From c3b9bd6cb3b7c6a692c3f033153f57ddb1c396b6 Mon Sep 17 00:00:00 2001 From: WuXintong123 <13683168028@163.com> Date: Mon, 31 Mar 2025 04:05:29 +0000 Subject: [PATCH 1/2] LeNet --- examples/CMakeLists.txt | 4 + examples/HeterLeNet/.gitignore | 10 ++ examples/HeterLeNet/CMakeLists.txt | 163 ++++++++++++++++++ examples/HeterLeNet/README.md | 104 +++++++++++ examples/HeterLeNet/buddy-lenet-import.py | 126 ++++++++++++++ examples/HeterLeNet/buddy-lenet-main.cpp | 150 ++++++++++++++++ examples/HeterLeNet/images/0-28*28.png | Bin 0 -> 1850 bytes examples/HeterLeNet/images/0.png | Bin 0 -> 6765 bytes examples/HeterLeNet/images/1-28*28.png | Bin 0 -> 1439 bytes examples/HeterLeNet/images/1.png | Bin 0 -> 4597 bytes examples/HeterLeNet/images/2.png | Bin 0 -> 7304 bytes examples/HeterLeNet/images/3.png | Bin 0 -> 6847 bytes examples/HeterLeNet/images/4.png | Bin 0 -> 6113 bytes examples/HeterLeNet/images/5.png | Bin 0 -> 5615 bytes examples/HeterLeNet/images/6.png | Bin 0 -> 6500 bytes examples/HeterLeNet/images/7.png | Bin 0 -> 6377 bytes .../HeterLeNet/images/8-16bit-565-28*28.bmp | Bin 0 -> 1634 bytes examples/HeterLeNet/images/8-24bit-28*28.bmp | Bin 0 -> 2406 bytes examples/HeterLeNet/images/8.bmp | Bin 0 -> 3190 bytes examples/HeterLeNet/images/8.png | Bin 0 -> 6195 bytes examples/HeterLeNet/images/9.png | Bin 0 -> 5031 bytes examples/HeterLeNet/model.py | 41 +++++ examples/lit.cfg.py | 1 + 23 files changed, 599 insertions(+) create mode 100644 examples/HeterLeNet/.gitignore create mode 100644 examples/HeterLeNet/CMakeLists.txt create mode 100644 examples/HeterLeNet/README.md create mode 100644 examples/HeterLeNet/buddy-lenet-import.py create mode 100644 examples/HeterLeNet/buddy-lenet-main.cpp create mode 100644 examples/HeterLeNet/images/0-28*28.png create mode 100644 examples/HeterLeNet/images/0.png create mode 100644 examples/HeterLeNet/images/1-28*28.png create mode 100644 examples/HeterLeNet/images/1.png create mode 100644 examples/HeterLeNet/images/2.png create mode 100644 examples/HeterLeNet/images/3.png create mode 100644 examples/HeterLeNet/images/4.png create mode 100644 examples/HeterLeNet/images/5.png create mode 100644 examples/HeterLeNet/images/6.png create mode 100644 examples/HeterLeNet/images/7.png create mode 100644 examples/HeterLeNet/images/8-16bit-565-28*28.bmp create mode 100644 examples/HeterLeNet/images/8-24bit-28*28.bmp create mode 100644 examples/HeterLeNet/images/8.bmp create mode 100644 examples/HeterLeNet/images/8.png create mode 100644 examples/HeterLeNet/images/9.png create mode 100644 examples/HeterLeNet/model.py diff --git a/examples/CMakeLists.txt b/examples/CMakeLists.txt index acdbeced..28035863 100644 --- a/examples/CMakeLists.txt +++ b/examples/CMakeLists.txt @@ -12,6 +12,10 @@ if(BUDDY_DIS_LLAMA_EXAMPLES) add_subdirectory(LlamaTest) endif() +if(BUDDY_HETER_LENET_EXAMPLES) + add_subdirectory(HeterLeNet) +endif() + if(BUDDY_DEEPSEEKR1_EXAMPLES) add_subdirectory(BuddyDeepSeekR1) endif() diff --git a/examples/HeterLeNet/.gitignore b/examples/HeterLeNet/.gitignore new file mode 100644 index 00000000..8ef196d7 --- /dev/null +++ b/examples/HeterLeNet/.gitignore @@ -0,0 +1,10 @@ +log.mlir +log.ll +log.s +data +*.data +__pycache__ +*.pth +lenet.mlir +forward.mlir +subgraph0.mlir diff --git a/examples/HeterLeNet/CMakeLists.txt b/examples/HeterLeNet/CMakeLists.txt new file mode 100644 index 00000000..6e3c3db7 --- /dev/null +++ b/examples/HeterLeNet/CMakeLists.txt @@ -0,0 +1,163 @@ +add_custom_command( + OUTPUT ${CMAKE_CURRENT_BINARY_DIR}/forward0.mlir + ${CMAKE_CURRENT_BINARY_DIR}/forward1.mlir + ${CMAKE_CURRENT_BINARY_DIR}/subgraph0.mlir + ${CMAKE_CURRENT_BINARY_DIR}/subgraph1.mlir + ${CMAKE_CURRENT_BINARY_DIR}/arg0.data + COMMAND ${Python3_EXECUTABLE} ${CMAKE_CURRENT_SOURCE_DIR}/buddy-lenet-import.py + --output-dir ${CMAKE_CURRENT_BINARY_DIR} + COMMENT "Generating forward.mlir, subgraph0.mlir and parameter files" +) + +add_custom_command( + OUTPUT forward0.o + COMMAND ${LLVM_TOOLS_BINARY_DIR}/mlir-opt ${CMAKE_CURRENT_BINARY_DIR}/forward0.mlir + -pass-pipeline "builtin.module(func.func(tosa-to-linalg-named, tosa-to-linalg, tosa-to-tensor, tosa-to-arith), empty-tensor-to-alloc-tensor, convert-elementwise-to-linalg, arith-bufferize, func.func(linalg-bufferize, tensor-bufferize), func-bufferize)" | + ${LLVM_TOOLS_BINARY_DIR}/mlir-opt + -pass-pipeline "builtin.module(func.func(buffer-deallocation-simplification, convert-linalg-to-loops), eliminate-empty-tensors, func.func(llvm-request-c-wrappers),convert-math-to-llvm, convert-math-to-libm, convert-scf-to-cf, convert-arith-to-llvm, expand-strided-metadata, finalize-memref-to-llvm, convert-func-to-llvm, reconcile-unrealized-casts)" | + ${LLVM_TOOLS_BINARY_DIR}/mlir-translate -mlir-to-llvmir | + ${LLVM_TOOLS_BINARY_DIR}/llvm-as | + ${LLVM_TOOLS_BINARY_DIR}/llc -filetype=obj -relocation-model=pic -O0 -o ${CMAKE_CURRENT_BINARY_DIR}/forward0.o + DEPENDS ${CMAKE_CURRENT_BINARY_DIR}/forward0.mlir + COMMENT "Building forward0.o" + VERBATIM) + +add_custom_command( + OUTPUT subgraph0.o + COMMAND ${LLVM_TOOLS_BINARY_DIR}/mlir-opt ${CMAKE_CURRENT_BINARY_DIR}/subgraph0.mlir + -pass-pipeline "builtin.module(func.func(tosa-to-linalg-named, tosa-to-linalg, tosa-to-tensor, tosa-to-arith))" | + ${BUDDY_BINARY_DIR}/buddy-opt + -eliminate-empty-tensors + -convert-tensor-to-linalg + -linalg-bufferize + -batchmatmul-optimize + -convert-linalg-to-affine-loops + -lower-affine + -func-bufferize-dynamic-offset + -arith-bufferize + -tensor-bufferize + -buffer-deallocation + -finalizing-bufferize + -convert-vector-to-scf + -expand-strided-metadata + -convert-vector-to-llvm + -convert-arith-to-llvm + -finalize-memref-to-llvm + -convert-scf-to-cf + -llvm-request-c-wrappers + -convert-arith-to-llvm + -convert-func-to-llvm + -reconcile-unrealized-casts | + ${LLVM_TOOLS_BINARY_DIR}/mlir-translate -mlir-to-llvmir | + ${LLVM_TOOLS_BINARY_DIR}/llvm-as | + ${LLVM_TOOLS_BINARY_DIR}/llc -filetype=obj -relocation-model=pic -O0 -o ${CMAKE_CURRENT_BINARY_DIR}/subgraph0.o + DEPENDS ${CMAKE_CURRENT_BINARY_DIR}/subgraph0.mlir + COMMENT "Building subgraph0.o" + VERBATIM) + + add_custom_command( + OUTPUT forward1.o + COMMAND ${LLVM_TOOLS_BINARY_DIR}/mlir-opt ${CMAKE_CURRENT_BINARY_DIR}/forward1.mlir + -pass-pipeline "builtin.module(func.func(tosa-to-linalg-named, tosa-to-linalg, tosa-to-tensor, tosa-to-arith), empty-tensor-to-alloc-tensor, convert-elementwise-to-linalg, arith-bufferize, func.func(linalg-bufferize, tensor-bufferize), func-bufferize)" | + ${LLVM_TOOLS_BINARY_DIR}/mlir-opt + -pass-pipeline "builtin.module(func.func(buffer-deallocation-simplification, convert-linalg-to-loops), eliminate-empty-tensors, func.func(llvm-request-c-wrappers),convert-math-to-llvm, convert-math-to-libm, convert-scf-to-cf, convert-arith-to-llvm, expand-strided-metadata, finalize-memref-to-llvm, convert-func-to-llvm, reconcile-unrealized-casts)" | + ${LLVM_TOOLS_BINARY_DIR}/mlir-translate -mlir-to-llvmir | + ${LLVM_TOOLS_BINARY_DIR}/llvm-as | + ${LLVM_TOOLS_BINARY_DIR}/llc -filetype=obj -relocation-model=pic -O0 -o ${CMAKE_CURRENT_BINARY_DIR}/forward1.o + DEPENDS ${CMAKE_CURRENT_BINARY_DIR}/forward1.mlir + COMMENT "Building forward1.o" + VERBATIM) + + add_custom_command( + OUTPUT subgraph1.o + COMMAND ${LLVM_TOOLS_BINARY_DIR}/mlir-opt ${CMAKE_CURRENT_BINARY_DIR}/subgraph1.mlir + -pass-pipeline "builtin.module(func.func(tosa-to-linalg-named, tosa-to-linalg, tosa-to-tensor, tosa-to-arith))" | + ${BUDDY_BINARY_DIR}/buddy-opt + -eliminate-empty-tensors + -convert-tensor-to-linalg + -linalg-bufferize + -batchmatmul-optimize + -convert-linalg-to-affine-loops + -lower-affine + -func-bufferize-dynamic-offset + -arith-bufferize + -tensor-bufferize + -buffer-deallocation + -finalizing-bufferize + -convert-vector-to-scf + -expand-strided-metadata + -convert-vector-to-llvm + -convert-arith-to-llvm + -finalize-memref-to-llvm + -convert-scf-to-cf + -llvm-request-c-wrappers + -convert-arith-to-llvm + -convert-func-to-llvm + -reconcile-unrealized-casts | + ${LLVM_TOOLS_BINARY_DIR}/mlir-translate -mlir-to-llvmir | + ${LLVM_TOOLS_BINARY_DIR}/llvm-as | + ${LLVM_TOOLS_BINARY_DIR}/llc -filetype=obj -relocation-model=pic -O0 -o ${CMAKE_CURRENT_BINARY_DIR}/subgraph1.o + DEPENDS ${CMAKE_CURRENT_BINARY_DIR}/subgraph1.mlir + COMMENT "Building subgraph1.o" + VERBATIM) +set(LENET_EXAMPLE_PATH ${CMAKE_CURRENT_SOURCE_DIR}) +set(LENET_EXAMPLE_BUILD_PATH ${CMAKE_CURRENT_BINARY_DIR}) + +# set(ONE_SHOT_BUFFERIZE_OPTION "bufferize-function-boundaries=1 function-boundary-type-conversion=identity-layout-map") +# set(LOWER_TO_NVVM_OPTION "cubin-chip=sm_80 cubin-features=+ptx71 cubin-format=fatbin") +# set(CONVERT_MEMCPY_TO_GPU_OPTION "process-args=1") +# set(CONVERT_MEMCPY_TO_GPU_OPTION_DISABLE_PROCESS_ARG "process-args=0") + +# add_custom_command( +# OUTPUT forward1.o +# COMMAND ${BUDDY_BINARY_DIR}/buddy-opt ${CMAKE_CURRENT_BINARY_DIR}/forward1.mlir +# -buffer-deallocation +# -canonicalize -cse -expand-strided-metadata -convert-memcpy-to-gpu -gpu-async-region | +# ${LLVM_TOOLS_BINARY_DIR}/mlir-opt -llvm-request-c-wrappers --gpu-to-llvm | +# ${LLVM_TOOLS_BINARY_DIR}/mlir-translate -mlir-to-llvmir | +# ${LLVM_TOOLS_BINARY_DIR}/llvm-as | +# ${LLVM_TOOLS_BINARY_DIR}/llc -filetype=obj -relocation-model=pic -O0 -o ${CMAKE_CURRENT_BINARY_DIR}/forward1.o +# DEPENDS ${CMAKE_CURRENT_BINARY_DIR}/forward1.mlir +# COMMENT "Building forward1.o" +# VERBATIM) + +# add_custom_command( +# OUTPUT subgraph1.o +# COMMAND ${LLVM_TOOLS_BINARY_DIR}/mlir-opt ${CMAKE_CURRENT_BINARY_DIR}/subgraph1.mlir +# -pass-pipeline "builtin.module(func.func(tosa-to-linalg-named, tosa-to-linalg, tosa-to-tensor, tosa-to-arith))" | +# ${BUDDY_BINARY_DIR}/buddy-opt +# -one-shot-bufferize +# -func-bufferize-dynamic-offset +# -convert-linalg-to-parallel-loops +# -canonicalize +# -gpu-map-parallel-loops +# -convert-parallel-loops-to-gpu +# -gpu-kernel-outlining +# -buffer-deallocation +# -canonicalize +# -cse | +# ${BUDDY_BINARY_DIR}/buddy-opt -convert-memcpy-to-gpu=${CONVERT_MEMCPY_TO_GPU_OPTION_DISABLE_PROCESS_ARG} -gpu-async-region -canonicalize | +# ${LLVM_TOOLS_BINARY_DIR}/mlir-opt -llvm-request-c-wrappers --test-lower-to-nvvm=${LOWER_TO_NVVM_OPTION} | +# ${LLVM_TOOLS_BINARY_DIR}/mlir-translate -mlir-to-llvmir | +# ${LLVM_TOOLS_BINARY_DIR}/llvm-as | +# ${LLVM_TOOLS_BINARY_DIR}/llc -filetype=obj -relocation-model=pic -O0 -o ${CMAKE_CURRENT_BINARY_DIR}/subgraph1.o +# DEPENDS ${CMAKE_CURRENT_BINARY_DIR}/subgraph1.mlir +# COMMENT "Building subgraph1.o" +# VERBATIM) + +add_library(LENET_HETER0 STATIC subgraph0.o forward0.o) +add_library(LENET_HETER1 STATIC subgraph1.o forward1.o) + +SET_TARGET_PROPERTIES(LENET_HETER0 LENET_HETER1 PROPERTIES LINKER_LANGUAGE C) + +add_executable(buddy-lenet-run-heter buddy-lenet-main.cpp) +target_link_directories(buddy-lenet-run-heter PRIVATE ${LLVM_LIBRARY_DIR}) + +set(BUDDY_LENET_LIBS_GPU LENET_HETER0 LENET_HETER1 mlir_c_runner_utils mlir_async_runtime mlir_runner_utils ${PNG_LIBRARIES}) + +target_link_libraries(buddy-lenet-run-heter ${BUDDY_LENET_LIBS_GPU}) + +target_compile_definitions(buddy-lenet-run-heter PRIVATE + LENET_EXAMPLE_PATH="${LENET_EXAMPLE_PATH}" + LENET_EXAMPLE_BUILD_PATH="${LENET_EXAMPLE_BUILD_PATH}" +) diff --git a/examples/HeterLeNet/README.md b/examples/HeterLeNet/README.md new file mode 100644 index 00000000..15528451 --- /dev/null +++ b/examples/HeterLeNet/README.md @@ -0,0 +1,104 @@ +# Buddy Compiler LeNet Example + +## Train the LeNet Model + +Activate your python environment. + +```bash +$ cd buddy-mlir +$ cd examples/BuddyLeNet +$ python pytorch-lenet-train.py +``` + +## LeNet Model Inference + +### Activate your python environment. + +```bash +$ conda activate +``` + +### Build LLVM + +```bash +$ cd buddy-mlir +$ mkdir llvm/build +$ cd llvm/build + +// CPU +$ cmake -G Ninja ../llvm \ + -DLLVM_ENABLE_PROJECTS="mlir;clang;openmp" \ + -DLLVM_TARGETS_TO_BUILD="host;RISCV" \ + -DLLVM_ENABLE_ASSERTIONS=ON \ + -DOPENMP_ENABLE_LIBOMPTARGET=OFF \ + -DCMAKE_BUILD_TYPE=RELEASE \ + -DMLIR_ENABLE_BINDINGS_PYTHON=ON \ + -DPython3_EXECUTABLE=$(which python3) + +// GPU +$ cmake -G Ninja ../llvm \ + -DLLVM_ENABLE_PROJECTS="mlir;clang;openmp" \ + -DLLVM_TARGETS_TO_BUILD="host;RISCV;NVPTX" \ + -DMLIR_ENABLE_CUDA_RUNNER=ON \ + -DLLVM_ENABLE_ASSERTIONS=ON \ + -DOPENMP_ENABLE_LIBOMPTARGET=OFF \ + -DCMAKE_BUILD_TYPE=RELEASE \ + -DMLIR_ENABLE_BINDINGS_PYTHON=ON \ + -DPython3_EXECUTABLE=$(which python3) + +$ ninja check-clang check-mlir omp +``` + +### Build buddy-mlir + +```bash +$ cd buddy-mlir +$ mkdir build && cd build +$ cmake -G Ninja .. \ + -DMLIR_DIR=$PWD/../llvm/build/lib/cmake/mlir \ + -DLLVM_DIR=$PWD/../llvm/build/lib/cmake/llvm \ + -DLLVM_ENABLE_ASSERTIONS=ON \ + -DCMAKE_BUILD_TYPE=RELEASE \ + -DBUDDY_MLIR_ENABLE_PYTHON_PACKAGES=ON \ + -DPython3_EXECUTABLE=$(which python3) \ + -DBUDDY_MLIR_ENABLE_DIP_LIB=ON \ + -DBUDDY_ENABLE_PNG=ON +$ ninja +$ ninja check-buddy +``` + +### Set the `PYTHONPATH` environment variable. + +Make sure you are in the build directory. + +```bash +$ export BUDDY_MLIR_BUILD_DIR=$PWD +$ export LLVM_MLIR_BUILD_DIR=$PWD/../llvm/build +$ export PYTHONPATH=${LLVM_MLIR_BUILD_DIR}/tools/mlir/python_packages/mlir_core:${BUDDY_MLIR_BUILD_DIR}/python_packages:${PYTHONPATH} +``` + +### Build and run the LeNet example + +```bash +$ cmake -G Ninja .. -DBUDDY_LENET_EXAMPLES=ON + +// CPU +$ ninja buddy-lenet-run +$ cd bin +$ ./buddy-lenet-run + +// GPU +$ ninja buddy-lenet-run-gpu +$ cd bin +$ ./buddy-lenet-run-gpu +``` + +## Debug the Lowering Pass Pipeline with Fake Parameters. + +```bash +$ cd buddy-mlir +$ cd examples/BuddyLeNet +$ make buddy-lenet-lower +$ make buddy-lenet-translate +$ make buddy-lenet-run +``` diff --git a/examples/HeterLeNet/buddy-lenet-import.py b/examples/HeterLeNet/buddy-lenet-import.py new file mode 100644 index 00000000..6117e385 --- /dev/null +++ b/examples/HeterLeNet/buddy-lenet-import.py @@ -0,0 +1,126 @@ +# ===- buddy-lenet-import.py --------------------------------------------------- +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# 