Perform a quantized matrix multiplication of `a` by the matrix `b` with bias add and relu and requantize fusion.
The inputs must be two-dimensional matrices and 1D bias vector. And the inner dimension of `a` (after being transposed if `transpose_a` is non-zero) must match the outer dimension of `b` (after being transposed if `transposed_b` is non-zero). Then do broadcast add operation with bias values on the matrix multiplication result. The bias size must match inner dimension of `b`. Then do relu activation to get non-negative result. Then do requantize operation to get final uint8 result.
Nested Classes
| class | QuantizedMatMulWithBiasAndReluAndRequantize.Options | Optional attributes for QuantizedMatMulWithBiasAndReluAndRequantize
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Constants
| String | OP_NAME | The name of this op, as known by TensorFlow core engine |
Public Methods
| static <W extends TType> QuantizedMatMulWithBiasAndReluAndRequantize<W> |
create(Scope scope, Operand<? extends TType> a, Operand<? extends TType> b, Operand<? extends TType> bias, Operand<TFloat32> minA, Operand<TFloat32> maxA, Operand<TFloat32> minB, Operand<TFloat32> maxB, Operand<TFloat32> minFreezedOutput, Operand<TFloat32> maxFreezedOutput, Class<W> Toutput, Options... options)
Factory method to create a class wrapping a new QuantizedMatMulWithBiasAndReluAndRequantize operation.
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| static QuantizedMatMulWithBiasAndReluAndRequantize.Options |
inputQuantMode(String inputQuantMode)
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| Output<TFloat32> |
maxOut()
The float value that the highest quantized output value represents.
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| Output<TFloat32> |
minOut()
The float value that the lowest quantized output value represents.
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| Output<W> |
out()
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| static QuantizedMatMulWithBiasAndReluAndRequantize.Options |
transposeA(Boolean transposeA)
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| static QuantizedMatMulWithBiasAndReluAndRequantize.Options |
transposeB(Boolean transposeB)
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Inherited Methods
Constants
public static final String OP_NAME
The name of this op, as known by TensorFlow core engine
Public Methods
public static QuantizedMatMulWithBiasAndReluAndRequantize<W> create (Scope scope, Operand<? extends TType> a, Operand<? extends TType> b, Operand<? extends TType> bias, Operand<TFloat32> minA, Operand<TFloat32> maxA, Operand<TFloat32> minB, Operand<TFloat32> maxB, Operand<TFloat32> minFreezedOutput, Operand<TFloat32> maxFreezedOutput, Class<W> Toutput, Options... options)
Factory method to create a class wrapping a new QuantizedMatMulWithBiasAndReluAndRequantize operation.
Parameters
| scope | current scope |
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| a | A matrix to be multiplied. Must be a two-dimensional tensor of type `quint8`. |
| b | A matrix to be multiplied and must be a two-dimensional tensor of type `qint8`. |
| bias | A 1D bias tensor with size matching with inner dimension of `b` (after being transposed if `transposed_b` is non-zero). |
| minA | The float value that the lowest quantized `a` value represents. |
| maxA | The float value that the highest quantized `a` value represents. |
| minB | The float value that the lowest quantized `b` value represents. |
| maxB | The float value that the highest quantized `b` value represents. |
| minFreezedOutput | The float value that the highest quantized output value after requantize. |
| options | carries optional attributes values |
Returns
- a new instance of QuantizedMatMulWithBiasAndReluAndRequantize
public static QuantizedMatMulWithBiasAndReluAndRequantize.Options inputQuantMode (String inputQuantMode)
Parameters
| inputQuantMode | Input data quantization mode. Either MIN_FIRST(default) or SCALED. |
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public Output<TFloat32> maxOut ()
The float value that the highest quantized output value represents.
public Output<TFloat32> minOut ()
The float value that the lowest quantized output value represents.
public static QuantizedMatMulWithBiasAndReluAndRequantize.Options transposeA (Boolean transposeA)
Parameters
| transposeA | If true, `a` is transposed before multiplication. |
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public static QuantizedMatMulWithBiasAndReluAndRequantize.Options transposeB (Boolean transposeB)
Parameters
| transposeB | If true, `b` is transposed before multiplication. |
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