COMPMID-2794: Add support for QASYMM8_SIGNED in CLGEMMLowpOutputStage
Change-Id: I93ad3e5b9531ce1699214ff6e657a76ffdaacedd
Signed-off-by: Manuel Bottini <manuel.bottini@arm.com>
Reviewed-on: https://review.mlplatform.org/c/2396
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Michele Di Giorgio <michele.digiorgio@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
diff --git a/arm_compute/core/CL/CLKernels.h b/arm_compute/core/CL/CLKernels.h
index 78437be..d070d6a 100644
--- a/arm_compute/core/CL/CLKernels.h
+++ b/arm_compute/core/CL/CLKernels.h
@@ -80,6 +80,7 @@
#include "arm_compute/core/CL/kernels/CLGEMMLowpOffsetContributionKernel.h"
#include "arm_compute/core/CL/kernels/CLGEMMLowpOffsetContributionOutputStageKernel.h"
#include "arm_compute/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel.h"
+#include "arm_compute/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel.h"
#include "arm_compute/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel.h"
#include "arm_compute/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFloatKernel.h"
#include "arm_compute/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToUint8ScaleKernel.h"
diff --git a/arm_compute/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel.h b/arm_compute/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel.h
new file mode 100644
index 0000000..22ac8fa
--- /dev/null
+++ b/arm_compute/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel.h
@@ -0,0 +1,96 @@
+/*
+ * Copyright (c) 2019 ARM Limited.
+ *
+ * SPDX-License-Identifier: MIT
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to
+ * deal in the Software without restriction, including without limitation the
+ * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
+ * sell copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in all
+ * copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+ * SOFTWARE.
+ */
+#ifndef ARM_COMPUTE_CLGEMMLOWPQUANTIZEDOWNINT32TOINT8SCALEBYFIXEDPOINTKERNEL_H
+#define ARM_COMPUTE_CLGEMMLOWPQUANTIZEDOWNINT32TOINT8SCALEBYFIXEDPOINTKERNEL_H
+
+#include "arm_compute/core/CL/ICLKernel.h"
+
+namespace arm_compute
+{
+class ICLTensor;
+
+/** OpenCL kernel used to quantize down the int32 accumulator values of GEMMLowp to QASYMM8_SIGNED
+ *
+ * This kernel takes a final int32 accumulator value (the output of @ref CLGEMMLowpMatrixMultiplyKernel), and processes it to obtain the final QASYMM8_SIGNED value.
+ * The following computations will be performed by the kernel:
+ *
+ * -# Compute fixed point multiplication between each entry of input by result_fixedpoint_multiplier
+ * -# Add bias to final result if bias tensor is not a nullptr
+ * -# Round to nearest division by a power-of-two using result_shift
+ * -# Add offset to each result
+ * -# Clamp the value between the specified min and max bounds
+ * -# Clamp the resulting int32 values to the [-128..127] range and cast to QASYMM8_SIGNED.
+ */
+class CLGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel : public ICLKernel
+{
+public:
+ /** Constructor */
+ CLGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel();
+ /** Prevent instances of this class from being copied (As this class contains pointers)*/
+ CLGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel(const CLGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel &) = delete;
+ /** Prevent instances of this class from being copied (As this class contains pointers)*/
+ CLGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel &operator=(const CLGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel &) = delete;
+ /** Allow instances of this class to be moved */
+ CLGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel(CLGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel &&) = default;
+ /** Allow instances of this class to be moved */
+ CLGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel &operator=(CLGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel &&) = default;
+ /** Initialise the kernel's input and 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: 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 Integer value used to round to nearest division by a power-of-two 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
+ * @param[in] min (Optional) Min value used to saturate down the output result before converting back to QASYMM8_SIGNED. Defaults to 0
+ * @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
+ */
+ void configure(const ICLTensor *input, const ICLTensor *bias, ICLTensor *output, int result_fixedpoint_multiplier, int result_shift, int result_offset_after_shift,
+ int min = 0, int max = 0);
