// Copyright 2020 Tencent // SPDX-License-Identifier: BSD-3-Clause #include "testutil.h" static int cast_cpu_naive(const ncnn::Mat& a, ncnn::Mat& b, int type_from, int type_to) { ncnn::ParamDict pd; pd.set(0, type_from); pd.set(1, type_to); std::vector weights(0); ncnn::Option opt; opt.num_threads = 1; ncnn::Layer* op = ncnn::create_layer_naive("Cast"); op->load_param(pd); ncnn::ModelBinFromMatArray mb(weights.data()); op->load_model(mb); op->create_pipeline(opt); op->forward(a, b, opt); op->destroy_pipeline(opt); delete op; return 0; } static int test_cast_cpu(const ncnn::Mat& a, int type_from, int type_to) { ncnn::ParamDict pd; pd.set(0, type_from); pd.set(1, type_to); std::vector weights(0); ncnn::Option opt; opt.num_threads = 1; opt.use_vulkan_compute = false; opt.use_int8_inference = false; opt.use_packing_layout = false; ncnn::Layer* op = ncnn::create_layer_cpu("Cast"); op->load_param(pd); ncnn::ModelBinFromMatArray mb(weights.data()); op->load_model(mb); op->create_pipeline(opt); ncnn::Mat a_fp16; cast_cpu_naive(a, a_fp16, 1, type_from); ncnn::Mat b; cast_cpu_naive(a_fp16, b, type_from, type_to); ncnn::Mat c; op->forward(a_fp16, c, opt); op->destroy_pipeline(opt); delete op; if (CompareMat(b, c, 0.001) != 0) { fprintf(stderr, "test_cast_cpu failed a.dims=%d a=(%d %d %d %d) type_from=%d type_to=%d\n", a.dims, a.w, a.h, a.d, a.c, type_from, type_to); return -1; } return 0; } static int test_cast_cpu_packed(const ncnn::Mat& a, int type_from, int type_to) { ncnn::ParamDict pd; pd.set(0, type_from); pd.set(1, type_to); std::vector weights(0); ncnn::Option opt; opt.num_threads = 1; opt.use_vulkan_compute = false; opt.use_packing_layout = false; ncnn::Layer* op = ncnn::create_layer_cpu("Cast"); op->load_param(pd); ncnn::ModelBinFromMatArray mb(weights.data()); op->load_model(mb); op->create_pipeline(opt); ncnn::Mat a_fp16; cast_cpu_naive(a, a_fp16, 1, type_from); ncnn::Mat b; cast_cpu_naive(a_fp16, b, type_from, type_to); ncnn::Mat a4; ncnn::convert_packing(a, a4, 4, opt); ncnn::Mat a4_fp16; cast_cpu_naive(a4, a4_fp16, 1, type_from); ncnn::Mat c; op->forward(a4_fp16, c, opt); op->destroy_pipeline(opt); delete op; if (CompareMat(b, c, 0.001) != 0) { fprintf(stderr, "test_cast_cpu_packed failed a.dims=%d a=(%d %d %d %d) type_from=%d type_to=%d\n", a.dims, a.w, a.h, a.d, a.c, type_from, type_to); return -1; } return 0; } #if NCNN_VULKAN static int test_cast_gpu_fp16p(const ncnn::Mat& a, int type_from, int type_to) { if (type_to == 4 || type_from == 4) return 0; ncnn::ParamDict pd; pd.set(0, type_from); pd.set(1, type_to); std::vector weights(0); ncnn::Option opt; opt.num_threads = 1; opt.use_vulkan_compute = true; opt.use_int8_inference = false; opt.use_fp16_packed = true; opt.use_fp16_storage = false; opt.use_fp16_arithmetic = false; opt.use_int8_storage = false; opt.use_int8_arithmetic = false; opt.use_packing_layout = true; ncnn::VulkanDevice* vkdev = ncnn::get_gpu_device(); ncnn::VkAllocator* blob_vkallocator = vkdev->acquire_blob_allocator(); ncnn::VkAllocator* staging_vkallocator = vkdev->acquire_staging_allocator(); opt.blob_vkallocator = blob_vkallocator; opt.workspace_vkallocator = blob_vkallocator; opt.staging_vkallocator = staging_vkallocator; if (!vkdev->info.support_fp16_packed()) opt.use_fp16_packed = false; if (!vkdev->info.support_fp16_storage()) opt.use_fp16_storage = false; ncnn::Layer* op = ncnn::create_layer_vulkan("Cast"); op->vkdev = vkdev; op->load_param(pd); ncnn::ModelBinFromMatArray mb(weights.data()); op->load_model(mb); op->create_pipeline(opt); ncnn::Mat a_fp16; if (type_from == 2) { ncnn::cast_float32_to_float16(a, a_fp16, opt); } else { a_fp16 = a; } ncnn::Mat b; cast_cpu_naive(a_fp16, b, type_from, type_to); ncnn::Mat d; // pack ncnn::Mat a4; ncnn::convert_packing(a, a4, 4, opt); ncnn::Mat a4_fp16; if (type_from == 2) { ncnn::cast_float32_to_float16(a4, a4_fp16, opt); } else { a4_fp16 = a4; } // forward ncnn::VkCompute cmd(vkdev); // upload ncnn::VkMat a4_gpu; cmd.record_clone(a4_fp16, a4_gpu, opt); ncnn::VkMat d4_gpu; if (op->support_inplace) { op->forward_inplace(a4_gpu, cmd, opt); d4_gpu = a4_gpu; } else { op->forward(a4_gpu, d4_gpu, cmd, opt); } // download cmd.record_clone(d4_gpu, d, opt); cmd.submit_and_wait(); op->destroy_pipeline(opt); delete op; vkdev->reclaim_blob_allocator(blob_vkallocator); vkdev->reclaim_staging_allocator(staging_vkallocator); if (CompareMat(b, d, 0.001) != 0) { fprintf(stderr, "test_cast_gpu_fp16p failed a.dims=%d a=(%d %d %d %d) type_from=%d type_to=%d\n", a.dims, a.w, a.h, a.d, a.c, type_from, type_to); return -1; } return 0; } static int test_cast_gpu_fp16p_pack8(const ncnn::Mat& a, int type_from, int type_to) { if (type_to == 4 || type_from == 4) return 0; ncnn::ParamDict pd; pd.set(0, type_from); pd.set(1, type_to); std::vector weights(0); ncnn::Option opt; opt.num_threads = 1; opt.use_vulkan_compute = true; opt.use_int8_inference = false; opt.use_fp16_packed = true; opt.use_fp16_storage = false; opt.use_fp16_arithmetic = false; opt.use_int8_storage = false; opt.use_int8_arithmetic = false; opt.use_packing_layout = true; opt.use_shader_pack8 = true; ncnn::VulkanDevice* vkdev = ncnn::get_gpu_device(); ncnn::VkAllocator* blob_vkallocator = vkdev->acquire_blob_allocator(); ncnn::VkAllocator* staging_vkallocator = vkdev->acquire_staging_allocator(); opt.blob_vkallocator = blob_vkallocator; opt.workspace_vkallocator = blob_vkallocator; opt.staging_vkallocator = staging_vkallocator; if (!vkdev->info.support_fp16_packed()) opt.use_fp16_packed = false; if (!vkdev->info.support_fp16_storage()) opt.use_fp16_storage = false; ncnn::Layer* op = ncnn::create_layer_vulkan("Cast"); op->vkdev = vkdev; op->load_param(pd); ncnn::ModelBinFromMatArray mb(weights.data()); op->load_model(mb); op->create_pipeline(opt); ncnn::Mat a_fp16; if (type_from == 