COMPMID-2789: Add support for QASYMM8_SIGNED in CLGEMMDeconvolutionLayer
Change-Id: I7e3bcb01025e827f6f62491749c691c205ee7481
Signed-off-by: Sheri Zhang <sheri.zhang@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/2844
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Michele Di Giorgio <michele.digiorgio@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
diff --git a/arm_compute/runtime/CL/functions/CLGEMMDeconvolutionLayer.h b/arm_compute/runtime/CL/functions/CLGEMMDeconvolutionLayer.h
index 3df9205..01687b6 100644
--- a/arm_compute/runtime/CL/functions/CLGEMMDeconvolutionLayer.h
+++ b/arm_compute/runtime/CL/functions/CLGEMMDeconvolutionLayer.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2019 ARM Limited.
+ * Copyright (c) 2019-2020 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -68,7 +68,7 @@
* This function calls the following OpenCL kernels/functions:
*
* -# @ref CLGEMMLowpMatrixMultiplyCore
- * -# @ref CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint
+ * -# @ref CLGEMMLowpOutputStage
* -# @ref CLPermute
* -# @ref CLPermute
* -# @ref CLReshapeLayer
@@ -91,7 +91,8 @@
CLGEMMDeconvolutionLayer &operator=(CLGEMMDeconvolutionLayer &&) = default;
/** Set the input, weights, biases and output tensors.
*
- * @param[in,out] input Input tensor. 3 lower dimensions represent a single input, and an optional 4th dimension for batch of inputs. Data types supported: F16/F32. Data layout supported: NHWC
+ * @param[in,out] input Input tensor. 3 lower dimensions represent a single input, and an optional 4th dimension for batch of inputs.
+ * Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32. Data layout supported: NHWC
* @param[in] weights The 4d weights with dimensions [width, height, IFM, OFM]. Data type supported: Same as @p input. Data layout supported: same as @p input.
* @param[in] bias (Optional) The biases have one dimension. Data type supported: Same as @p input. Data layout supported: same as @p input.
* @param[out] output Output tensor. The output has the same number of dimensions as the @p input. Data layout supported: same as @p input.
@@ -100,7 +101,8 @@
void configure(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *bias, ICLTensor *output, const PadStrideInfo &deconv_info);
/** Static function to check if given info will lead to a valid configuration of @ref CLDeconvolutionLayer
*
- * @param[in] input Input tensor info. 3 lower dimensions represent a single input, and an optional 4th dimension for batch of inputs. Data types supported: F16/F32. Data layout supported: NHWC
+ * @param[in] input Input tensor info. 3 lower dimensions represent a single input, and an optional 4th dimension for batch of inputs.
+ * Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32. Data layout supported: NHWC
* @param[in] weights The 4d weights info with dimensions [width, height, IFM, OFM]. Data type supported: Same as @p input. Data layout supported: same as @p input.
* @param[in] bias (Optional) The biases have one dimension. Data type supported: Same as @p input. Data layout supported: same as @p input.
* @param[in] output Output tensor info. The output has the same number of dimensions as the @p input. Data layout supported: same as @p input.
@@ -117,15 +119,15 @@
private:
MemoryGroup _memory_group;
- CLGEMM _mm_gemm;
- CLGEMMLowpMatrixMultiplyCore _mm_gemmlowp;
- CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint _gemmlowp_output_stage;
- CLPermute _permute_input_to_nhwc;
- CLPermute _permute_weights_to_nhwc;
- CLReshapeLayer _reshape_weights;
- CLTranspose _transpose_weights;
- CLDeconvolutionReshapeOutputKernel _deconv_reshape;
- CLSlice _slice_gemm;
+ CLGEMM _mm_gemm;
+ CLGEMMLowpMatrixMultiplyCore _mm_gemmlowp;
+ CLGEMMLowpOutputStage _gemmlowp_output_stage;
+ CLPermute _permute_input_to_nhwc;
+ CLPermute _permute_weights_to_nhwc;
+ CLReshapeLayer _reshape_weights;
+ CLTranspose _transpose_weights;
+ CLDeconvolutionReshapeOutputKernel _deconv_reshape;
+ CLSlice _slice_gemm;
CLTensor _gemmlowp_final;
CLTensor _reshaped_weights;
diff --git a/arm_compute/runtime/CL/functions/CLGEMMLowpOutputStage.h b/arm_compute/runtime/CL/functions/CLGEMMLowpOutputStage.h
index 564135e..b6619da 100644
--- a/arm_compute/runtime/CL/functions/CLGEMMLowpOutputStage.h
+++ b/arm_compute/runtime/CL/functions/CLGEMMLowpOutputStage.h
@@ -64,7 +64,7 @@
* @param[in] input Input tensor. It is the output of @ref CLGEMMLowpMatrixMultiplyCore function. Data type supported: S32
* @param[in] bias Biases tensor. Only shared biases supported and it can be a nullptr if the addition of biases is not required.
* Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p input.
- * @param[out] output Output tensor. Data type supported: Data type supported: QASYMM8
+ * @param[out] output Output tensor. Data type supported: QASYMM8
* @param[in] result_offset Offset to be added to each element of the input matrix
* @param[in] result_mult_int Value to be multiplied to each element of the input matrix when once the result_offset has been add
* @param[in] result_shift Number of bits to shift right the result before converting back to QASYMM8
@@ -79,7 +79,7 @@
* @param[in] input Input tensor. It is the output of @ref CLGEMMLowpMatrixMultiplyCore function. Data type supported: S32
* @param[in] bias Biases tensor. Only shared biases supported and it can be a nullptr if the addition of biases is not required.
* Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p input.
- * @param[in] output Output tensor. Data type supported: Data type supported: QASYMM8
+ * @param[in] output Output tensor. Data type supported: QASYMM8
* @param[in] min (Optional) Min value used to saturate down the output result before converting back to QASYMM8. Defaults to the minimum possible 32-bit signed integer.
* @param[in] max (Optional) Max value used to saturate up the output result before converting back to QASYMM8,
* Along with @p min, this value can be used to implement "rectified linear unit" activation functions. Defaults to the maximum possible 32-bit signed integer.
@@ -125,7 +125,7 @@
* @param[in] input Input tensor. Data type supported: S32
* @param[in] bias Biases tensor. Only shared biases supported and it can be a nullptr if the biases addition is not required.
* Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p input.
- * @param[out] output Output tensor. Data type supported: Data type supported: QASYMM8
+ * @param[out] output Output tensor. Data type supported: QASYMM8
* @param[in] result_fixedpoint_multiplier Fixed point value to be multiplied to each element of the input matrix when once the result_offset has been add
* @param[in] result_shift Number of bits to shift right the result after the fixed point multiplication
* @param[in] result_offset_after_shift Offset to be applied to result before converting it back to QASYMM8
@@ -140,7 +140,7 @@
* @param[in] input Input tensor. It is the output of @ref CLGEMMLowpMatrixMultiplyCore function. Data type supported: S32
* @param[in] bias Biases tensor. Only shared biases supported and it can be a nullptr if the addition of biases is not required.
* Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p input.
- * @param[in] output Output tensor. Data type supported: Data type supported: QASYMM8
+ * @param[in] output Output tensor. Data type supported: QASYMM8
* @param[in] min (Optional) Min value used to saturate down the output result before converting back to QASYMM8. Defaults to the minimum possible 32-bit signed integer.
* @param[in] max (Optional) Max value used to saturate up the output result before converting back to QASYMM8,
* Along with @p min, this value can be used to implement "rectified linear unit" activation functions. Defaults to the maximum possible 32-bit signed integer.
@@ -186,7 +186,7 @@
* @param[in] input Input tensor. Data type supported: S32
* @param[in] bias Biases tensor. Only shared biases supported and it can be a nullptr if the biases addition is not required.
* Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p input.
- * @param[out] output Output tensor. Data type supported: Data type supported: QASYMM8_SIGNED
+ * @param[out] output Output tensor. Data type supported: QASYMM8_SIGNED
* @param[in] result_fixedpoint_multiplier Fixed point value to be multiplied to each element of the input matrix when once the result_offset has been add
* @param[in] result_shift Number of bits to shift right the result after the fixed point multiplication
* @param[in] result_offset_after_shift Offset to be applied to result before converting it back to QASYMM8_SIGNED
@@ -201,7 +201,7 @@
* @param[in] input Input tensor. It is the output of @ref CLGEMMLowpMatrixMultiplyCore function. Data type supported: S32
* @param[in] bias Biases tensor. Only shared biases supported and it can be a nullptr if the addition of biases is not required.
* Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p input.
- * @param[in] output Output tensor. Data type supported: Data type supported: QASYMM8_SIGNED
+ * @param[in] output Output tensor. Data type supported: QASYMM8_SIGNED
* @param[in] min (Optional) Min value used to saturate down the output result before converting back to QASYMM8_SIGNED. Defaults to the minimum possible 32-bit signed integer.
* @param[in] max (Optional) Max value used to saturate up the output result before converting back to QASYMM8_SIGNED. Defaults to 0
* Along with @p min, this value can be used to implement "rectified linear unit" activation functions. Defaults to the maximum possible 32-bit signed integer.
@@ -228,7 +228,7 @@
* @param[in] input Input tensor. Data type supported: S32
* @param[in] bias Biases tensor. Only shared biases supported and it can be a nullptr if the biases addition is not required.
* Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p input.
- * @param[out] output Output tensor. Data type supported: Data type supported: QASYMM8
+ * @param[out] output Output tensor. Data type supported: QASYMM8
* @param[in] multiplier Float multiplier to be multiplied to each element of the input matrix
* @param[in] offset Offset to be applied to result before converting it back to QASYMM8
* @param[in] min (Optional) Min value used to saturate down the output result before converting back to QASYMM8. Defaults to the minimum possible 32-bit signed integer.
@@ -242,7 +242,7 @@
* @param[in] input Input tensor. It is the output of @ref CLGEMMLowpMatrixMultiplyCore function. Data type supported: S32
* @param[in] bias Biases tensor. Only shared biases supported and it can be a nullptr if the addition of biases is not required.
* Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p input.
- * @param[in] output Output tensor. Data type supported: Data type supported: QASYMM8
+ * @param[in] output Output tensor. Data type supported: QASYMM8
* @param[in] min (Optional) Min value used to saturate down the output result before converting back to QASYMM8. Defaults to the minimum possible 32-bit signed integer.
* @param[in] max (Optional) Max value used to saturate up the output result before converting back to QASYMM8,
* Along with @p min, this value can be used to implement "rectified linear unit" activation functions. Defaults to the maximum possible 32-bit signed integer.
@@ -287,7 +287,7 @@
* @param[in] input Input tensor. Data type supported: S32
* @param[in] bias Biases tensor. Only shared biases supported and it can be a nullptr if the biases addition is not required.
* Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p input.
- * @param[out] output Output tensor. Data type supported: Data type supported: QSYMM16
+ * @param[out] output Output tensor. Data type supported: QSYMM16
* @param[in] result_fixedpoint_multiplier Fixed point value to be multiplied to each element of the input matrix when once the result_offset has been add
* @param[in] result_shift Number of bits to shift right the result after the fixed point multiplication
* @param[in] min (Optional) Min value used to saturate down the output result before converting back to QSYMM16. Defaults to the minimum possible 32-bit signed integer.
@@ -301,7 +301,7 @@
* @param[in] input Input tensor info. It is the output of @ref CLGEMMLowpMatrixMultiplyCore function. Data type supported: S32
* @param[in] bias Biases tensor info. Only shared biases supported and it can be a nullptr if the addition of biases is not required.
* Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p input.
- * @param[in] output Output tensor info. Data type supported: Data type supported: QSYMM16
+ * @param[in] output Output tensor info. Data type supported: QSYMM16
* @param[in] min (Optional) Min value used to saturate down the output result before converting back to QSYMM16. Defaults to the minimum possible 32-bit signed integer.
* @param[in] max (Optional) Max value used to saturate up the output result before converting back to QSYMM16,
* Along with @p min, this value can be used to implement "rectified linear unit" activation functions. Defaults to the maximum possible 32-bit signed integer.
@@ -310,5 +310,36 @@
*/
static Status validate(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, int min = std::numeric_limits<int32_t>::lowest(), int max = std::numeric_limits<int32_t>::max());
};
+/** Basic function to execute GEMMLowpQuantizeDown kernels on CL.
+ *
+ * This function calls the following CL kernels:
+ *
+ * -# @ref CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel
+ * -# @ref CLGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel
+*/
+class CLGEMMLowpOutputStage : public ICLSimpleFunction
+{
+public:
+ /** Initialise the kernel's inputs, output
+ *
+ * @param[in] input Input tensor. Data type supported: S32
+ * @param[in] bias Biases tensor. Only shared biases supported and it can be a nullptr if the biases addition is not required.
+ * Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p input.
+ * @param[out] output Output tensor. Data type supported: QASYMM8/QASYMM8_SIGNED
+ * @param[in] info GEMMLowp output stage metadata.
+ */
+ void configure(const ICLTensor *input, const ICLTensor *bias, ICLTensor *output, const GEMMLowpOutputStageInfo &info);
+ /** Static function to check if given info will lead to a valid configuration of @ref CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel
+ *
+ * @param[in] input Input tensor. It is the output of @ref CLGEMMLowpMatrixMultiplyCore function. Data type supported: S32
+ * @param[in] bias Biases tensor. Only shared biases supported and it can be a nullptr if the addition of biases is not required.
+ * Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p input.
+ * @param[in] output Output tensor. Data type supported: QASYMM8/QASYMM8_SIGNED
+ * @param[in] info GEMMLowp output stage metadata.
+ *
+ * @return a status
+ */
+ static Status validate(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, const GEMMLowpOutputStageInfo &info);
+};
} // namespace arm_compute
#endif /*ARM_COMPUTE_CLGEMMLOWPOUTPUTSTAGE_H */
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