/* * 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. */ #ifndef CKW_VALIDATION_TESTS_CLKERNELWRITEROPLOADSTORETEST_H #define CKW_VALIDATION_TESTS_CLKERNELWRITEROPLOADSTORETEST_H #include "ckw/TileInfo.h" #include "ckw/types/DataType.h" #include "src/cl/CLKernelWriter.h" #include "validation/tests/common/KernelWriterInterceptor.h" #include "validation/tests/common/Common.h" #include "ckw/TensorSampler.h" #include "ckw/types/MemoryOperation.h" #include "ckw/types/TensorSamplerTypes.h" #include namespace ckw { class CLKernelWriterOpLoadStoreTest : public ITest { private: using AddressModeX = TensorSamplerAddressModeX; using AddressModeY = TensorSamplerAddressModeY; using AddressModeZ = TensorSamplerAddressModeZ; using Format = TensorSamplerFormat; using Storage = TensorStorageType; struct Coordinates { Coordinates(std::string x, std::string y, std::string z, std::string batch) : x(x), y(y), z(z), batch(batch) { } std::string x; std::string y; std::string z; std::string batch; }; struct SamplerData { SamplerData(Format format, AddressModeX mode_x, AddressModeY mode_y, AddressModeZ mode_z) : format(format), mode_x(mode_x), mode_y(mode_y), mode_z(mode_z) { } Format format; AddressModeX mode_x; AddressModeY mode_y; AddressModeZ mode_z; }; struct Dilations { Dilations(std::string dilation_x, std::string dilation_y) : dilation_x(dilation_x), dilation_y(dilation_y) { } std::string dilation_x; std::string dilation_y; }; using CLKernelWriterOpLoadStoreConfig = std::tuple; public: CLKernelWriterOpLoadStoreTest() { // Cases const std::string load_fp_2x3_tile = R"_( G0__tile__0 = vload3(0, (__global float*)(G0__tensor_ptr + (G0__x) * sizeof(float) + (G0__y + 0) * G0__tensor_stride1 + (G0__z) * G0__tensor_stride2 + (G0__b) * G0__tensor_stride3)); G0__tile__1 = vload3(0, (__global float*)(G0__tensor_ptr + (G0__x) * sizeof(float) + (G0__y + 1) * G0__tensor_stride1 + (G0__z) * G0__tensor_stride2 + (G0__b) * G0__tensor_stride3)); )_"; const std::string load_half_2x4_tile_image_clamp_y = R"_( G0__tile__0 = read_imageh(G0__tensor_img2d, CLK_NORMALIZED_COORDS_FALSE | CLK_ADDRESS_CLAMP | CLK_FILTER_NEAREST, (int2)((G0__x) >> 2, (G0__y + 0 + (G0__z) * G0__tensor_dim1 + (G0__b) * G0__tensor_dim1 * G0__tensor_dim2))); G0__tile__1 = read_imageh(G0__tensor_img2d, CLK_NORMALIZED_COORDS_FALSE | CLK_ADDRESS_CLAMP | CLK_FILTER_NEAREST, (int2)((G0__x) >> 2, (G0__y + 1 + (G0__z) * G0__tensor_dim1 + (G0__b) * G0__tensor_dim1 * G0__tensor_dim2))); )_"; const std::string store_fp_2x3_tile = R"_( vstore3(G0__tile__0, 0, (__global float*)(G0__tensor_ptr + (G0__x) * sizeof(float) + (G0__y + 0) * G0__tensor_stride1 + (G0__b) * G0__tensor_stride3)); vstore3(G0__tile__1, 0, (__global float*)(G0__tensor_ptr + (G0__x) * sizeof(float) + (G0__y + 1) * G0__tensor_stride1 + (G0__b) * G0__tensor_stride3)); )_"; const std::string store_int8_4x4_y_dilation_batch_eq_0 = R"_( vstore4(G0__tile__0, 0, (__global char*)(G0__tensor_ptr + (((int)(1))) * sizeof(char) + (G0__y + 0 * G0__y_dilation) * G0__tensor_stride1 + (G0__z) * G0__tensor_stride2 + (((int)(0))) * G0__tensor_stride3)); vstore4(G0__tile__1, 0, (__global char*)(G0__tensor_ptr + (((int)(1))) * sizeof(char) + (G0__y + 1 * G0__y_dilation) * G0__tensor_stride1 + (G0__z) * G0__tensor_stride2 + (((int)(0))) * G0__tensor_stride3)); vstore4(G0__tile__2, 0, (__global char*)(G0__tensor_ptr + (((int)(1))) * sizeof(char) + (G0__y + 2 * G0__y_dilation) * G0__tensor_stride1 + (G0__z) * G0__tensor_stride2 + (((int)(0))) * G0__tensor_stride3)); vstore4(G0__tile__3, 0, (__global char*)(G0__tensor_ptr + (((int)(1))) * sizeof(char) + (G0__y + 3 * G0__y_dilation) * G0__tensor_stride1 + (G0__z) * G0__tensor_stride2 + (((int)(0))) * G0__tensor_stride3)); )_"; // tensor dimension is 10 const std::string load_fp_2x3_tile_x_overlapping_min_y_eq_0_batch_eq_1 = R"_( if(G0__x > 0) { G0__tile__0 = vload3(0, (__global float*)(G0__tensor_ptr + (G0__x) * sizeof(float) + (((int)(0)) + 0) * G0__tensor_stride1 + (G0__z) * G0__tensor_stride2 + (((int)(1))) * G0__tensor_stride3)); G0__tile__1 = vload3(0, (__global float*)(G0__tensor_ptr + (G0__x) * sizeof(float) + (((int)(0)) + 1) * G0__tensor_stride1 + (G0__z) * G0__tensor_stride2 + (((int)(1))) * G0__tensor_stride3)); } else { G0__tile__0.s0 = *((__global float*)(G0__tensor_ptr + (G0__x + 0) * sizeof(float) + (((int)(0)) + 0) * G0__tensor_stride1 + (G0__z) * G0__tensor_stride2 + (((int)(1))) * G0__tensor_stride3)); G0__tile__1.s0 = *((__global float*)(G0__tensor_ptr + (G0__x + 0) * sizeof(float) + (((int)(0)) + 1) * G0__tensor_stride1 + (G0__z) * G0__tensor_stride2 + (((int)(1))) * G0__tensor_stride3)); } )_"; const std::string store_fp_2x3_tile_x_overlapping_min_y_clamp_to_border_max_only = R"_( if(G0__x > 0) { if(G0__y + 0 < G0__tensor_dim1) { vstore3(G0__tile__0, 0, (__global float*)(G0__tensor_ptr + (G0__x) * sizeof(float) + (G0__y + 0) * G0__tensor_stride1 + (G0__z) * G0__tensor_stride2 + (G0__b) * G0__tensor_stride3)); } else { G0__tile__0 = 0.0f; } if(G0__y + 1 < G0__tensor_dim1) { vstore3(G0__tile__1, 0, (__global float*)(G0__tensor_ptr + (G0__x) * sizeof(float) + (G0__y + 1) * G0__tensor_stride1 + (G0__z) * G0__tensor_stride2 + (G0__b) * G0__tensor_stride3)); } else { G0__tile__1 = 0.0f; } } else { if(G0__y + 0 < G0__tensor_dim1) { *((__global float*)(G0__tensor_ptr + (G0__x + 0) * sizeof(float) + (G0__y + 0) * G0__tensor_stride1 + (G0__z) * G0__tensor_stride2 + (G0__b) * G0__tensor_stride3)) = G0__tile__0.s0; } else { G0__tile__0.s0 = 0.0f; } if(G0__y + 1 < G0__tensor_dim1) { *((__global float*)(G0__tensor_ptr + (G0__x + 0) * sizeof(float) + (G0__y + 1) * G0__tensor_stride1 + (G0__z) * G0__tensor_stride2 + (G0__b) * G0__tensor_stride3)) = G0__tile__1.s0; } else { G0__tile__1.s0 = 0.0f; } } )_"; const std::string store_half_2x4_tile_x_image_y_dilation = R"_( write_imageh(G0__tensor_img2d, (int2)((G0__x) >> 2, (((int)(0)) + 0 * G0__y_dilation + (G0__z) * G0__tensor_dim1 + (((int)(1))) * G0__tensor_dim1 * G0__tensor_dim2)), G0__tile__0); write_imageh(G0__tensor_img2d, (int2)((G0__x) >> 2, (((int)(0)) + 1 * G0__y_dilation + (G0__z) * G0__tensor_dim1 + (((int)(1))) * G0__tensor_dim1 * G0__tensor_dim2)), G0__tile__1); )_"; // Configs Bundled _configs = { // op, tile, storage, sampler, coordinates, dilation, expected { MemoryOperation::Load, TileInfo(DataType::Fp32, 2, 3), TensorStorageType::BufferUint8Ptr, SamplerData(Format::Dim0_Dim1_Dim2, AddressModeX::None, AddressModeY::None, AddressModeZ::None), Coordinates("x", "y", "z", "b"), Dilations("1", "1"), load_fp_2x3_tile }, { MemoryOperation::Load, TileInfo(DataType::Fp16, 2, 4), TensorStorageType::Texture2dReadOnly, SamplerData(Format::Dim0_Dim1_Dim2, AddressModeX::None, AddressModeY::ClampToBorderMaxOnly, AddressModeZ::None), Coordinates("x", "y", "z", "b"), Dilations("1", "1"), load_half_2x4_tile_image_clamp_y }, { MemoryOperation::Store, TileInfo(DataType::Fp32, 2, 3), TensorStorageType::BufferUint8Ptr, SamplerData(Format::Dim0_Dim1xDim2_1,AddressModeX::None, AddressModeY::None, AddressModeZ::None), Coordinates("x", "y", "z", "b"), Dilations("1", "1"), store_fp_2x3_tile }, { MemoryOperation::Store, TileInfo(DataType::Int8, 4, 