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36.9 kB
| // Tencent is pleased to support the open source community by making ncnn available. | |
| // | |
| // Copyright (C) 2019 THL A29 Limited, a Tencent company. All rights reserved. | |
| // | |
| // Licensed under the BSD 3-Clause License (the "License"); you may not use this file except | |
| // in compliance with the License. You may obtain a copy of the License at | |
| // | |
| // https://opensource.org/licenses/BSD-3-Clause | |
| // | |
| // Unless required by applicable law or agreed to in writing, software distributed | |
| // under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR | |
| // CONDITIONS OF ANY KIND, either express or implied. See the License for the | |
| // specific language governing permissions and limitations under the License. | |
| namespace ncnn { | |
| InstanceNorm_vulkan::InstanceNorm_vulkan() | |
| { | |
| support_vulkan = true; | |
| support_image_storage = true; | |
| pipeline_instancenorm_reduce_sum4_fp16_to_fp32 = 0; | |
| pipeline_instancenorm_reduce_sum4_fp32[0] = 0; | |
| pipeline_instancenorm_reduce_sum4_fp32[1] = 0; | |
| pipeline_instancenorm_reduce_mean = 0; | |
| pipeline_instancenorm_sub_mean_square = 0; | |
| pipeline_instancenorm_coeffs = 0; | |
| pipeline_instancenorm_norm = 0; | |
| pipeline_instancenorm_reduce_sum4_fp16_to_fp32_pack4 = 0; | |
| pipeline_instancenorm_reduce_sum4_fp32_pack4[0] = 0; | |
| pipeline_instancenorm_reduce_sum4_fp32_pack4[1] = 0; | |
| pipeline_instancenorm_reduce_mean_pack4 = 0; | |
| pipeline_instancenorm_sub_mean_square_pack4 = 0; | |
| pipeline_instancenorm_coeffs_pack4 = 0; | |
| pipeline_instancenorm_norm_pack4 = 0; | |
| pipeline_instancenorm_reduce_sum4_fp16_to_fp32_pack8 = 0; | |
| pipeline_instancenorm_reduce_sum4_fp32_pack8[0] = 0; | |
| pipeline_instancenorm_reduce_sum4_fp32_pack8[1] = 0; | |
| pipeline_instancenorm_reduce_mean_pack8 = 0; | |
| pipeline_instancenorm_sub_mean_square_pack8 = 0; | |
| pipeline_instancenorm_coeffs_pack8 = 0; | |
| pipeline_instancenorm_norm_pack8 = 0; | |
| } | |
| int InstanceNorm_vulkan::create_pipeline(const Option& opt) | |
| { | |
| const Mat& shape = top_shapes.empty() ? Mat() : top_shapes[0]; | |
| int _channels = channels; | |
| if (shape.dims == 3) _channels = shape.c; | |
| int elempack = 1; | |
| if (_channels != 0) elempack = opt.use_shader_pack8 && _channels % 8 == 0 ? 8 : _channels % 4 == 0 ? 4 : 1; | |
| size_t elemsize; | |
| if (opt.use_fp16_storage) | |
| { | |
| elemsize = elempack * 2u; | |
| } | |
| else if (opt.use_fp16_packed) | |
| { | |
| elemsize = elempack == 1 ? 4u : elempack * 2u; | |
| } | |
| else | |
| { | |
| elemsize = elempack * 4u; | |
| } | |
| Mat shape_packed; | |
| if (shape.dims == 3) shape_packed = Mat(shape.w, shape.h, shape.c / elempack, (void*)0, elemsize, elempack); | |
| // TODO resolve workspace_shape.w | |
| Mat workspace_shape_packed; | |
| if (_channels != 0) workspace_shape_packed = Mat(1, 1, _channels / elempack, (void*)0, elemsize, elempack); | |
| { | |
| Mat local_size_xyz; | |
| if (opt.use_image_storage) | |
| { | |
| local_size_xyz = Mat(4, 4, _channels ? std::min(4, _channels / elempack) : 4, (void*)0); | |
| if (workspace_shape_packed.dims != 0) | |
| { | |
| local_size_xyz.w = 4; | |
| local_size_xyz.h = 4; | |
| local_size_xyz.c = std::min(4, workspace_shape_packed.c); | |
| } | |
| } | |
| else | |
| { | |
| local_size_xyz = Mat(16, 1, _channels ? std::min(4, _channels / elempack) : 4, (void*)0); | |
| if (workspace_shape_packed.dims != 0) | |
| { | |
| local_size_xyz.w = 16; | |
| local_size_xyz.h = 1; | |
| local_size_xyz.c = std::min(4, workspace_shape_packed.c); | |
| } | |
| } | |
| // pack1 | |
| if (elempack == 1 || _channels == 0) | |
| { | |
| pipeline_instancenorm_reduce_sum4_fp16_to_fp32 = new Pipeline(vkdev); | |
| pipeline_instancenorm_reduce_sum4_fp16_to_fp32->set_optimal_local_size_xyz(local_size_xyz); | |
| pipeline_instancenorm_reduce_sum4_fp16_to_fp32->create(LayerShaderType::instancenorm_reduce_sum4_fp16_to_fp32, opt, std::vector<vk_specialization_type>()); | |
| pipeline_instancenorm_reduce_sum4_fp32[0] = new Pipeline(vkdev); | |