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. +# +# ===--------------------------------------------------------------------------- +# +# This is the LeNet model AOT importer. +# +# ===--------------------------------------------------------------------------- + +import os +from pathlib import Path +import argparse + +import numpy as np +import torch +from buddy.compiler.frontend import DynamoCompiler +from buddy.compiler.graph import GraphDriver +from buddy.compiler.graph.type import DeviceType +from buddy.compiler.graph.transform import simply_fuse, apply_classic_fusion +from buddy.compiler.ops import tosa +from buddy.compiler.graph.operation import * +from model import LeNet + +# Parse command-line arguments. +parser = argparse.ArgumentParser(description="LeNet model AOT importer") +parser.add_argument( + "--output-dir", + type=str, + default="./", + help="Directory to save output files." +) +args = parser.parse_args() + +# Ensure output directory exists. +output_dir = Path(args.output_dir) +output_dir.mkdir(parents=True, exist_ok=True) + +# Retrieve the LeNet model path. +model_path = os.path.dirname(os.path.abspath(__file__)) + +model = LeNet() +model = torch.load(model_path + "/lenet-model.pth", weights_only=False) +model = model.eval() + +# Initialize Dynamo Compiler with specific configurations as an importer. +dynamo_compiler = DynamoCompiler( + primary_registry=tosa.ops_registry, +) + +data = torch.randn([1, 1, 28, 28]) +# Import the model into MLIR module and parameters. +with torch.no_grad(): + graphs = dynamo_compiler.importer(model, data) + +graph = graphs[0] +params = dynamo_compiler.imported_params[graph] +group = [] +for i, op in enumerate(graph._body): + if isinstance(op, PlaceholderOp) or isinstance(op, OutputOp) or i == 25: + continue + group.append(op) + subgraph_name = "subgraph0" + graph.group_map_device[subgraph_name] = DeviceType.CPU + graph.op_groups[subgraph_name] = group +new_group = [graph._body[25]] +subgraph_name = "subgraph1" +graph.group_map_device[subgraph_name] = DeviceType.GPU +graph.op_groups[subgraph_name] = new_group + +# pattern_list = [simply_fuse] +# graphs[0].fuse_ops(pattern_list) +driver = GraphDriver(graphs[0]) +for i in range(len(driver.subgraphs)): + driver.subgraphs[i].lower_to_top_level_ir() +# driver.subgraphs[0].lower_to_top_level_ir() +driver.construct_main_graph(True) +# Save the generated files to the specified output directory. +for i in range(len(driver.modules)): + with open(os.path.join(output_dir, f"subgraph{i}.mlir"), "w") as module_file: + print(driver.subgraphs[i]._imported_module, file=module_file) + with open(os.path.join(output_dir, f"forward{i}.mlir"), "w") as module_file: + print(driver.modules[i], file=module_file) + # 从 GraphDriver 中获取该子图收集到的参数索引列表 + param_indices = driver.subgraph_param_indices[i] + + # 根据参数索引从 loaded_params 中提取参数，并拼接为一维数组 + selected_arrays = [] + js = 0 + for idx in param_indices: + # 注意：loaded_params 中的每个参数都是一个 tensor + arr = params[idx].detach().cpu().numpy().reshape(-1) + print(len(arr)) + js = js + len(arr) + selected_arrays.append(arr) + print(js) + if selected_arrays: + concat_arr = np.concatenate(selected_arrays) + else: + concat_arr = np.array([]) + + # 定义输出文件名，数字 i 与子图对应 + filename = os.path.join(output_dir, f"arg{i}.data") + concat_arr.tofile(filename) +# with open(output_dir / "subgraph0.mlir", "w") as module_file: +# print(driver.subgraphs[0]._imported_module, file=module_file) +# with open(output_dir / "forward.mlir", "w") as module_file: +# print(driver.construct_main_graph(True), file=module_file) + +# params = dynamo_compiler.imported_params[graph] + +# float32_param = np.concatenate( +# [param.detach().numpy().reshape([-1]) for param in params] +# ) + +# float32_param.tofile(output_dir / "arg0.data") diff --git a/examples/HeterLeNet/buddy-lenet-main.cpp b/examples/HeterLeNet/buddy-lenet-main.cpp new file mode 100644 index 00000000..708f83b6 --- /dev/null +++ b/examples/HeterLeNet/buddy-lenet-main.cpp @@ -0,0 +1,150 @@ +//===- buddy-lenet-main.cpp -----------------------------------------------===// +// +// Licensed under the Apache License, Version 2.0 (the "License"); +// you may not use this file except in compliance with the License. +// You may obtain a copy of the License at +// +// http://www.apache.org/licenses/LICENSE-2.0 +// +// 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. +// +//===----------------------------------------------------------------------===// + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +constexpr size_t ParamsSize0 = 44416; +constexpr size_t ParamsSize1 = 10; + +const std::string ImgName = "1-28*28.png"; + +/// Declare LeNet forward function. +extern "C" void _mlir_ciface_forward0(MemRef *output0, + MemRef *output1, + MemRef *arg0, + dip::Image *input); +extern "C" void _mlir_ciface_forward1(MemRef *output, + MemRef *arg1, + MemRef *output0, + MemRef *output1); +/// Print [Log] label in bold blue format. +void printLogLabel() { std::cout << "\033[34;1m[Log] \033[0m"; } + +/// Load parameters into data container. +void loadParameters(const std::string ¶mFilePath, + MemRef ¶ms) { + const auto loadStart = std::chrono::high_resolution_clock::now(); + // Open the parameter file in binary mode. + std::ifstream paramFile(paramFilePath, std::ios::in | std::ios::binary); + if (!paramFile.is_open()) { + throw std::runtime_error("[Error] Failed to open params file!"); + } + printLogLabel(); + std::cout << "Loading params..." << std::endl; + printLogLabel(); + // Print the canonical path of the parameter file. + std::cout << "Params file: " << std::filesystem::canonical(paramFilePath) + << std::endl; + // Read the parameter data into the provided memory reference. + paramFile.read(reinterpret_cast(params.getData()), + sizeof(float) * (params.getSize())); + if (paramFile.fail()) { + throw std::runtime_error("Error occurred while reading params file!"); + } + paramFile.close(); + const auto loadEnd = std::chrono::high_resolution_clock::now(); + const std::chrono::duration loadTime = + loadEnd - loadStart; + printLogLabel(); + std::cout << "Params load time: " << (double)(loadTime.count()) / 1000 + << "s\n" + << std::endl; +} + +/// Softmax function to convert logits to probabilities. +void softmax(float *input, size_t size) { + size_t i; + float max_value = -INFINITY; + double sum = 0.0; + // Find the maximum value in the input array for numerical stability. + for (i = 0; i < size; ++i) { + if (max_value < input[i]) { + max_value = input[i]; + } + } + // Calculate the sum of the exponentials of the input elements, normalized by + // the max value. + for (i = 0; i < size; ++i) { + sum += exp(input[i] - max_value); + } + // Normalize the input array with the softmax calculation. + for (i = 0; i < size; ++i) { + input[i] = exp(input[i] - max_value) / sum; + } +} + +int main() { + // Print the title of this example. + const std::string title = "LeNet Inference Powered by Buddy Compiler"; + std::cout << "\033[33;1m" << title << "\033[0m" << std::endl; + + // Define the sizes of the output tensors. + intptr_t sizesOutput[2] = {1, 10}; + intptr_t sizesOutput0[2] = {1, 84}; + intptr_t sizesOutput1[2] = {84, 10}; + + // Create input and output containers for the image and model output. + std::string lenetDir = LENET_EXAMPLE_PATH; + std::string lenetBuildDir = LENET_EXAMPLE_BUILD_PATH; + std::string imgPath = lenetDir + "/images/" + ImgName; + dip::Image input(imgPath, dip::DIP_GRAYSCALE, true /* norm */); + MemRef output(sizesOutput); + MemRef output0(sizesOutput0); + MemRef output1(sizesOutput1); + // Load model parameters from the specified file. + + std::string paramsDir0 = lenetBuildDir + "/arg0.data"; + std::cout << paramsDir0 << std::endl; + MemRef paramsContainer0({ParamsSize0}); + loadParameters(paramsDir0, paramsContainer0); + std::string paramsDir1 = lenetBuildDir + "/arg1.data"; + MemRef paramsContainer1({ParamsSize1}); + loadParameters(paramsDir1, paramsContainer1); + std::cout << "++++++++++" << std::endl; + // Call the forward function of the model. + _mlir_ciface_forward0(&output0, &output1, ¶msContainer0, &input); + std::cout << "++++++++++" << std::endl; + _mlir_ciface_forward1(&output, ¶msContainer1, &output0, &output1); + std::cout << "++++++++++" << std::endl; + // Apply softmax to the output logits to get probabilities. + auto out = output.getData(); + softmax(out, 10); + + // Find the classification and print the result. + float maxVal = 0; + float maxIdx = 0; + for (int i = 0; i < 10; ++i) { + if (out[i] > maxVal) { + maxVal = out[i]; + maxIdx = i; + } + } + + std::cout << "Classification: " << maxIdx << std::endl; + std::cout << "Probability: " << maxVal << std::endl; + + return 0; +} diff --git a/examples/HeterLeNet/images/0-28*28.png b/examples/HeterLeNet/images/0-28*28.png new file mode 100644 index 0000000000000000000000000000000000000000..a7a3b2a327dfaa54515fe5b24ac6c1261745ca75 GIT binary patch literal 1850 zcmV-A2gUe_P)4Tx04UFWkWWhjQ540`s3nvOqX?1~vk0QFkWnexnMDOI1}*vnEykyff=-W_ ziD(mjfR@pwee?~a2X 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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. +# +# ===--------------------------------------------------------------------------- +# +# LeNet model definition. +# +# ===--------------------------------------------------------------------------- + +import torch +import torch.nn as nn + +class LeNet(nn.Module): + def __init__(self): + super(LeNet, self).__init__() + self.conv1 = nn.Conv2d(1, 6, 5) + self.pool = nn.MaxPool2d(2, 2) + self.conv2 = nn.Conv2d(6, 16, 5) + self.fc1 = nn.Linear(16 * 4 * 4, 120) + self.fc2 = nn.Linear(120, 84) + self.fc3 = nn.Linear(84, 10) + + def forward(self, x): + x = self.pool(torch.relu(self.conv1(x))) + x = self.pool(torch.relu(self.conv2(x))) + x = x.view(-1, 16 * 4 * 4) + x = torch.relu(self.fc1(x)) + x = torch.relu(self.fc2(x)) + x = self.fc3(x) + return x diff --git a/examples/lit.cfg.py b/examples/lit.cfg.py index 7282a5bd..efbb7c0f 100644 --- a/examples/lit.cfg.py +++ b/examples/lit.cfg.py @@ -46,6 +46,7 @@ 'BuddyDeepSeekR1' 'BuddyResNet18', 'BuddyGPU', + 'HeterLeNet', 'ConvOpt', 'DAPDialect', 'DIPDialect', From c6db7fe8dd069d91fac2a04e1e6a3abd239967cd Mon Sep 17 00:00:00 2001 From: WuXintong123 <13683168028@163.com> Date: Fri, 30 May 2025 05:07:03 +0000 Subject: [PATCH 2/2] wuxintong --- examples/HeterLeNet/CMakeCache.txt | 379 +++++++++ .../CMakeFiles/3.22.1/CMakeCCompiler.cmake | 72 ++ .../CMakeFiles/3.22.1/CMakeCXXCompiler.cmake | 83 ++ .../3.22.1/CMakeDetermineCompilerABI_C.bin | Bin 0 -> 15968 bytes .../3.22.1/CMakeDetermineCompilerABI_CXX.bin | Bin 0 -> 15992 bytes .../CMakeFiles/3.22.1/CMakeSystem.cmake | 15 + .../3.22.1/CompilerIdC/CMakeCCompilerId.c | 803 ++++++++++++++++++ .../CMakeFiles/3.22.1/CompilerIdC/a.out | Bin 0 -> 16088 bytes 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DEC(__TI_COMPILER_VERSION__/1000000) +# define COMPILER_VERSION_MINOR DEC(__TI_COMPILER_VERSION__/1000 % 1000) +# define COMPILER_VERSION_PATCH DEC(__TI_COMPILER_VERSION__ % 1000) + +#elif defined(__CLANG_FUJITSU) +# define COMPILER_ID "FujitsuClang" +# define COMPILER_VERSION_MAJOR DEC(__FCC_major__) +# define COMPILER_VERSION_MINOR DEC(__FCC_minor__) +# define COMPILER_VERSION_PATCH DEC(__FCC_patchlevel__) +# define COMPILER_VERSION_INTERNAL_STR __clang_version__ + + +#elif defined(__FUJITSU) +# define COMPILER_ID "Fujitsu" +# if defined(__FCC_version__) +# define COMPILER_VERSION __FCC_version__ +# elif defined(__FCC_major__) +# define COMPILER_VERSION_MAJOR DEC(__FCC_major__) +# define COMPILER_VERSION_MINOR DEC(__FCC_minor__) +# define COMPILER_VERSION_PATCH DEC(__FCC_patchlevel__) +# endif +# if defined(__fcc_version) +# define COMPILER_VERSION_INTERNAL DEC(__fcc_version) +# elif defined(__FCC_VERSION) +# define COMPILER_VERSION_INTERNAL DEC(__FCC_VERSION) +# endif + + +#elif defined(__ghs__) +# define COMPILER_ID "GHS" +/* __GHS_VERSION_NUMBER = VVVVRP */ +# ifdef __GHS_VERSION_NUMBER +# define COMPILER_VERSION_MAJOR DEC(__GHS_VERSION_NUMBER / 100) +# define COMPILER_VERSION_MINOR DEC(__GHS_VERSION_NUMBER / 10 % 10) +# define COMPILER_VERSION_PATCH DEC(__GHS_VERSION_NUMBER % 10) +# endif + +#elif defined(__TINYC__) +# define COMPILER_ID "TinyCC" + +#elif defined(__BCC__) +# define COMPILER_ID "Bruce" + +#elif defined(__SCO_VERSION__) +# define COMPILER_ID "SCO" + +#elif defined(__ARMCC_VERSION) && !defined(__clang__) +# define COMPILER_ID "ARMCC" +#if __ARMCC_VERSION >= 1000000 + /* __ARMCC_VERSION = VRRPPPP */ + # define COMPILER_VERSION_MAJOR DEC(__ARMCC_VERSION/1000000) + # define COMPILER_VERSION_MINOR DEC(__ARMCC_VERSION/10000 % 100) + # define COMPILER_VERSION_PATCH DEC(__ARMCC_VERSION % 10000) +#else + /* __ARMCC_VERSION = VRPPPP */ + # define COMPILER_VERSION_MAJOR DEC(__ARMCC_VERSION/100000) + # define COMPILER_VERSION_MINOR DEC(__ARMCC_VERSION/10000 % 10) + # define COMPILER_VERSION_PATCH DEC(__ARMCC_VERSION % 10000) +#endif + + +#elif defined(__clang__) && defined(__apple_build_version__) +# define COMPILER_ID "AppleClang" +# if defined(_MSC_VER) +# define SIMULATE_ID "MSVC" +# endif +# define COMPILER_VERSION_MAJOR DEC(__clang_major__) +# define COMPILER_VERSION_MINOR DEC(__clang_minor__) +# define COMPILER_VERSION_PATCH DEC(__clang_patchlevel__) +# if defined(_MSC_VER) + /* _MSC_VER = VVRR */ +# define SIMULATE_VERSION_MAJOR DEC(_MSC_VER / 100) +# define SIMULATE_VERSION_MINOR DEC(_MSC_VER % 100) +# endif +# define COMPILER_VERSION_TWEAK DEC(__apple_build_version__) + +#elif defined(__clang__) && defined(__ARMCOMPILER_VERSION) +# define COMPILER_ID "ARMClang" + # define COMPILER_VERSION_MAJOR DEC(__ARMCOMPILER_VERSION/1000000) + # define COMPILER_VERSION_MINOR DEC(__ARMCOMPILER_VERSION/10000 % 100) + # define COMPILER_VERSION_PATCH DEC(__ARMCOMPILER_VERSION % 10000) +# define COMPILER_VERSION_INTERNAL DEC(__ARMCOMPILER_VERSION) + +#elif defined(__clang__) +# define COMPILER_ID "Clang" +# if