+ /** Static function to check if given info will lead to a valid configuration of @ref CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel
+ *
+ * @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[in] output Output tensor. Data type supported: Data type supported: QASYMM8_SIGNED
+ * @param[in] min (Optional) Min value used to saturate down the output result before converting back to QASYMM8_SIGNED
+ * @param[in] max (Optional) Max value used to saturate up the output result before converting back to QASYMM8_SIGNED,
+ * Along with @p min, this value can be used to implement "rectified linear unit" activation functions
+ *
+ * @return a status
+ */
+ static Status validate(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, int min = 0, int max = 0);
+
+ // Inherited methods overridden:
+ void run(const Window &window, cl::CommandQueue &queue) override;
+
+private:
+ const ICLTensor *_input;
+ const ICLTensor *_bias;
+ ICLTensor *_output;
+};
+} // namespace arm_compute
+#endif /* ARM_COMPUTE_CLGEMMLOWPQUANTIZEDOWNINT32TOINT8SCALEBYFIXEDPOINTKERNEL_H */
diff --git a/arm_compute/runtime/CL/functions/CLGEMMLowpOutputStage.h b/arm_compute/runtime/CL/functions/CLGEMMLowpOutputStage.h
index 0e70223..25fa142 100644
--- a/arm_compute/runtime/CL/functions/CLGEMMLowpOutputStage.h
+++ b/arm_compute/runtime/CL/functions/CLGEMMLowpOutputStage.h
@@ -21,15 +21,15 @@
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
-#ifndef __ARM_COMPUTE_CLGEMMLOWPOUTPUTSTAGE_H__
-#define __ARM_COMPUTE_CLGEMMLOWPOUTPUTSTAGE_H__
+#ifndef ARM_COMPUTE_CLGEMMLOWPOUTPUTSTAGE_H
+#define ARM_COMPUTE_CLGEMMLOWPOUTPUTSTAGE_H
#include "arm_compute/runtime/CL/ICLSimpleFunction.h"
/** This file contains all available output stages for GEMMLowp on OpenCL.
*
* In gemmlowp, the "output stage" is the process that takes a final int32 accumulator value (the output of @ref CLGEMMLowpMatrixMultiplyCore),
- * and processes it to obtain the final ASYMM8 value.
+ * and processes it to obtain the final QASYMM8/QASYMM8_SIGNED value.
*
* More information about the GEMMLowp output stage can be found at https://github.com/google/gemmlowp/blob/master/doc/output.md
*/
@@ -149,6 +149,67 @@
static Status validate(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, int min = 0, int max = 0);
};
+/** Basic function to execute CLGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPoint on OpenCL.
+ *
+ * CLGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPoint depends on 3 parameters:
+ *
+ * result_fixedpoint_multiplier, result_shift, result_offset_after_shift
+ *
+ * The final result is:
+ *
+ * (FixedPointMul(input[i][k], result_fixedpoint_multiplier) >> result_shift) + result_offset_after_shift
+ *
+ * where FixedPointMul(x, y) is the nearest integer to the following
+ * mathematical expression, evaluated without overflow or intermediate rounding:
+ *
+ * (x * y) / 2^31
+ *
+ * For more information: https://github.com/google/gemmlowp/blob/master/public/output_stages.h#L68
+ *
+ * In case the bias tensor is provided, the final result is:
+ *
+ * ((FixedPointMul(input[i][k] + bias[k], result_fixedpoint_multiplier)) >> result_shift) + result_offset_after_shift
+ *
+ * This function calls the following OpenCL kernels:
+ *
+ * -# @ref CLGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel
+ *
+ * @note The function accepts also 2 optional input arguments (min and max) which can be used to implement "rectified linear unit" activation functions
+ * after the result is shifted right by result_shift
+*/
+class CLGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPoint : 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: 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
+ * @param[in] min (Optional) Min value used to saturate down the output result before converting back to QASYMM8_SIGNED. Defaults to 0
+ * @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
+ */
+ void configure(const ICLTensor *input, const ICLTensor *bias, ICLTensor *output, int result_fixedpoint_multiplier, int result_shift, int result_offset_after_shift,
+ int min = 0, int max = 0);
+ /** Static function to check if given info will lead to a valid configuration of @ref CLGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPoint
+ *
+ * @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] min (Optional) Min value used to saturate down the output result before converting back to QASYMM8_SIGNED. Defaults to 0
+ * @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
+ *
+ * @return a status
+ */
+ static Status validate(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, int min = 0, int max = 0);
+};
+
/** Basic function to execute CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFloat on OpenCL.
