| /* |
| * Copyright (c) 2023 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/ClMatMulLowpNativeKernel.h" |
| |
| #include "arm_compute/core/utils/ActivationFunctionUtils.h" |
| #include "arm_compute/core/CL/CLHelpers.h" |
| #include "arm_compute/core/CL/ICLTensor.h" |
| #include "arm_compute/core/ITensorPack.h" |
| #include "arm_compute/core/TensorInfo.h" |
| #include "arm_compute/core/utils/helpers/AdjustVecSize.h" |
| #include "arm_compute/core/utils/misc/ShapeCalculator.h" |
| #include "arm_compute/core/utils/quantization/AsymmHelpers.h" |
| #include "arm_compute/core/utils/StringUtils.h" |
| |
| #include "src/common/utils/Log.h" |
| #include "src/core/helpers/AutoConfiguration.h" |
| #include "src/core/helpers/WindowHelpers.h" |
| #include "src/gpu/cl/ClCompileContext.h" |
| |
| #include "arm_compute/core/QuantizationInfo.h" |
| |
| #include "support/Cast.h" |
| #include "support/StringSupport.h" |
| |
| namespace arm_compute |
| { |
| namespace opencl |
| { |
| namespace kernels |
| { |
| namespace |
| { |
| Status validate_matmul_kernel_info(const MatMulKernelInfo &matmul_kernel_info) |
| { |
| const bool adj_lhs = matmul_kernel_info.adj_lhs; |
| const bool adj_rhs = matmul_kernel_info.adj_rhs; |
| const int m0 = matmul_kernel_info.m0; |
| const int n0 = matmul_kernel_info.n0; |
| const int k0 = matmul_kernel_info.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{}; |
| } |
| |
| Status validate_input_shapes(const TensorShape &lhs_shape, const TensorShape &rhs_shape, const MatMulKernelInfo &matmul_kernel_info) |
| { |
| const size_t lhs_k = matmul_kernel_info.adj_lhs ? lhs_shape.y() : lhs_shape.x(); |
| const size_t rhs_k = matmul_kernel_info.adj_rhs ? rhs_shape.x() : rhs_shape.y(); |
| |
| ARM_COMPUTE_RETURN_ERROR_ON_MSG(lhs_k != rhs_k, "K dimension in Lhs and Rhs matrices must match."); |
| ARM_COMPUTE_RETURN_ERROR_ON_MSG(lhs_shape.total_size() == 0, "Lhs tensor can't be empty"); |
| ARM_COMPUTE_RETURN_ERROR_ON_MSG(rhs_shape.total_size() == 0, "Rhs tensor can't be empty"); |
| |
| constexpr size_t batch_dim_start = 2; |
| for(size_t i = batch_dim_start; i < Coordinates::num_max_dimensions; ++i) |
| { |
| ARM_COMPUTE_RETURN_ERROR_ON_MSG(lhs_shape[i] != rhs_shape[i], "Batch dimension broadcasting is not supported"); |
| } |
| |
| return Status{}; |
| } |
| } |
| ClMatMulLowpNativeKernel::ClMatMulLowpNativeKernel() |
| { |
| _type = CLKernelType::GEMM; |
| } |
| Status ClMatMulLowpNativeKernel::validate(const ITensorInfo *lhs, const ITensorInfo *rhs, const ITensorInfo *bias, const ITensorInfo *dst, const MatMulKernelInfo &matmul_kernel_info, |
| const ActivationLayerInfo &act_info) |
| { |
| ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(lhs, rhs, dst); |
| ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(lhs, 1, DataType::QASYMM8, DataType::QASYMM8_SIGNED); |
| ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(lhs, rhs); |
| ARM_COMPUTE_RETURN_ON_ERROR(validate_matmul_kernel_info(matmul_kernel_info)); |
| ARM_COMPUTE_RETURN_ON_ERROR(validate_input_shapes(lhs->tensor_shape(), rhs->tensor_shape(), matmul_kernel_info)); |
| |
| ARM_COMPUTE_RETURN_ERROR_ON_MSG((act_info.activation() != ActivationFunction::IDENTITY && act_info.activation() != ActivationFunction::RELU |
| && act_info.activation() != ActivationFunction::LU_BOUNDED_RELU && act_info.activation() != ActivationFunction::BOUNDED_RELU), |
| "Activation Function specified is unsupported."); |
