Move CPU/GPU files from Core/Runtime to the respective backend folders
Legacy structure contained two libraries core/runtime with two backends
in each.
We reduce the core/runtime libraries to a single library thus merging
the backend files
Signed-off-by: Georgios Pinitas <georgios.pinitas@arm.com>
Change-Id: I69545765fe7a730368105cdbd067d3135ec7a174
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/6155
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/src/gpu/cl/kernels/ClGemmLowpReductionKernel.cpp b/src/gpu/cl/kernels/ClGemmLowpReductionKernel.cpp
new file mode 100644
index 0000000..7f6f573
--- /dev/null
+++ b/src/gpu/cl/kernels/ClGemmLowpReductionKernel.cpp
@@ -0,0 +1,219 @@
+/*
+ * Copyright (c) 2017-2021 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 "src/gpu/cl/kernels/ClGemmLowpReductionKernel.h"
+
+#include "arm_compute/core/CL/CLHelpers.h"
+#include "arm_compute/core/CL/ICLTensor.h"
+#include "arm_compute/core/KernelDescriptors.h"
+
+#include "src/core/helpers/AutoConfiguration.h"
+#include "src/core/helpers/WindowHelpers.h"
+
+#include "support/Cast.h"
+#include "support/StringSupport.h"
+
+namespace arm_compute
+{
+namespace opencl
+{
+namespace kernels
+{
+namespace
+{
+Status validate_arguments_matrix_a_reduction(const ITensorInfo *src, const ITensorInfo *dst)
+{
+ ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(src, dst);
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(src, 1, DataType::QASYMM8, DataType::QASYMM8_SIGNED, DataType::QSYMM8);
+
+ if(dst->total_size() > 0)
+ {
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(dst, 1, DataType::S32);
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG(dst->dimension(0) != src->dimension(1), "Output vector must have length equal to the number of rows of the input matrix");
+ }
+ return Status{};
+}
+
+Status validate_arguments_matrix_b_reduction(const ITensorInfo *src, const ITensorInfo *dst)
+{
+ ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(src, dst);
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(src, 1, DataType::QASYMM8, DataType::QASYMM8_SIGNED, DataType::QSYMM8, DataType::QSYMM8_PER_CHANNEL);
+
+ if(dst->total_size() > 0)
+ {
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(dst, 1, DataType::S32);
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG(dst->dimension(0) != src->dimension(0), "Output vector must have length equal to the number of columns of the input matrix");
+ }
+ return Status{};
+}
+} // namespace
+
+IClGemmLowpReductionKernel::IClGemmLowpReductionKernel()
+{
+ _type = CLKernelType::ELEMENTWISE;
+}
+
+void ClGemmLowpMatrixAReductionKernel::configure(const CLCompileContext &compile_context, const ITensorInfo *mtx_a, ITensorInfo *vector_sum_row, const GEMMLowpReductionKernelInfo &info)
+{
+ // Perform validate step
+ ARM_COMPUTE_ERROR_ON_NULLPTR(mtx_a, vector_sum_row);
+ ARM_COMPUTE_ERROR_THROW_ON(validate_arguments_matrix_a_reduction(mtx_a, vector_sum_row));
+
+ // Output auto initialization if not yet initialized
+ auto_init_if_empty(*vector_sum_row, TensorShape(mtx_a->dimension(1)), 1, DataType::S32);
+
+ auto padding_info = get_padding_info({ mtx_a, vector_sum_row });
+
+ // Set the arguments to pass at compile time
+ CLBuildOptions build_opts;
+ build_opts.add_option("-DCOLS_A=" + support::cpp11::to_string(mtx_a->dimension(0)));
+ build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(mtx_a->data_type()));
+ build_opts.add_option("-DACC_DATA_TYPE=" + get_cl_dot8_acc_type_from_data_type(mtx_a->data_type()));
+ build_opts.add_option_if(info.mul_by_scalar, "-DSCALAR=" + support::cpp11::to_string(info.scalar));
+
+ const bool is_dot8_supported = dot8_supported(CLKernelLibrary::get().get_device());
+
+ std::string kernel_name = "gemmlowp_matrix_a_reduction" + std::string(is_dot8_supported ? "_dot8" : "");
+
+ // Create kernel
+ _kernel = create_kernel(compile_context, kernel_name, build_opts.options());
+
+ // Configure kernel window
+ // This kernel does not need padding
+ Window win = calculate_max_window(*vector_sum_row, Steps());
+ ICLKernel::configure_internal(win);
+
+ _config_id = kernel_name;
+ _config_id += "_";
+ _config_id += support::cpp11::to_string(mtx_a->dimension(0));
+ _config_id += "_";
+ _config_id += support::cpp11::to_string(mtx_a->dimension(1));
+ _config_id += "_";
+ _config_id += support::cpp11::to_string(mtx_a->dimension(2));
+
+ ARM_COMPUTE_ERROR_ON(has_padding_changed(padding_info));
+}
+
+Status ClGemmLowpMatrixAReductionKernel::validate(const ITensorInfo *mtx_a, const ITensorInfo *vector_sum_row, const GEMMLowpReductionKernelInfo &info)
+{
+ ARM_COMPUTE_UNUSED(info);
+ ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments_matrix_a_reduction(mtx_a, vector_sum_row));
+
+ return Status{};
+}
+
+void ClGemmLowpMatrixAReductionKernel::run_op(ITensorPack &tensors, const Window &window, cl::CommandQueue &queue)
+{
+ ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
+ ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICLKernel::window(), window);
+
+ const auto src = utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_SRC));
+ auto dst = utils::cast::polymorphic_downcast<ICLTensor *>(tensors.get_tensor(TensorType::ACL_DST));
+
+ Window collapsed = window.collapse_if_possible(ICLKernel::window(), Window::DimY);
+ Window slice_in = collapsed.first_slice_window_2D();
+ Window slice_out = collapsed.first_slice_window_2D();
+
+ // Setup input slice. Its dimensions are increased in the cl kernel.