*
* This function calls the following OpenCL kernels:
diff --git a/docs/06_functions_list.dox b/docs/06_functions_list.dox
index 30b522b..b6b94c4 100644
--- a/docs/06_functions_list.dox
+++ b/docs/06_functions_list.dox
@@ -93,6 +93,7 @@
- @ref NEGEMMInterleave4x4
- @ref NEGEMMLowpQuantizeDownInt32ToUint8Scale
- @ref NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint
+ - @ref NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint
- @ref NEGEMMTranspose1xW
- @ref NEHOGDetector
- @ref NEMagnitude
@@ -298,6 +299,7 @@
- @ref CLGaussian3x3
- @ref CLGEMMLowpQuantizeDownInt32ToUint8Scale
- @ref CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint
+ - @ref CLGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPoint
- @ref CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFloat
- @ref CLMagnitude
- @ref CLMeanStdDevNormalizationLayer
diff --git a/src/core/CL/CLHelpers.cpp b/src/core/CL/CLHelpers.cpp
index 9754beb..47472a3 100644
--- a/src/core/CL/CLHelpers.cpp
+++ b/src/core/CL/CLHelpers.cpp
@@ -44,6 +44,7 @@
case DataType::S8:
case DataType::QASYMM8_SIGNED:
case DataType::QSYMM8:
+ case DataType::QASYMM8_SIGNED:
case DataType::QSYMM8_PER_CHANNEL:
return "char";
case DataType::U16:
diff --git a/src/core/CL/cl_kernels/gemmlowp.cl b/src/core/CL/cl_kernels/gemmlowp.cl
index 47791fb..2a1c156 100644
--- a/src/core/CL/cl_kernels/gemmlowp.cl
+++ b/src/core/CL/cl_kernels/gemmlowp.cl
@@ -1824,11 +1824,14 @@
* -# Round to nearest division by a power-of-two using result_shift
* -# Add offset to each result
* -# Clamp the value between the specified min and max bounds
- * -# Clamp the resulting int32 values to the [0..255] range and cast to QASYMM8.
+ * -# Clamp the resulting int32 values:
+ * - to the [0..255] range and cast to QASYMM8.
+ * - to the [-128..127] range and cast to QASYMM8_SIGNED.
*
* @attention The offset, scalar scale factor and number of bits to shift right of output tensor must be passed at compile time using -DRESULT_OFFSET_AFTER_SHIFT, -DRESULT_FIXEDPOINT_MULTIPLIER and -DRESULT_SHIFT
*
* @note In case the addition of int32 biases is required, -DADD_BIAS should be passed at compile time
+ * @note The output datatype should be passed at compile time using -DOUTPUT_DATA_TYPE
* @note In case the clamping of the result is required, the min and max bounds can be passed at compile time using -DMIN_BOUND and -DMAX_BOUND.
* These values can be used to implement "rectified linear unit" activation functions
*
@@ -1888,17 +1891,18 @@
// Add the offset terms to GEMM's result
input_values += (int4)RESULT_OFFSET_AFTER_SHIFT;
- uchar4 res = convert_uchar4_sat(input_values);
+ VEC_DATA_TYPE(OUTPUT_DATA_TYPE, 4)
+ res = CONVERT_SAT(input_values, VEC_DATA_TYPE(OUTPUT_DATA_TYPE, 4));
#if defined(MIN_BOUND)
- res = max(res, (uchar4)MIN_BOUND);
+ res = max(res, (VEC_DATA_TYPE(OUTPUT_DATA_TYPE, 4))MIN_BOUND);
#endif // defined(MIN_BOUND)
#if defined(MAX_BOUND)
- res = min(res, (uchar4)MAX_BOUND);
+ res = min(res, (VEC_DATA_TYPE(OUTPUT_DATA_TYPE, 4))MAX_BOUND);
#endif // defined(MAX_BOUND)
// Store the result
- vstore4(res, 0, dst_addr);
+ vstore4(res, 0, (__global OUTPUT_DATA_TYPE *)dst_addr);
}
#endif // defined(RESULT_OFFSET_AFTER_SHIFT) && defined(RESULT_FIXEDPOINT_MULTIPLIER) && defined(RESULT_SHIFT)
diff --git a/src/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel.cpp b/src/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel.cpp
new file mode 100644
index 0000000..3de3182
--- /dev/null
+++ b/src/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel.cpp
@@ -0,0 +1,181 @@
+/*
+ * Copyright (c) 2019 ARM Limited.
