| /* |
| * Copyright (c) 2022 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/runtime/heuristics/direct_conv/ClDirectConvDefaultConfigValhall.h" |
| |
| #include "arm_compute/core/CL/CLHelpers.h" |
| #include "arm_compute/core/CL/CLKernelLibrary.h" |
| #include "arm_compute/core/GPUTarget.h" |
| #include "arm_compute/core/TensorInfo.h" |
| #include "arm_compute/core/TensorShape.h" |
| #include "arm_compute/core/utils/misc/ShapeCalculator.h" |
| |
| #include <utility> |
| |
| namespace arm_compute |
| { |
| namespace cl_direct_conv |
| { |
| using namespace arm_compute::misc::shape_calculator; |
| |
| ClDirectConvDefaultConfigValhall::ClDirectConvDefaultConfigValhall(GPUTarget gpu) : IClDirectConvKernelConfig(gpu) |
| { |
| } |
| |
| DirectConvComputeKernelInfo ClDirectConvDefaultConfigValhall::configure(const ITensorInfo *src, |
| const ITensorInfo *wei, |
| const PadStrideInfo &conv_info) |
| { |
| using ConfigurationFunctionExecutorPtr = DirectConvComputeKernelInfo (ClDirectConvDefaultConfigValhall::*)( |
| const ITensorInfo *src, const ITensorInfo *wei, const PadStrideInfo &conv_info); |
| |
| ClDirectConvConfigArray<ConfigurationFunctionExecutorPtr> configs_G78( |
| &ClDirectConvDefaultConfigValhall::configure_G78_f32, &ClDirectConvDefaultConfigValhall::configure_G78_f16, |
| &ClDirectConvDefaultConfigValhall::configure_G78_u8); |
| |
| ClDirectConvConfigArray<ConfigurationFunctionExecutorPtr> configs_G57( |
| &ClDirectConvDefaultConfigValhall::configure_G57_f32, &ClDirectConvDefaultConfigValhall::configure_G57_f16, |
| &ClDirectConvDefaultConfigValhall::configure_G78_u8); |
| |
| ConfigurationFunctionExecutorPtr func = nullptr; |
| switch (_target) |
| { |
| case GPUTarget::G57: |
| func = configs_G57.get_function(src->data_type()); |
| break; |
| case GPUTarget::G78: |
| default: |
| func = configs_G78.get_function(src->data_type()); |
| break; |
| } |
| |
| ARM_COMPUTE_ERROR_ON_MSG(func == nullptr, "Data type not supported for direct convolution"); |
| return (this->*func)(src, wei, conv_info); |
| } |
| |
| DirectConvComputeKernelInfo ClDirectConvDefaultConfigValhall::configure_G78_f32(const ITensorInfo *src, |
| const ITensorInfo *wei, |
| const PadStrideInfo &conv_info) |
| { |
| DirectConvComputeKernelInfo desc; |
| |
| if (src->data_layout() == DataLayout::NHWC) |
| { |
| // Get the output shape |
| const TensorShape wei_shape = wei->tensor_shape(); |
| const TensorShape dst_shape = misc::shape_calculator::compute_deep_convolution_shape(*src, *wei, conv_info); |
| const bool export_weights_to_cl_image = export_to_cl_image(wei); |
| |
| const int32_t ofm = dst_shape[0]; |
| const int32_t m = dst_shape[1] * dst_shape[2]; |
| const bool is_pointwise = (wei_shape[1] == wei_shape[2]) && wei_shape[1] == 1; |
| |
| desc.export_weights_to_cl_image = export_weights_to_cl_image; |
| |
| if (dst_shape[0] <= 4) |
| { |
| if (is_pointwise) |
| { |