| pipeline_instancenorm_reduce_sum4_fp32[0]->set_optimal_local_size_xyz(local_size_xyz); | |
| pipeline_instancenorm_reduce_sum4_fp32[0]->create(LayerShaderType::instancenorm_reduce_sum4_fp32, opt, std::vector<vk_specialization_type>()); | |
| pipeline_instancenorm_reduce_sum4_fp32[1] = new Pipeline(vkdev); | |
| pipeline_instancenorm_reduce_sum4_fp32[1]->set_optimal_local_size_xyz(local_size_xyz); | |
| pipeline_instancenorm_reduce_sum4_fp32[1]->create(LayerShaderType::instancenorm_reduce_sum4_fp32, opt, std::vector<vk_specialization_type>()); | |
| } | |
| // pack4 | |
| if (elempack == 4 || _channels == 0) | |
| { | |
| pipeline_instancenorm_reduce_sum4_fp16_to_fp32_pack4 = new Pipeline(vkdev); | |
| pipeline_instancenorm_reduce_sum4_fp16_to_fp32_pack4->set_optimal_local_size_xyz(local_size_xyz); | |
| pipeline_instancenorm_reduce_sum4_fp16_to_fp32_pack4->create(LayerShaderType::instancenorm_reduce_sum4_fp16_to_fp32_pack4, opt, std::vector<vk_specialization_type>()); | |
| pipeline_instancenorm_reduce_sum4_fp32_pack4[0] = new Pipeline(vkdev); | |
| pipeline_instancenorm_reduce_sum4_fp32_pack4[0]->set_optimal_local_size_xyz(local_size_xyz); | |
| pipeline_instancenorm_reduce_sum4_fp32_pack4[0]->create(LayerShaderType::instancenorm_reduce_sum4_fp32_pack4, opt, std::vector<vk_specialization_type>()); | |
| pipeline_instancenorm_reduce_sum4_fp32_pack4[1] = new Pipeline(vkdev); | |
| pipeline_instancenorm_reduce_sum4_fp32_pack4[1]->set_optimal_local_size_xyz(local_size_xyz); | |
| pipeline_instancenorm_reduce_sum4_fp32_pack4[1]->create(LayerShaderType::instancenorm_reduce_sum4_fp32_pack4, opt, std::vector<vk_specialization_type>()); | |
| } | |
| // pack8 | |
| if (elempack == 8 || _channels == 0) | |
| { | |
| pipeline_instancenorm_reduce_sum4_fp16_to_fp32_pack8 = new Pipeline(vkdev); | |
| pipeline_instancenorm_reduce_sum4_fp16_to_fp32_pack8->set_optimal_local_size_xyz(local_size_xyz); | |
| pipeline_instancenorm_reduce_sum4_fp16_to_fp32_pack8->create(LayerShaderType::instancenorm_reduce_sum4_fp16_to_fp32_pack8, opt, std::vector<vk_specialization_type>()); | |
| pipeline_instancenorm_reduce_sum4_fp32_pack8[0] = new Pipeline(vkdev); | |
| pipeline_instancenorm_reduce_sum4_fp32_pack8[0]->set_optimal_local_size_xyz(local_size_xyz); | |
| pipeline_instancenorm_reduce_sum4_fp32_pack8[0]->create(LayerShaderType::instancenorm_reduce_sum4_fp32_pack8, opt, std::vector<vk_specialization_type>()); | |
| pipeline_instancenorm_reduce_sum4_fp32_pack8[1] = new Pipeline(vkdev); | |
| pipeline_instancenorm_reduce_sum4_fp32_pack8[1]->set_optimal_local_size_xyz(local_size_xyz); | |
| pipeline_instancenorm_reduce_sum4_fp32_pack8[1]->create(LayerShaderType::instancenorm_reduce_sum4_fp32_pack8, opt, std::vector<vk_specialization_type>()); | |
| } | |
| } | |
| { | |
| std::vector<vk_specialization_type> specializations(0 + 4); | |
| specializations[0].i = 0; // TODO resolve workspace_shape_packed.w; | |
| specializations[1].i = 0; // TODO resolve workspace_shape_packed.h; | |
| specializations[2].i = workspace_shape_packed.c; | |
| specializations[3].i = 0; // TODO resolve workspace_shape_packed.cstep; | |
| Mat local_size_xyz(_channels ? std::min(64, _channels / elempack) : 64, 1, 1, (void*)0); | |
| if (workspace_shape_packed.dims != 0) | |
| { | |
| local_size_xyz.w = std::min(64, workspace_shape_packed.c); | |
| local_size_xyz.h = 1; | |
| local_size_xyz.c = 1; | |
| } | |
| if (elempack == 1 || _channels == 0) | |
| { | |
| pipeline_instancenorm_reduce_mean = new Pipeline(vkdev); | |
| pipeline_instancenorm_reduce_mean->set_optimal_local_size_xyz(local_size_xyz); | |
| pipeline_instancenorm_reduce_mean->create(LayerShaderType::instancenorm_reduce_mean, opt, specializations); | |
| } | |
| if (elempack == 4 || _channels == 0) | |
| { | |
| pipeline_instancenorm_reduce_mean_pack4 = new Pipeline(vkdev); | |
| pipeline_instancenorm_reduce_mean_pack4->set_optimal_local_size_xyz(local_size_xyz); | |
| pipeline_instancenorm_reduce_mean_pack4->create(LayerShaderType::instancenorm_reduce_mean_pack4, opt, specializations); | |
| } | |
| if (elempack == 8 || _channels == 0) | |
| { | |
| pipeline_instancenorm_reduce_mean_pack8 = new Pipeline(vkdev); | |