+ *
+ * SPDX-License-Identifier: MIT
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to
+ * deal in the Software without restriction, including without limitation the
+ * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
+ * sell copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in all
+ * copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+ * SOFTWARE.
+ */
+#include "arm_compute/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel.h"
+
+#include "arm_compute/core/AccessWindowStatic.h"
+#include "arm_compute/core/CL/CLHelpers.h"
+#include "arm_compute/core/CL/ICLTensor.h"
+#include "arm_compute/core/Error.h"
+#include "arm_compute/core/Helpers.h"
+#include "arm_compute/core/TensorInfo.h"
+#include "arm_compute/core/Types.h"
+#include "arm_compute/core/Validate.h"
+#include "arm_compute/core/Window.h"
+#include "arm_compute/core/utils/misc/ShapeCalculator.h"
+
+#include "support/ToolchainSupport.h"
+
+namespace arm_compute
+{
+namespace
+{
+Status validate_arguments(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output,
+ int min, int max)
+{
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::S32);
+ ARM_COMPUTE_RETURN_ERROR_ON(max > 127);
+ ARM_COMPUTE_RETURN_ERROR_ON(min < -128 || min > max);
+
+ // Check biases if exist
+ if(bias != nullptr)
+ {
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, bias);
+ ARM_COMPUTE_RETURN_ERROR_ON(bias->num_dimensions() > 1);
+ ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(0) != bias->dimension(0));
+ }
+
+ if(output->total_size() != 0)
+ {
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::QASYMM8_SIGNED);
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input, output);
+ }
+
+ return Status{};
+}
+
+std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *bias, ITensorInfo *output)
+{
+ constexpr unsigned int num_elems_processed_per_iteration = 4;
+
+ // Output auto inizialitation if not yet initialized
+ auto_init_if_empty(*output, input->clone()->set_data_type(DataType::QASYMM8_SIGNED));
+
+ // Configure kernel window
+ Window win = calculate_max_window(*input, Steps(num_elems_processed_per_iteration));
+
+ AccessWindowHorizontal input_access(input, 0, num_elems_processed_per_iteration);
+
+ bool window_changed = update_window_and_padding(win, input_access);
+
+ if(output->total_size() != 0)
+ {
+ Window win_out = calculate_max_window(*output, Steps(num_elems_processed_per_iteration));
+ AccessWindowHorizontal output_result_access(output, 0, num_elems_processed_per_iteration);
+ window_changed = window_changed || update_window_and_padding(win_out, output_result_access);
+ output_result_access.set_valid_region(win, ValidRegion(Coordinates(), output->tensor_shape()));
+ }
+
+ if(bias != nullptr)
+ {
+ AccessWindowStatic bias_access(bias, 0, 0, ceil_to_multiple(bias->dimension(0), num_elems_processed_per_iteration), bias->tensor_shape()[1]);
+ window_changed = window_changed || update_window_and_padding(win, bias_access);
+ }
+
+ Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{};
+ return std::make_pair(err, win);
+}
+} // namespace
+
+CLGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel::CLGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel()
+ : _input(nullptr), _bias(nullptr), _output(nullptr)
+{
+}
+
+Status CLGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel::validate(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output,
+ int min, int max)
+{
+ ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
+ ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, bias, output, min, max));
+ ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(),
+ (bias != nullptr) ? bias->clone().get() : nullptr,
+ output->clone().get())
+ .first);
+
+ return Status{};
+}
+
+void CLGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel::configure(const ICLTensor *input, const ICLTensor *bias, ICLTensor *output,
+ int result_fixedpoint_multiplier, int result_shift, int result_offset_after_shift,
+ int min, int max)
+{
+ // Perform validate step
+ ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
+ ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), (bias != nullptr) ? bias->info() : nullptr, output->info(), min, max));
