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-rw-r--r--src/core/CL/kernels/CLGEMMMatrixMultiplyReshapedKernel.cpp401
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diff --git a/src/core/CL/kernels/CLGEMMMatrixMultiplyReshapedKernel.cpp b/src/core/CL/kernels/CLGEMMMatrixMultiplyReshapedKernel.cpp
deleted file mode 100644
index 09e4e98a87..0000000000
--- a/src/core/CL/kernels/CLGEMMMatrixMultiplyReshapedKernel.cpp
+++ /dev/null
@@ -1,401 +0,0 @@
-/*
- * Copyright (c) 2018-2020 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/CLGEMMMatrixMultiplyReshapedKernel.h"
-
-#include "arm_compute/core/AccessWindowStatic.h"
-#include "arm_compute/core/CL/CLHelpers.h"
-#include "arm_compute/core/CL/CLKernelLibrary.h"
-#include "arm_compute/core/CL/CLValidate.h"
-#include "arm_compute/core/CL/ICLTensor.h"
-#include "arm_compute/core/CL/OpenCL.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/Utils.h"
-#include "arm_compute/core/Validate.h"
-#include "arm_compute/core/Window.h"
-#include "arm_compute/core/utils/helpers/float_ops.h"
-#include "arm_compute/core/utils/misc/ShapeCalculator.h"
-#include "support/StringSupport.h"
-
-#include <cstddef>
-#include <cstdint>
-#include <tuple>
-
-using namespace arm_compute;
-using namespace arm_compute::misc::shape_calculator;
-
-namespace arm_compute
-{
-class Coordinates;
-} // namespace arm_compute
-
-namespace
-{
-using ElementsProcessed = Steps;
-
-Status validate_arguments(const ITensorInfo *input0, const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, float alpha, float beta, const GEMMLHSMatrixInfo &lhs_info,
- const GEMMRHSMatrixInfo &rhs_info,
- const GEMMKernelInfo &gemm_info)
-{
- ARM_COMPUTE_UNUSED(alpha);
- ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input0, input1, output);
- ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input0);
- ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input0, 1, DataType::F16, DataType::F32);
- ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input0, input1);
- ARM_COMPUTE_RETURN_ERROR_ON_MSG(input0->num_dimensions() > 4, "The number of dimensions for the LHS matrix must be <= 4");
- ARM_COMPUTE_RETURN_ERROR_ON_MSG(input1->num_dimensions() > 3, "The number of dimensions for the RHS matrix must be <= 3");
- ARM_COMPUTE_RETURN_ERROR_ON(lhs_info.k0 != rhs_info.k0);
- ARM_COMPUTE_RETURN_ERROR_ON(lhs_info.transpose == rhs_info.transpose);
- ARM_COMPUTE_RETURN_ERROR_ON_MSG(((lhs_info.k0 & (lhs_info.k0 - 1)) && lhs_info.k0 != 3), "Only 2,3,4,8,16 are supported for k0");
- ARM_COMPUTE_RETURN_ERROR_ON(lhs_info.k0 > 16);
- ARM_COMPUTE_RETURN_ERROR_ON(lhs_info.m0 < 2 || lhs_info.m0 > 8);
- ARM_COMPUTE_RETURN_ERROR_ON_MSG((lhs_info.transpose) && ((lhs_info.m0 & (lhs_info.m0 - 1)) && lhs_info.m0 != 3), "Only 2,3,4,8,16 are supported for m0");
- ARM_COMPUTE_RETURN_ERROR_ON_MSG((rhs_info.transpose) && ((rhs_info.n0 & (rhs_info.n0 - 1)) && rhs_info.n0 != 3), "Only 2,3,4,8,16 are supported for n0");
- ARM_COMPUTE_RETURN_ERROR_ON_MSG((gemm_info.reinterpret_input_as_3d || gemm_info.depth_output_gemm3d != 0) && (input2 != nullptr)
- && (!gemm_info.broadcast_bias),
- "Bias addition only supported with broadcast mode in case the input or output has to be reinterpreted as 3D");
- ARM_COMPUTE_RETURN_ERROR_ON_MSG(gemm_info.fp_mixed_precision && (input0->data_type() == DataType::F32), "Mixed precision only supported for F16 data type");
-
- const unsigned int m = gemm_info.m;
- const unsigned int n = gemm_info.n;
- const unsigned int k = gemm_info.k;
-
- TensorShape tensor_shape0{ input0->tensor_shape() };
- tensor_shape0.set(0, k);
- tensor_shape0.set(1, m);
-
- TensorShape tensor_shape1{ input1->tensor_shape() };
- tensor_shape1.set(0, n);
- tensor_shape1.set(1, k);
