COMPMID-2410: Create a new GEMMLowpQuantizeDownInt32ToInt16ScaleKernel for CL
Change-Id: Iab74b72f7adf712a1baf16aab916ea7c8d2bf92f
Signed-off-by: Manuel Bottini <manuel.bottini@arm.com>
Reviewed-on: https://review.mlplatform.org/c/1497
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Pablo Marquez <pablo.tello@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
diff --git a/src/core/CL/CLKernelLibrary.cpp b/src/core/CL/CLKernelLibrary.cpp
index 36d8bed..8b64b1f 100644
--- a/src/core/CL/CLKernelLibrary.cpp
+++ b/src/core/CL/CLKernelLibrary.cpp
@@ -342,6 +342,7 @@
{ "gemmlowp_offset_contribution_quantize_down_fixedpoint", "gemmlowp.cl" },
{ "gemmlowp_output_stage_quantize_down", "gemmlowp.cl" },
{ "gemmlowp_output_stage_quantize_down_fixedpoint", "gemmlowp.cl" },
+ { "gemmlowp_output_stage_quantize_down_fixedpoint_qsymm16", "gemmlowp.cl" },
{ "gemmlowp_output_stage_quantize_down_float", "gemmlowp.cl" },
{ "generate_proposals_compute_all_anchors", "generate_proposals.cl" },
{ "harris_score_3x3", "harris_corners.cl" },
diff --git a/src/core/CL/cl_kernels/gemmlowp.cl b/src/core/CL/cl_kernels/gemmlowp.cl
index 65c31ef..4b86955 100644
--- a/src/core/CL/cl_kernels/gemmlowp.cl
+++ b/src/core/CL/cl_kernels/gemmlowp.cl
@@ -2861,6 +2861,89 @@
}
#endif // defined(RESULT_OFFSET_AFTER_SHIFT) && defined(RESULT_FIXEDPOINT_MULTIPLIER) && defined(RESULT_SHIFT)
+#if defined(RESULT_FIXEDPOINT_MULTIPLIER) && defined(RESULT_SHIFT)
+
+/** This OpenCL kernel is used to quantize down the int32 accumulator values of GEMMLowp to QASYMM16
+ *
+ * This kernel takes a final int32 accumulator value (the output of @ref CLGEMMLowpMatrixMultiplyKernel), and processes it to obtain the final QSYMM16 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 [-32768..32767] range and cast to QSYMM16.
+ *
+ * @attention The offset, scalar scale factor and number of bits to shift right of output tensor must be passed at compile time using -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 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
+ *
+ * @param[in] src_ptr Pointer to the source tensor. Supported data type: S32
+ * @param[in] src_stride_x Stride of the source tensor in X dimension (in bytes)
+ * @param[in] src_step_x src_stride_x * number of elements along X processed per workitem(in bytes)
+ * @param[in] src_stride_y Stride of the source tensor in Y dimension (in bytes)
+ * @param[in] src_step_y src_stride_y * number of elements along Y processed per workitem(in bytes)
+ * @param[in] src_stride_z Stride of the source tensor in Z dimension (in bytes)
+ * @param[in] src_step_z src_stride_z * number of elements along Z processed per workitem(in bytes)
+ * @param[in] src_offset_first_element_in_bytes The offset of the first element in the source tensor
+ * @param[in] biases_ptr (Optional) Pointer to the biases tensor. Supported data type: same as @p src_ptr
+ * @param[in] biases_stride_x (Optional) Stride of the biases tensor in X dimension (in bytes)
+ * @param[in] biases_step_x (Optional) biases_stride_x * number of elements along X processed per workitem(in bytes)
+ * @param[in] biases_offset_first_element_in_bytes (Optional) The offset of the first element in the biases tensor
+ * @param[out] dst_ptr Pointer to the destination tensor Supported data type: QASYMM8
+ * @param[in] dst_stride_x Stride of the destination tensor in X dimension (in bytes)
+ * @param[in] dst_step_x dst_gx_stride_x * number of elements along X processed per workitem(in bytes)
+ * @param[in] dst_stride_y Stride of the destination tensor in Y dimension (in bytes)
+ * @param[in] dst_step_y dst_gx_stride_y * number of elements along Y processed per workitem(in bytes)
+ * @param[in] dst_stride_z Stride of the source tensor in Z dimension (in bytes)
+ * @param[in] dst_step_z src_stride_z * number of elements along Z processed per workitem(in bytes)
+ * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination tensor
+ */
+__kernel void gemmlowp_output_stage_quantize_down_fixedpoint_qsymm16(TENSOR3D_DECLARATION(src),
+#if defined(ADD_BIAS)
+ VECTOR_DECLARATION(biases),
+#endif // defined(ADD_BIAS)
+ TENSOR3D_DECLARATION(dst))
+{
+ // Compute source and destination addresses
+ int x = get_global_id(0) * 4;
+ int y = get_global_id(1);
+ int z = get_global_id(2);
+
+ __global short *src_addr = src_ptr + src_offset_first_element_in_bytes + x * sizeof(int) + y * src_stride_y + z * src_stride_z;
+
+ __global short *dst_addr = dst_ptr + dst_offset_first_element_in_bytes + x * 2 + y * dst_stride_y + z * dst_stride_z;
+
+ int4 input_values = vload4(0, (__global int *)src_addr);
+
+#if defined(ADD_BIAS)
+ // Add bias