+ ARM_COMPUTE_ERROR_THROW_ON(validate_and_configure_window(input->info(),
+ (bias != nullptr) ? bias->info() : nullptr,
+ output->info())
+ .first);
+
+ _input = input;
+ _bias = bias;
+ _output = output;
+
+ // Set the arguments to pass at compile time
+ CLBuildOptions build_opts;
+ build_opts.add_option("-DRESULT_OFFSET_AFTER_SHIFT=" + support::cpp11::to_string(result_offset_after_shift));
+ build_opts.add_option("-DRESULT_FIXEDPOINT_MULTIPLIER=" + support::cpp11::to_string(result_fixedpoint_multiplier));
+ build_opts.add_option("-DRESULT_SHIFT=" + support::cpp11::to_string(result_shift));
+ build_opts.add_option("-DOUTPUT_DATA_TYPE=" + get_cl_type_from_data_type(output->info()->data_type()));
+ build_opts.add_option_if((min != -128) && (min != max), "-DMIN_BOUND=" + support::cpp11::to_string(min));
+ build_opts.add_option_if((max != 127) && (min != max), "-DMAX_BOUND=" + support::cpp11::to_string(max));
+ build_opts.add_option_if(bias != nullptr, "-DADD_BIAS");
+
+ // Create kernel
+ _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("gemmlowp_output_stage_quantize_down_fixedpoint", build_opts.options()));
+
+ // Configure kernel window
+ auto win_config = validate_and_configure_window(input->info(), (bias != nullptr) ? bias->info() : nullptr, output->info());
+ ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
+ ICLKernel::configure_internal(win_config.second);
+}
+
+void CLGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel::run(const Window &window, cl::CommandQueue &queue)
+{
+ ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
+ ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICLKernel::window(), window);
+
+ // Create input window
+ Window collapsed = window.collapse_if_possible(ICLKernel::window(), Window::DimZ);
+ Window slice = collapsed.first_slice_window_3D();
+
+ // Setup bias slice
+ unsigned int idx1 = num_arguments_per_3D_tensor();
+ if(_bias != nullptr)
+ {
+ Window biases_slice(slice);
+ biases_slice.set(Window::DimY, Window::Dimension(0, 1, 1));
+ biases_slice.set(Window::DimZ, Window::Dimension(0, 1, 1));
+ add_1D_tensor_argument(idx1, _bias, biases_slice);
+ }
+
+ do
+ {
+ unsigned int idx = 0;
+ add_3D_tensor_argument(idx, _input, slice);
+ add_3D_tensor_argument(idx1, _output, slice);
+ enqueue(queue, *this, slice, lws_hint());
+ }
+ while(collapsed.slide_window_slice_3D(slice));
+}
+} // namespace arm_compute
diff --git a/src/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel.cpp b/src/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel.cpp
index a98eae6..a5b00d1 100644
--- a/src/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel.cpp
+++ b/src/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel.cpp
@@ -24,6 +24,7 @@
#include "arm_compute/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel.h"
#include "arm_compute/core/AccessWindowStatic.h"
+#include "arm_compute/core/CL/CLHelpers.h"
#include "arm_compute/core/CL/ICLTensor.h"
#include "arm_compute/core/Error.h"
#include "arm_compute/core/Helpers.h"
@@ -75,15 +76,13 @@
AccessWindowHorizontal input_access(input, 0, num_elems_processed_per_iteration);
- bool window_changed = update_window_and_padding(win,
- input_access);
+ bool window_changed = update_window_and_padding(win, input_access);
if(output->total_size() != 0)
{
Window win_out = calculate_max_window(*output, Steps(num_elems_processed_per_iteration));
AccessWindowHorizontal output_result_access(output, 0, num_elems_processed_per_iteration);
window_changed = window_changed || update_window_and_padding(win_out, output_result_access);
-
output_result_access.set_valid_region(win, ValidRegion(Coordinates(), output->tensor_shape()));
}
@@ -122,8 +121,11 @@
{
// Perform validate step
ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
- ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), (bias != nullptr) ? bias->info() : nullptr, output->info(),
- min, max));
+ ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), (bias != nullptr) ? bias->info() : nullptr, output->info(), min, max));
+ ARM_COMPUTE_ERROR_THROW_ON(validate_and_configure_window(input->info(),