| pipeline_instancenorm_reduce_mean_pack8->set_optimal_local_size_xyz(local_size_xyz); | |
| pipeline_instancenorm_reduce_mean_pack8->create(LayerShaderType::instancenorm_reduce_mean_pack8, opt, specializations); | |
| } | |
| } | |
| Mat square_workspace_packed; | |
| if (shape.dims == 3) square_workspace_packed = Mat(shape.w, shape.h, shape.c / elempack, (void*)0, elempack * 4u, elempack); | |
| { | |
| std::vector<vk_specialization_type> specializations(0 + 10); | |
| specializations[0 + 0].i = shape_packed.dims; | |
| specializations[0 + 1].i = shape_packed.w; | |
| specializations[0 + 2].i = shape_packed.h; | |
| specializations[0 + 3].i = shape_packed.c; | |
| specializations[0 + 4].i = shape_packed.cstep; | |
| specializations[0 + 5].i = square_workspace_packed.dims; | |
| specializations[0 + 6].i = square_workspace_packed.w; | |
| specializations[0 + 7].i = square_workspace_packed.h; | |
| specializations[0 + 8].i = square_workspace_packed.c; | |
| specializations[0 + 9].i = square_workspace_packed.cstep; | |
| Mat local_size_xyz(4, 4, _channels ? std::min(4, _channels / elempack) : 4, (void*)0); | |
| if (square_workspace_packed.dims != 0) | |
| { | |
| local_size_xyz.w = std::min(4, square_workspace_packed.w); | |
| local_size_xyz.h = std::min(4, square_workspace_packed.h); | |
| local_size_xyz.c = std::min(4, square_workspace_packed.c); | |
| } | |
| if (elempack == 1 || _channels == 0) | |
| { | |
| pipeline_instancenorm_sub_mean_square = new Pipeline(vkdev); | |
| pipeline_instancenorm_sub_mean_square->set_optimal_local_size_xyz(local_size_xyz); | |
| pipeline_instancenorm_sub_mean_square->create(LayerShaderType::instancenorm_sub_mean_square, opt, specializations); | |
| } | |
| if (elempack == 4 || _channels == 0) | |
| { | |
| pipeline_instancenorm_sub_mean_square_pack4 = new Pipeline(vkdev); | |
| pipeline_instancenorm_sub_mean_square_pack4->set_optimal_local_size_xyz(local_size_xyz); | |
| pipeline_instancenorm_sub_mean_square_pack4->create(LayerShaderType::instancenorm_sub_mean_square_pack4, opt, specializations); | |
| } | |
| if (elempack == 8 || _channels == 0) | |
| { | |
| pipeline_instancenorm_sub_mean_square_pack8 = new Pipeline(vkdev); | |
| pipeline_instancenorm_sub_mean_square_pack8->set_optimal_local_size_xyz(local_size_xyz); | |
| pipeline_instancenorm_sub_mean_square_pack8->create(LayerShaderType::instancenorm_sub_mean_square_pack8, opt, specializations); | |
| } | |
| } | |
| { | |
| std::vector<vk_specialization_type> specializations(3); | |
| specializations[0].f = eps; | |
| specializations[1].i = affine; | |
| specializations[2].i = _channels / elempack; | |
| Mat local_size_xyz(_channels ? std::min(64, _channels / elempack) : 64, 1, 1, (void*)0); | |
| if (workspace_shape_packed.dims != 0) | |
| { | |
| local_size_xyz.w = std::min(64, workspace_shape_packed.c); | |
| local_size_xyz.h = 1; | |
| local_size_xyz.c = 1; | |
| } | |
| if (elempack == 1 || _channels == 0) | |
| { | |
| pipeline_instancenorm_coeffs = new Pipeline(vkdev); | |
| pipeline_instancenorm_coeffs->set_optimal_local_size_xyz(local_size_xyz); | |
| pipeline_instancenorm_coeffs->create(LayerShaderType::instancenorm_coeffs, opt, specializations); | |
| } | |
| if (elempack == 4 || _channels == 0) | |
| { | |
| pipeline_instancenorm_coeffs_pack4 = new Pipeline(vkdev); | |
| pipeline_instancenorm_coeffs_pack4->set_optimal_local_size_xyz(local_size_xyz); | |
| pipeline_instancenorm_coeffs_pack4->create(LayerShaderType::instancenorm_coeffs_pack4, opt, specializations); | |
| } | |
| if (elempack == 8 || _channels == 0) | |
| { | |
| pipeline_instancenorm_coeffs_pack8 = new Pipeline(vkdev); | |
| pipeline_instancenorm_coeffs_pack8->set_optimal_local_size_xyz(local_size_xyz); | |
| pipeline_instancenorm_coeffs_pack8->create(LayerShaderType::instancenorm_coeffs_pack8, opt, specializations); | |
| } | |
| } | |
| { | |
| std::vector<vk_specialization_type> specializations(0 + 5); | |
| specializations[0 + 0].i = shape_packed.dims; | |
| specializations[0 + 1].i = shape_packed.w; | |
| specializations[0 + 2].i = shape_packed.h; | |
| specializations[0 + 3].i = shape_packed.c; | |
| specializations[0 + 4].i = shape_packed.cstep; | |