-
- if(input2 != nullptr && !(helpers::float_ops::is_zero(beta)))
- {
- const unsigned int input2_dim0 = input2->dimension(0);
- const unsigned int input2_dim1 = input2->dimension(1);
-
- ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input2, input1);
- if(gemm_info.broadcast_bias)
- {
- ARM_COMPUTE_RETURN_ERROR_ON_MSG((input2_dim1 != 1 || input2_dim0 != n), "Incorrect dimension of bias matrix which is to be broadcasted");
- }
- else
- {
- ARM_COMPUTE_RETURN_ERROR_ON_MSG((input2_dim0 != n || input2_dim1 != m), "Incorrect dimension of bias matrix");
- }
- }
-
- const TensorInfo tensor_info0 = input0->clone()->set_tensor_shape(tensor_shape0);
- const TensorInfo tensor_info1 = input1->clone()->set_tensor_shape(tensor_shape1);
-
- const TensorInfo tensor_info_reshaped0 = input0->clone()->set_tensor_shape(compute_lhs_reshaped_shape(tensor_info0, lhs_info));
- const TensorInfo tensor_info_reshaped1 = input1->clone()->set_tensor_shape(compute_rhs_reshaped_shape(tensor_info1, rhs_info));
-
- ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input0, &tensor_info_reshaped0);
- ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input1, &tensor_info_reshaped1);
-
- if(output->total_size() != 0)
- {
- const TensorInfo tensor_info_output = output->clone()->set_tensor_shape(compute_mm_shape(*input0, *input1, gemm_info));
- ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(output, &tensor_info_output);
- ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input0, output);
- }
-
- return Status{};
-}
-
-std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input0, ITensorInfo *input1, ITensorInfo *input2, ITensorInfo *output, const GEMMLHSMatrixInfo &lhs_info,
- const GEMMRHSMatrixInfo &rhs_info,
- const GEMMKernelInfo &gemm_info, ElementsProcessed &num_elements_processed)
-{
- unsigned int &num_elems_processed_per_iteration_x = num_elements_processed[0];
- unsigned int &num_elems_processed_per_iteration_y = num_elements_processed[1];
- bool reinterpret_output_as_3d = gemm_info.depth_output_gemm3d != 0;
-
- Window win{};
- Window win_out{};
- bool window_changed = false;
-
- // Output tensor auto initialization if not yet initialized
- auto_init_if_empty(*output, input0->clone()->set_tensor_shape(compute_mm_shape(*input0, *input1, gemm_info)));
-
- TensorInfo tmp_info(*output);
-
- if(reinterpret_output_as_3d)
- {
- // Since the output tensor has to be reinterpreted as 3D and the execute window is based on a 2D GEMM,
- // the window needs to be constructed on the 2D collapsed version of the tensor
- TensorShape tmp_shape(output->tensor_shape());
- tmp_shape.collapse(2U, 1U);
- tmp_info.set_tensor_shape(tmp_shape);
- }
-
- // Configure kernel window
- num_elems_processed_per_iteration_x = rhs_info.n0;
- num_elems_processed_per_iteration_y = lhs_info.m0;
-
- // Note: bottom paddings are calculated manually as the output can be reinterpreted as 3D tensor
- // The only way to set properly the paddings, it is to set those explicitly through the AccessWindowStatic
- const unsigned int m = gemm_info.m;
- const unsigned int bottom_pad = (num_elems_processed_per_iteration_y - (m % num_elems_processed_per_iteration_y)) % num_elems_processed_per_iteration_y;
-
- win = calculate_max_window(tmp_info, Steps(num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y));
- win_out = calculate_max_window(*output, Steps(num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y));
-
- AccessWindowStatic input0_access(input0, 0, 0,
- ceil_to_multiple(input0->dimension(0), num_elems_processed_per_iteration_y),
- input0->dimension(1));
- AccessWindowStatic input1_access(input1, 0, 0,
- ceil_to_multiple(input1->dimension(0), num_elems_processed_per_iteration_x),
- input1->dimension(1));