| if (ofm == 4) |
| { |
| desc.m0 = 1; |
| desc.n0 = 4; |
| desc.k0 = 16; |
| } |
| else |
| { |
| desc.m0 = 1; |
| desc.n0 = 1; |
| desc.k0 = 16; |
| } |
| } |
| else |
| { |
| desc.m0 = 1; |
| desc.n0 = 2; |
| desc.k0 = 16; |
| } |
| } |
| else |
| { |
| if (m < 64) |
| { |
| desc.m0 = 1; |
| desc.n0 = 1; |
| desc.k0 = 16; |
| } |
| else |
| { |
| desc.m0 = 4; |
| desc.n0 = 4; |
| desc.k0 = 4; |
| } |
| } |
| } |
| |
| return desc; |
| } |
| |
| DirectConvComputeKernelInfo ClDirectConvDefaultConfigValhall::configure_G78_f16(const ITensorInfo *src, |
| const ITensorInfo *wei, |
| const PadStrideInfo &conv_info) |
| { |
| DirectConvComputeKernelInfo desc; |
| |
| if (src->data_layout() == DataLayout::NHWC) |
| { |
| // Get the output shape |
| const TensorShape wei_shape = wei->tensor_shape(); |
| const TensorShape dst_shape = misc::shape_calculator::compute_deep_convolution_shape(*src, *wei, conv_info); |
| const bool export_weights_to_cl_image = export_to_cl_image(wei); |
| |
| const int32_t ofm = dst_shape[0]; |
| const int32_t m = dst_shape[1] * dst_shape[2]; |
| const int32_t k = wei_shape[0]; |
| const bool is_pointwise = (wei_shape[1] == wei_shape[2]) && wei_shape[1] == 1; |
| |
| desc.export_weights_to_cl_image = export_weights_to_cl_image; |
| |
| if (dst_shape[0] <= 4) |
| { |
| // k0 should be as larger as possible. However, we should avoid |
| // having left-over for loops that make the implementation slower. |
| if ((k % 16) == 0) |
| { |
| desc.k0 = 16; |
| } |
| else if ((k % 8) == 0) |
| { |
| desc.k0 = 8; |
| } |
| else |
| { |
| desc.k0 = 4; |
| } |
| |
| if (is_pointwise) |
| { |
| if (ofm == 4) |
| { |
| desc.m0 = 1; |
| desc.n0 = 4; |
| } |
| else |
| { |
| desc.m0 = 1; |
| desc.n0 = 1; |
| } |
| } |
| else |
| { |
| desc.m0 = 1; |
| desc.n0 = dst_shape[0]; |
| } |
| } |
| else |
| { |
| if (m < 64) |
| { |
| desc.m0 = 1; |
| desc.n0 = 1; |
| if ((k % 16) == 0) |
| { |
| desc.k0 = 16; |
| } |
| else if ((k % 8) == 0) |
| { |
| desc.k0 = 8; |
| } |
| else |
| { |
| desc.k0 = 4; |
| } |
| } |
| else |
| { |
| if (ofm >= 16) |
| { |
| if (m / 6 > 24000) |
| { |
| desc.m0 = 6; |
| } |
| else |
| { |
| desc.m0 = 5; |
| } |
| desc.n0 = 8; |
| desc.k0 = 4; |
| } |
| else |
| { |
| desc.m0 = 2; |
| desc.n0 = 8; |
| if ((k % 16) == 0) |
| { |
| desc.k0 = 16; |
| } |
| else if ((k % 8) == 0) |
| { |
| desc.k0 = 8; |
| } |
| else |
| { |
| desc.k0 = 4; |
| } |
| } |
| } |
| } |
| } |
| |
| return desc; |
| } |
| |
| DirectConvComputeKernelInfo ClDirectConvDefaultConfigValhall::configure_G78_u8(const ITensorInfo *src, |
| const ITensorInfo *wei, |
| const PadStrideInfo &conv_info) |
| { |
| DirectConvComputeKernelInfo desc; |
| |
| if (src->data_layout() == DataLayout::NHWC) |
| { |
| // Get the output shape |
| TensorShape output_shape = misc::shape_calculator::compute_deep_convolution_shape(*src, *wei, conv_info); |
| |
| desc.n0 = 4; |
| |