| Mat local_size_xyz(4, 4, _channels ? std::min(4, _channels / elempack) : 4, (void*)0); | |
| if (shape_packed.dims != 0) | |
| { | |
| local_size_xyz.w = std::min(4, shape_packed.w); | |
| local_size_xyz.h = std::min(4, shape_packed.h); | |
| local_size_xyz.c = std::min(4, shape_packed.c); | |
| } | |
| if (elempack == 1 || _channels == 0) | |
| { | |
| pipeline_instancenorm_norm = new Pipeline(vkdev); | |
| pipeline_instancenorm_norm->set_optimal_local_size_xyz(local_size_xyz); | |
| pipeline_instancenorm_norm->create(LayerShaderType::instancenorm_norm, opt, specializations); | |
| } | |
| if (elempack == 4 || _channels == 0) | |
| { | |
| pipeline_instancenorm_norm_pack4 = new Pipeline(vkdev); | |
| pipeline_instancenorm_norm_pack4->set_optimal_local_size_xyz(local_size_xyz); | |
| pipeline_instancenorm_norm_pack4->create(LayerShaderType::instancenorm_norm_pack4, opt, specializations); | |
| } | |
| if (elempack == 8 || _channels == 0) | |
| { | |
| pipeline_instancenorm_norm_pack8 = new Pipeline(vkdev); | |
| pipeline_instancenorm_norm_pack8->set_optimal_local_size_xyz(local_size_xyz); | |
| pipeline_instancenorm_norm_pack8->create(LayerShaderType::instancenorm_norm_pack8, opt, specializations); | |
| } | |
| } | |
| return 0; | |
| } | |
| int InstanceNorm_vulkan::destroy_pipeline(const Option& /*opt*/) | |
| { | |
| delete pipeline_instancenorm_reduce_sum4_fp16_to_fp32; | |
| pipeline_instancenorm_reduce_sum4_fp16_to_fp32 = 0; | |
| delete pipeline_instancenorm_reduce_sum4_fp32[0]; | |
| delete pipeline_instancenorm_reduce_sum4_fp32[1]; | |
| pipeline_instancenorm_reduce_sum4_fp32[0] = 0; | |
| pipeline_instancenorm_reduce_sum4_fp32[1] = 0; | |
| delete pipeline_instancenorm_reduce_mean; | |
| pipeline_instancenorm_reduce_mean = 0; | |
| delete pipeline_instancenorm_sub_mean_square; | |
| pipeline_instancenorm_sub_mean_square = 0; | |
| delete pipeline_instancenorm_coeffs; | |
| pipeline_instancenorm_coeffs = 0; | |
| delete pipeline_instancenorm_norm; | |
| pipeline_instancenorm_norm = 0; | |
| delete pipeline_instancenorm_reduce_sum4_fp16_to_fp32_pack4; | |
| pipeline_instancenorm_reduce_sum4_fp16_to_fp32_pack4 = 0; | |
| delete pipeline_instancenorm_reduce_sum4_fp32_pack4[0]; | |
| delete pipeline_instancenorm_reduce_sum4_fp32_pack4[1]; | |
| pipeline_instancenorm_reduce_sum4_fp32_pack4[0] = 0; | |
| pipeline_instancenorm_reduce_sum4_fp32_pack4[1] = 0; | |
| delete pipeline_instancenorm_reduce_mean_pack4; | |
| pipeline_instancenorm_reduce_mean_pack4 = 0; | |
| delete pipeline_instancenorm_sub_mean_square_pack4; | |
| pipeline_instancenorm_sub_mean_square_pack4 = 0; | |
| delete pipeline_instancenorm_coeffs_pack4; | |
| pipeline_instancenorm_coeffs_pack4 = 0; | |
| delete pipeline_instancenorm_norm_pack4; | |
| pipeline_instancenorm_norm_pack4 = 0; | |
| delete pipeline_instancenorm_reduce_sum4_fp16_to_fp32_pack8; | |
| pipeline_instancenorm_reduce_sum4_fp16_to_fp32_pack8 = 0; | |
| delete pipeline_instancenorm_reduce_sum4_fp32_pack8[0]; | |
| delete pipeline_instancenorm_reduce_sum4_fp32_pack8[1]; | |
| pipeline_instancenorm_reduce_sum4_fp32_pack8[0] = 0; | |
| pipeline_instancenorm_reduce_sum4_fp32_pack8[1] = 0; | |
| delete pipeline_instancenorm_reduce_mean_pack8; | |
| pipeline_instancenorm_reduce_mean_pack8 = 0; | |
| delete pipeline_instancenorm_sub_mean_square_pack8; | |
| pipeline_instancenorm_sub_mean_square_pack8 = 0; | |
| delete pipeline_instancenorm_coeffs_pack8; | |
| pipeline_instancenorm_coeffs_pack8 = 0; | |
| delete pipeline_instancenorm_norm_pack8; | |
| pipeline_instancenorm_norm_pack8 = 0; | |
| return 0; | |
| } | |
| int InstanceNorm_vulkan::upload_model(VkTransfer& cmd, const Option& opt) | |
| { | |
| if (affine == 0) | |
| return 0; | |
| int elempack = opt.use_shader_pack8 && channels % 8 == 0 ? 8 : channels % 4 == 0 ? 4 : 1; | |
| Mat gamma_data_packed; | |
| convert_packing(gamma_data, gamma_data_packed, elempack, opt); | |
| if (opt.use_image_storage) | |
| { | |
| cmd.record_upload(gamma_data_packed, gamma_data_gpu_image, opt); | |
| } | |
| else | |
| { | |
| cmd.record_upload(gamma_data_packed, gamma_data_gpu, opt); | |
| } | |
| Mat beta_data_packed; | |
| convert_packing(beta_data, beta_data_packed, elempack, opt); | |