+ (bias != nullptr) ? bias->info() : nullptr,
+ output->info())
+ .first);
_input = input;
_bias = bias;
@@ -134,6 +136,7 @@
build_opts.add_option("-DRESULT_OFFSET_AFTER_SHIFT=" + support::cpp11::to_string(result_offset_after_shift));
build_opts.add_option("-DRESULT_FIXEDPOINT_MULTIPLIER=" + support::cpp11::to_string(result_fixedpoint_multiplier));
build_opts.add_option("-DRESULT_SHIFT=" + support::cpp11::to_string(result_shift));
+ build_opts.add_option("-DOUTPUT_DATA_TYPE=" + get_cl_type_from_data_type(output->info()->data_type()));
build_opts.add_option_if((min != 0) && (min != max), "-DMIN_BOUND=" + support::cpp11::to_string(min));
build_opts.add_option_if((max != 255) && (min != max), "-DMAX_BOUND=" + support::cpp11::to_string(max));
build_opts.add_option_if(bias != nullptr, "-DADD_BIAS");
diff --git a/src/runtime/CL/functions/CLGEMMLowpOutputStage.cpp b/src/runtime/CL/functions/CLGEMMLowpOutputStage.cpp
index 020fbbe..9551fc7 100644
--- a/src/runtime/CL/functions/CLGEMMLowpOutputStage.cpp
+++ b/src/runtime/CL/functions/CLGEMMLowpOutputStage.cpp
@@ -25,6 +25,7 @@
#include "arm_compute/core/CL/ICLTensor.h"
#include "arm_compute/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel.h"
+#include "arm_compute/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel.h"
#include "arm_compute/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel.h"
#include "arm_compute/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFloatKernel.h"
#include "arm_compute/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToUint8ScaleKernel.h"
@@ -59,6 +60,21 @@
return CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel::validate(input, bias, output, min, max);
}
+void CLGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPoint::configure(const ICLTensor *input, const ICLTensor *bias, ICLTensor *output,
+ int result_fixedpoint_multiplier, int result_shift, int result_offset_after_shift,
+ int min, int max)
+{
+ auto k = arm_compute::support::cpp14::make_unique<CLGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel>();
+ k->configure(input, bias, output, result_fixedpoint_multiplier, result_shift, result_offset_after_shift, min, max);
+ _kernel = std::move(k);
+}
+
+Status CLGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPoint::validate(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output,
+ int min, int max)
+{
+ return CLGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel::validate(input, bias, output, min, max);
+}
+
void CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFloat::configure(const ICLTensor *input, const ICLTensor *bias, ICLTensor *output,
float multiplier, int offset,
int min, int max)
diff --git a/tests/validation/CL/GEMMLowp.cpp b/tests/validation/CL/GEMMLowp.cpp
index 39543b1..2890eb1 100644
--- a/tests/validation/CL/GEMMLowp.cpp
+++ b/tests/validation/CL/GEMMLowp.cpp
@@ -211,9 +211,7 @@
}
TEST_SUITE_END() // BoundedReLu
TEST_SUITE_END() // QuantizeDownInt32ToUint8Scale
-
TEST_SUITE(QuantizeDownInt32ToUint8ScaleByFixedPoint)
-
const auto quantize_down_int32_to_uint8_scale_by_fixedpoint_cases = framework::dataset::make("result_fixedpoint_multiplier", 254601600, 254601602) * framework::dataset::make("result_shift", 1,
2)
* framework::dataset::make("result_offset_after_shift", 2, 3) * framework::dataset::make("min", 0) * framework::dataset::make("max", 0) * framework::dataset::make("addBias", { false, true });
@@ -221,12 +219,10 @@
const auto quantize_down_int32_to_uint8_scale_by_fixedpoint_relu_cases = framework::dataset::make("result_fixedpoint_multiplier", 254601600, 254601602) * framework::dataset::make("result_shift", 1,
2)
* framework::dataset::make("result_offset_after_shift", 2, 3) * framework::dataset::make("min", 0, 2) * framework::dataset::make("max", 171, 174) * framework::dataset::make("addBias", { false, true });
-
using CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointFixture =
GEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointValidationFixture<CLTensor, CLAccessor, CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint>;
-DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(datasets::SmallShapes(),
