/* * Copyright (c) 2023-2024 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/dynamic_fusion/sketch/gpu/components/cl/ClComponentMatMul.h" #include "arm_compute/core/utils/misc/ShapeCalculator.h" #include "arm_compute/core/Validate.h" #include "arm_compute/dynamic_fusion/sketch/attributes/MatMulAttributes.h" #include "src/core/CL/CLValidate.h" #include "src/dynamic_fusion/sketch/gpu/ckw_driver/components/GpuCkwMatMul.h" #include "src/gpu/cl/kernels/helpers/MatMulKernelHelpers.h" namespace arm_compute { namespace experimental { namespace dynamic_fusion { namespace { using Attributes = MatMulAttributes; using Settings = GpuMatMulSettings; Status validate_matmul_kernel_info(Attributes attributes, Settings settings) { const bool adj_lhs = attributes.adj_lhs(); const bool adj_rhs = attributes.adj_rhs(); const int m0 = settings.m0(); const int n0 = settings.n0(); const int k0 = settings.k0(); // Validate M0 ARM_COMPUTE_RETURN_ERROR_ON_MSG(m0 < 1, "Only positive integers are supported for M0"); if (adj_lhs) { ARM_COMPUTE_RETURN_ERROR_ON_MSG(((m0 & (m0 - 1)) && (m0 != 3)) || (m0 > 16), "Only 1,2,3,4,8,16 are supported for M0 for Lhs transposed"); } // Validate N0 ARM_COMPUTE_RETURN_ERROR_ON_MSG(n0 < 1, "Only positive integers are supported for N0"); ARM_COMPUTE_RETURN_ERROR_ON_MSG(((n0 & (n0 - 1)) && (n0 != 3)) || (n0 > 16), "Only 1,2,3,4,8,16 are supported for N0"); // Validate K0 ARM_COMPUTE_RETURN_ERROR_ON_MSG(k0 < 1, "Only positive integers are supported for K0"); if (!adj_lhs || adj_rhs) { ARM_COMPUTE_RETURN_ERROR_ON_MSG(((k0 & (k0 - 1)) && (k0 != 3)) || (k0 > 16), "Only 1,2,3,4,8,16 are supported for K0"); } return Status{}; } } // namespace Status ClComponentMatMul::validate(const Properties &properties, const ArgumentPack &tensors, const Attributes &attributes, const Settings &settings) { ARM_COMPUTE_UNUSED(properties); ARM_COMPUTE_UNUSED(attributes); const auto lhs = tensors.get_const_tensor(TensorType::ACL_SRC_0); const auto rhs = tensors.get_const_tensor(TensorType::ACL_SRC_1); const auto dst = tensors.get_const_tensor(TensorType::ACL_DST_0); // Currently, the only supported case is when adj_lhs = false and adj_rhs = true ARM_COMPUTE_RETURN_ERROR_ON((attributes.adj_lhs() != false) && (attributes.adj_rhs() != true)); // Check if Matching data type ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(lhs, rhs); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(lhs, dst); // Data type ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(lhs, 1, DataType::F16, DataType::F32); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(lhs, dst); // All tensor infos are initialized ARM_COMPUTE_RETURN_ERROR_ON(lhs->tensor_shape().total_size() == 0); ARM_COMPUTE_RETURN_ERROR_ON(rhs->tensor_shape().total_size() == 0); ARM_COMPUTE_RETURN_ERROR_ON(dst->tensor_shape().total_size() == 0); // Device requirements are met ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(lhs); // Check if block sizes are supported MatMulKernelInfo matmul_kernel_info = MatMulKernelInfo(attributes.adj_lhs(), attributes.adj_rhs(), settings.m0(), settings.n0(), settings.k0()); ARM_COMPUTE_RETURN_ON_ERROR(validate_matmul_kernel_info(attributes, settings)); ARM_COMPUTE_RETURN_ON_ERROR( opencl::kernels::validate_matmul_input_shapes(lhs->tensor_shape(), rhs->tensor_shape(), matmul_kernel_info)); // Check if dst shape is correct const auto expected_dst_shape = misc::shape_calculator::compute_matmul_shape(lhs->tensor_shape(), rhs->tensor_shape(), matmul_kernel_info); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(dst->tensor_shape(), expected_dst_shape); return Status{}; } ClComponentMatMul::ClComponentMatMul(ComponentId id, const Properties &properties, const ArgumentPack &tensors, const Attributes &attributes, const Settings &settings) : IGpuKernelComponent{id, properties, tensors}, _component_writer{std::make_unique(id, tensors, attributes, settings)} { } ClComponentMatMul::~ClComponentMatMul() { } const IGpuCkwComponentDriver *ClComponentMatMul::ckw_component_driver() const { return _component_writer.get(); } } // namespace dynamic_fusion } // namespace experimental } // namespace arm_compute