| if (opt.use_image_storage) | |
| { | |
| cmd.record_upload(beta_data_packed, beta_data_gpu_image, opt); | |
| } | |
| else | |
| { | |
| cmd.record_upload(beta_data_packed, beta_data_gpu, opt); | |
| } | |
| return 0; | |
| } | |
| int InstanceNorm_vulkan::forward_inplace(VkMat& bottom_top_blob, VkCompute& cmd, const Option& opt) const | |
| { | |
| int w = bottom_top_blob.w; | |
| int h = bottom_top_blob.h; | |
| int c = bottom_top_blob.c; | |
| int size = w * h; | |
| size_t elemsize = bottom_top_blob.elemsize; | |
| int elempack = bottom_top_blob.elempack; | |
| // mean | |
| VkMat mean_workspace(c, 4u * elempack, elempack, opt.workspace_vkallocator); | |
| { | |
| // reduce sum | |
| VkMat sum_workspace; | |
| { | |
| int reduced_w = (bottom_top_blob.w * bottom_top_blob.h + 3) / 4; | |
| int reduced_h = 1; | |
| int reduced_c = bottom_top_blob.c; | |
| sum_workspace.create(reduced_w, reduced_h, reduced_c, 4u * elempack, elempack, opt.workspace_vkallocator); | |
| { | |
| std::vector<VkMat> bindings(2); | |
| bindings[0] = bottom_top_blob; | |
| bindings[1] = sum_workspace; | |
| std::vector<vk_constant_type> constants(8); | |
| constants[0].i = bottom_top_blob.w * bottom_top_blob.h; | |
| constants[1].i = 1; | |
| constants[2].i = bottom_top_blob.c; | |
| constants[3].i = bottom_top_blob.cstep; | |
| constants[4].i = sum_workspace.w; | |
| constants[5].i = 1; | |
| constants[6].i = sum_workspace.c; | |
| constants[7].i = sum_workspace.cstep; | |
| const Pipeline* pipeline = elempack == 8 ? pipeline_instancenorm_reduce_sum4_fp16_to_fp32_pack8 | |
| : elempack == 4 ? pipeline_instancenorm_reduce_sum4_fp16_to_fp32_pack4 | |
| : pipeline_instancenorm_reduce_sum4_fp16_to_fp32; | |
| cmd.record_pipeline(pipeline, bindings, constants, sum_workspace); | |
| } | |
| } | |
| int pb = 0; | |
| while (sum_workspace.w > 4) | |
| { | |
| int reduced_w = (sum_workspace.w + 3) / 4; | |
| int reduced_h = 1; | |
| int reduced_c = sum_workspace.c; | |
| VkMat sum_workspace_reduced; | |
| sum_workspace_reduced.create(reduced_w, reduced_h, reduced_c, 4u * elempack, elempack, opt.workspace_vkallocator); | |
| { | |
| std::vector<VkMat> bindings(2); | |
| bindings[0] = sum_workspace; | |
| bindings[1] = sum_workspace_reduced; | |
| std::vector<vk_constant_type> constants(8); | |
| constants[0].i = sum_workspace.w; | |
| constants[1].i = 1; | |
| constants[2].i = sum_workspace.c; | |
| constants[3].i = sum_workspace.cstep; | |
| constants[4].i = sum_workspace_reduced.w; | |
| constants[5].i = 1; | |
| constants[6].i = sum_workspace_reduced.c; | |
| constants[7].i = sum_workspace_reduced.cstep; | |
| const Pipeline* pipeline = elempack == 8 ? pipeline_instancenorm_reduce_sum4_fp32_pack8[pb % 2] | |
| : elempack == 4 ? pipeline_instancenorm_reduce_sum4_fp32_pack4[pb % 2] | |
| : pipeline_instancenorm_reduce_sum4_fp32[pb % 2]; | |
| cmd.record_pipeline(pipeline, bindings, constants, sum_workspace_reduced); | |
| pb++; | |
| } | |
| sum_workspace = sum_workspace_reduced; | |
| } | |
| { | |
| std::vector<VkMat> bindings(2); | |
| bindings[0] = sum_workspace; | |
| bindings[1] = mean_workspace; | |
| std::vector<vk_constant_type> constants(5); | |
| constants[0].i = sum_workspace.w; | |
| constants[1].i = 1; | |
| constants[2].i = sum_workspace.c; | |
| constants[3].i = sum_workspace.cstep; | |
| constants[4].f = size; | |
| const Pipeline* pipeline = elempack == 8 ? pipeline_instancenorm_reduce_mean_pack8 | |
| : elempack == 4 ? pipeline_instancenorm_reduce_mean_pack4 | |
| : pipeline_instancenorm_reduce_mean; | |
| cmd.record_pipeline(pipeline, bindings, constants, mean_workspace); | |
| } | |
| } | |
| // var | |
| VkMat var_workspace(c, 4u * elempack, elempack, opt.workspace_vkallocator); | |
| { | |
| // sub mean and square | |
| VkMat square_workspace; | |
| square_workspace.create(w, h, c, 4u * elempack, elempack, opt.workspace_vkallocator); | |
| { | |
| std::vector<VkMat> bindings(3); | |
| bindings[0] = bottom_top_blob; | |
| bindings[1] = mean_workspace; | |
| bindings[2] = square_workspace; | |
| std::vector<vk_constant_type> constants(10); | |
| constants[0].i = bottom_top_blob.dims; | |
