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

UniformQuantizedDot

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public final class UniformQuantizedDot

Perform quantized dot of quantized Tensor `lhs` and quantized Tensor `rhs` to make quantized `output`.

Given quantized `lhs` and quantized `rhs`, performs quantized dot on `lhs` and `rhs` to make quantized `output`. `lhs` and `rhs` must be 2D Tensors and the lhs.dim_size(1) must match rhs.dim_size(0). `lhs` and `rhs` must be quantized Tensor, where data value is quantized using the formula: quantized_data = clip(original_data / scale + zero_point, quantization_min_val, quantization_max_val). `output` is also quantized, using the same formula. If `rhs` is per-tensor quantized, `output` must be also per-tensor quantized.

Nested Classes

class UniformQuantizedDot.Options Optional attributes for UniformQuantizedDot  

Public Methods

Output<U>
asOutput()
Returns the symbolic handle of a tensor.
static <U, T> UniformQuantizedDot<U>
create(Scope scope, Operand<T> lhs, Operand<T> rhs, Operand<Float> lhsScales, Operand<Integer> lhsZeroPoints, Operand<Float> rhsScales, Operand<Integer> rhsZeroPoints, Operand<Float> outputScales, Operand<Integer> outputZeroPoints, Class<U> Tout, Long lhsQuantizationMinVal, Long lhsQuantizationMaxVal, Long rhsQuantizationMinVal, Long rhsQuantizationMaxVal, Long outputQuantizationMinVal, Long outputQuantizationMaxVal, Options... options)
Factory method to create a class wrapping a new UniformQuantizedDot operation.
static UniformQuantizedDot.Options
lhsQuantizationAxis(Long lhsQuantizationAxis)
Output<U>
output()
The output 2D Tensor of Tout, whose shape is (lhs.dim_size(0), rhs.dim_size(1)).
static UniformQuantizedDot.Options
outputQuantizationAxis(Long outputQuantizationAxis)
static UniformQuantizedDot.Options
rhsQuantizationAxis(Long rhsQuantizationAxis)

Inherited Methods

Public Methods

public Output<U> 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 UniformQuantizedDot<U> create (Scope scope, Operand<T> lhs, Operand<T> rhs, Operand<Float> lhsScales, Operand<Integer> lhsZeroPoints, Operand<Float> rhsScales, Operand<Integer> rhsZeroPoints, Operand<Float> outputScales, Operand<Integer> outputZeroPoints, Class<U> Tout, Long lhsQuantizationMinVal, Long lhsQuantizationMaxVal, Long rhsQuantizationMinVal, Long rhsQuantizationMaxVal, Long outputQuantizationMinVal, Long outputQuantizationMaxVal, Options... options)

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

Parameters
scope current scope
lhs Must be a 2D Tensor of Tin.
rhs Must be a 2D Tensor of Tin.
lhsScales The float value(s) used as scale when quantizing original data that lhs represents. Must be a scalar Tensor (lhs supports only per-tensor quantization).
lhsZeroPoints The int32 value(s) used as zero_point when quantizing original data that lhs represents. Same shape condition as lhs_scales.
rhsScales The float value(s) used as scale when quantizing original data that rhs represents. Must be a scalar Tensor (per-tensor quantization) or 1D Tensor of size (rhs.dim_size(1),) (per-channel quantization).
rhsZeroPoints The int32 value(s) used as zero_point when quantizing original data that rhs represents. Same shape condition as rhs_scales.
outputScales The float value(s) to use as scales when quantizing original data that output represents. Must be a scalar Tensor (per-tensor quantization) or 1D Tensor of size (output.dim_size(1),) (per-channel quantization). If rhs is per-tensor quantized, output must be also per-tensor quantized. This means that if rhs_scales and rhs_zero_points are scalar Tensors, output_scales and output_zero_points must be scalar Tensors as well.
outputZeroPoints The int32 value(s) used as zero_point when quantizing original data that output represents. Same shape condition as rhs_scales.
Tout The type of output Tensor.
lhsQuantizationMinVal The min value of the quantized data stored in lhs. For example, if Tin is qint8, this must be set to -127 if narrow range quantized or -128 if not.
lhsQuantizationMaxVal The max value of the quantized data stored in rhs. For example, if Tin is qint8, this must be set to 127.
rhsQuantizationMinVal The min value of the quantized data stored in rhs. For example, if Trhs is qint8, this must be set to -127 if narrow range quantized or -128 if not.
rhsQuantizationMaxVal The max value of the quantized data stored in rhs. For example, if Trhs is qint8, this must be set to 127.
outputQuantizationMinVal The min value of the quantized data stored in output. For example, if Tout is qint8, this must be set to -127 if narrow range quantized or -128 if not.
outputQuantizationMaxVal The max value of the quantized data stored in output. For example, if Tout is qint8, this must be set to 127.
options carries optional attributes values
Returns
  • a new instance of UniformQuantizedDot

public static UniformQuantizedDot.Options lhsQuantizationAxis (Long lhsQuantizationAxis)

Parameters
lhsQuantizationAxis 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. For dot op lhs, only per-tensor quantization is supported. Thus, this attribute must be set to -1. Other values are rejected.

public Output<U> output ()

The output 2D Tensor of Tout, whose shape is (lhs.dim_size(0), rhs.dim_size(1)).

public static UniformQuantizedDot.Options outputQuantizationAxis (Long outputQuantizationAxis)

Parameters
outputQuantizationAxis 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. For dot op output, only per-tensor quantization or per-channel quantization along dimension 1 is supported. Thus, this attribute must be set to -1 or 1. Other values are rejected.

public static UniformQuantizedDot.Options rhsQuantizationAxis (Long rhsQuantizationAxis)

Parameters
rhsQuantizationAxis 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. For dot op rhs, only per-tensor quantization or per-channel quantization along dimension 1 is supported. Thus, this attribute must be set to -1 or 1. Other values are rejected.