+ __global short *bias_addr = biases_ptr + biases_offset_first_element_in_bytes + x * sizeof(int);
+
+ int4 biases_values = vload4(0, (__global int *)bias_addr);
+ input_values += (int4)biases_values;
+#endif // defined(ADD_BIAS)
+
+ // Multiply by result_mult_int and shift
+ input_values = ASYMM_MULT_BY_QUANT_MULTIPLIER_LESS_THAN_ONE(input_values, RESULT_FIXEDPOINT_MULTIPLIER, RESULT_SHIFT, 4);
+
+ short4 res = convert_short4_sat(input_values);
+
+#if defined(MIN_BOUND)
+ res = max(res, (short4)MIN_BOUND);
+#endif // defined(MIN_BOUND)
+#if defined(MAX_BOUND)
+ res = min(res, (short4)MAX_BOUND);
+#endif // defined(MAX_BOUND)
+
+ // Store the result
+ vstore4(res, 0, dst_addr);
+}
+#endif // defined(RESULT_FIXEDPOINT_MULTIPLIER) && defined(RESULT_SHIFT)
+
#if defined(REAL_MULTIPLIER) && defined(OUTPUT_OFFSET)
/** This OpenCL kernel is used to quantize down the int32 accumulator values of GEMMLowp to QASYMM8
*
diff --git a/src/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel.cpp b/src/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel.cpp
new file mode 100644
index 0000000..557e82d
--- /dev/null
+++ b/src/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel.cpp
@@ -0,0 +1,180 @@
+/*
+ * Copyright (c) 2017-2019 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/CLGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel.h"
+
+#include "arm_compute/core/AccessWindowStatic.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"
+
+using namespace arm_compute;
+
+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 > 32767);
+ ARM_COMPUTE_RETURN_ERROR_ON(min < -32768 || 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::QSYMM16);
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(output, input);
+ }
+
+ 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::QSYMM16));
+
+ // 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
+
+class Coordinates;
+} // namespace arm_compute
+
+CLGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel::CLGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel()
+ : _input(nullptr), _bias(nullptr), _output(nullptr)
+{
+}
+
+Status CLGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel::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 CLGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel::configure(const ICLTensor *input, const ICLTensor *bias, ICLTensor *output,
+ int result_fixedpoint_multiplier, int result_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));
+
+ _input = input;
+ _bias = bias;
+ _output = output;
+
+ // Set the arguments to pass at compile time
+ CLBuildOptions build_opts;
+ 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_if((min != -32768) && (min != max), "-DMIN_BOUND=" + support::cpp11::to_string(min));
+ build_opts.add_option_if((max != 32767) && (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_qsymm16", 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 CLGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel::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);
+ }
+ while(collapsed.slide_window_slice_3D(slice));
+}
diff --git a/src/runtime/CL/functions/CLGEMMLowpOutputStage.cpp b/src/runtime/CL/functions/CLGEMMLowpOutputStage.cpp
index f1282cb..020fbbe 100644
--- a/src/runtime/CL/functions/CLGEMMLowpOutputStage.cpp
+++ b/src/runtime/CL/functions/CLGEMMLowpOutputStage.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017-2018 ARM Limited.
+ * Copyright (c) 2017-2019 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -24,6 +24,7 @@
#include "arm_compute/runtime/CL/functions/CLGEMMLowpOutputStage.h"
#include "arm_compute/core/CL/ICLTensor.h"
+#include "arm_compute/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel.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"
@@ -72,4 +73,20 @@
{
return CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFloatKernel::validate(input, bias, output, min, max);
}
+
+void CLGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPoint::configure(const ICLTensor *input, const ICLTensor *bias, ICLTensor *output,
+ int result_fixedpoint_multiplier, int result_shift,
+ int min, int max)
+{
+ auto k = arm_compute::support::cpp14::make_unique<CLGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel>();
+ k->configure(input, bias, output, result_fixedpoint_multiplier, result_shift, min, max);
+ _kernel = std::move(k);
+}
+
+Status CLGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPoint::validate(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output,
+ int min, int max)
+{
+ return CLGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel::validate(input, bias, output, min, max);
+}
+
} // namespace arm_compute
\ No newline at end of file