+ slice_in.set(Window::DimX, Window::Dimension(0, 0, 0));
+ slice_in.set(Window::DimY, Window::Dimension(0, 0, 0));
+ slice_in.set(Window::DimZ, Window::Dimension(0, 0, 0));
+
+ do
+ {
+ unsigned int idx = 0;
+ add_3D_tensor_argument(idx, src, slice_in);
+ add_2D_tensor_argument(idx, dst, slice_out);
+ enqueue(queue, *this, slice_out, lws_hint());
+ }
+ while(collapsed.slide_window_slice_2D(slice_out));
+}
+
+void ClGemmLowpMatrixBReductionKernel::configure(const CLCompileContext &compile_context, const ITensorInfo *mtx_b, ITensorInfo *vector_sum_col, const GEMMLowpReductionKernelInfo &info)
+{
+ ARM_COMPUTE_ERROR_ON_NULLPTR(mtx_b, vector_sum_col);
+ ARM_COMPUTE_ERROR_THROW_ON(validate_arguments_matrix_b_reduction(mtx_b, vector_sum_col));
+
+ // Output auto initialization if not yet initialized
+ auto_init_if_empty(*vector_sum_col, TensorShape(mtx_b->dimension(0)), 1, DataType::S32);
+
+ auto padding_info = get_padding_info({ mtx_b, vector_sum_col });
+
+ const unsigned int num_elems_processed_per_iteration = adjust_vec_size(16, mtx_b->dimension(0));
+
+ // Set the arguments to pass at compile time
+ CLBuildOptions build_opts;
+ build_opts.add_option("-DVEC_SIZE=" + support::cpp11::to_string(num_elems_processed_per_iteration));
+ build_opts.add_option("-DVEC_SIZE_LEFTOVER=" + support::cpp11::to_string(mtx_b->dimension(0) % num_elems_processed_per_iteration));
+ build_opts.add_option("-DCOLS_B=" + support::cpp11::to_string(mtx_b->dimension(0)));
+ build_opts.add_option("-DROWS_B=" + support::cpp11::to_string(mtx_b->dimension(1)));
+ build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(mtx_b->data_type()));
+ build_opts.add_option("-DACC_DATA_TYPE=" + get_cl_dot8_acc_type_from_data_type(mtx_b->data_type()));
+ build_opts.add_option_if(info.mul_by_scalar, "-DSCALAR=" + support::cpp11::to_string(info.scalar));
+
+ // Create kernel
+ _kernel = create_kernel(compile_context, "gemmlowp_matrix_b_reduction", build_opts.options());
+
+ // Configure kernel window
+ Window win = calculate_max_window(*vector_sum_col, Steps(num_elems_processed_per_iteration));
+ IClKernel::configure_internal(win);
+
+ ARM_COMPUTE_ERROR_ON(has_padding_changed(padding_info));
+}
+
+Status ClGemmLowpMatrixBReductionKernel::validate(const ITensorInfo *mtx_b, const ITensorInfo *vector_sum_col, const GEMMLowpReductionKernelInfo &info)
+{
+ ARM_COMPUTE_UNUSED(info);
+ ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments_matrix_b_reduction(mtx_b, vector_sum_col));
+
+ return Status{};
+}
+
+void ClGemmLowpMatrixBReductionKernel::run_op(ITensorPack &tensors, const Window &window, cl::CommandQueue &queue)
+{
+ ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
+ ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICLKernel::window(), window);
+
+ const auto src = utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_SRC));
+ auto dst = utils::cast::polymorphic_downcast<ICLTensor *>(tensors.get_tensor(TensorType::ACL_DST));
+
+ Window collapsed = window.collapse_if_possible(IKernel::window(), Window::DimY);
+
+ Window slice_out = collapsed.first_slice_window_2D();
+ Window slice_in = slice_out;
+
+ slice_in.set(Window::DimY, Window::Dimension(0, 0, 0));
+ slice_in.set(Window::DimZ, Window::Dimension(0, 0, 0));
+
+ do
+ {
+ unsigned int idx = 0;
+ add_3D_tensor_argument(idx, src, slice_in);
+ add_2D_tensor_argument(idx, dst, slice_out);
+ enqueue(queue, *this, slice_out, lws_hint());
+ }
+ while(collapsed.slide_window_slice_2D(slice_out));
+}
+} // namespace kernels
+} // namespace opencl
+} // namespace arm_compute