| const TensorShape expected_output_shape = misc::shape_calculator::compute_matmul_shape(lhs->tensor_shape(), rhs->tensor_shape(), matmul_kernel_info); |
| |
| if(dst->total_size() != 0) |
| { |
| const TensorInfo tensor_info_output = dst->clone()->set_tensor_shape(expected_output_shape); |
| ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(dst, &tensor_info_output); |
| ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(lhs, dst); |
| } |
| |
| if(bias != nullptr) |
| { |
| ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(bias, 1, DataType::S32); |
| ARM_COMPUTE_RETURN_ERROR_ON(bias->num_dimensions() > 1); |
| ARM_COMPUTE_RETURN_ERROR_ON(expected_output_shape[0] != bias->dimension(0)); |
| } |
| |
| return Status{}; |
| } |
| void ClMatMulLowpNativeKernel::configure(const ClCompileContext &compile_context, ITensorInfo *lhs, ITensorInfo *rhs, ITensorInfo *bias, ITensorInfo *dst, const MatMulKernelInfo &matmul_kernel_info, |
| const ActivationLayerInfo &act_info) |
| { |
| ARM_COMPUTE_ERROR_ON_NULLPTR(lhs, rhs, dst, &compile_context, &matmul_kernel_info); |
| ARM_COMPUTE_LOG_PARAMS(lhs, rhs, bias, dst, matmul_kernel_info); |
| ARM_COMPUTE_ERROR_THROW_ON(validate(lhs, rhs, bias, dst, matmul_kernel_info)); |
| |
| // dst tensor auto initialization if not yet initialized |
| auto_init_if_empty(*dst, lhs->clone()->set_tensor_shape(misc::shape_calculator::compute_matmul_shape(lhs->tensor_shape(), rhs->tensor_shape(), matmul_kernel_info))); |
| |
| const int m = dst->dimension(1); |
| const int n = dst->dimension(0); |
| const int k = matmul_kernel_info.adj_lhs ? lhs->tensor_shape().y() : lhs->tensor_shape().x(); |
| const bool adj_lhs = matmul_kernel_info.adj_lhs; |
| |
| int m0 = adj_lhs ? adjust_vec_size(matmul_kernel_info.m0, m) : std::min(matmul_kernel_info.m0, m); |
| int n0 = adjust_vec_size(matmul_kernel_info.n0, n); |
| |
| // Configure kernel window |
| Window win = calculate_max_window(*dst, Steps(n0, m0)); |
| win = win.collapse(win, Window::DimZ); |
| IClKernel::configure_internal(win); |
| |
| // Calculate partial (store instead of load) M0 and partial N0 for the partial blocks at the end of a row/column if any. This is to avoid padding. |
| const unsigned int partial_store_m0 = m % m0; |
| const unsigned int partial_store_n0 = n % n0; |
| |
| CLBuildOptions build_opts; |
| build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(lhs->data_type())); |
| build_opts.add_option("-DM0=" + support::cpp11::to_string(m0)); |
| build_opts.add_option("-DN0=" + support::cpp11::to_string(n0)); |
| build_opts.add_option("-DK0=" + support::cpp11::to_string(matmul_kernel_info.k0)); |
| build_opts.add_option("-DPARTIAL_STORE_M0=" + support::cpp11::to_string(partial_store_m0)); |
| build_opts.add_option("-DPARTIAL_STORE_N0=" + support::cpp11::to_string(partial_store_n0)); |
| build_opts.add_option("-DK=" + support::cpp11::to_string(k)); |
| |
| const UniformQuantizationInfo lqinfo = lhs->quantization_info().uniform(); |
| const UniformQuantizationInfo rqinfo = rhs->quantization_info().uniform(); |
| const UniformQuantizationInfo dqinfo = dst->quantization_info().uniform(); |
| |
| float multiplier = lqinfo.scale * rqinfo.scale / dqinfo.scale; |
| int output_multiplier = 0; |
| int output_shift = 0; |
| arm_compute::quantization::calculate_quantized_multiplier(multiplier, &output_multiplier, &output_shift); |
| |
| build_opts.add_option("-DDST_MULTIPLIER=" + support::cpp11::to_string(output_multiplier)); |