- quantize_down_int32_to_uint8_scale_by_fixedpoint_cases),
+DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(datasets::SmallShapes(), quantize_down_int32_to_uint8_scale_by_fixedpoint_cases),
shape, result_fixedpoint_multiplier, result_shift, result_offset_after_shift, min, max, add_bias)
{
TensorShape shape_bias(shape[0]);
@@ -297,6 +293,73 @@
}
TEST_SUITE_END() // BoundedReLu
TEST_SUITE_END() // QuantizeDownInt32ToUint8ScaleByFixedPoint
+TEST_SUITE(QuantizeDownInt32ToInt8ScaleByFixedPoint)
+const auto quantize_down_int32_to_int8_scale_by_fixedpoint_cases = framework::dataset::make("result_fixedpoint_multiplier", 254601600, 254601602) * framework::dataset::make("result_shift", 1, 2)
+ * framework::dataset::make("result_offset_after_shift", 2, 3) * framework::dataset::make("min", 0) * framework::dataset::make("max", 0) * framework::dataset::make("addBias", { false, true });
+
+const auto quantize_down_int32_to_int8_scale_by_fixedpoint_relu_cases = framework::dataset::make("result_fixedpoint_multiplier", 254601600, 254601602) * framework::dataset::make("result_shift", 1, 2)
+ * framework::dataset::make("result_offset_after_shift", 2, 3) * framework::dataset::make("min", -128, -126) * framework::dataset::make("max", 110, 112) * framework::dataset::make("addBias", { false, true });
+using CLGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointFixture =
+ GEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointValidationFixture<CLTensor, CLAccessor, CLGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPoint>;
+
+DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(datasets::SmallShapes(), quantize_down_int32_to_int8_scale_by_fixedpoint_cases),
+ shape, result_fixedpoint_multiplier, result_shift, result_offset_after_shift, min, max, add_bias)
+{
+ TensorShape shape_bias(shape[0]);
+
+ // Create tensors
+ CLTensor in = create_tensor<CLTensor>(shape, DataType::S32);
+ CLTensor bias = create_tensor<CLTensor>(shape_bias, DataType::S32);
+ CLTensor out = create_tensor<CLTensor>(shape, DataType::QASYMM8_SIGNED);
+
+ ARM_COMPUTE_EXPECT(in.info()->is_resizable(), framework::LogLevel::ERRORS);
+ ARM_COMPUTE_EXPECT(bias.info()->is_resizable(), framework::LogLevel::ERRORS);
+ ARM_COMPUTE_EXPECT(out.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+ // Create and configure function
+ CLGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPoint output_stage;
+ output_stage.configure(&in, add_bias ? &bias : nullptr, &out, result_fixedpoint_multiplier, result_shift, result_offset_after_shift, min, max);
+
+ // Validate valid region input and output
+ const ValidRegion valid_region = shape_to_valid_region(shape);
+ validate(in.info()->valid_region(), valid_region);
+ validate(out.info()->valid_region(), valid_region);
+
+ // Validate valid region bias
+ if(add_bias)
+ {
+ const ValidRegion valid_region_bias = shape_to_valid_region(shape_bias);
+ validate(bias.info()->valid_region(), valid_region_bias);
+ }
+
+ // Validate padding
+ const PaddingSize padding = PaddingCalculator(shape.x(), 4).required_padding();
+ validate(in.info()->padding(), padding);
+ validate(out.info()->padding(), padding);
+
+ if(add_bias)
+ {
+ validate(bias.info()->padding(), padding);
+ }
+}
+
+FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointFixture, framework::DatasetMode::ALL, combine(datasets::SmallShapes(),
+ quantize_down_int32_to_int8_scale_by_fixedpoint_cases))
+{
+ // Validate output
+ validate(CLAccessor(_target), _reference);
+}
+
+TEST_SUITE(BoundedReLu)
+FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointFixture, framework::DatasetMode::ALL, combine(datasets::SmallShapes(),
+ quantize_down_int32_to_int8_scale_by_fixedpoint_relu_cases))
+{
+ // Validate output
+ validate(CLAccessor(_target), _reference);
+}
+
+TEST_SUITE_END() // BoundedReLu
+TEST_SUITE_END() // QuantizeDownInt32ToInt8ScaleByFixedPoint
TEST_SUITE(QuantizeDownInt32ToInt16ScaleByFixedPoint)
const auto quantize_down_int32_to_int16_scale_by_fixedpoint_cases = framework::dataset::make("result_fixedpoint_multiplier", 254601600, 254601602) * framework::dataset::make("result_shift", 1,