| if (output_shape[0] > 16) |
| { |
| desc.m0 = 4; |
| } |
| |
| desc.k0 = 16; |
| |
| desc.export_weights_to_cl_image = false; |
| } |
| |
| return desc; |
| } |
| |
| DirectConvComputeKernelInfo ClDirectConvDefaultConfigValhall::configure_G57_f32(const ITensorInfo *src, |
| const ITensorInfo *wei, |
| const PadStrideInfo &conv_info) |
| { |
| DirectConvComputeKernelInfo desc; |
| |
| if (src->data_layout() == DataLayout::NHWC) |
| { |
| // Get the output shape |
| const TensorShape wei_shape = wei->tensor_shape(); |
| const TensorShape dst_shape = misc::shape_calculator::compute_deep_convolution_shape(*src, *wei, conv_info); |
| const bool export_weights_to_cl_image = export_to_cl_image(wei); |
| |
| const int32_t m = dst_shape[1] * dst_shape[2]; |
| const bool is_pointwise = (wei_shape[1] == wei_shape[2]) && wei_shape[1] == 1; |
| |
| desc.export_weights_to_cl_image = export_weights_to_cl_image; |
| |
| if (dst_shape[0] <= 4) |
| { |
| if (is_pointwise) |
| { |
| desc.m0 = 1; |
| desc.n0 = 1; |
| desc.k0 = 16; |
| } |
| else |
| { |
| desc.m0 = 1; |
| desc.n0 = dst_shape[0]; |
| desc.k0 = 16; |
| } |
| } |
| else |
| { |
| if (m < 64) |
| { |
| if (m == 1) |
| { |
| desc.m0 = 1; |
| desc.n0 = 1; |
| desc.k0 = 16; |
| } |
| else |
| { |
| desc.m0 = 4; |
| desc.n0 = 2; |
| desc.k0 = 8; |
| } |
| } |
| else |
| { |
| desc.m0 = 4; |
| desc.n0 = 4; |
| desc.k0 = 4; |
| } |
| } |
| } |
| |
| return desc; |
| } |
| |
| DirectConvComputeKernelInfo ClDirectConvDefaultConfigValhall::configure_G57_f16(const ITensorInfo *src, |
| const ITensorInfo *wei, |
| const PadStrideInfo &conv_info) |
| { |
| DirectConvComputeKernelInfo desc; |
| |
| if (src->data_layout() == DataLayout::NHWC) |
| { |
| // Get the output shape |
| const TensorShape wei_shape = wei->tensor_shape(); |
| const TensorShape dst_shape = misc::shape_calculator::compute_deep_convolution_shape(*src, *wei, conv_info); |
| const bool export_weights_to_cl_image = export_to_cl_image(wei); |
| |
| const int32_t ofm = dst_shape[0]; |
| const int32_t m = dst_shape[1] * dst_shape[2]; |
| const bool is_pointwise = (wei_shape[1] == wei_shape[2]) && wei_shape[1] == 1; |
| |
| desc.export_weights_to_cl_image = export_weights_to_cl_image; |
| |
| if (dst_shape[0] <= 4) |
| { |
| if (is_pointwise) |
| { |
| desc.m0 = 2; |
| desc.n0 = 1; |
| desc.k0 = 16; |
| } |
| else |
| { |
| desc.m0 = 1; |
| desc.n0 = dst_shape[0]; |
| desc.k0 = 16; |
| } |
| } |
| else |
| { |
| if (m < 64) |
| { |
| if (m == 1) |
| { |
| desc.m0 = 1; |
| desc.n0 = 1; |
| desc.k0 = 16; |
| } |
| else |
| { |
| desc.m0 = 4; |
| desc.n0 = 2; |
| desc.k0 = 8; |
| } |
| } |
| else |
| { |
| if (ofm > 16) |
| { |
| desc.m0 = 4; |
| desc.n0 = 8; |
| desc.k0 = 8; |
| } |
| else |
| { |
| desc.m0 = 8; |
| desc.n0 = 4; |
| desc.k0 = 4; |
| } |
| } |
| } |
| } |
| |
| return desc; |
| } |
| } // namespace cl_direct_conv |
| } // namespace arm_compute |