4), TensorStorageType::BufferUint8Ptr, SamplerData(Format::Dim0_Dim1_Dim2, AddressModeX::None, AddressModeY::None, AddressModeZ::None), Coordinates("1", "y", "z", "0"), Dilations("1", "y_dilation"), store_int8_4x4_y_dilation_batch_eq_0 }, { MemoryOperation::Load, TileInfo(DataType::Fp32, 2, 3), TensorStorageType::BufferUint8Ptr, SamplerData(Format::Dim0_Dim1_Dim2, AddressModeX::OverlappingMin, AddressModeY::None, AddressModeZ::None), Coordinates("x", "0", "z", "1"), Dilations("1", "1"), load_fp_2x3_tile_x_overlapping_min_y_eq_0_batch_eq_1 }, { MemoryOperation::Store, TileInfo(DataType::Fp32, 2, 3), TensorStorageType::BufferUint8Ptr, SamplerData(Format::Dim0_Dim1_Dim2, AddressModeX::OverlappingMin, AddressModeY::ClampToBorderMaxOnly, AddressModeZ::None), Coordinates("x", "y", "z", "b"), Dilations("1", "1"), store_fp_2x3_tile_x_overlapping_min_y_clamp_to_border_max_only }, { MemoryOperation::Store, TileInfo(DataType::Fp16, 2, 4), TensorStorageType::Texture2dWriteOnly, SamplerData(Format::Dim0_Dim1_Dim2, AddressModeX::None, AddressModeY::None, AddressModeZ::None), Coordinates("x", "0", "z", "1"), Dilations("1", "y_dilation"), store_half_2x4_tile_x_image_y_dilation } }; } TileOperand declare_tile_helper(KernelWriter &writer, std::string tile) { if(tile == "0" || tile == "1") { return writer.declare_constant_tile(ConstantData({{std::stoi(tile)}}, DataType::Int32)); } else { return writer.declare_tile(tile, TileInfo(DataType::Int32)); } } bool run() override { bool all_tests_passed = true; int32_t test_idx = 0; for(auto _config: _configs) { KernelWriterInterceptor writer; const MemoryOperation op = std::get<0>(_config); const TileInfo tile_info = std::get<1>(_config); const Storage storage = std::get<2>(_config); const SamplerData sampler_data = std::get<3>(_config); const Coordinates coord = std::get<4>(_config); const Dilations dilations = std::get<5>(_config); const std::string expected_code = std::get<6>(_config).substr(1); // ignore initial newline, which was added for convenience TileOperand tile_op = writer.declare_tile("tile", tile_info); TileOperand x_op = declare_tile_helper(writer, coord.x); TileOperand y_op = declare_tile_helper(writer, coord.y); TileOperand z_op = declare_tile_helper(writer, coord.z); TileOperand batch_op = declare_tile_helper(writer, coord.batch); TileOperand dil_x_op = declare_tile_helper(writer, dilations.dilation_x); TileOperand dil_y_op = declare_tile_helper(writer, dilations.dilation_y); TensorShape tensor_shape {10, 10, 10, 10}; TensorInfo tensor_info(tile_info.data_type(), tensor_shape, TensorDataLayout::Nhwc, 0 /* id */); TensorOperand tensor_op = writer.declare_tensor_argument("tensor", tensor_info); TensorSampler sampler(storage, sampler_data.format, sampler_data.mode_x, sampler_data.mode_y, sampler_data.mode_z); const bool no_dilation = (dilations.dilation_x == "1" && dilations.dilation_y == "1"); writer.start_capture_code(); if(op == MemoryOperation::Load) { if(no_dilation) { writer.op_load(tile_op, tensor_op, sampler, x_op, y_op, z_op, batch_op); } else { writer.op_load_dilated(tile_op, tensor_op, sampler, x_op, y_op, z_op, batch_op, dil_x_op, dil_y_op); } } else { if(no_dilation) { writer.op_store(tensor_op, tile_op, sampler, x_op, y_op, z_op, batch_op); } else { writer.op_store_dilated(tensor_op, tile_op, sampler, x_op, y_op, z_op, batch_op, dil_x_op, dil_y_op); } } VALIDATE_TEST(writer.check_added_code(expected_code), all_tests_passed, test_idx++); } return all_tests_passed; } std::string name() override { return "CLKernelWriterOpLoadStoreTest"; } private: std::vector _configs {}; }; } // namespace ckw #endif // CKW_VALIDATION_TESTS_CLKERNELWRITEROPLOADSTORETEST_H