| constants[1].i = bottom_top_blob.w; | |
| constants[2].i = bottom_top_blob.h; | |
| constants[3].i = bottom_top_blob.c; | |
| constants[4].i = bottom_top_blob.cstep; | |
| constants[5].i = square_workspace.dims; | |
| constants[6].i = square_workspace.w; | |
| constants[7].i = square_workspace.h; | |
| constants[8].i = square_workspace.c; | |
| constants[9].i = square_workspace.cstep; | |
| const Pipeline* pipeline = elempack == 8 ? pipeline_instancenorm_sub_mean_square_pack8 | |
| : elempack == 4 ? pipeline_instancenorm_sub_mean_square_pack4 | |
| : pipeline_instancenorm_sub_mean_square; | |
| cmd.record_pipeline(pipeline, bindings, constants, square_workspace); | |
| } | |
| // reduce square | |
| VkMat sqsum_workspace = square_workspace; | |
| sqsum_workspace.w = sqsum_workspace.w * sqsum_workspace.h; | |
| sqsum_workspace.h = 1; | |
| int pb = 0; | |
| while (sqsum_workspace.w > 4) | |
| { | |
| int reduced_w = (sqsum_workspace.w + 3) / 4; | |
| int reduced_h = 1; | |
| int reduced_c = sqsum_workspace.c; | |
| VkMat sqsum_workspace_reduced; | |
| sqsum_workspace_reduced.create(reduced_w, reduced_h, reduced_c, 4u * elempack, elempack, opt.workspace_vkallocator); | |
| { | |
| std::vector<VkMat> bindings(2); | |
| bindings[0] = sqsum_workspace; | |
| bindings[1] = sqsum_workspace_reduced; | |
| std::vector<vk_constant_type> constants(8); | |
| constants[0].i = sqsum_workspace.w; | |
| constants[1].i = 1; | |
| constants[2].i = sqsum_workspace.c; | |
| constants[3].i = sqsum_workspace.cstep; | |
| constants[4].i = sqsum_workspace_reduced.w; | |
| constants[5].i = 1; | |
| constants[6].i = sqsum_workspace_reduced.c; | |
| constants[7].i = sqsum_workspace_reduced.cstep; | |
| const Pipeline* pipeline = elempack == 8 ? pipeline_instancenorm_reduce_sum4_fp32_pack8[pb % 2] | |
| : elempack == 4 ? pipeline_instancenorm_reduce_sum4_fp32_pack4[pb % 2] | |
| : pipeline_instancenorm_reduce_sum4_fp32[pb % 2]; | |
| cmd.record_pipeline(pipeline, bindings, constants, sqsum_workspace_reduced); | |
| pb++; | |
| } | |
| sqsum_workspace = sqsum_workspace_reduced; | |
| } | |
| { | |
| std::vector<VkMat> bindings(2); | |
| bindings[0] = sqsum_workspace; | |
| bindings[1] = var_workspace; | |
| std::vector<vk_constant_type> constants(5); | |
| constants[0].i = sqsum_workspace.w; | |
| constants[1].i = 1; | |
| constants[2].i = sqsum_workspace.c; | |
| constants[3].i = sqsum_workspace.cstep; | |
| constants[4].f = size; | |
| const Pipeline* pipeline = elempack == 8 ? pipeline_instancenorm_reduce_mean_pack8 | |
| : elempack == 4 ? pipeline_instancenorm_reduce_mean_pack4 | |
| : pipeline_instancenorm_reduce_mean; | |
| cmd.record_pipeline(pipeline, bindings, constants, var_workspace); | |
| } | |
| } | |
| // coeffs | |
| VkMat coeffs_workspace; | |
| coeffs_workspace.create(c, elemsize * 2, elempack * 2, opt.workspace_vkallocator); | |
| { | |
| std::vector<VkMat> bindings(5); | |
| bindings[0] = coeffs_workspace; | |
| bindings[1] = mean_workspace; | |
| bindings[2] = var_workspace; | |
| bindings[3] = gamma_data_gpu; | |
| bindings[4] = beta_data_gpu; | |
| std::vector<vk_constant_type> constants(1); | |
| constants[0].i = c; | |
| const Pipeline* pipeline = elempack == 8 ? pipeline_instancenorm_coeffs_pack8 | |
| : elempack == 4 ? pipeline_instancenorm_coeffs_pack4 | |
| : pipeline_instancenorm_coeffs; | |
| cmd.record_pipeline(pipeline, bindings, constants, coeffs_workspace); | |
| } | |
| // norm | |
| { | |
| std::vector<VkMat> bindings(2); | |
| bindings[0] = bottom_top_blob; | |
| bindings[1] = coeffs_workspace; | |
| std::vector<vk_constant_type> constants(5); | |
| constants[0].i = bottom_top_blob.dims; | |
| constants[1].i = bottom_top_blob.w; | |
| constants[2].i = bottom_top_blob.h; | |
| constants[3].i = bottom_top_blob.c; | |
| constants[4].i = bottom_top_blob.cstep; | |
| const Pipeline* pipeline = elempack == 8 ? pipeline_instancenorm_norm_pack8 | |
| : elempack == 4 ? pipeline_instancenorm_norm_pack4 | |
| : pipeline_instancenorm_norm; | |
| cmd.record_pipeline(pipeline, bindings, constants, bottom_top_blob); | |
| } | |
| return 0; | |
| } | |
| int InstanceNorm_vulkan::forward_inplace(VkImageMat& bottom_top_blob, VkCompute& cmd, const Option& opt) const | |