2) { ncnn::cast_float32_to_float16(a, a_fp16, opt); } else { a_fp16 = a; } ncnn::Mat b; cast_cpu_naive(a_fp16, b, type_from, type_to); ncnn::Mat d; // pack ncnn::Mat a4; ncnn::convert_packing(a, a4, 8, opt); if (a4.elempack != 8) ncnn::convert_packing(a, a4, 4, opt); ncnn::Mat a4_fp16; if (type_from == 2) { ncnn::cast_float32_to_float16(a4, a4_fp16, opt); } else { a4_fp16 = a4; } // forward ncnn::VkCompute cmd(vkdev); // upload ncnn::VkMat a4_gpu; cmd.record_clone(a4_fp16, a4_gpu, opt); ncnn::VkMat d4_gpu; if (op->support_inplace) { op->forward_inplace(a4_gpu, cmd, opt); d4_gpu = a4_gpu; } else { op->forward(a4_gpu, d4_gpu, cmd, opt); } // download cmd.record_clone(d4_gpu, d, opt); cmd.submit_and_wait(); op->destroy_pipeline(opt); delete op; vkdev->reclaim_blob_allocator(blob_vkallocator); vkdev->reclaim_staging_allocator(staging_vkallocator); if (CompareMat(b, d, 0.001) != 0) { fprintf(stderr, "test_cast_gpu_fp16p_pack8 failed a.dims=%d a=(%d %d %d %d) type_from=%d type_to=%d\n", a.dims, a.w, a.h, a.d, a.c, type_from, type_to); return -1; } return 0; } #endif // NCNN_VULKAN static int test_cast(const ncnn::Mat& a, int type_from, int type_to) { return 0 || test_cast_cpu(a, type_from, type_to) || test_cast_cpu_packed(a, type_from, type_to) #if NCNN_VULKAN || test_cast_gpu_fp16p(a, type_from, type_to) || test_cast_gpu_fp16p_pack8(a, type_from, type_to) #endif // NCNN_VULKAN ; } static int test_cast_0() { return 0 || test_cast(RandomMat(5, 6, 7, 16), 1, 2) || test_cast(RandomMat(3, 4, 5, 13), 1, 2) || test_cast(RandomMat(5, 6, 7, 16), 2, 1) || test_cast(RandomMat(3, 4, 5, 13), 2, 1) || test_cast(RandomMat(5, 6, 7, 16), 1, 4) || test_cast(RandomMat(3, 4, 5, 13), 1, 4) || test_cast(RandomMat(5, 6, 7, 16), 4, 1) || test_cast(RandomMat(3, 4, 5, 13), 4, 1); } static int test_cast_1() { return 0 || test_cast(RandomMat(5, 7, 16), 1, 2) || test_cast(RandomMat(3, 5, 13), 1, 2) || test_cast(RandomMat(5, 7, 16), 2, 1) || test_cast(RandomMat(3, 5, 13), 2, 1) || test_cast(RandomMat(5, 7, 16), 1, 4) || test_cast(RandomMat(3, 5, 13), 1, 4) || test_cast(RandomMat(5, 7, 16), 4, 1) || test_cast(RandomMat(3, 5, 13), 4, 1); } static int test_cast_2() { return 0 || test_cast(RandomMat(6, 16), 1, 2) || test_cast(RandomMat(7, 15), 1, 2) || test_cast(RandomMat(6, 16), 2, 1) || test_cast(RandomMat(7, 15), 2, 1) || test_cast(RandomMat(6, 16), 1, 4) || test_cast(RandomMat(7, 15), 1, 4) || test_cast(RandomMat(6, 16), 4, 1) || test_cast(RandomMat(7, 15), 4, 1); } static int test_cast_3() { return 0 || test_cast(RandomMat(128), 1, 2) || test_cast(RandomMat(127), 1, 2) || test_cast(RandomMat(128), 2, 1) || test_cast(RandomMat(127), 2, 1) || test_cast(RandomMat(128), 1, 4) || test_cast(RandomMat(127), 1, 4) || test_cast(RandomMat(128), 4, 1) || test_cast(RandomMat(127), 4, 1); } int main() { SRAND(7767517); return 0 || test_cast_0() || test_cast_1() || test_cast_2() || test_cast_3(); }