- AccessWindowStatic output_access(output, 0, 0,
- ceil_to_multiple(output->dimension(0), num_elems_processed_per_iteration_x),
- output->dimension(1) + bottom_pad);
-
- if(input2 != nullptr)
- {
- const int bias_processed_per_iteration_x = num_elems_processed_per_iteration_x;
-
- const int bias_processed_per_iteration_y = gemm_info.broadcast_bias ? 1 : num_elems_processed_per_iteration_y;
-
- AccessWindowStatic input2_access(input2, 0, 0,
- ceil_to_multiple(input2->dimension(0), bias_processed_per_iteration_x),
- ceil_to_multiple(input2->dimension(1), bias_processed_per_iteration_y));
-
- window_changed = update_window_and_padding(win, input0_access, input1_access, input2_access) || // window used by the execute_window_loop
- update_window_and_padding(win_out, output_access); // window used to update the padding requirements of output tensor
- }
- else
- {
- window_changed = update_window_and_padding(win, input0_access, input1_access) || // window used by the execute_window_loop
- update_window_and_padding(win_out, output_access); // window used to update the padding requirements of output tensor
- }
-
- output_access.set_valid_region(win_out, ValidRegion(Coordinates(0, 0), output->tensor_shape()));
-
- // Collapse along the Z direction
- // This collapse needs to be here in order to tune the Z dimension of LWS
- Window collapsed = win;
- const unsigned int dimension_to_collapse = std::min(static_cast<unsigned int>(output->num_dimensions()), 2u);
- collapsed = win.collapse(win, dimension_to_collapse);
-
- Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{};
- return std::make_pair(err, collapsed);
-}
-} // namespace
-
-CLGEMMMatrixMultiplyReshapedKernel::CLGEMMMatrixMultiplyReshapedKernel()
- : _input0(nullptr), _input1(nullptr), _input2(nullptr), _output(nullptr), _slide_matrix_b(true), _reinterpret_output_as_3d(false), _k(1), _use_dummy_work_items(false), _add_bias(false),
- _broadcast_bias(false)
-{
-}
-
-void CLGEMMMatrixMultiplyReshapedKernel::configure(const ICLTensor *input0, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, float alpha, float beta,
- const GEMMLHSMatrixInfo &lhs_info,
- const GEMMRHSMatrixInfo &rhs_info, const GEMMKernelInfo &gemm_info)
-{
- configure(CLKernelLibrary::get().get_compile_context(), input0, input1, input2, output, alpha, beta, lhs_info, rhs_info, gemm_info);
-}
-
-void CLGEMMMatrixMultiplyReshapedKernel::configure(const CLCompileContext &compile_context, const ICLTensor *input0, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, float alpha,
- float beta,
- const GEMMLHSMatrixInfo &lhs_info,
- const GEMMRHSMatrixInfo &rhs_info, const GEMMKernelInfo &gemm_info)
-{
- ARM_COMPUTE_ERROR_ON_NULLPTR(input0, input1, output);
-
- ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input0->info(), input1->info(), (input2 != nullptr ? input2->info() : nullptr), output->info(), alpha, beta, lhs_info, rhs_info, gemm_info));
-
- _input0 = input0;
- _input1 = input1;
- _input2 = helpers::float_ops::is_zero(beta) ? nullptr : input2;
- _output = output;
- _reinterpret_output_as_3d = gemm_info.depth_output_gemm3d != 0;
- _k = gemm_info.k;
- _use_dummy_work_items = preferred_dummy_work_items_support(CLKernelLibrary::get().get_device());
- _add_bias = _input2 != nullptr;
- _broadcast_bias = gemm_info.broadcast_bias;
-
- // Check if we need to slide the matrix B
- const unsigned int num_dimensions_input0 = _input0->info()->num_dimensions();
- _slide_matrix_b = (_input1->info()->num_dimensions() >= num_dimensions_input0);
-
- ElementsProcessed num_elements_processed{};
-
- // Configure kernel window
- auto win_config = validate_and_configure_window(input0->info(), input1->info(), input2 != nullptr ? input2->info() : nullptr, output->info(), lhs_info, rhs_info, gemm_info, num_elements_processed);
- ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
- ICLKernel::configure_internal(win_config.second);
-
- const bool enable_mixed_precision = gemm_info.fp_mixed_precision;
- const DataType data_type = input0->info()->data_type();
-
- // Create build options
- CLBuildOptions build_opts;
- build_opts.add_option_if(!(helpers::float_ops::is_one(alpha)), "-DALPHA=" + float_to_string_with_full_precision(alpha));
- build_opts.add_option_if(_input2 != nullptr, "-DBETA=" + float_to_string_with_full_precision(beta));
- build_opts.add_option_if(helpers::float_ops::is_one(beta), "-DUNIT_BETA");
- build_opts.add_option_if(_reinterpret_output_as_3d, "-DREINTERPRET_OUTPUT_AS_3D");
- build_opts.add_option_if(_reinterpret_output_as_3d, "-DHEIGHT_GEMM3D=" + support::cpp11::to_string(output->info()->dimension(1)));
- build_opts.add_option_if(_reinterpret_output_as_3d, "-DDEPTH_GEMM3D=" + support::cpp11::to_string(output->info()->dimension(2)));
- build_opts.add_option_if(gemm_info.broadcast_bias, "-DBROADCAST_BIAS");
- build_opts.add_option_if(!_slide_matrix_b, "-DMATRIX_B_DEPTH=" + support::cpp11::to_string(input1->info()->dimension(2)));
- build_opts.add_option_if(lhs_info.interleave, "-DLHS_INTERLEAVE");
- build_opts.add_option_if(rhs_info.interleave, "-DRHS_INTERLEAVE");
- build_opts.add_option_if(lhs_info.transpose, "-DLHS_TRANSPOSE");
- build_opts.add_option_if(_use_dummy_work_items, "-DDUMMY_WORK_ITEMS");
- build_opts.add_option_if(gemm_info.activation_info.enabled(), "-DACTIVATION_TYPE=" + lower_string(string_from_activation_func(gemm_info.activation_info.activation())));
- build_opts.add_option_if(gemm_info.activation_info.enabled(), "-DA_VAL=" + float_to_string_with_full_precision(gemm_info.activation_info.a()));
- build_opts.add_option_if(gemm_info.activation_info.enabled(), "-DB_VAL=" + float_to_string_with_full_precision(gemm_info.activation_info.b()));
- build_opts.add_option_if(enable_mixed_precision, "-DMIXED_PRECISION");
- build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(data_type));
- build_opts.add_option("-DDATA_TYPE_ACCUMULATOR=" + (enable_mixed_precision ? get_cl_type_from_data_type(DataType::F32) : get_cl_type_from_data_type(data_type)));
- build_opts.add_option("-DM=" + support::cpp11::to_string(gemm_info.m));
- build_opts.add_option("-DN=" + support::cpp11::to_string(gemm_info.n));
- build_opts.add_option("-DM0=" + support::cpp11::to_string(lhs_info.m0));
- build_opts.add_option("-DN0=" + support::cpp11::to_string(rhs_info.n0));
- build_opts.add_option("-DK0=" + support::cpp11::to_string(lhs_info.k0));
- build_opts.add_option("-DV0=" + support::cpp11::to_string(lhs_info.v0));
- build_opts.add_option("-DH0=" + support::cpp11::to_string(rhs_info.h0));
-
- std::string kernel_name("gemm_mm_reshaped_");
- kernel_name += lhs_info.transpose ? "lhs_t_" : "lhs_nt_";
- kernel_name += rhs_info.transpose ? "rhs_t" : "rhs_nt";
-
- // Create kernel
- _kernel = create_kernel(compile_context, kernel_name, build_opts.options());
-
- // Set config_id for enabling LWS tuning
- _config_id = kernel_name;
- _config_id += "_";
- _config_id += (_add_bias ? "add_bias_" : "");
- _config_id += (_broadcast_bias ? "broadcast_bias_" : "");
- _config_id += (_reinterpret_output_as_3d ? "3do_" : "");
- _config_id += (gemm_info.activation_info.enabled() ? "fused_activation_" : "");
- _config_id += lower_string(string_from_data_type(input0->info()->data_type()));
- _config_id += "_";
- _config_id += (enable_mixed_precision ? "mixed_precision_" : "");
- _config_id += support::cpp11::to_string(output->info()->dimension(1));
- _config_id += "_";
- _config_id += support::cpp11::to_string(output->info()->dimension(0));