defined(_MSC_VER) +# define SIMULATE_ID "MSVC" +# endif +# define COMPILER_VERSION_MAJOR DEC(__clang_major__) +# define COMPILER_VERSION_MINOR DEC(__clang_minor__) +# define COMPILER_VERSION_PATCH DEC(__clang_patchlevel__) +# if defined(_MSC_VER) + /* _MSC_VER = VVRR */ +# define SIMULATE_VERSION_MAJOR DEC(_MSC_VER / 100) +# define SIMULATE_VERSION_MINOR DEC(_MSC_VER % 100) +# endif + +#elif defined(__GNUC__) +# define COMPILER_ID "GNU" +# define COMPILER_VERSION_MAJOR DEC(__GNUC__) +# if defined(__GNUC_MINOR__) +# define COMPILER_VERSION_MINOR DEC(__GNUC_MINOR__) +# endif +# if defined(__GNUC_PATCHLEVEL__) +# define COMPILER_VERSION_PATCH DEC(__GNUC_PATCHLEVEL__) +# endif + +#elif defined(_MSC_VER) +# define COMPILER_ID "MSVC" + /* _MSC_VER = VVRR */ +# define COMPILER_VERSION_MAJOR DEC(_MSC_VER / 100) +# define COMPILER_VERSION_MINOR DEC(_MSC_VER % 100) +# if defined(_MSC_FULL_VER) +# if _MSC_VER >= 1400 + /* _MSC_FULL_VER = VVRRPPPPP */ +# define COMPILER_VERSION_PATCH DEC(_MSC_FULL_VER % 100000) +# else + /* _MSC_FULL_VER = VVRRPPPP */ +# define COMPILER_VERSION_PATCH DEC(_MSC_FULL_VER % 10000) +# endif +# endif +# if defined(_MSC_BUILD) +# define COMPILER_VERSION_TWEAK DEC(_MSC_BUILD) +# endif + +#elif defined(__VISUALDSPVERSION__) || defined(__ADSPBLACKFIN__) || defined(__ADSPTS__) || defined(__ADSP21000__) +# define COMPILER_ID "ADSP" +#if defined(__VISUALDSPVERSION__) + /* __VISUALDSPVERSION__ = 0xVVRRPP00 */ +# define COMPILER_VERSION_MAJOR HEX(__VISUALDSPVERSION__>>24) +# define COMPILER_VERSION_MINOR HEX(__VISUALDSPVERSION__>>16 & 0xFF) +# define COMPILER_VERSION_PATCH HEX(__VISUALDSPVERSION__>>8 & 0xFF) +#endif + +#elif defined(__IAR_SYSTEMS_ICC__) || defined(__IAR_SYSTEMS_ICC) +# define COMPILER_ID "IAR" +# if defined(__VER__) && defined(__ICCARM__) +# define COMPILER_VERSION_MAJOR DEC((__VER__) / 1000000) +# define COMPILER_VERSION_MINOR DEC(((__VER__) / 1000) % 1000) +# define COMPILER_VERSION_PATCH DEC((__VER__) % 1000) +# define COMPILER_VERSION_INTERNAL DEC(__IAR_SYSTEMS_ICC__) +# elif defined(__VER__) && (defined(__ICCAVR__) || defined(__ICCRX__) || defined(__ICCRH850__) || defined(__ICCRL78__) || defined(__ICC430__) || defined(__ICCRISCV__) || defined(__ICCV850__) || defined(__ICC8051__) || defined(__ICCSTM8__)) +# define COMPILER_VERSION_MAJOR DEC((__VER__) / 100) +# define COMPILER_VERSION_MINOR DEC((__VER__) - (((__VER__) / 100)*100)) +# define COMPILER_VERSION_PATCH DEC(__SUBVERSION__) +# define COMPILER_VERSION_INTERNAL DEC(__IAR_SYSTEMS_ICC__) +# endif + +#elif defined(__SDCC_VERSION_MAJOR) || defined(SDCC) +# define COMPILER_ID "SDCC" +# if defined(__SDCC_VERSION_MAJOR) +# define COMPILER_VERSION_MAJOR DEC(__SDCC_VERSION_MAJOR) +# define COMPILER_VERSION_MINOR DEC(__SDCC_VERSION_MINOR) +# define COMPILER_VERSION_PATCH DEC(__SDCC_VERSION_PATCH) +# else + /* SDCC = VRP */ +# define COMPILER_VERSION_MAJOR DEC(SDCC/100) +# define COMPILER_VERSION_MINOR DEC(SDCC/10 % 10) +# define COMPILER_VERSION_PATCH DEC(SDCC % 10) +# endif + + +/* These compilers are either not known or too old to define an + identification macro. Try to identify the platform and guess that + it is the native compiler. */ +#elif defined(__hpux) || defined(__hpua) +# define COMPILER_ID "HP" + +#else /* unknown compiler */ +# define COMPILER_ID "" +#endif + +/* Construct the string literal in pieces to prevent the source from + getting matched. Store it in a pointer rather than an array + because some compilers will just produce instructions to fill the + array rather than assigning a pointer to a static array. */ +char const* info_compiler = "INFO" ":" "compiler[" COMPILER_ID "]"; +#ifdef SIMULATE_ID +char const* info_simulate = "INFO" ":" "simulate[" SIMULATE_ID "]"; +#endif + +#ifdef __QNXNTO__ +char const* qnxnto = "INFO" ":" "qnxnto[]"; +#endif + +#if defined(__CRAYXT_COMPUTE_LINUX_TARGET) +char const *info_cray = "INFO" ":" "compiler_wrapper[CrayPrgEnv]"; +#endif + +#define STRINGIFY_HELPER(X) #X +#define STRINGIFY(X) STRINGIFY_HELPER(X) + +/* Identify known platforms by name. */ +#if defined(__linux) || defined(__linux__) || defined(linux) +# define PLATFORM_ID "Linux" + +#elif defined(__MSYS__) +# define PLATFORM_ID "MSYS" + +#elif defined(__CYGWIN__) +# define PLATFORM_ID "Cygwin" + +#elif defined(__MINGW32__) +# define PLATFORM_ID "MinGW" + +#elif defined(__APPLE__) +# define PLATFORM_ID "Darwin" + +#elif defined(_WIN32) || defined(__WIN32__) || defined(WIN32) +# define PLATFORM_ID "Windows" + +#elif defined(__FreeBSD__) || defined(__FreeBSD) +# define PLATFORM_ID "FreeBSD" + +#elif defined(__NetBSD__) || defined(__NetBSD) +# define PLATFORM_ID "NetBSD" + +#elif defined(__OpenBSD__) || defined(__OPENBSD) +# define PLATFORM_ID "OpenBSD" + +#elif defined(__sun) || defined(sun) +# define PLATFORM_ID "SunOS" + +#elif defined(_AIX) || defined(__AIX) || defined(__AIX__) || defined(__aix) || defined(__aix__) +# define PLATFORM_ID "AIX" + +#elif defined(__hpux) || defined(__hpux__) +# define PLATFORM_ID "HP-UX" + +#elif defined(__HAIKU__) +# define PLATFORM_ID "Haiku" + +#elif defined(__BeOS) || defined(__BEOS__) || defined(_BEOS) +# define PLATFORM_ID "BeOS" + +#elif defined(__QNX__) || defined(__QNXNTO__) +# define PLATFORM_ID "QNX" + +#elif defined(__tru64) || defined(_tru64) || defined(__TRU64__) +# define PLATFORM_ID "Tru64" + +#elif defined(__riscos) || defined(__riscos__) +# define PLATFORM_ID "RISCos" + +#elif defined(__sinix) || defined(__sinix__) || defined(__SINIX__) +# define PLATFORM_ID "SINIX" + +#elif defined(__UNIX_SV__) +# define PLATFORM_ID "UNIX_SV" + +#elif defined(__bsdos__) +# define PLATFORM_ID "BSDOS" + +#elif defined(_MPRAS) || defined(MPRAS) +# define PLATFORM_ID "MP-RAS" + +#elif defined(__osf) || defined(__osf__) +# define PLATFORM_ID "OSF1" + +#elif defined(_SCO_SV) || defined(SCO_SV) || defined(sco_sv) +# define PLATFORM_ID "SCO_SV" + +#elif defined(__ultrix) || defined(__ultrix__) || defined(_ULTRIX) +# define PLATFORM_ID "ULTRIX" + +#elif defined(__XENIX__) || defined(_XENIX) || defined(XENIX) +# define PLATFORM_ID "Xenix" + +#elif defined(__WATCOMC__) +# if defined(__LINUX__) +# define PLATFORM_ID "Linux" + +# elif defined(__DOS__) +# define PLATFORM_ID "DOS" + +# elif defined(__OS2__) +# define PLATFORM_ID "OS2" + +# elif defined(__WINDOWS__) +# define PLATFORM_ID "Windows3x" + +# elif defined(__VXWORKS__) +# define PLATFORM_ID "VxWorks" + +# else /* unknown platform */ +# define PLATFORM_ID +# endif + +#elif defined(__INTEGRITY) +# if defined(INT_178B) +# define PLATFORM_ID "Integrity178" + +# else /* regular Integrity */ +# define PLATFORM_ID "Integrity" +# endif + +#else /* unknown platform */ +# define PLATFORM_ID + +#endif + +/* For windows compilers MSVC and Intel we can determine + the architecture of the compiler being used. This is because + the compilers do not have flags that can change the architecture, + but rather depend on which compiler is being used +*/ +#if defined(_WIN32) && defined(_MSC_VER) +# if defined(_M_IA64) +# define ARCHITECTURE_ID "IA64" + +# elif defined(_M_ARM64EC) +# define ARCHITECTURE_ID "ARM64EC" + +# elif defined(_M_X64) || defined(_M_AMD64) +# define ARCHITECTURE_ID "x64" + +# elif defined(_M_IX86) +# define ARCHITECTURE_ID "X86" + +# elif defined(_M_ARM64) +# define ARCHITECTURE_ID "ARM64" + +# elif defined(_M_ARM) +# if _M_ARM == 4 +# define ARCHITECTURE_ID "ARMV4I" +# elif _M_ARM == 5 +# define ARCHITECTURE_ID "ARMV5I" +# else +# define ARCHITECTURE_ID "ARMV" STRINGIFY(_M_ARM) +# endif + +# elif defined(_M_MIPS) +# define ARCHITECTURE_ID "MIPS" + +# elif defined(_M_SH) +# define ARCHITECTURE_ID "SHx" + +# else /* unknown architecture */ +# define ARCHITECTURE_ID "" +# endif + +#elif defined(__WATCOMC__) +# if defined(_M_I86) +# define ARCHITECTURE_ID "I86" + +# elif defined(_M_IX86) +# define ARCHITECTURE_ID "X86" + +# else /* unknown architecture */ +# define ARCHITECTURE_ID "" +# endif + +#elif defined(__IAR_SYSTEMS_ICC__) || defined(__IAR_SYSTEMS_ICC) +# if defined(__ICCARM__) +# define ARCHITECTURE_ID "ARM" + +# elif defined(__ICCRX__) +# define ARCHITECTURE_ID "RX" + +# elif defined(__ICCRH850__) +# define ARCHITECTURE_ID "RH850" + +# elif defined(__ICCRL78__) +# define ARCHITECTURE_ID "RL78" + +# elif defined(__ICCRISCV__) +# define ARCHITECTURE_ID "RISCV" + +# elif defined(__ICCAVR__) +# define ARCHITECTURE_ID "AVR" + +# elif defined(__ICC430__) +# define ARCHITECTURE_ID "MSP430" + +# elif defined(__ICCV850__) +# define ARCHITECTURE_ID "V850" + +# elif defined(__ICC8051__) +# define ARCHITECTURE_ID "8051" + +# elif defined(__ICCSTM8__) +# define ARCHITECTURE_ID "STM8" + +# else /* unknown architecture */ +# define ARCHITECTURE_ID "" +# endif + +#elif defined(__ghs__) +# if defined(__PPC64__) +# define ARCHITECTURE_ID "PPC64" + +# elif defined(__ppc__) +# define ARCHITECTURE_ID "PPC" + +# elif defined(__ARM__) +# define ARCHITECTURE_ID "ARM" + +# elif defined(__x86_64__) +# define ARCHITECTURE_ID "x64" + +# elif defined(__i386__) +# define ARCHITECTURE_ID "X86" + +# else /* unknown architecture */ +# define ARCHITECTURE_ID "" +# endif + +#elif defined(__TI_COMPILER_VERSION__) +# if defined(__TI_ARM__) +# define ARCHITECTURE_ID "ARM" + +# elif defined(__MSP430__) +# define ARCHITECTURE_ID "MSP430" + +# elif defined(__TMS320C28XX__) +# define ARCHITECTURE_ID "TMS320C28x" + +# elif defined(__TMS320C6X__) || defined(_TMS320C6X) +# define ARCHITECTURE_ID "TMS320C6x" + +# else /* unknown architecture */ +# define ARCHITECTURE_ID "" +# endif + +#else +# define ARCHITECTURE_ID +#endif + +/* Convert integer to decimal digit literals. */ +#define DEC(n) \ + ('0' + (((n) / 10000000)%10)), \ + ('0' + (((n) / 1000000)%10)), \ + ('0' + (((n) / 100000)%10)), \ + ('0' + (((n) / 10000)%10)), \ + ('0' + (((n) / 1000)%10)), \ + ('0' + (((n) / 100)%10)), \ + ('0' + (((n) / 10)%10)), \ + ('0' + ((n) % 10)) + +/* Convert integer to hex digit literals. */ +#define HEX(n) \ + ('0' + ((n)>>28 & 0xF)), \ + ('0' + ((n)>>24 & 0xF)), \ + ('0' + ((n)>>20 & 0xF)), \ + ('0' + ((n)>>16 & 0xF)), \ + ('0' + ((n)>>12 & 0xF)), \ + ('0' + ((n)>>8 & 0xF)), \ + ('0' + ((n)>>4 & 0xF)), \ + ('0' + ((n) & 0xF)) + +/* Construct a string literal encoding the version number. */ +#ifdef COMPILER_VERSION +char const* info_version = "INFO" ":" "compiler_version[" COMPILER_VERSION "]"; + +/* Construct a string literal encoding the version number components. */ +#elif defined(COMPILER_VERSION_MAJOR) +char const info_version[] = { + 'I', 'N', 'F', 'O', ':', + 'c','o','m','p','i','l','e','r','_','v','e','r','s','i','o','n','[', + COMPILER_VERSION_MAJOR, +# ifdef COMPILER_VERSION_MINOR + '.', COMPILER_VERSION_MINOR, +# ifdef COMPILER_VERSION_PATCH + '.', COMPILER_VERSION_PATCH, +# ifdef COMPILER_VERSION_TWEAK + '.', COMPILER_VERSION_TWEAK, +# endif +# endif +# endif + ']','\0'}; +#endif + +/* Construct a string literal encoding the internal version number. */ +#ifdef COMPILER_VERSION_INTERNAL +char const info_version_internal[] = { + 'I', 'N', 'F', 'O', ':', + 'c','o','m','p','i','l','e','r','_','v','e','r','s','i','o','n','_', + 'i','n','t','e','r','n','a','l','[', + COMPILER_VERSION_INTERNAL,']','\0'}; +#elif defined(COMPILER_VERSION_INTERNAL_STR) +char const* info_version_internal = "INFO" ":" "compiler_version_internal[" COMPILER_VERSION_INTERNAL_STR "]"; +#endif + +/* Construct a string literal encoding the version number components. */ +#ifdef SIMULATE_VERSION_MAJOR +char const info_simulate_version[] = { + 'I', 'N', 'F', 'O', ':', + 's','i','m','u','l','a','t','e','_','v','e','r','s','i','o','n','[', + SIMULATE_VERSION_MAJOR, +# ifdef SIMULATE_VERSION_MINOR + '.', SIMULATE_VERSION_MINOR, +# ifdef SIMULATE_VERSION_PATCH + '.', SIMULATE_VERSION_PATCH, +# ifdef SIMULATE_VERSION_TWEAK + '.', SIMULATE_VERSION_TWEAK, +# endif +# endif +# endif + ']','\0'}; +#endif + +/* Construct the string literal in pieces to prevent the source from + getting matched. Store it in a pointer rather than an array + because some compilers will just produce instructions to fill the + array rather than assigning a pointer to a static array. */ +char const* info_platform = "INFO" ":" "platform[" PLATFORM_ID "]"; +char const* info_arch = "INFO" ":" "arch[" ARCHITECTURE_ID "]"; + + + +#if !defined(__STDC__) && !defined(__clang__) +# if defined(_MSC_VER) || defined(__ibmxl__) || defined(__IBMC__) +# define C_VERSION "90" +# else +# define C_VERSION +# endif +#elif __STDC_VERSION__ > 201710L +# define C_VERSION "23" +#elif __STDC_VERSION__ >= 201710L +# define C_VERSION "17" +#elif __STDC_VERSION__ >= 201000L +# define C_VERSION "11" +#elif __STDC_VERSION__ >= 199901L +# define C_VERSION "99" +#else +# define C_VERSION "90" +#endif +const char* info_language_standard_default = + "INFO" ":" "standard_default[" C_VERSION "]"; + +const char* info_language_extensions_default = "INFO" ":" "extensions_default[" +/* !defined(_MSC_VER) to exclude Clang's MSVC compatibility mode. */ +#if (defined(__clang__) || defined(__GNUC__) || \ + defined(__TI_COMPILER_VERSION__)) && \ + !defined(__STRICT_ANSI__) && !defined(_MSC_VER) + "ON" +#else + "OFF" +#endif +"]"; + +/*--------------------------------------------------------------------------*/ + +#ifdef ID_VOID_MAIN +void main() {} +#else +# if defined(__CLASSIC_C__) +int main(argc, argv) int argc; char *argv[]; +# else +int main(int argc, char* argv[]) +# endif +{ + int require = 0; + require += info_compiler[argc]; + require += info_platform[argc]; + require += info_arch[argc]; +#ifdef COMPILER_VERSION_MAJOR + require += info_version[argc]; +#endif +#ifdef COMPILER_VERSION_INTERNAL + require += info_version_internal[argc]; +#endif +#ifdef SIMULATE_ID + require += info_simulate[argc]; +#endif +#ifdef SIMULATE_VERSION_MAJOR + require += info_simulate_version[argc]; +#endif +#if defined(__CRAYXT_COMPUTE_LINUX_TARGET) + require += info_cray[argc]; +#endif + require += info_language_standard_default[argc]; + require += info_language_extensions_default[argc]; + (void)argv; + return require; +} +#endif diff --git a/examples/HeterLeNet/CMakeFiles/3.22.1/CompilerIdC/a.out b/examples/HeterLeNet/CMakeFiles/3.22.1/CompilerIdC/a.out new file mode 100755 index 0000000000000000000000000000000000000000..c786756abbd10a6ac500dd20933efa409d328d0c GIT binary patch literal 16088 zcmeHOeQX>@6`woj!