| { | |
| int w = bottom_top_blob.w; | |
| int h = bottom_top_blob.h; | |
| int c = bottom_top_blob.c; | |
| int size = w * h; | |
| size_t elemsize = bottom_top_blob.elemsize; | |
| int elempack = bottom_top_blob.elempack; | |
| // mean | |
| VkImageMat mean_workspace(c, 4u * elempack, elempack, opt.workspace_vkallocator); | |
| { | |
| // reduce sum | |
| VkImageMat sum_workspace; | |
| { | |
| int reduced_w = (bottom_top_blob.w + 1) / 2; | |
| int reduced_h = (bottom_top_blob.h + 1) / 2; | |
| int reduced_c = bottom_top_blob.c; | |
| sum_workspace.create(reduced_w, reduced_h, reduced_c, 4u * elempack, elempack, opt.workspace_vkallocator); | |
| { | |
| std::vector<VkImageMat> bindings(2); | |
| bindings[0] = bottom_top_blob; | |
| bindings[1] = sum_workspace; | |
| std::vector<vk_constant_type> constants(8); | |
| constants[0].i = bottom_top_blob.w; | |
| constants[1].i = bottom_top_blob.h; | |
| constants[2].i = bottom_top_blob.c; | |
| constants[3].i = 0; //bottom_top_blob.cstep; | |
| constants[4].i = sum_workspace.w; | |
| constants[5].i = sum_workspace.h; | |
| constants[6].i = sum_workspace.c; | |
| constants[7].i = 0; //sum_workspace.cstep; | |
| const Pipeline* pipeline = elempack == 8 ? pipeline_instancenorm_reduce_sum4_fp16_to_fp32_pack8 | |
| : elempack == 4 ? pipeline_instancenorm_reduce_sum4_fp16_to_fp32_pack4 | |
| : pipeline_instancenorm_reduce_sum4_fp16_to_fp32; | |
| cmd.record_pipeline(pipeline, bindings, constants, sum_workspace); | |
| } | |
| } | |
| int pb = 0; | |
| while (sum_workspace.w > 2 || sum_workspace.h > 2) | |
| { | |
| int reduced_w = (sum_workspace.w + 1) / 2; | |
| int reduced_h = (sum_workspace.h + 1) / 2; | |
| int reduced_c = sum_workspace.c; | |
| VkImageMat sum_workspace_reduced; | |
| sum_workspace_reduced.create(reduced_w, reduced_h, reduced_c, 4u * elempack, elempack, opt.workspace_vkallocator); | |
| { | |
| std::vector<VkImageMat> bindings(2); | |
| bindings[0] = sum_workspace; | |
| bindings[1] = sum_workspace_reduced; | |
| std::vector<vk_constant_type> constants(8); | |
| constants[0].i = sum_workspace.w; | |
| constants[1].i = sum_workspace.h; | |
| constants[2].i = sum_workspace.c; | |
| constants[3].i = 0; //sum_workspace.cstep; | |
| constants[4].i = sum_workspace_reduced.w; | |
| constants[5].i = sum_workspace_reduced.h; | |
| constants[6].i = sum_workspace_reduced.c; | |
| constants[7].i = 0; //sum_workspace_reduced.cstep; | |
| const Pipeline* pipeline = elempack == 8 ? pipeline_instancenorm_reduce_sum4_fp32_pack8[pb % 2] | |
| : elempack == 4 ? pipeline_instancenorm_reduce_sum4_fp32_pack4[pb % 2] | |
| : pipeline_instancenorm_reduce_sum4_fp32[pb % 2]; | |
| cmd.record_pipeline(pipeline, bindings, constants, sum_workspace_reduced); | |
| pb++; | |
| } | |
| sum_workspace = sum_workspace_reduced; | |
| } | |
| { | |
| std::vector<VkImageMat> bindings(2); | |
| bindings[0] = sum_workspace; | |
| bindings[1] = mean_workspace; | |
| std::vector<vk_constant_type> constants(5); | |
| constants[0].i = sum_workspace.w; | |
| constants[1].i = sum_workspace.h; | |
| constants[2].i = sum_workspace.c; | |
| constants[3].i = 0; //sum_workspace.cstep; | |
| constants[4].f = size; | |
| const Pipeline* pipeline = elempack == 8 ? pipeline_instancenorm_reduce_mean_pack8 | |
| : elempack == 4 ? pipeline_instancenorm_reduce_mean_pack4 | |
| : pipeline_instancenorm_reduce_mean; | |
| cmd.record_pipeline(pipeline, bindings, constants, mean_workspace); | |
| } | |
| } | |
| // var | |
| VkImageMat var_workspace(c, 4u * elempack, elempack, opt.workspace_vkallocator); | |
| { | |
| // sub mean and square | |
| VkImageMat square_workspace; | |
| square_workspace.create(w, h, c, 4u * elempack, elempack, opt.workspace_vkallocator); | |
| { | |
| std::vector<VkImageMat> bindings(3); | |
| bindings[0] = bottom_top_blob; | |
| bindings[1] = mean_workspace; | |
| bindings[2] = square_workspace; | |
| std::vector<vk_constant_type> constants(10); | |
| constants[0].i = bottom_top_blob.dims; | |
| constants[1].i = bottom_top_blob.w; | |
| constants[2].i = bottom_top_blob.h; | |
| constants[3].i = bottom_top_blob.c; | |
| constants[4].i = 0; //bottom_top_blob.cstep; | |