- _config_id += "_";
- _config_id += support::cpp11::to_string(gemm_info.k);
- _config_id += "_";
- _config_id += support::cpp11::to_string(output->info()->dimension(2));
- _config_id += "_";
- _config_id += support::cpp11::to_string(lhs_info.m0);
- _config_id += "_";
- _config_id += support::cpp11::to_string(rhs_info.n0);
- _config_id += "_";
- _config_id += support::cpp11::to_string(lhs_info.k0);
- _config_id += "_";
- _config_id += support::cpp11::to_string(lhs_info.v0);
- _config_id += "_";
- _config_id += support::cpp11::to_string(rhs_info.h0);
- _config_id += "_";
- _config_id += support::cpp11::to_string(lhs_info.interleave);
- _config_id += "_";
- _config_id += support::cpp11::to_string(rhs_info.interleave);
-}
-
-Status CLGEMMMatrixMultiplyReshapedKernel::validate(const ITensorInfo *input0, const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, float alpha, float beta,
- const GEMMLHSMatrixInfo &lhs_info,
- const GEMMRHSMatrixInfo &rhs_info, const GEMMKernelInfo &gemm_info)
-{
- ElementsProcessed num_elements_processed{};
- ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input0, input1, input2, output, alpha, beta, lhs_info, rhs_info, gemm_info));
- ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input0->clone().get(),
- input1->clone().get(),
- input2 != nullptr ? input2->clone().get() : nullptr,
- output->clone().get(),
- lhs_info,
- rhs_info,
- gemm_info,
- num_elements_processed)
- .first);
-
- return Status{};
-}
-
-void CLGEMMMatrixMultiplyReshapedKernel::run(const Window &window, cl::CommandQueue &queue)
-{
- ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
- ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICLKernel::window(), window);
-
- if(_input1->info()->num_dimensions() < 3)
- {
- // The stride_z for matrix B must be zero if we do not slice
- ARM_COMPUTE_ERROR_ON(_input1->info()->strides_in_bytes()[3] != 0);
- }
-
- Window slice = window.first_slice_window_3D();
- Window slice_matrix_b = slice;
-
- slice_matrix_b.set(Window::DimX, Window::Dimension(0, 1, 1));
- slice_matrix_b.set(Window::DimY, Window::Dimension(0, 1, 1));
-
- if(_reinterpret_output_as_3d)
- {
- // Pass bottom paddings to the kernel if the output has to be reinterpreted as 3D tensor
- unsigned int idx0;
- if(_add_bias)
- {
- idx0 = 4 * num_arguments_per_2D_tensor() + 5;
- }
- else
- {
- idx0 = 3 * num_arguments_per_2D_tensor() + 4;
- }
- const unsigned int total_cross_plane_pad = _output->info()->padding().top + _output->info()->padding().bottom;
- _kernel.setArg<cl_uint>(idx0, static_cast<unsigned int>(total_cross_plane_pad));
- }
-
- do
- {
- Window slice_b = slice;
- // Don't slice matrix B along the z dimension if matrix B has just 2 dimensions and matrix A more than 2
- // This scenario can happen when the matrix multiplication is used to perform a convolution operation
- if(!_slide_matrix_b)
- {
- slice_b = slice_matrix_b;
- }
-
- unsigned int idx = 0;
- add_2D_tensor_argument(idx, _input0, slice);
- add_2D_tensor_argument(idx, _input1, slice_b);
- add_2D_tensor_argument_if((_add_bias), idx, _input2, slice);
- add_2D_tensor_argument(idx, _output, slice);
- _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(_k));
- _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(_input0->info()->strides_in_bytes()[2]));
- _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(_input1->info()->strides_in_bytes()[2]));
- if(_add_bias)
- {
- _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(_input2->info()->strides_in_bytes()[2]));
- }
- _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(_output->info()->strides_in_bytes()[2]));
- enqueue(queue, *this, slice, lws_hint(), _use_dummy_work_items);
- }
- while(window.slide_window_slice_3D(slice));
-}