a new instance of UniformQuantizedClipByValue

public Output<T> output ()

The output clipped Tensor of T, whose shape is same as operand.

public static UniformQuantizedClipByValue.Options quantizationAxis (Long quantizationAxis)

Parameters

quantizationAxis	Indicates the dimension index of the tensor where per-axis quantization is applied for the slices along that dimension. If set to -1 (default), this indicates per-tensor quantization. Otherwise, it must be set within range [0, operand.dims()).