| constants[5].i = square_workspace.dims; | |
| constants[6].i = square_workspace.w; | |
| constants[7].i = square_workspace.h; | |
| constants[8].i = square_workspace.c; | |
| constants[9].i = 0; //square_workspace.cstep; | |
| const Pipeline* pipeline = elempack == 8 ? pipeline_instancenorm_sub_mean_square_pack8 | |
| : elempack == 4 ? pipeline_instancenorm_sub_mean_square_pack4 | |
| : pipeline_instancenorm_sub_mean_square; | |
| cmd.record_pipeline(pipeline, bindings, constants, square_workspace); | |
| } | |
| // reduce square | |
| VkImageMat sqsum_workspace = square_workspace; | |
| int pb = 0; | |
| while (sqsum_workspace.w > 2 || sqsum_workspace.h > 2) | |
| { | |
| int reduced_w = (sqsum_workspace.w + 1) / 2; | |
| int reduced_h = (sqsum_workspace.h + 1) / 2; | |
| int reduced_c = sqsum_workspace.c; | |
| VkImageMat sqsum_workspace_reduced; | |
| sqsum_workspace_reduced.create(reduced_w, reduced_h, reduced_c, 4u * elempack, elempack, opt.workspace_vkallocator); | |
| { | |
| std::vector<VkImageMat> bindings(2); | |
| bindings[0] = sqsum_workspace; | |
| bindings[1] = sqsum_workspace_reduced; | |
| std::vector<vk_constant_type> constants(8); | |
| constants[0].i = sqsum_workspace.w; | |
| constants[1].i = sqsum_workspace.h; | |
| constants[2].i = sqsum_workspace.c; | |
| constants[3].i = 0; //sqsum_workspace.cstep; | |
| constants[4].i = sqsum_workspace_reduced.w; | |
| constants[5].i = sqsum_workspace_reduced.h; | |
| constants[6].i = sqsum_workspace_reduced.c; | |
| constants[7].i = 0; //sqsum_workspace_reduced.cstep; | |
| const Pipeline* pipeline = elempack == 8 ? pipeline_instancenorm_reduce_sum4_fp32_pack8[pb % 2] | |
| : elempack == 4 ? pipeline_instancenorm_reduce_sum4_fp32_pack4[pb % 2] | |
| : pipeline_instancenorm_reduce_sum4_fp32[pb % 2]; | |
| cmd.record_pipeline(pipeline, bindings, constants, sqsum_workspace_reduced); | |
| pb++; | |
| } | |
| sqsum_workspace = sqsum_workspace_reduced; | |
| } | |
| { | |
| std::vector<VkImageMat> bindings(2); | |
| bindings[0] = sqsum_workspace; | |
| bindings[1] = var_workspace; | |
| std::vector<vk_constant_type> constants(5); | |
| constants[0].i = sqsum_workspace.w; | |
| constants[1].i = sqsum_workspace.h; | |
| constants[2].i = sqsum_workspace.c; | |
| constants[3].i = 0; //sqsum_workspace.cstep; | |
| constants[4].f = size; | |
| const Pipeline* pipeline = elempack == 8 ? pipeline_instancenorm_reduce_mean_pack8 | |
| : elempack == 4 ? pipeline_instancenorm_reduce_mean_pack4 | |
| : pipeline_instancenorm_reduce_mean; | |
| cmd.record_pipeline(pipeline, bindings, constants, var_workspace); | |
| } | |
| } | |
| // coeffs | |
| VkImageMat coeffs_workspace; | |
| coeffs_workspace.create(c * 2, elemsize, elempack, opt.workspace_vkallocator); | |
| { | |
| std::vector<VkImageMat> bindings(5); | |
| bindings[0] = coeffs_workspace; | |
| bindings[1] = mean_workspace; | |
| bindings[2] = var_workspace; | |
| bindings[3] = gamma_data_gpu_image; | |
| bindings[4] = beta_data_gpu_image; | |
| std::vector<vk_constant_type> constants(1); | |
| constants[0].i = c; | |
| const Pipeline* pipeline = elempack == 8 ? pipeline_instancenorm_coeffs_pack8 | |
| : elempack == 4 ? pipeline_instancenorm_coeffs_pack4 | |
| : pipeline_instancenorm_coeffs; | |
| VkImageMat dispatcher; | |
| dispatcher.w = c; | |
| dispatcher.h = 1; | |
| dispatcher.c = 1; | |
| cmd.record_pipeline(pipeline, bindings, constants, dispatcher); | |
| } | |
| // norm | |
| { | |
| std::vector<VkImageMat> bindings(3); | |
| bindings[0] = bottom_top_blob; | |
| bindings[1] = bottom_top_blob; | |
| bindings[2] = coeffs_workspace; | |
| std::vector<vk_constant_type> constants(5); | |
| constants[0].i = bottom_top_blob.dims; | |
| constants[1].i = bottom_top_blob.w; | |
| constants[2].i = bottom_top_blob.h; | |
| constants[3].i = bottom_top_blob.c; | |
| constants[4].i = 0; //bottom_top_blob.cstep; | |
| const Pipeline* pipeline = elempack == 8 ? pipeline_instancenorm_norm_pack8 | |
| : elempack == 4 ? pipeline_instancenorm_norm_pack4 | |
| : pipeline_instancenorm_norm; | |
| cmd.record_pipeline(pipeline, bindings, constants, bottom_top_blob); | |
| } | |
| return 0; | |
| } | |
| } // namespace ncnn | |