=Xv+xG^?KX|^GSgwz|`aZ(eMW8 zZjag(l%SLnlSXPGD*Xebst77RDuINGhy*wk1zHMfB&3G_Oh2R`h1PskrbId3n|Z(U zc{vA(_75a>EbnjLZ{B+|`(}1;c6a7;@qxZ*B%+Y&)IP;htkEzrDR}&D$q>X;w^~ET z_o~~}3X+#;&XmUtP^n2*qKmO!_&P$iYvoK0yv@*5gGp#1Bik*NQrsX)KqcqFcFVay zWcgdL0e6l|kU-C>g8jMN82 zJUJ%(-!1VBV!OBj2JKQ}7sOt%19Balj=$z7{+s%airovAcB6uLm!TC9^?j7=q-#av z=74TKCiN}V4~-IkpoCZL$fQShckRd|+A`@}X|ipydw1LJF1whwJ9Wj}E{pzoOdUFW zLXn#p<|K?NddkS~$7SoKob{J)zUNZi`461`=J4bz`+nZ{vYKsP&pO<0wqYGk><>eP zWzKV*tYhNwdCJMyCcK>dZB`RY9N2$Tjj|r%tQx$#1fN@i=XPzb;YYdd=%nY4rE^{; 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DEC((__WATCOMC__ / 10) % 10) +# if (__WATCOMC__ % 10) > 0 +# define COMPILER_VERSION_PATCH DEC(__WATCOMC__ % 10) +# endif + +#elif defined(__SUNPRO_CC) +# define COMPILER_ID "SunPro" +# if __SUNPRO_CC >= 0x5100 + /* __SUNPRO_CC = 0xVRRP */ +# define COMPILER_VERSION_MAJOR HEX(__SUNPRO_CC>>12) +# define COMPILER_VERSION_MINOR HEX(__SUNPRO_CC>>4 & 0xFF) +# define COMPILER_VERSION_PATCH HEX(__SUNPRO_CC & 0xF) +# else + /* __SUNPRO_CC = 0xVRP */ +# define COMPILER_VERSION_MAJOR HEX(__SUNPRO_CC>>8) +# define COMPILER_VERSION_MINOR HEX(__SUNPRO_CC>>4 & 0xF) +# define COMPILER_VERSION_PATCH HEX(__SUNPRO_CC & 0xF) +# endif + +#elif defined(__HP_aCC) +# define COMPILER_ID "HP" + /* __HP_aCC = VVRRPP */ +# define COMPILER_VERSION_MAJOR DEC(__HP_aCC/10000) +# define COMPILER_VERSION_MINOR DEC(__HP_aCC/100 % 100) +# define COMPILER_VERSION_PATCH DEC(__HP_aCC % 100) + +#elif defined(__DECCXX) +# define COMPILER_ID "Compaq" + /* __DECCXX_VER = VVRRTPPPP */ +# define COMPILER_VERSION_MAJOR DEC(__DECCXX_VER/10000000) +# define COMPILER_VERSION_MINOR DEC(__DECCXX_VER/100000 % 100) +# define COMPILER_VERSION_PATCH DEC(__DECCXX_VER % 10000) + +#elif defined(__IBMCPP__) && defined(__COMPILER_VER__) +# define COMPILER_ID "zOS" + /* __IBMCPP__ = VRP */ +# define COMPILER_VERSION_MAJOR DEC(__IBMCPP__/100) +# define COMPILER_VERSION_MINOR DEC(__IBMCPP__/10 % 10) +# define COMPILER_VERSION_PATCH DEC(__IBMCPP__ % 10) + +#elif defined(__ibmxl__) && defined(__clang__) +# define COMPILER_ID "XLClang" +# define COMPILER_VERSION_MAJOR DEC(__ibmxl_version__) +# define COMPILER_VERSION_MINOR DEC(__ibmxl_release__) +# define COMPILER_VERSION_PATCH DEC(__ibmxl_modification__) +# define COMPILER_VERSION_TWEAK DEC(__ibmxl_ptf_fix_level__) + + +#elif defined(__IBMCPP__) && !defined(__COMPILER_VER__) && __IBMCPP__ >= 800 +# define COMPILER_ID "XL" + /* __IBMCPP__ = VRP */ +# define COMPILER_VERSION_MAJOR DEC(__IBMCPP__/100) +# define COMPILER_VERSION_MINOR DEC(__IBMCPP__/10 % 10) +# define COMPILER_VERSION_PATCH DEC(__IBMCPP__ % 10) + +#elif defined(__IBMCPP__) && !defined(__COMPILER_VER__) && __IBMCPP__ < 800 +# define COMPILER_ID "VisualAge" + /* __IBMCPP__ = VRP */ +# define COMPILER_VERSION_MAJOR DEC(__IBMCPP__/100) +# define COMPILER_VERSION_MINOR DEC(__IBMCPP__/10 % 10) +# define COMPILER_VERSION_PATCH DEC(__IBMCPP__ % 10) + +#elif defined(__NVCOMPILER) +# define COMPILER_ID "NVHPC" +# define COMPILER_VERSION_MAJOR DEC(__NVCOMPILER_MAJOR__) +# define COMPILER_VERSION_MINOR DEC(__NVCOMPILER_MINOR__) +# if defined(__NVCOMPILER_PATCHLEVEL__) +# define COMPILER_VERSION_PATCH DEC(__NVCOMPILER_PATCHLEVEL__) +# endif + +#elif defined(__PGI) +# define COMPILER_ID "PGI" +# define COMPILER_VERSION_MAJOR DEC(__PGIC__) +# define COMPILER_VERSION_MINOR DEC(__PGIC_MINOR__) +# if defined(__PGIC_PATCHLEVEL__) +# define COMPILER_VERSION_PATCH DEC(__PGIC_PATCHLEVEL__) +# endif + +#elif defined(_CRAYC) +# define COMPILER_ID "Cray" +# define COMPILER_VERSION_MAJOR DEC(_RELEASE_MAJOR) +# define COMPILER_VERSION_MINOR DEC(_RELEASE_MINOR) + +#elif defined(__TI_COMPILER_VERSION__) +# define COMPILER_ID "TI" + /* __TI_COMPILER_VERSION__ = VVVRRRPPP */ +# define COMPILER_VERSION_MAJOR DEC(__TI_COMPILER_VERSION__/1000000) +# define COMPILER_VERSION_MINOR DEC(__TI_COMPILER_VERSION__/1000 % 1000) +# define COMPILER_VERSION_PATCH DEC(__TI_COMPILER_VERSION__ % 1000) + +#elif defined(__CLANG_FUJITSU) +# define COMPILER_ID "FujitsuClang" +# define COMPILER_VERSION_MAJOR DEC(__FCC_major__) +# define COMPILER_VERSION_MINOR DEC(__FCC_minor__) +# define COMPILER_VERSION_PATCH DEC(__FCC_patchlevel__) +# define COMPILER_VERSION_INTERNAL_STR __clang_version__ + + +#elif defined(__FUJITSU) +# define COMPILER_ID "Fujitsu" +# if defined(__FCC_version__) +# define COMPILER_VERSION __FCC_version__ +# elif defined(__FCC_major__) +# define COMPILER_VERSION_MAJOR DEC(__FCC_major__) +# define COMPILER_VERSION_MINOR DEC(__FCC_minor__) +# define COMPILER_VERSION_PATCH DEC(__FCC_patchlevel__) +# endif +# if defined(__fcc_version) +# define COMPILER_VERSION_INTERNAL DEC(__fcc_version) +# elif defined(__FCC_VERSION) +# define COMPILER_VERSION_INTERNAL DEC(__FCC_VERSION) +# endif + + +#elif defined(__ghs__) +# define COMPILER_ID "GHS" +/* __GHS_VERSION_NUMBER = VVVVRP */ +# ifdef __GHS_VERSION_NUMBER +# define COMPILER_VERSION_MAJOR DEC(__GHS_VERSION_NUMBER / 100) +# define COMPILER_VERSION_MINOR DEC(__GHS_VERSION_NUMBER / 10 % 10) +# define COMPILER_VERSION_PATCH DEC(__GHS_VERSION_NUMBER % 10) +# endif + +#elif defined(__SCO_VERSION__) +# define COMPILER_ID "SCO" + +#elif defined(__ARMCC_VERSION) && !defined(__clang__) +# define COMPILER_ID "ARMCC" +#if __ARMCC_VERSION >= 1000000 + /* __ARMCC_VERSION = VRRPPPP */ + # define COMPILER_VERSION_MAJOR DEC(__ARMCC_VERSION/1000000) + # define COMPILER_VERSION_MINOR DEC(__ARMCC_VERSION/10000 % 100) + # define COMPILER_VERSION_PATCH DEC(__ARMCC_VERSION % 10000) +#else + /* __ARMCC_VERSION = VRPPPP */ + # define COMPILER_VERSION_MAJOR DEC(__ARMCC_VERSION/100000) + # define COMPILER_VERSION_MINOR DEC(__ARMCC_VERSION/10000 % 10) + # define COMPILER_VERSION_PATCH DEC(__ARMCC_VERSION % 10000) +#endif + + +#elif defined(__clang__) && defined(__apple_build_version__) +# define COMPILER_ID "AppleClang" +# if defined(_MSC_VER) +# define SIMULATE_ID "MSVC" +# endif +# define COMPILER_VERSION_MAJOR DEC(__clang_major__) +# define COMPILER_VERSION_MINOR DEC(__clang_minor__) +# define COMPILER_VERSION_PATCH DEC(__clang_patchlevel__) +# if defined(_MSC_VER) + /* _MSC_VER = VVRR */ +# define SIMULATE_VERSION_MAJOR DEC(_MSC_VER / 100) +# define SIMULATE_VERSION_MINOR DEC(_MSC_VER % 100) +# endif +# define COMPILER_VERSION_TWEAK DEC(__apple_build_version__) + +#elif defined(__clang__) && defined(__ARMCOMPILER_VERSION) +# define COMPILER_ID "ARMClang" + # define COMPILER_VERSION_MAJOR DEC(__ARMCOMPILER_VERSION/1000000) + # define COMPILER_VERSION_MINOR DEC(__ARMCOMPILER_VERSION/10000 % 100) + # define COMPILER_VERSION_PATCH DEC(__ARMCOMPILER_VERSION % 10000) +# define COMPILER_VERSION_INTERNAL DEC(__ARMCOMPILER_VERSION) + +#elif defined(__clang__) +# define COMPILER_ID "Clang" +# if defined(_MSC_VER) +# define SIMULATE_ID "MSVC" +# endif +# define COMPILER_VERSION_MAJOR DEC(__clang_major__) +# define COMPILER_VERSION_MINOR DEC(__clang_minor__) +# define COMPILER_VERSION_PATCH DEC(__clang_patchlevel__) +# if defined(_MSC_VER) + /* _MSC_VER = VVRR */ +# define SIMULATE_VERSION_MAJOR DEC(_MSC_VER / 100) +# define SIMULATE_VERSION_MINOR DEC(_MSC_VER % 100) +# endif + +#elif defined(__GNUC__) || defined(__GNUG__) +# define COMPILER_ID "GNU" +# if defined(__GNUC__) +# define COMPILER_VERSION_MAJOR DEC(__GNUC__) +# else +# define COMPILER_VERSION_MAJOR DEC(__GNUG__) +# endif +# if defined(__GNUC_MINOR__) +# define COMPILER_VERSION_MINOR DEC(__GNUC_MINOR__) +# endif +# if defined(__GNUC_PATCHLEVEL__) +# define COMPILER_VERSION_PATCH DEC(__GNUC_PATCHLEVEL__) +# endif + +#elif defined(_MSC_VER) +# define COMPILER_ID "MSVC" + /* _MSC_VER = VVRR */ +# define COMPILER_VERSION_MAJOR DEC(_MSC_VER / 100) +# define COMPILER_VERSION_MINOR DEC(_MSC_VER % 100) +# if defined(_MSC_FULL_VER) +# if _MSC_VER >= 1400 + /* _MSC_FULL_VER = VVRRPPPPP */ +# define COMPILER_VERSION_PATCH DEC(_MSC_FULL_VER % 100000) +# else + /* _MSC_FULL_VER = VVRRPPPP */ +# define COMPILER_VERSION_PATCH DEC(_MSC_FULL_VER % 10000) +# endif +# endif +# if defined(_MSC_BUILD) +# define COMPILER_VERSION_TWEAK DEC(_MSC_BUILD) +# endif + +#elif defined(__VISUALDSPVERSION__) || defined(__ADSPBLACKFIN__) || defined(__ADSPTS__) || defined(__ADSP21000__) +# define COMPILER_ID "ADSP" +#if defined(__VISUALDSPVERSION__) + /* __VISUALDSPVERSION__ = 0xVVRRPP00 */ +# define COMPILER_VERSION_MAJOR HEX(__VISUALDSPVERSION__>>24) +# define COMPILER_VERSION_MINOR HEX(__VISUALDSPVERSION__>>16 & 0xFF) +# define COMPILER_VERSION_PATCH HEX(__VISUALDSPVERSION__>>8 & 0xFF) +#endif + +#elif defined(__IAR_SYSTEMS_ICC__) || defined(__IAR_SYSTEMS_ICC) +# define COMPILER_ID "IAR" +# if defined(__VER__) && defined(__ICCARM__) +# define COMPILER_VERSION_MAJOR DEC((__VER__) / 1000000) +# define COMPILER_VERSION_MINOR DEC(((__VER__) / 1000) % 1000) +# define COMPILER_VERSION_PATCH DEC((__VER__) % 1000) +# define COMPILER_VERSION_INTERNAL DEC(__IAR_SYSTEMS_ICC__) +# elif defined(__VER__) && (defined(__ICCAVR__) || defined(__ICCRX__) || defined(__ICCRH850__) || defined(__ICCRL78__) || defined(__ICC430__) || defined(__ICCRISCV__) || defined(__ICCV850__) || defined(__ICC8051__) || defined(__ICCSTM8__)) +# define COMPILER_VERSION_MAJOR DEC((__VER__) / 100) +# define COMPILER_VERSION_MINOR DEC((__VER__) - (((__VER__) / 100)*100)) +# define COMPILER_VERSION_PATCH DEC(__SUBVERSION__) +# define COMPILER_VERSION_INTERNAL DEC(__IAR_SYSTEMS_ICC__) +# endif + + +/* These compilers are either not known or too old to define an + identification macro. Try to identify the platform and guess that + it is the native compiler. */ +#elif defined(__hpux) || defined(__hpua) +# define COMPILER_ID "HP" + +#else /* unknown compiler */ +# define COMPILER_ID "" +#endif + +/* Construct the string literal in pieces to prevent the source from + getting matched. Store it in a pointer rather than an array + because some compilers will just produce instructions to fill the + array rather than assigning a pointer to a static array. */ +char const* info_compiler = "INFO" ":" "compiler[" COMPILER_ID "]"; +#ifdef SIMULATE_ID +char const* info_simulate = "INFO" ":" "simulate[" SIMULATE_ID "]"; +#endif + +#ifdef __QNXNTO__ +char const* qnxnto = "INFO" ":" "qnxnto[]"; +#endif + +#if defined(__CRAYXT_COMPUTE_LINUX_TARGET) +char const *info_cray = "INFO" ":" "compiler_wrapper[CrayPrgEnv]"; +#endif + +#define STRINGIFY_HELPER(X) #X +#define STRINGIFY(X) STRINGIFY_HELPER(X) + +/* Identify known platforms by name. */ +#if defined(__linux) || defined(__linux__) || defined(linux) +# define PLATFORM_ID "Linux" + +#elif defined(__MSYS__) +# define PLATFORM_ID "MSYS" + +#elif defined(__CYGWIN__) +# define PLATFORM_ID "Cygwin" + +#elif defined(__MINGW32__) +# define PLATFORM_ID "MinGW" + +#elif defined(__APPLE__) +# define PLATFORM_ID "Darwin" + +#elif defined(_WIN32) || defined(__WIN32__) || defined(WIN32) +# define PLATFORM_ID "Windows" + +#elif defined(__FreeBSD__) || defined(__FreeBSD) +# define PLATFORM_ID "FreeBSD" + +#elif defined(__NetBSD__) || defined(__NetBSD) +# define PLATFORM_ID "NetBSD" + +#elif defined(__OpenBSD__) || defined(__OPENBSD) +# define PLATFORM_ID "OpenBSD" + +#elif defined(__sun) || defined(sun) +# define PLATFORM_ID "SunOS" + +#elif defined(_AIX) || defined(__AIX) || defined(__AIX__) || defined(__aix) || defined(__aix__) +# define PLATFORM_ID "AIX" + +#elif defined(__hpux) || defined(__hpux__) +# define PLATFORM_ID "HP-UX" + +#elif defined(__HAIKU__) +# define PLATFORM_ID "Haiku" + +#elif defined(__BeOS) || defined(__BEOS__) || defined(_BEOS) +# define PLATFORM_ID "BeOS" + +#elif defined(__QNX__) || defined(__QNXNTO__) +# define PLATFORM_ID "QNX" + +#elif defined(__tru64) || defined(_tru64) || defined(__TRU64__) +# define PLATFORM_ID "Tru64" + +#elif defined(__riscos) || defined(__riscos__) +# define PLATFORM_ID "RISCos" + +#elif defined(__sinix) || defined(__sinix__) || defined(__SINIX__) +# define PLATFORM_ID "SINIX" + +#elif defined(__UNIX_SV__) +# define PLATFORM_ID "UNIX_SV" + +#elif defined(__bsdos__) +# define PLATFORM_ID "BSDOS" + +#elif defined(_MPRAS) || defined(MPRAS) +# define PLATFORM_ID "MP-RAS" + +#elif defined(__osf) || defined(__osf__) +# define PLATFORM_ID "OSF1" + +#elif defined(_SCO_SV) || defined(SCO_SV) || defined(sco_sv) +# define PLATFORM_ID "SCO_SV" + +#elif defined(__ultrix) || defined(__ultrix__) || defined(_ULTRIX) +# define PLATFORM_ID "ULTRIX" + +#elif defined(__XENIX__) || defined(_XENIX) || defined(XENIX) +# define PLATFORM_ID "Xenix" + +#elif defined(__WATCOMC__) +# if defined(__LINUX__) +# define PLATFORM_ID "Linux" + +# elif defined(__DOS__) +# define PLATFORM_ID "DOS" + +# elif defined(__OS2__) +# define PLATFORM_ID "OS2" + +# elif defined(__WINDOWS__) +# define PLATFORM_ID "Windows3x" + +# elif defined(__VXWORKS__) +# define PLATFORM_ID "VxWorks" + +# else /* unknown platform */ +# define PLATFORM_ID +# endif + +#elif defined(__INTEGRITY) +# if defined(INT_178B) +# define PLATFORM_ID "Integrity178" + +# else /* regular Integrity */ +# define PLATFORM_ID "Integrity" +# endif + +#else /* unknown platform */ +# define PLATFORM_ID + +#endif + +/* For windows compilers MSVC and Intel we can determine + the architecture of the compiler being used. 