| build_opts.add_option("-DDST_SHIFT=" + support::cpp11::to_string(output_shift)); |
| |
| // Note : Offset is not negated, unlike gemmlowp kernels |
| build_opts.add_option("-DLHS_OFFSET=" + support::cpp11::to_string(lqinfo.offset)); |
| build_opts.add_option("-DRHS_OFFSET=" + support::cpp11::to_string(rqinfo.offset)); |
| build_opts.add_option("-DDST_OFFSET=" + support::cpp11::to_string(dqinfo.offset)); |
| build_opts.add_option_if(bias != nullptr, "-DBIAS"); |
| |
| // Floating point boundaries are quantized prior to being passed as arguments. |
| // Note: We expect the input and output tensors to always adopt a per-tensor quantization approach |
| int a_val{}; |
| int b_val{}; |
| std::tie(b_val, a_val) = get_quantized_activation_min_max(act_info, dst->data_type(), dqinfo); |
| |
| build_opts.add_option("-DA_VAL=" + support::cpp11::to_string(a_val)); |
| build_opts.add_option("-DB_VAL=" + support::cpp11::to_string(b_val)); |
| build_opts.add_option("-DACTIVATION_TYPE=" + lower_string(string_from_activation_func(act_info.activation()))); |
| build_opts.add_option("-DZERO_POINT=" + support::cpp11::to_string(dqinfo.offset)); |
| |
| std::string kernel_name("mat_mul_native_quantized"); |
| kernel_name += matmul_kernel_info.adj_lhs ? "_t" : "_nt"; |
| kernel_name += matmul_kernel_info.adj_rhs ? "_t" : "_nt"; |
| |
| // A macro guard to compile ONLY the kernel of interest |
| build_opts.add_option("-D" + upper_string(kernel_name)); |
| |
| // Create kernel |
| _kernel = create_kernel(compile_context, kernel_name, build_opts.options()); |
| |
| // Set config_id for enabling LWS tuning |
| const size_t number_of_batches = dst->tensor_shape().total_size() / (m * n); |
| |
| _config_id = kernel_name; |
| _config_id += "_"; |
| _config_id += lower_string(string_from_data_type(lhs->data_type())); |
| _config_id += "_"; |
| _config_id += support::cpp11::to_string(m); |
| _config_id += "_"; |
| _config_id += support::cpp11::to_string(n); |
| _config_id += "_"; |
| _config_id += support::cpp11::to_string(k); |
| _config_id += "_"; |
| _config_id += support::cpp11::to_string(number_of_batches); |
| _config_id += "_"; |
| _config_id += support::cpp11::to_string(m0); |
| _config_id += "_"; |
| _config_id += support::cpp11::to_string(n0); |
| _config_id += "_"; |
| _config_id += support::cpp11::to_string(matmul_kernel_info.k0); |
| } |
| |
| void ClMatMulLowpNativeKernel::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 ICLTensor *lhs = utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_SRC_0)); |
| const ICLTensor *rhs = utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_SRC_1)); |
| const ICLTensor *bias = utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_SRC_2)); |
| ICLTensor *dst = utils::cast::polymorphic_downcast<ICLTensor *>(tensors.get_tensor(TensorType::ACL_DST)); |
| ARM_COMPUTE_ERROR_ON_NULLPTR(lhs, rhs, dst); |
| ARM_COMPUTE_LOG_PARAMS(lhs, rhs, bias, dst); |
| |
| unsigned int idx = 0; |
| Window window_collapsed = window.collapse(ICLKernel::window(), Window::DimZ); |
| |
| add_3d_tensor_nhw_argument(idx, lhs); |
| add_3d_tensor_nhw_argument(idx, rhs); |
| if(bias != nullptr) |
| { |
| add_3d_tensor_nhw_argument(idx, bias); |
| } |
| add_3d_tensor_nhw_argument(idx, dst); |
| |
| enqueue(queue, *this, window_collapsed, lws_hint()); |
| } |
| |
| } // namespace kernels |
| } // namespace opencl |
| } // namespace arm_compute |