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+ +/* Construct a string literal encoding the version number components. */ +#elif defined(COMPILER_VERSION_MAJOR) +char const info_version[] = { + 'I', 'N', 'F', 'O', ':', + 'c','o','m','p','i','l','e','r','_','v','e','r','s','i','o','n','[', + COMPILER_VERSION_MAJOR, +# ifdef COMPILER_VERSION_MINOR + '.', COMPILER_VERSION_MINOR, +# ifdef COMPILER_VERSION_PATCH + '.', COMPILER_VERSION_PATCH, +# ifdef COMPILER_VERSION_TWEAK + '.', COMPILER_VERSION_TWEAK, +# endif +# endif +# endif + ']','\0'}; +#endif + +/* Construct a string literal encoding the internal version number. */ +#ifdef COMPILER_VERSION_INTERNAL +char const info_version_internal[] = { + 'I', 'N', 'F', 'O', ':', + 'c','o','m','p','i','l','e','r','_','v','e','r','s','i','o','n','_', + 'i','n','t','e','r','n','a','l','[', + COMPILER_VERSION_INTERNAL,']','\0'}; +#elif defined(COMPILER_VERSION_INTERNAL_STR) +char const* info_version_internal = "INFO" ":" "compiler_version_internal[" COMPILER_VERSION_INTERNAL_STR "]"; +#endif + +/* Construct a string literal encoding the version number components. */ +#ifdef SIMULATE_VERSION_MAJOR +char const info_simulate_version[] = { + 'I', 'N', 'F', 'O', ':', + 's','i','m','u','l','a','t','e','_','v','e','r','s','i','o','n','[', + SIMULATE_VERSION_MAJOR, +# ifdef SIMULATE_VERSION_MINOR + '.', SIMULATE_VERSION_MINOR, +# ifdef SIMULATE_VERSION_PATCH + '.', SIMULATE_VERSION_PATCH, +# ifdef SIMULATE_VERSION_TWEAK + '.', SIMULATE_VERSION_TWEAK, +# endif +# endif +# endif + ']','\0'}; +#endif + +/* Construct the string literal in pieces to prevent the source from + getting matched. Store it in a pointer rather than an array + because some compilers will just produce instructions to fill the + array rather than assigning a pointer to a static array. */ +char const* info_platform = "INFO" ":" "platform[" PLATFORM_ID "]"; +char const* info_arch = "INFO" ":" "arch[" ARCHITECTURE_ID "]"; + + + +#if defined(__INTEL_COMPILER) && defined(_MSVC_LANG) && _MSVC_LANG < 201403L +# if defined(__INTEL_CXX11_MODE__) +# if defined(__cpp_aggregate_nsdmi) +# define CXX_STD 201402L +# else +# define CXX_STD 201103L +# endif +# else +# define CXX_STD 199711L +# endif +#elif defined(_MSC_VER) && defined(_MSVC_LANG) +# define CXX_STD _MSVC_LANG +#else +# define CXX_STD __cplusplus +#endif + +const char* info_language_standard_default = "INFO" ":" "standard_default[" +#if CXX_STD > 202002L + "23" +#elif CXX_STD > 201703L + "20" +#elif CXX_STD >= 201703L + "17" +#elif CXX_STD >= 201402L + "14" +#elif CXX_STD >= 201103L + "11" +#else + "98" +#endif +"]"; + +const char* info_language_extensions_default = "INFO" ":" "extensions_default[" +/* !defined(_MSC_VER) to exclude Clang's MSVC compatibility mode. */ +#if (defined(__clang__) || defined(__GNUC__) || \ + defined(__TI_COMPILER_VERSION__)) && \ + !defined(__STRICT_ANSI__) && !defined(_MSC_VER) + "ON" +#else + "OFF" +#endif +"]"; + +/*--------------------------------------------------------------------------*/ + +int main(int argc, char* argv[]) +{ + int require = 0; + require += info_compiler[argc]; + require += info_platform[argc]; +#ifdef COMPILER_VERSION_MAJOR + require += info_version[argc]; +#endif +#ifdef COMPILER_VERSION_INTERNAL + require += info_version_internal[argc]; +#endif +#ifdef SIMULATE_ID + require += info_simulate[argc]; +#endif +#ifdef SIMULATE_VERSION_MAJOR + require += info_simulate_version[argc]; +#endif +#if defined(__CRAYXT_COMPUTE_LINUX_TARGET) + require += info_cray[argc]; +#endif + require += info_language_standard_default[argc]; + require += 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[/usr/lib/x86_64-linux-gnu/Scrt1.o;/usr/lib/x86_64-linux-gnu/crti.o;/usr/lib/gcc/x86_64-linux-gnu/11/crtbeginS.o;/usr/lib/gcc/x86_64-linux-gnu/11/crtendS.o;/usr/lib/x86_64-linux-gnu/crtn.o] + implicit dirs: [/usr/lib/gcc/x86_64-linux-gnu/11;/usr/lib/x86_64-linux-gnu;/usr/lib;/lib/x86_64-linux-gnu;/lib] + implicit fwks: [] + + diff --git a/examples/HeterLeNet/CMakeFiles/cmake.check_cache b/examples/HeterLeNet/CMakeFiles/cmake.check_cache new file mode 100644 index 00000000..3dccd731 --- /dev/null +++ b/examples/HeterLeNet/CMakeFiles/cmake.check_cache @@ -0,0 +1 @@ +# This file is generated by cmake for dependency checking of the CMakeCache.txt file diff --git a/examples/HeterLeNet/CMakeLists.txt b/examples/HeterLeNet/CMakeLists.txt index 6e3c3db7..5de77a1c 100644 --- a/examples/HeterLeNet/CMakeLists.txt +++ b/examples/HeterLeNet/CMakeLists.txt @@ -1,20 +1,81 @@ add_custom_command( OUTPUT ${CMAKE_CURRENT_BINARY_DIR}/forward0.mlir ${CMAKE_CURRENT_BINARY_DIR}/forward1.mlir + ${CMAKE_CURRENT_BINARY_DIR}/forward2.mlir + ${CMAKE_CURRENT_BINARY_DIR}/forward3.mlir ${CMAKE_CURRENT_BINARY_DIR}/subgraph0.mlir ${CMAKE_CURRENT_BINARY_DIR}/subgraph1.mlir + ${CMAKE_CURRENT_BINARY_DIR}/subgraph2.mlir + ${CMAKE_CURRENT_BINARY_DIR}/subgraph3.mlir ${CMAKE_CURRENT_BINARY_DIR}/arg0.data + ${CMAKE_CURRENT_BINARY_DIR}/arg1.data + ${CMAKE_CURRENT_BINARY_DIR}/arg2.data + ${CMAKE_CURRENT_BINARY_DIR}/arg3.data COMMAND ${Python3_EXECUTABLE} ${CMAKE_CURRENT_SOURCE_DIR}/buddy-lenet-import.py --output-dir ${CMAKE_CURRENT_BINARY_DIR} COMMENT "Generating forward.mlir, subgraph0.mlir and parameter files" ) +set(ONE_SHOT_BUFFERIZE_OPTION "bufferize-function-boundaries=1 function-boundary-type-conversion=identity-layout-map") +set(LOWER_TO_NVVM_OPTION "cubin-chip=sm_80 cubin-features=+ptx71 cubin-format=fatbin") +set(CONVERT_MEMCPY_TO_GPU_OPTION "process-args=1") +set(CONVERT_MEMCPY_TO_GPU_OPTION_DISABLE_PROCESS_ARG "process-args=0") + +# foreach(i RANGE 0 3) +# add_custom_command( +# OUTPUT forward${i}.o +# COMMAND ${LLVM_TOOLS_BINARY_DIR}/mlir-opt ${CMAKE_CURRENT_BINARY_DIR}/forward${i}.mlir +# -pass-pipeline "builtin.module(func.func(tosa-to-linalg-named, tosa-to-linalg, tosa-to-tensor, tosa-to-arith), empty-tensor-to-alloc-tensor, convert-elementwise-to-linalg, arith-bufferize, func.func(linalg-bufferize, tensor-bufferize), func-bufferize)" | +# ${LLVM_TOOLS_BINARY_DIR}/mlir-opt +# -pass-pipeline "builtin.module(func.func(buffer-deallocation-simplification, convert-linalg-to-loops), eliminate-empty-tensors, func.func(llvm-request-c-wrappers),convert-math-to-llvm, convert-math-to-libm, convert-scf-to-cf, convert-arith-to-llvm, expand-strided-metadata, finalize-memref-to-llvm, convert-func-to-llvm, reconcile-unrealized-casts)" | +# ${LLVM_TOOLS_BINARY_DIR}/mlir-translate -mlir-to-llvmir | +# ${LLVM_TOOLS_BINARY_DIR}/llvm-as | +# ${LLVM_TOOLS_BINARY_DIR}/llc -filetype=obj -relocation-model=pic -O0 -o ${CMAKE_CURRENT_BINARY_DIR}/forward${i}.o +# DEPENDS ${CMAKE_CURRENT_BINARY_DIR}/forward${i}.mlir +# COMMENT "Building forward${i}.o" +# VERBATIM) +# +# add_custom_command( +# OUTPUT subgraph${i}.o +# COMMAND ${LLVM_TOOLS_BINARY_DIR}/mlir-opt ${CMAKE_CURRENT_BINARY_DIR}/subgraph${i}.mlir +# -pass-pipeline "builtin.module(func.func(tosa-to-linalg-named, tosa-to-linalg, tosa-to-tensor, tosa-to-arith))" | +# ${BUDDY_BINARY_DIR}/buddy-opt +# -eliminate-empty-tensors +# -convert-tensor-to-linalg +# -linalg-bufferize +# -batchmatmul-optimize +# -convert-linalg-to-affine-loops +# -lower-affine +# -func-bufferize-dynamic-offset +# -arith-bufferize +# -tensor-bufferize +# -buffer-deallocation +# -finalizing-bufferize +# -convert-vector-to-scf +# -expand-strided-metadata +# -convert-vector-to-llvm +# -convert-arith-to-llvm +# -finalize-memref-to-llvm +# -convert-scf-to-cf +# -llvm-request-c-wrappers +# -convert-arith-to-llvm +# -convert-func-to-llvm +# -reconcile-unrealized-casts | +# ${LLVM_TOOLS_BINARY_DIR}/mlir-translate -mlir-to-llvmir | +# ${LLVM_TOOLS_BINARY_DIR}/llvm-as | +# ${LLVM_TOOLS_BINARY_DIR}/llc -filetype=obj -relocation-model=pic -O0 -o ${CMAKE_CURRENT_BINARY_DIR}/subgraph${i}.o +# DEPENDS ${CMAKE_CURRENT_BINARY_DIR}/subgraph${i}.mlir +# COMMENT "Building subgraph${i}.o" +# VERBATIM) +# endforeach() + + add_custom_command( OUTPUT forward0.o - COMMAND ${LLVM_TOOLS_BINARY_DIR}/mlir-opt ${CMAKE_CURRENT_BINARY_DIR}/forward0.mlir - -pass-pipeline "builtin.module(func.func(tosa-to-linalg-named, tosa-to-linalg, tosa-to-tensor, tosa-to-arith), empty-tensor-to-alloc-tensor, convert-elementwise-to-linalg, arith-bufferize, func.func(linalg-bufferize, tensor-bufferize), func-bufferize)" | - ${LLVM_TOOLS_BINARY_DIR}/mlir-opt - -pass-pipeline "builtin.module(func.func(buffer-deallocation-simplification, convert-linalg-to-loops), eliminate-empty-tensors, func.func(llvm-request-c-wrappers),convert-math-to-llvm, convert-math-to-libm, convert-scf-to-cf, convert-arith-to-llvm, expand-strided-metadata, finalize-memref-to-llvm, convert-func-to-llvm, reconcile-unrealized-casts)" | + COMMAND ${BUDDY_BINARY_DIR}/buddy-opt ${CMAKE_CURRENT_BINARY_DIR}/forward0.mlir + -buffer-deallocation + -canonicalize -cse -expand-strided-metadata -convert-memcpy-to-gpu -gpu-async-region | + ${LLVM_TOOLS_BINARY_DIR}/mlir-opt -llvm-request-c-wrappers --gpu-to-llvm | ${LLVM_TOOLS_BINARY_DIR}/mlir-translate -mlir-to-llvmir | ${LLVM_TOOLS_BINARY_DIR}/llvm-as | ${LLVM_TOOLS_BINARY_DIR}/llc -filetype=obj -relocation-model=pic -O0 -o ${CMAKE_CURRENT_BINARY_DIR}/forward0.o @@ -27,27 +88,18 @@ add_custom_command( COMMAND ${LLVM_TOOLS_BINARY_DIR}/mlir-opt ${CMAKE_CURRENT_BINARY_DIR}/subgraph0.mlir -pass-pipeline "builtin.module(func.func(tosa-to-linalg-named, tosa-to-linalg, tosa-to-tensor, tosa-to-arith))" | ${BUDDY_BINARY_DIR}/buddy-opt - -eliminate-empty-tensors - -convert-tensor-to-linalg - -linalg-bufferize - -batchmatmul-optimize - -convert-linalg-to-affine-loops - -lower-affine - -func-bufferize-dynamic-offset - -arith-bufferize - -tensor-bufferize - -buffer-deallocation - -finalizing-bufferize - -convert-vector-to-scf - -expand-strided-metadata - -convert-vector-to-llvm - -convert-arith-to-llvm - -finalize-memref-to-llvm - -convert-scf-to-cf - -llvm-request-c-wrappers - -convert-arith-to-llvm - -convert-func-to-llvm - -reconcile-unrealized-casts | + -one-shot-bufferize + -func-bufferize-dynamic-offset + -convert-linalg-to-parallel-loops + -canonicalize + -gpu-map-parallel-loops + -convert-parallel-loops-to-gpu + -gpu-kernel-outlining + -buffer-deallocation + -canonicalize + -cse | + ${BUDDY_BINARY_DIR}/buddy-opt -convert-memcpy-to-gpu=${CONVERT_MEMCPY_TO_GPU_OPTION_DISABLE_PROCESS_ARG} -gpu-async-region -canonicalize | + ${LLVM_TOOLS_BINARY_DIR}/mlir-opt -llvm-request-c-wrappers --test-lower-to-nvvm=${LOWER_TO_NVVM_OPTION} | ${LLVM_TOOLS_BINARY_DIR}/mlir-translate -mlir-to-llvmir | ${LLVM_TOOLS_BINARY_DIR}/llvm-as | ${LLVM_TOOLS_BINARY_DIR}/llc -filetype=obj -relocation-model=pic -O0 -o ${CMAKE_CURRENT_BINARY_DIR}/subgraph0.o @@ -55,6 +107,42 @@ add_custom_command( COMMENT "Building subgraph0.o" VERBATIM) +# add_custom_command( +# OUTPUT forward1.o +# COMMAND ${BUDDY_BINARY_DIR}/buddy-opt ${CMAKE_CURRENT_BINARY_DIR}/forward1.mlir +# -buffer-deallocation +# -canonicalize -cse -expand-strided-metadata -convert-memcpy-to-gpu -gpu-async-region | +# ${LLVM_TOOLS_BINARY_DIR}/mlir-opt -llvm-request-c-wrappers --gpu-to-llvm | +# ${LLVM_TOOLS_BINARY_DIR}/mlir-translate -mlir-to-llvmir | +# ${LLVM_TOOLS_BINARY_DIR}/llvm-as | +# ${LLVM_TOOLS_BINARY_DIR}/llc -filetype=obj -relocation-model=pic -O0 -o ${CMAKE_CURRENT_BINARY_DIR}/forward1.o +# DEPENDS ${CMAKE_CURRENT_BINARY_DIR}/forward1.mlir +# COMMENT "Building forward1.o" +# VERBATIM) + +# add_custom_command( +# OUTPUT subgraph1.o +# COMMAND ${LLVM_TOOLS_BINARY_DIR}/mlir-opt ${CMAKE_CURRENT_BINARY_DIR}/subgraph1.mlir +# -pass-pipeline "builtin.module(func.func(tosa-to-linalg-named, tosa-to-linalg, tosa-to-tensor, tosa-to-arith))" | +# ${BUDDY_BINARY_DIR}/buddy-opt +# -one-shot-bufferize +# -func-bufferize-dynamic-offset +# -convert-linalg-to-parallel-loops +# -canonicalize +# -gpu-map-parallel-loops +# -convert-parallel-loops-to-gpu +# -gpu-kernel-outlining +# -buffer-deallocation +# -canonicalize +# -cse | +# ${BUDDY_BINARY_DIR}/buddy-opt -convert-memcpy-to-gpu=${CONVERT_MEMCPY_TO_GPU_OPTION_DISABLE_PROCESS_ARG} -gpu-async-region -canonicalize | +# ${LLVM_TOOLS_BINARY_DIR}/mlir-opt -llvm-request-c-wrappers --test-lower-to-nvvm=${LOWER_TO_NVVM_OPTION} | +# ${LLVM_TOOLS_BINARY_DIR}/mlir-translate -mlir-to-llvmir | +# ${LLVM_TOOLS_BINARY_DIR}/llvm-as | +# ${LLVM_TOOLS_BINARY_DIR}/llc -filetype=obj -relocation-model=pic -O0 -o ${CMAKE_CURRENT_BINARY_DIR}/subgraph1.o +# DEPENDS ${CMAKE_CURRENT_BINARY_DIR}/subgraph1.mlir +# COMMENT "Building subgraph1.o" +# VERBATIM) add_custom_command( OUTPUT forward1.o COMMAND ${LLVM_TOOLS_BINARY_DIR}/mlir-opt ${CMAKE_CURRENT_BINARY_DIR}/forward1.mlir @@ -100,62 +188,106 @@ add_custom_command( DEPENDS ${CMAKE_CURRENT_BINARY_DIR}/subgraph1.mlir COMMENT "Building subgraph1.o" VERBATIM) -set(LENET_EXAMPLE_PATH ${CMAKE_CURRENT_SOURCE_DIR}) -set(LENET_EXAMPLE_BUILD_PATH ${CMAKE_CURRENT_BINARY_DIR}) -# set(ONE_SHOT_BUFFERIZE_OPTION "bufferize-function-boundaries=1 function-boundary-type-conversion=identity-layout-map") -# set(LOWER_TO_NVVM_OPTION "cubin-chip=sm_80 cubin-features=+ptx71 cubin-format=fatbin") -# set(CONVERT_MEMCPY_TO_GPU_OPTION "process-args=1") -# set(CONVERT_MEMCPY_TO_GPU_OPTION_DISABLE_PROCESS_ARG "process-args=0") +add_custom_command( + OUTPUT forward2.o + COMMAND ${BUDDY_BINARY_DIR}/buddy-opt ${CMAKE_CURRENT_BINARY_DIR}/forward2.mlir + -buffer-deallocation + -canonicalize -cse -expand-strided-metadata -convert-memcpy-to-gpu -gpu-async-region | + ${LLVM_TOOLS_BINARY_DIR}/mlir-opt -llvm-request-c-wrappers --gpu-to-llvm | + ${LLVM_TOOLS_BINARY_DIR}/mlir-translate -mlir-to-llvmir | + ${LLVM_TOOLS_BINARY_DIR}/llvm-as | + ${LLVM_TOOLS_BINARY_DIR}/llc -filetype=obj -relocation-model=pic -O0 -o ${CMAKE_CURRENT_BINARY_DIR}/forward2.o + DEPENDS ${CMAKE_CURRENT_BINARY_DIR}/forward2.mlir + COMMENT "Building forward2.o" + VERBATIM) -# add_custom_command( -# OUTPUT forward1.o -# COMMAND ${BUDDY_BINARY_DIR}/buddy-opt ${CMAKE_CURRENT_BINARY_DIR}/forward1.mlir -# -buffer-deallocation -# -canonicalize -cse -expand-strided-metadata -convert-memcpy-to-gpu -gpu-async-region | -# ${LLVM_TOOLS_BINARY_DIR}/mlir-opt -llvm-request-c-wrappers --gpu-to-llvm | -# ${LLVM_TOOLS_BINARY_DIR}/mlir-translate -mlir-to-llvmir | -# ${LLVM_TOOLS_BINARY_DIR}/llvm-as | -# ${LLVM_TOOLS_BINARY_DIR}/llc -filetype=obj -relocation-model=pic -O0 -o ${CMAKE_CURRENT_BINARY_DIR}/forward1.o -# DEPENDS ${CMAKE_CURRENT_BINARY_DIR}/forward1.mlir -# COMMENT "Building forward1.o" -# VERBATIM) + add_custom_command( + OUTPUT subgraph2.o + COMMAND ${LLVM_TOOLS_BINARY_DIR}/mlir-opt ${CMAKE_CURRENT_BINARY_DIR}/subgraph2.mlir + -pass-pipeline "builtin.module(func.func(tosa-to-linalg-named, tosa-to-linalg, tosa-to-tensor, tosa-to-arith))" | + ${BUDDY_BINARY_DIR}/buddy-opt + -one-shot-bufferize + -func-bufferize-dynamic-offset + -convert-linalg-to-parallel-loops + -canonicalize + -gpu-map-parallel-loops + -convert-parallel-loops-to-gpu + -gpu-kernel-outlining + -buffer-deallocation + -canonicalize + -cse | + ${BUDDY_BINARY_DIR}/buddy-opt -convert-memcpy-to-gpu=${CONVERT_MEMCPY_TO_GPU_OPTION_DISABLE_PROCESS_ARG} -gpu-async-region -canonicalize | + ${LLVM_TOOLS_BINARY_DIR}/mlir-opt -llvm-request-c-wrappers --test-lower-to-nvvm=${LOWER_TO_NVVM_OPTION} | + ${LLVM_TOOLS_BINARY_DIR}/mlir-translate -mlir-to-llvmir | + ${LLVM_TOOLS_BINARY_DIR}/llvm-as | + ${LLVM_TOOLS_BINARY_DIR}/llc -filetype=obj -relocation-model=pic -O0 -o ${CMAKE_CURRENT_BINARY_DIR}/subgraph2.o + DEPENDS ${CMAKE_CURRENT_BINARY_DIR}/subgraph2.mlir + COMMENT "Building subgraph2.o" + VERBATIM) -# add_custom_command( -# OUTPUT subgraph1.o -# COMMAND ${LLVM_TOOLS_BINARY_DIR}/mlir-opt ${CMAKE_CURRENT_BINARY_DIR}/subgraph1.mlir -# -pass-pipeline "builtin.module(func.func(tosa-to-linalg-named, tosa-to-linalg, tosa-to-tensor, tosa-to-arith))" | -# ${BUDDY_BINARY_DIR}/buddy-opt -# -one-shot-bufferize -# -func-bufferize-dynamic-offset -# -convert-linalg-to-parallel-loops -# -canonicalize -# -gpu-map-parallel-loops -# -convert-parallel-loops-to-gpu -# -gpu-kernel-outlining -# -buffer-deallocation -# -canonicalize -# -cse | -# ${BUDDY_BINARY_DIR}/buddy-opt -convert-memcpy-to-gpu=${CONVERT_MEMCPY_TO_GPU_OPTION_DISABLE_PROCESS_ARG} -gpu-async-region -canonicalize | -# ${LLVM_TOOLS_BINARY_DIR}/mlir-opt -llvm-request-c-wrappers --test-lower-to-nvvm=${LOWER_TO_NVVM_OPTION} | -# ${LLVM_TOOLS_BINARY_DIR}/mlir-translate -mlir-to-llvmir | -# ${LLVM_TOOLS_BINARY_DIR}/llvm-as | -# ${LLVM_TOOLS_BINARY_DIR}/llc -filetype=obj -relocation-model=pic -O0 -o ${CMAKE_CURRENT_BINARY_DIR}/subgraph1.o -# DEPENDS ${CMAKE_CURRENT_BINARY_DIR}/subgraph1.mlir -# COMMENT "Building subgraph1.o" -# VERBATIM) + add_custom_command( + OUTPUT forward3.o + COMMAND ${LLVM_TOOLS_BINARY_DIR}/mlir-opt ${CMAKE_CURRENT_BINARY_DIR}/forward3.mlir + -pass-pipeline "builtin.module(func.func(tosa-to-linalg-named, tosa-to-linalg, tosa-to-tensor, tosa-to-arith), empty-tensor-to-alloc-tensor, convert-elementwise-to-linalg, arith-bufferize, func.func(linalg-bufferize, tensor-bufferize), func-bufferize)" | + ${LLVM_TOOLS_BINARY_DIR}/mlir-opt + -pass-pipeline "builtin.module(func.func(buffer-deallocation-simplification, convert-linalg-to-loops), eliminate-empty-tensors, func.func(llvm-request-c-wrappers),convert-math-to-llvm, convert-math-to-libm, convert-scf-to-cf, convert-arith-to-llvm, expand-strided-metadata, finalize-memref-to-llvm, convert-func-to-llvm, reconcile-unrealized-casts)" | + ${LLVM_TOOLS_BINARY_DIR}/mlir-translate -mlir-to-llvmir | + ${LLVM_TOOLS_BINARY_DIR}/llvm-as | + ${LLVM_TOOLS_BINARY_DIR}/llc -filetype=obj -relocation-model=pic -O0 -o ${CMAKE_CURRENT_BINARY_DIR}/forward3.o + DEPENDS ${CMAKE_CURRENT_BINARY_DIR}/forward3.mlir + COMMENT "Building forward3.o" + VERBATIM) + +add_custom_command( + OUTPUT subgraph3.o + COMMAND ${LLVM_TOOLS_BINARY_DIR}/mlir-opt ${CMAKE_CURRENT_BINARY_DIR}/subgraph3.mlir + -pass-pipeline "builtin.module(func.func(tosa-to-linalg-named, tosa-to-linalg, tosa-to-tensor, tosa-to-arith))" | + ${BUDDY_BINARY_DIR}/buddy-opt + -eliminate-empty-tensors + -convert-tensor-to-linalg + -linalg-bufferize + -batchmatmul-optimize + -convert-linalg-to-affine-loops + -lower-affine + -func-bufferize-dynamic-offset + -arith-bufferize + -tensor-bufferize + -buffer-deallocation + -finalizing-bufferize + -convert-vector-to-scf + -expand-strided-metadata + -convert-vector-to-llvm + -convert-arith-to-llvm + -finalize-memref-to-llvm + -convert-scf-to-cf + -llvm-request-c-wrappers + -convert-arith-to-llvm + -convert-func-to-llvm + -reconcile-unrealized-casts | + ${LLVM_TOOLS_BINARY_DIR}/mlir-translate -mlir-to-llvmir | + ${LLVM_TOOLS_BINARY_DIR}/llvm-as | + ${LLVM_TOOLS_BINARY_DIR}/llc -filetype=obj -relocation-model=pic -O0 -o ${CMAKE_CURRENT_BINARY_DIR}/subgraph3.o + DEPENDS ${CMAKE_CURRENT_BINARY_DIR}/subgraph3.mlir + COMMENT "Building subgraph3.o" + VERBATIM) + +set(LENET_EXAMPLE_PATH ${CMAKE_CURRENT_SOURCE_DIR}) +set(LENET_EXAMPLE_BUILD_PATH ${CMAKE_CURRENT_BINARY_DIR}) add_library(LENET_HETER0 STATIC subgraph0.o forward0.o) add_library(LENET_HETER1 STATIC subgraph1.o forward1.o) +add_library(LENET_HETER2 STATIC subgraph2.o forward2.o) +add_library(LENET_HETER3 STATIC subgraph3.o forward3.o) -SET_TARGET_PROPERTIES(LENET_HETER0 LENET_HETER1 PROPERTIES LINKER_LANGUAGE C) +SET_TARGET_PROPERTIES(LENET_HETER0 LENET_HETER1 LENET_HETER2 LENET_HETER3 PROPERTIES LINKER_LANGUAGE C) add_executable(buddy-lenet-run-heter buddy-lenet-main.cpp) target_link_directories(buddy-lenet-run-heter PRIVATE ${LLVM_LIBRARY_DIR}) -set(BUDDY_LENET_LIBS_GPU LENET_HETER0 LENET_HETER1 mlir_c_runner_utils mlir_async_runtime mlir_runner_utils ${PNG_LIBRARIES}) - -target_link_libraries(buddy-lenet-run-heter ${BUDDY_LENET_LIBS_GPU}) +set(BUDDY_LENET_LIBS_GPU LENET_HETER0 LENET_HETER2 mlir_c_runner_utils mlir_async_runtime mlir_runner_utils mlir_cuda_runtime ${PNG_LIBRARIES}) +set(BUDDY_LENET_LIBS_CPU LENET_HETER1 LENET_HETER3 mlir_c_runner_utils mlir_async_runtime mlir_runner_utils ${PNG_LIBRARIES}) +target_link_libraries(buddy-lenet-run-heter ${BUDDY_LENET_LIBS_CPU} ${BUDDY_LENET_LIBS_GPU}) target_compile_definitions(buddy-lenet-run-heter PRIVATE LENET_EXAMPLE_PATH="${LENET_EXAMPLE_PATH}" diff --git a/examples/HeterLeNet/buddy-lenet-import-test.py b/examples/HeterLeNet/buddy-lenet-import-test.py new file mode 100644 index 00000000..5d976b1a --- /dev/null +++ b/examples/HeterLeNet/buddy-lenet-import-test.py @@ -0,0 +1,147 @@ +# ===- buddy-lenet-import.py --------------------------------------------------- +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# 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. +# +# ===--------------------------------------------------------------------------- +# +# This is the LeNet model AOT importer. +# +# ===--------------------------------------------------------------------------- + +import os +from pathlib import Path +import argparse + +import numpy as np +import torch +from buddy.compiler.frontend import DynamoCompiler +from buddy.compiler.graph import GraphDriver +from buddy.compiler.graph.type import DeviceType +from buddy.compiler.graph.transform import simply_fuse, apply_classic_fusion +from buddy.compiler.ops import tosa +from buddy.compiler.graph.operation import * +from model import LeNet + +# Parse command-line arguments. +parser = argparse.ArgumentParser(description="LeNet model AOT importer") +parser.add_argument( + "--output-dir", + type=str, + default="./", + help="Directory to save output files." +) +args = parser.parse_args() + +# Ensure output directory exists. +output_dir = Path(args.output_dir) +output_dir.mkdir(parents=True, exist_ok=True) + +# Retrieve the LeNet model path. +model_path = os.path.dirname(os.path.abspath(__file__)) + +model = LeNet() +model = torch.load(model_path + "/lenet-model.pth", weights_only=False) +model = model.eval() + +# Initialize Dynamo Compiler with specific configurations as an importer. +dynamo_compiler = DynamoCompiler( + primary_registry=tosa.ops_registry, +) + +data = torch.randn([1, 1, 28, 28]) +# Import the model into MLIR module and parameters. +with torch.no_grad(): + graphs = dynamo_compiler.importer(model, data) + +pattern_list = [apply_classic_fusion] +graphs[0].fuse_ops(pattern_list) + +graph = graphs[0] +params = dynamo_compiler.imported_params[graph] +new_group = [graph._body[11]] +subgraph_name = "subgraph0" +graph.group_map_device[subgraph_name] = DeviceType.CPU +graph.op_groups[subgraph_name] = new_group + +params = dynamo_compiler.imported_params[graph] +new_group = [graph._body[12],graph._body[13]] +subgraph_name = "subgraph1" +graph.group_map_device[subgraph_name] = DeviceType.CPU +graph.op_groups[subgraph_name] = new_group + +params = dynamo_compiler.imported_params[graph] +new_group = [graph._body[14], graph._body[15], graph._body[16],graph._body[17]] +subgraph_name = "subgraph2" +graph.group_map_device[subgraph_name] = DeviceType.CPU +graph.op_groups[subgraph_name] = new_group + +params = dynamo_compiler.imported_params[graph] +new_group = [graph._body[18],graph._body[19]] +subgraph_name = "subgraph3" +graph.group_map_device[subgraph_name] = DeviceType.CPU +graph.op_groups[subgraph_name] = new_group +group = [] + +for i, op in enumerate(graph._body): + if isinstance(op, PlaceholderOp) or isinstance(op, OutputOp) or i < 20: + continue + print(i, op) + group.append(op) + subgraph_name = "subgraph4" + graph.group_map_device[subgraph_name] = DeviceType.CPU + graph.op_groups[subgraph_name] = group + +# pattern_list = [simply_fuse] +# graphs[0].fuse_ops(pattern_list) +driver = GraphDriver(graphs[0]) +for i in range(len(driver.subgraphs)): + driver.subgraphs[i].lower_to_top_level_ir() +# driver.subgraphs[0].lower_to_top_level_ir() +driver.construct_main_graph(True) +# Save the generated files to the specified output directory. +for i in range(len(driver.modules)): + with open(os.path.join(output_dir, f"subgraph{i}.mlir"), "w") as module_file: + print(driver.subgraphs[i]._imported_module, file=module_file) + with open(os.path.join(output_dir, f"forward{i}.mlir"), "w") as module_file: + print(driver.modules[i], file=module_file) + # 从 GraphDriver 中获取该子图收集到的参数索引列表 + param_indices = driver.subgraph_param_indices[i] + + # 根据参数索引从 loaded_params 中提取参数，并拼接为一维数组 + selected_arrays = [] + js = 0 + for idx in param_indices: + # 注意：loaded_params 中的每个参数都是一个 tensor + arr = params[idx].detach().cpu().numpy().reshape(-1) + js = js + len(arr) + selected_arrays.append(arr) + if selected_arrays: + concat_arr = np.concatenate(selected_arrays) + else: + concat_arr = np.array([]) + + # 定义输出文件名，数字 i 与子图对应 + filename = os.path.join(output_dir, f"arg{i}.data") + concat_arr.tofile(filename) +# with open(output_dir / "subgraph0.mlir", "w") as module_file: +# print(driver.subgraphs[0]._imported_module, file=module_file) +# with open(output_dir / "forward.mlir", "w") as module_file: +# print(driver.construct_main_graph(True), file=module_file) + +# params = dynamo_compiler.imported_params[graph] + +# float32_param = np.concatenate( +# [param.detach().numpy().reshape([-1]) for param in params] +# ) + +# float32_param.tofile(output_dir / "arg0.data") diff --git a/examples/HeterLeNet/buddy-lenet-import.py b/examples/HeterLeNet/buddy-lenet-import.py index 6117e385..1641bb1f 100644 --- a/examples/HeterLeNet/buddy-lenet-import.py +++ b/examples/HeterLeNet/buddy-lenet-import.py @@ -56,6 +56,7 @@ # Initialize Dynamo Compiler with specific configurations as an importer. dynamo_compiler = DynamoCompiler( primary_registry=tosa.ops_registry, + verbose = True, ) data = torch.randn([1, 1, 28, 28]) @@ -63,20 +64,38 @@ with torch.no_grad(): graphs = dynamo_compiler.importer(model, data) +graph = graphs[0] +for i, op in enumerate(graph._body): + print(i, op) +params = dynamo_compiler.imported_params[graph] +new_group = [graph._body[11]] +subgraph_name = "subgraph0" +graph.group_map_device[subgraph_name] = DeviceType.CPU +graph.op_groups[subgraph_name] = new_group + +graph = graphs[0] +params = dynamo_compiler.imported_params[graph] +new_group = [graph._body[12], graph._body[13]] +subgraph_name = "subgraph1" +graph.group_map_device[subgraph_name] = DeviceType.CPU +graph.op_groups[subgraph_name] = new_group + graph = graphs[0] params = dynamo_compiler.imported_params[graph] +new_group = [graph._body[14]] +subgraph_name = "subgraph2" +graph.group_map_device[subgraph_name] = DeviceType.CPU +graph.op_groups[subgraph_name] = new_group group = [] + for i, op in enumerate(graph._body): - if isinstance(op, PlaceholderOp) or isinstance(op, OutputOp) or i == 25: + if isinstance(op, PlaceholderOp) or isinstance(op, OutputOp) or i == 11 or i == 12 or i == 13 or i == 14: continue + print(i, op) group.append(op) - subgraph_name = "subgraph0" + subgraph_name = "subgraph3" graph.group_map_device[subgraph_name] = DeviceType.CPU graph.op_groups[subgraph_name] = group -new_group = [graph._body[25]] -subgraph_name = "subgraph1" -graph.group_map_device[subgraph_name] = DeviceType.GPU -graph.op_groups[subgraph_name] = new_group # pattern_list = [simply_fuse] # graphs[0].fuse_ops(pattern_list) @@ -100,10 +119,8 @@ for idx in param_indices: # 注意：loaded_params 中的每个参数都是一个 tensor arr = params[idx].detach().cpu().numpy().reshape(-1) - print(len(arr)) js = js + len(arr) selected_arrays.append(arr) - print(js) if selected_arrays: concat_arr = np.concatenate(selected_arrays) else: diff --git a/examples/HeterLeNet/buddy-lenet-main-test.cpp b/examples/HeterLeNet/buddy-lenet-main-test.cpp new file mode 100644 index 00000000..b286fddf --- /dev/null +++ b/examples/HeterLeNet/buddy-lenet-main-test.cpp @@ -0,0 +1,212 @@ +//===- buddy-lenet-main.cpp -----------------------------------------------===// +// +// Licensed under the Apache License, Version 2.0 (the "License"); +// you may not use this file except in compliance with the License. +// You may obtain a copy of the License at +// +// http://www.apache.org/licenses/LICENSE-2.0 +// +// 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. +// +//===----------------------------------------------------------------------===// + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +constexpr size_t ParamsSize0 = 156; +constexpr size_t ParamsSize1 = 0; +constexpr size_t ParamsSize2 = 2416; +constexpr size_t ParamsSize3 = 30840; +constexpr size_t ParamsSize4 = 11014; + +const std::string ImgName = "1-28*28.png"; + +/// Declare LeNet forward function. +extern "C" void _mlir_ciface_forward0(MemRef *output0, + MemRef *arg0, + dip::Image *input); +extern "C" void _mlir_ciface_forward1(MemRef *output1, + MemRef *output0); +extern "C" void _mlir_ciface_forward2(MemRef *output2, + MemRef *arg2, + MemRef *output1); +extern "C" void _mlir_ciface_forward3(MemRef *output3, + MemRef *arg3, + MemRef *output2); +extern "C" void _mlir_ciface_forward4(MemRef *output, + MemRef *arg4, + MemRef *output3); +/// Print [Log] label in bold blue format. +void printLogLabel() { std::cout << "\033[34;1m[Log] \033[0m"; } + +/// Load parameters into data container. +void loadParameters(const std::string ¶mFilePath, + MemRef ¶ms) { + const auto loadStart = std::chrono::high_resolution_clock::now(); + // Open the parameter file in binary mode. + std::ifstream paramFile(paramFilePath, std::ios::in | std::ios::binary); + if (!paramFile.is_open()) { + throw std::runtime_error("[Error] Failed to open params file!"); + } + printLogLabel(); + std::cout << "Loading params..." << std::endl; + printLogLabel(); + // Print the canonical path of the parameter file. + std::cout << "Params file: " << std::filesystem::canonical(paramFilePath) + << std::endl; + // Read the parameter data into the provided memory reference. + paramFile.read(reinterpret_cast(params.getData()), + sizeof(float) * (params.getSize())); + if (paramFile.fail()) { + throw std::runtime_error("Error occurred while reading params file!"); + } + paramFile.close(); + const auto loadEnd = std::chrono::high_resolution_clock::now(); + const std::chrono::duration loadTime = + loadEnd - loadStart; + printLogLabel(); + std::cout << "Params load time: " << (double)(loadTime.count()) / 1000 + << "s\n" + << std::endl; +} + +/// Softmax function to convert logits to probabilities. +void softmax(float *input, size_t size) { + size_t i; + float max_value = -INFINITY; + double sum = 0.0; + // Find the maximum value in the input array for numerical stability. + for (i = 0; i < size; ++i) { + if (max_value < input[i]) { + max_value = input[i]; + } + } + // Calculate the sum of the exponentials of the input elements, normalized by + // the max value. + for (i = 0; i < size; ++i) { + sum += exp(input[i] - max_value); + } + // Normalize the input array with the softmax calculation. + for (i = 0; i < size; ++i) { + input[i] = exp(input[i] - max_value) / sum; + } +} + +int main() { + // Print the title of this example. + const std::string title = "LeNet Inference Powered by Buddy Compiler"; + std::cout << "\033[33;1m" << title << "\033[0m" << std::endl; + + // Define the sizes of the output tensors. + intptr_t sizesOutput[2] = {1, 10}; + intptr_t sizesOutput0[4] = {1, 6, 24, 24}; + intptr_t sizesOutput1[4] = {1, 6, 12, 12}; + intptr_t sizesOutput2[4] = {1, 16, 4, 4}; + intptr_t sizesOutput3[2] = {1, 120}; + + + // Create input and output containers for the image and model output. + std::string lenetDir = LENET_EXAMPLE_PATH; + std::string lenetBuildDir = LENET_EXAMPLE_BUILD_PATH; + std::string imgPath = lenetDir + "/images/" + ImgName; + dip::Image input(imgPath, dip::DIP_GRAYSCALE, true /* norm */); + MemRef output(sizesOutput); + MemRef output0(sizesOutput0, 0.0f); + MemRef output1(sizesOutput1, 0.0f); + MemRef output2(sizesOutput2, 0.0f); + MemRef output3(sizesOutput3, 0.0f); + + + // Load model parameters from the specified file. + + std::string paramsDir0 = lenetBuildDir + "/arg0.data"; + std::cout << paramsDir0 << std::endl; + MemRef paramsContainer0({ParamsSize0}); + loadParameters(paramsDir0, paramsContainer0); + // std::string paramsDir1 = lenetBuildDir + "/arg1.data"; + // MemRef paramsContainer1({ParamsSize1}); + // loadParameters(paramsDir1, paramsContainer1); + std::string paramsDir2 = lenetBuildDir + "/arg2.data"; + MemRef paramsContainer2({ParamsSize2}); + loadParameters(paramsDir2, paramsContainer2); + std::string paramsDir3 = lenetBuildDir + "/arg3.data"; + MemRef paramsContainer3({ParamsSize3}); + loadParameters(paramsDir3, paramsContainer3); + std::string paramsDir4 = lenetBuildDir + "/arg4.data"; + MemRef paramsContainer4({ParamsSize4}); + loadParameters(paramsDir4, paramsContainer4); + + // Timing forward0 + auto t0_start = std::chrono::high_resolution_clock::now(); + _mlir_ciface_forward0(&output0, ¶msContainer0, &input); + auto t0_end = std::chrono::high_resolution_clock::now(); + std::cout << "[Time] forward0: " + << std::chrono::duration(t0_end - t0_start).count() + << " ms" << std::endl; + + // Timing forward1 + auto t1_start = std::chrono::high_resolution_clock::now(); + _mlir_ciface_forward1(&output1, &output0); + auto t1_end = std::chrono::high_resolution_clock::now(); + std::cout << "[Time] forward1: " + << std::chrono::duration(t1_end - t1_start).count() + << " ms" << std::endl; + + // Timing forward2 + auto t2_start = std::chrono::high_resolution_clock::now(); + _mlir_ciface_forward2(&output2, ¶msContainer2, &output1); + auto t2_end = std::chrono::high_resolution_clock::now(); + std::cout << "[Time] forward2: " + << std::chrono::duration(t2_end - t2_start).count() + << " ms" << std::endl; + + + // Timing forward4 + auto t4_start = std::chrono::high_resolution_clock::now(); + _mlir_ciface_forward3(&output3, ¶msContainer3, &output2); + auto t4_end = std::chrono::high_resolution_clock::now(); + std::cout << "[Time] forward4: " + << std::chrono::duration(t4_end - t4_start).count() + << " ms" << std::endl; + + // Timing forward5 + auto t5_start = std::chrono::high_resolution_clock::now(); + _mlir_ciface_forward4(&output, ¶msContainer4, &output3); + auto t5_end = std::chrono::high_resolution_clock::now(); + std::cout << "[Time] forward5: " + << std::chrono::duration(t5_end - t5_start).count() + << " ms" << std::endl; + + + // Apply softmax to the output logits to get probabilities. + auto out = output.getData(); + softmax(out, 10); + + // Find the classification and print the result. + float maxVal = 0; + float maxIdx = 0; + for (int i = 0; i < 10; ++i) { + if (out[i] > maxVal) { + maxVal = out[i]; + maxIdx = i; + } + } + + std::cout << "Classification: " << maxIdx << std::endl; + std::cout << "Probability: " << maxVal << std::endl; + + return 0; +} diff --git a/examples/HeterLeNet/buddy-lenet-main.cpp b/examples/HeterLeNet/buddy-lenet-main.cpp index 708f83b6..7fc53e00 100644 --- a/examples/HeterLeNet/buddy-lenet-main.cpp +++ b/examples/HeterLeNet/buddy-lenet-main.cpp @@ -26,20 +26,25 @@ #include #include -constexpr size_t ParamsSize0 = 44416; -constexpr size_t ParamsSize1 = 10; +constexpr size_t ParamsSize0 = 156; +constexpr size_t ParamsSize1 = 0; +constexpr size_t ParamsSize2 = 2416; +constexpr size_t ParamsSize3 = 41854; const std::string ImgName = "1-28*28.png"; /// Declare LeNet forward function. -extern "C" void _mlir_ciface_forward0(MemRef *output0, - MemRef *output1, +extern "C" void _mlir_ciface_forward0(MemRef *output0, MemRef *arg0, dip::Image *input); -extern "C" void _mlir_ciface_forward1(MemRef *output, +extern "C" void _mlir_ciface_forward1(MemRef *output1, + MemRef *output0); +extern "C" void _mlir_ciface_forward2(MemRef *output2, + MemRef *arg2, + MemRef *output1); +extern "C" void _mlir_ciface_forward3(MemRef *output, MemRef *arg1, - MemRef *output0, - MemRef *output1); + MemRef *output2); /// Print [Log] label in bold blue format. void printLogLabel() { std::cout << "\033[34;1m[Log] \033[0m"; } @@ -103,8 +108,9 @@ int main() { // Define the sizes of the output tensors. intptr_t sizesOutput[2] = {1, 10}; - intptr_t sizesOutput0[2] = {1, 84}; - intptr_t sizesOutput1[2] = {84, 10}; + intptr_t sizesOutput0[4] = {1, 6, 24, 24}; + intptr_t sizesOutput1[4] = {1, 6, 12, 12}; + intptr_t sizesOutput2[4] = {1, 16, 8, 8}; // Create input and output containers for the image and model output. std::string lenetDir = LENET_EXAMPLE_PATH; @@ -112,23 +118,58 @@ int main() { std::string imgPath = lenetDir + "/images/" + ImgName; dip::Image input(imgPath, dip::DIP_GRAYSCALE, true /* norm */); MemRef output(sizesOutput); - MemRef output0(sizesOutput0); - MemRef output1(sizesOutput1); + MemRef output0(sizesOutput0, 0.0f); + MemRef output1(sizesOutput1, 0.0f); + MemRef output2(sizesOutput2, 0.0f); + + // Load model parameters from the specified file. std::string paramsDir0 = lenetBuildDir + "/arg0.data"; std::cout << paramsDir0 << std::endl; MemRef paramsContainer0({ParamsSize0}); loadParameters(paramsDir0, paramsContainer0); - std::string paramsDir1 = lenetBuildDir + "/arg1.data"; - MemRef paramsContainer1({ParamsSize1}); - loadParameters(paramsDir1, paramsContainer1); - std::cout << "++++++++++" << std::endl; + // std::string paramsDir1 = lenetBuildDir + "/arg1.data"; + // MemRef paramsContainer1({ParamsSize1}); + // loadParameters(paramsDir1, paramsContainer1); + std::string paramsDir2 = lenetBuildDir + "/arg2.data"; + MemRef paramsContainer2({ParamsSize2}); + loadParameters(paramsDir2, paramsContainer2); + std::string paramsDir3 = lenetBuildDir + "/arg3.data"; + MemRef paramsContainer3({ParamsSize3}); + loadParameters(paramsDir3, paramsContainer3); + // Call the forward function of the model. - _mlir_ciface_forward0(&output0, &output1, ¶msContainer0, &input); - std::cout << "++++++++++" << std::endl; - _mlir_ciface_forward1(&output, ¶msContainer1, &output0, &output1); - std::cout << "++++++++++" << std::endl; + const auto forward0Start = std::chrono::high_resolution_clock::now(); + _mlir_ciface_forward0(&output0, ¶msContainer0, &input); + const auto forward0End = std::chrono::high_resolution_clock::now(); + const std::chrono::duration forward0Time = forward0End - forward0Start; + printLogLabel(); + std::cout << "Forward0 execution time: " << forward0Time.count() << " ms\n"; + + const auto forward1Start = std::chrono::high_resolution_clock::now(); + _mlir_ciface_forward1(&output1, &output0); + const auto forward1End = std::chrono::high_resolution_clock::now(); + const std::chrono::duration forward1Time = forward1End - forward1Start; + printLogLabel(); + std::cout << "Forward1 execution time: " << forward1Time.count() << " ms\n"; + + const auto forward2Start = std::chrono::high_resolution_clock::now(); + _mlir_ciface_forward2(&output2, ¶msContainer2, &output1); + const auto forward2End = std::chrono::high_resolution_clock::now(); + const std::chrono::duration forward2Time = forward2End - forward2Start; + printLogLabel(); + std::cout << "Forward2 execution time: " << forward2Time.count() << " ms\n"; + + const auto forward3Start = std::chrono::high_resolution_clock::now(); + _mlir_ciface_forward3(&output, ¶msContainer3, &output2); + const auto forward3End = std::chrono::high_resolution_clock::now(); + const std::chrono::duration forward3Time = forward3End - forward3Start; + printLogLabel(); + std::cout << "Forward3 execution time: " << forward3Time.count() << " ms\n"; + + std::cout << forward0Time.count()+forward1Time.count()+forward2Time.count()+forward3Time.count() << " ms\n"; + // Apply softmax to the output logits to get probabilities. auto out = output.getData(); softmax(out, 10); diff --git a/examples/HeterLeNet/fake-lenet.mlir b/examples/HeterLeNet/fake-lenet.mlir new file mode 100644 index 00000000..d7d80a53 --- /dev/null +++ b/examples/HeterLeNet/fake-lenet.mlir @@ -0,0 +1,97 @@ +module { + func.func private @printMemrefF32(%ptr : tensor<*xf32>) + func.func private @rtclock() -> f64 + + func.func @forward(%arg0: tensor<44426xf32>, %arg1: tensor<1x1x28x28xf32>) -> tensor<1x10xf32> { + %extracted_slice = tensor.extract_slice %arg0[0] [150] [1] : tensor<44426xf32> to tensor<150xf32> + %expanded = tensor.expand_shape %extracted_slice [[0, 1, 2, 3]] : tensor<150xf32> into tensor<6x1x5x5xf32> + %extracted_slice_0 = tensor.extract_slice %arg0[150] [6] [1] : tensor<44426xf32> to tensor<6xf32> + %extracted_slice_1 = tensor.extract_slice %arg0[156] [2400] [1] : tensor<44426xf32> to tensor<2400xf32> + %expanded_2 = tensor.expand_shape %extracted_slice_1 [[0, 1, 2, 3]] : tensor<2400xf32> into tensor<16x6x5x5xf32> + %extracted_slice_3 = tensor.extract_slice %arg0[2556] [16] [1] : tensor<44426xf32> to tensor<16xf32> + %extracted_slice_4 = tensor.extract_slice %arg0[2572] [30720] [1] : tensor<44426xf32> to tensor<30720xf32> + %expanded_5 = tensor.expand_shape %extracted_slice_4 [[0, 1]] : tensor<30720xf32> into tensor<120x256xf32> + %extracted_slice_6 = tensor.extract_slice %arg0[33292] [120] [1] : tensor<44426xf32> to tensor<120xf32> + %extracted_slice_7 = tensor.extract_slice %arg0[33412] [10080] [1] : tensor<44426xf32> to tensor<10080xf32> + %expanded_8 = tensor.expand_shape %extracted_slice_7 [[0, 1]] : tensor<10080xf32> into tensor<84x120xf32> + %extracted_slice_9 = tensor.extract_slice %arg0[43492] [84] [1] : tensor<44426xf32> to tensor<84xf32> + %extracted_slice_10 = tensor.extract_slice %arg0[43576] [840] [1] : tensor<44426xf32> to tensor<840xf32> + %expanded_11 = tensor.expand_shape %extracted_slice_10 [[0, 1]] : tensor<840xf32> into tensor<10x84xf32> + %extracted_slice_12 = tensor.extract_slice %arg0[44416] [10] [1] : tensor<44426xf32> to tensor<10xf32> + %0 = "tosa.const"() <{value = dense<[0, 2, 3, 1]> : tensor<4xi32>}> : () -> tensor<4xi32> + %1 = tosa.transpose %arg1, %0 : (tensor<1x1x28x28xf32>, tensor<4xi32>) -> tensor<1x28x28x1xf32> + %2 = "tosa.const"() <{value = dense<[0, 2, 3, 1]> : tensor<4xi32>}> : () -> tensor<4xi32> + %3 = tosa.transpose %expanded, %2 : (tensor<6x1x5x5xf32>, tensor<4xi32>) -> tensor<6x5x5x1xf32> + %4 = tosa.conv2d %1, %3, %extracted_slice_0 {dilation = array, pad = array, stride = array} : (tensor<1x28x28x1xf32>, tensor<6x5x5x1xf32>, tensor<6xf32>) -> tensor<1x24x24x6xf32> + %5 = "tosa.const"() <{value = dense<[0, 3, 1, 2]> : tensor<4xi32>}> : () -> tensor<4xi32> + %6 = tosa.transpose %4, %5 : (tensor<1x24x24x6xf32>, tensor<4xi32>) -> tensor<1x6x24x24xf32> + %7 = "tosa.const"() <{value = dense<0.000000e+00> : tensor<1x6x24x24xf32>}> : () -> tensor<1x6x24x24xf32> + %8 = tosa.maximum %6, %7 : (tensor<1x6x24x24xf32>, tensor<1x6x24x24xf32>) -> tensor<1x6x24x24xf32> + %9 = "tosa.const"() <{value = dense<[0, 2, 3, 1]> : tensor<4xi32>}> : () -> tensor<4xi32> + %10 = tosa.transpose %8, %9 : (tensor<1x6x24x24xf32>, tensor<4xi32>) -> tensor<1x24x24x6xf32> + %11 = tosa.max_pool2d %10 {kernel = array, pad = array, stride = array} : (tensor<1x24x24x6xf32>) -> tensor<1x12x12x6xf32> + %12 = "tosa.const"() <{value = dense<[0, 3, 1, 2]> : tensor<4xi32>}> : () -> tensor<4xi32> + %13 = tosa.transpose %11, %12 : (tensor<1x12x12x6xf32>, tensor<4xi32>) -> tensor<1x6x12x12xf32> + %14 = "tosa.const"() <{value = dense<[0, 2, 3, 1]> : tensor<4xi32>}> : () -> tensor<4xi32> + %15 = tosa.transpose %13, %14 : (tensor<1x6x12x12xf32>, tensor<4xi32>) -> tensor<1x12x12x6xf32> + %16 = "tosa.const"() <{value = dense<[0, 2, 3, 1]> : tensor<4xi32>}> : () -> tensor<4xi32> + %17 = tosa.transpose %expanded_2, %16 : (tensor<16x6x5x5xf32>, tensor<4xi32>) -> tensor<16x5x5x6xf32> + %18 = tosa.conv2d %15, %17, %extracted_slice_3 {dilation = array, pad = array, stride = array} : (tensor<1x12x12x6xf32>, tensor<16x5x5x6xf32>, tensor<16xf32>) -> tensor<1x8x8x16xf32> + %19 = "tosa.const"() <{value = dense<[0, 3, 1, 2]> : tensor<4xi32>}> : () -> tensor<4xi32> + %20 = tosa.transpose %18, %19 : (tensor<1x8x8x16xf32>, tensor<4xi32>) -> tensor<1x16x8x8xf32> + %21 = "tosa.const"() <{value = dense<0.000000e+00> : tensor<1x16x8x8xf32>}> : () -> tensor<1x16x8x8xf32> + %22 = tosa.maximum %20, %21 : (tensor<1x16x8x8xf32>, tensor<1x16x8x8xf32>) -> tensor<1x16x8x8xf32> + %23 = "tosa.const"() <{value = dense<[0, 2, 3, 1]> : tensor<4xi32>}> : () -> tensor<4xi32> + %24 = tosa.transpose %22, %23 : (tensor<1x16x8x8xf32>, tensor<4xi32>) -> tensor<1x8x8x16xf32> + %25 = tosa.max_pool2d %24 {kernel = array, pad = array, stride = array} : (tensor<1x8x8x16xf32>) -> tensor<1x4x4x16xf32> + %26 = "tosa.const"() <{value = dense<[0, 3, 1, 2]> : tensor<4xi32>}> : () -> tensor<4xi32> + %27 = tosa.transpose %25, %26 : (tensor<1x4x4x16xf32>, tensor<4xi32>) -> tensor<1x16x4x4xf32> + %28 = tosa.reshape %27 {new_shape = array} : (tensor<1x16x4x4xf32>) -> tensor<1x256xf32> + %29 = "tosa.const"() <{value = dense<[1, 0]> : tensor<2xi32>}> : () -> tensor<2xi32> + %30 = tosa.transpose %expanded_5, %29 : (tensor<120x256xf32>, tensor<2xi32>) -> tensor<256x120xf32> + %31 = tosa.reshape %28 {new_shape = array} : (tensor<1x256xf32>) -> tensor<1x1x256xf32> + %32 = tosa.reshape %30 {new_shape = array} : (tensor<256x120xf32>) -> tensor<1x256x120xf32> + %33 = tosa.matmul %31, %32 : (tensor<1x1x256xf32>, tensor<1x256x120xf32>) -> tensor<1x1x120xf32> + %34 = tosa.reshape %33 {new_shape = array} : (tensor<1x1x120xf32>) -> tensor<1x120xf32> + %35 = tosa.reshape %extracted_slice_6 {new_shape = array} : (tensor<120xf32>) -> tensor<1x120xf32> + %36 = tosa.add %35, %34 : (tensor<1x120xf32>, tensor<1x120xf32>) -> tensor<1x120xf32> + %37 = "tosa.const"() <{value = dense<0.000000e+00> : tensor<1x120xf32>}> : () -> tensor<1x120xf32> + %38 = tosa.maximum %36, %37 : (tensor<1x120xf32>, tensor<1x120xf32>) -> tensor<1x120xf32> + %39 = "tosa.const"() <{value = dense<[1, 0]> : tensor<2xi32>}> : () -> tensor<2xi32> + %40 = tosa.transpose %expanded_8, %39 : (tensor<84x120xf32>, tensor<2xi32>) -> tensor<120x84xf32> + %41 = tosa.reshape %38 {new_shape = array} : (tensor<1x120xf32>) -> tensor<1x1x120xf32> + %42 = tosa.reshape %40 {new_shape = array} : (tensor<120x84xf32>) -> tensor<1x120x84xf32> + %43 = tosa.matmul %41, %42 : (tensor<1x1x120xf32>, tensor<1x120x84xf32>) -> tensor<1x1x84xf32> + %44 = tosa.reshape %43 {new_shape = array} : (tensor<1x1x84xf32>) -> tensor<1x84xf32> + %45 = tosa.reshape %extracted_slice_9 {new_shape = array} : (tensor<84xf32>) -> tensor<1x84xf32> + %46 = tosa.add %45, %44 : (tensor<1x84xf32>, tensor<1x84xf32>) -> tensor<1x84xf32> + %47 = "tosa.const"() <{value = dense<0.000000e+00> : tensor<1x84xf32>}> : () -> tensor<1x84xf32> + %48 = tosa.maximum %46, %47 : (tensor<1x84xf32>, tensor<1x84xf32>) -> tensor<1x84xf32> + %49 = "tosa.const"() <{value = dense<[1, 0]> : tensor<2xi32>}> : () -> tensor<2xi32> + %50 = tosa.transpose %expanded_11, %49 : (tensor<10x84xf32>, tensor<2xi32>) -> tensor<84x10xf32> + %51 = tosa.reshape %48 {new_shape = array} : (tensor<1x84xf32>) -> tensor<1x1x84xf32> + %52 = tosa.reshape %50 {new_shape = array} : (tensor<84x10xf32>) -> tensor<1x84x10xf32> + %53 = tosa.matmul %51, %52 : (tensor<1x1x84xf32>, tensor<1x84x10xf32>) -> tensor<1x1x10xf32> + %54 = tosa.reshape %53 {new_shape = array} : (tensor<1x1x10xf32>) -> tensor<1x10xf32> + %55 = tosa.reshape %extracted_slice_12 {new_shape = array} : (tensor<10xf32>) -> tensor<1x10xf32> + %56 = tosa.add %55, %54 : (tensor<1x10xf32>, tensor<1x10xf32>) -> tensor<1x10xf32> + return %56 : tensor<1x10xf32> + } + + func.func @main() { + %fake_params = arith.constant dense<1.0> : tensor<44426xf32> + %fake_input = arith.constant dense<2.0> : tensor<1x1x28x28xf32> + + %t_start = call @rtclock() : () -> f64 + %fake_output = call @forward(%fake_params, %fake_input) : (tensor<44426xf32>, tensor<1x1x28x28xf32>) -> tensor<1x10xf32> + %t_end = call @rtclock() : () -> f64 + + %tensor_unranked = tensor.cast %fake_output : tensor<1x10xf32> to tensor<*xf32> + call @printMemrefF32(%tensor_unranked) : (tensor<*xf32>) -> () + + %time = arith.subf %t_end, %t_start : f64 + vector.print %time : f64 + + return + } +} diff --git a/examples/HeterLeNet/makefile b/examples/HeterLeNet/makefile new file mode 100644 index 00000000..c8b53c01 --- /dev/null +++ b/examples/HeterLeNet/makefile @@ -0,0 +1,116 @@ +#!/bin/bash +BUDDY_BUILD_DIR := ../../build/ +LLVM_BUILD_DIR := ../../llvm/build/ +BUDDY_OPT := ${BUDDY_BUILD_DIR}/bin/buddy-opt +MLIR_OPT := ${LLVM_BUILD_DIR}/bin/mlir-opt +MLIR_TRANSLATE := ${LLVM_BUILD_DIR}/bin/mlir-translate +MLIR_CPU_RUNNER := ${LLVM_BUILD_DIR}/bin/mlir-cpu-runner +LLC := ${LLVM_BUILD_DIR}/bin/llc +OPT_FLAG := -O3 + +ifeq ($(shell uname),Linux) +MLIR_RUNNER_UTILS := ${LLVM_BUILD_DIR}/lib/libmlir_runner_utils.so +MLIR_C_RUNNER_UTILS := ${LLVM_BUILD_DIR}/lib/libmlir_c_runner_utils.so +MLIR_ASYNC_RUNTIME := ${LLVM_BUILD_DIR}/lib/libmlir_async_runtime.so +MTRIPLE := x86_64-unknown-linux-gnu +else ifeq ($(shell uname),Darwin) +MLIR_RUNNER_UTILS := ${LLVM_BUILD_DIR}/lib/libmlir_runner_utils.dylib +MLIR_C_RUNNER_UTILS := ${LLVM_BUILD_DIR}/lib/libmlir_c_runner_utils.dylib +MLIR_ASYNC_RUNTIME := ${LLVM_BUILD_DIR}/lib/libmlir_async_runtime.dylib +MTRIPLE := x86_64-apple-darwin +endif + +buddy-lenet-lower: + @${BUDDY_OPT} ./subgraph0.mlir \ + -pass-pipeline "builtin.module(func.func(tosa-to-linalg-named, tosa-to-linalg, tosa-to-tensor, tosa-to-arith))" | \ + ${BUDDY_OPT} \ + -one-shot-bufferize\ + -func-bufferize-dynamic-offset\ + -convert-linalg-to-parallel-loops\ + -canonicalize\ + -gpu-map-parallel-loops\ + -convert-parallel-loops-to-gpu\ + -gpu-kernel-outlining\ + -buffer-deallocation\ + -canonicalize\ + -cse\ + -o ./log.mlir + +buddy-lenet-translate: + @${BUDDY_OPT} ./fake-lenet.mlir \ + -pass-pipeline "builtin.module(func.func(tosa-to-linalg-named, tosa-to-linalg, tosa-to-tensor, tosa-to-arith))" | \ + ${BUDDY_OPT} \ + -eliminate-empty-tensors \ + -convert-tensor-to-linalg \ + -linalg-bufferize \ + -convert-linalg-to-affine-loops \ + -lower-affine \ + -func-bufferize \ + -arith-bufferize \ + -tensor-bufferize \ + -buffer-deallocation \ + -finalizing-bufferize \ + -convert-vector-to-scf \ + -expand-strided-metadata \ + -convert-vector-to-llvm \ + -convert-arith-to-llvm \ + -finalize-memref-to-llvm \ + -convert-scf-to-cf \ + -convert-arith-to-llvm \ + -convert-func-to-llvm \ + -reconcile-unrealized-casts | \ + ${MLIR_TRANSLATE} -mlir-to-llvmir -o log.ll + + +buddy-lenet-run: + @${BUDDY_OPT} ./fake-lenet.mlir \ + -pass-pipeline "builtin.module(func.func(tosa-to-linalg-named, tosa-to-linalg, tosa-to-tensor, tosa-to-arith))" | \ + ${BUDDY_OPT} \ + -eliminate-empty-tensors \ + -convert-tensor-to-linalg \ + -linalg-bufferize \ + -convert-linalg-to-affine-loops \ + -lower-affine \ + -func-bufferize \ + -arith-bufferize \ + -tensor-bufferize \ + -buffer-deallocation \ + -finalizing-bufferize \ + -convert-vector-to-scf \ + -expand-strided-metadata \ + -convert-vector-to-llvm \ + -convert-arith-to-llvm \ + -finalize-memref-to-llvm \ + -convert-scf-to-cf \ + -convert-arith-to-llvm \ + -convert-func-to-llvm \ + -reconcile-unrealized-casts | \ + ${MLIR_CPU_RUNNER} ${OPT_FLAG} -e main -entry-point-result=void \ + -shared-libs=${MLIR_RUNNER_UTILS} -shared-libs=${MLIR_C_RUNNER_UTILS} + +buddy-lenet-opt-run: + @${BUDDY_OPT} ./fake-lenet.mlir \ + -pass-pipeline "builtin.module(func.func(tosa-to-linalg-named, tosa-to-linalg, tosa-to-tensor, tosa-to-arith))" | \ + ${BUDDY_OPT} \ + -eliminate-empty-tensors \ + -convert-tensor-to-linalg \ + -linalg-bufferize \ + -batchmatmul-optimize \ + -convert-linalg-to-affine-loops \ + -lower-affine \ + -func-bufferize \ + -arith-bufferize \ + -tensor-bufferize \ + -buffer-deallocation \ + -finalizing-bufferize \ + -convert-vector-to-scf \ + -expand-strided-metadata \ + -convert-vector-to-llvm \ + -convert-arith-to-llvm \ + -finalize-memref-to-llvm \ + -convert-scf-to-cf \ + -convert-arith-to-llvm \ + -convert-func-to-llvm \ + -reconcile-unrealized-casts | \ + ${MLIR_CPU_RUNNER} ${OPT_FLAG} -e main -entry-point-result=void \ + -shared-libs=${MLIR_RUNNER_UTILS} -shared-libs=${MLIR_C_RUNNER_UTILS} diff --git a/examples/HeterLeNet/pytorch-lenet-inference.py b/examples/HeterLeNet/pytorch-lenet-inference.py new file mode 100644 index 00000000..772262b2 --- /dev/null +++ b/examples/HeterLeNet/pytorch-lenet-inference.py @@ -0,0 +1,66 @@ +# ===- pytorch-lenet-inference.py ---------------------------------------------- +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# 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. +# +# ===--------------------------------------------------------------------------- +# +# LeNet inference with PyTorch runtime. +# +# ===--------------------------------------------------------------------------- + +import torch +from torchvision import transforms +from PIL import Image + +from model import LeNet + +# Load model +model = LeNet() +torch.load("./lenet-model.pth") +# Set the model to evaluation mode +model.eval() + +# Prepare image and convert to grayscale +image_path = "./images/3.png" +image = Image.open(image_path).convert("L") + +# Resize image to match the model's expected input dimensions +# Convert to tensor +# - This conversion is achieved by dividing the original pixel values by 255. +# - Before: An image with pixel values typically in the range [0, 255]. +# - After: A PyTorch tensor with the shape (C, H, W) and pixel values +# normalized to [0.0, 1.0]. +# Normalize +# - This step normalizes each channel of the tensor to have a mean of 0.5 and +# a standard deviation of 0.5. +# - Before: A tensor with pixel values in the range [0.0, 1.0]. +# - After: A tensor with pixel values normalized to the range [-1.0, 1.0], +# making the network training process more stable and faster by +# standardizing the range of input values. +transform = transforms.Compose( + [ + transforms.Resize((28, 28)), + transforms.ToTensor(), + transforms.Normalize((0.5,), (0.5,)), + ] +) +# Add batch dimension: [CHW] -> [NCHW] +image = transform(image).unsqueeze(0) + +# Perform inference +# No gradient tracking in this block +with torch.no_grad(): + output = model(image) + prediction = output.argmax() + +print(f"Classification: {prediction.item()}") diff --git a/examples/HeterLeNet/pytorch-lenet-train.py b/examples/HeterLeNet/pytorch-lenet-train.py new file mode 100644 index 00000000..4ee9e3ed --- /dev/null +++ b/examples/HeterLeNet/pytorch-lenet-train.py @@ -0,0 +1,59 @@ +# ===- pytorch-lenet-train.py -------------------------------------------------- +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# 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. +# +# ===--------------------------------------------------------------------------- +# +# LeNet traning with PyTorch runtime. +# +# ===--------------------------------------------------------------------------- + +import torch +import torch.nn as nn +import torch.optim as optim +from torchvision import datasets, transforms +from torch.utils.data import DataLoader + +from model import LeNet + +# Initialize model, loss function, and optimizer +model = LeNet() +criterion = nn.CrossEntropyLoss() +optimizer = optim.Adam(model.parameters()) + +# Prepare data +transform = transforms.Compose( + [transforms.ToTensor(), transforms.Normalize((0.5,), (0.5,))] +) +train_dataset = datasets.MNIST( + root="./data", train=True, download=True, transform=transform +) +train_loader = DataLoader(train_dataset, batch_size=64, shuffle=True) + +# Train model +epochs = 150 +for epoch in range(epochs): + model.train() + running_loss = 0.0 + for images, labels in train_loader: + optimizer.zero_grad() + outputs = model(images) + loss = criterion(outputs, labels) + loss.backward() + optimizer.step() + running_loss += loss.item() + print(f"Epoch {epoch+1}/{epochs} - Loss: {running_loss/len(train_loader)}") + +# Save the complete model +torch.save(model, "lenet-model.pth") +print("Model saved successfully.") diff --git a/frontend/Python/graph/transform/fuse_ops.py b/frontend/Python/graph/transform/fuse_ops.py index 2d22a1f5..f9292349 100644 --- a/frontend/Python/graph/transform/fuse_ops.py +++ b/frontend/Python/graph/transform/fuse_ops.py @@ -45,7 +45,7 @@ def classic_fuse_check(graph: Graph): """ for op in graph.body: pattern = None - if isinstance(op, MatmulOp): + if isinstance(op, (MatmulOp, AddMMOp)): parentop = [graph.node_table[str(i)] for i in op._parents] for target in parentop: if isinstance(target, PermuteOp) and target.args[ @@ -106,13 +106,13 @@ def apply_classic_fusion(graph: Graph): device = DeviceType.CPU # Run the first round of op fusion classic_fuse_check(graph) - for op in graph.body: - if isinstance(op, PlaceholderOp): - continue - new_op_group.append(op) - graph.op_groups = {} - graph.op_groups["subgraph0"] = new_op_group - graph.group_map_device = {"subgraph0": device} + # for op in graph.body: + # if isinstance(op, PlaceholderOp): + # continue + # new_op_group.append(op) + # graph.op_groups = {} + # graph.op_groups["subgraph0"] = new_op_group + # graph.group_map_device = {"subgraph0": device} def simply_fuse(graph: Graph):