forked from jiuyuan/InfiniTensor
feat: 创建 pyinfinitensor 前端
- python 前端项目结构及打包和安装脚本 - 后端编译出 so 改名为 backend，增加 GraphHandler 修改图结构 - ci 支持测试这些功能 Signed-off-by: YdrMaster <ydrml@hotmail.com>
This commit is contained in:
parent
c7ec9ee6e7
commit
296fcc5aa0
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@ -6,8 +6,11 @@ on:
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- 'LICENSE'
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env:
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protobuf_download: https://github.com/protocolbuffers/protobuf/releases/download/v21.12/protobuf-cpp-3.21.12.tar.gz
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protobuf_version: 3.21.12
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protobuf-download: https://github.com/protocolbuffers/protobuf/releases/download/v21.12/protobuf-cpp-3.21.12.tar.gz
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protobuf-version: "3.21.12"
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python-version: "3.10"
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resnet-download: https://github.com/onnx/models/raw/main/vision/classification/resnet/model/resnet18-v2-7.onnx
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resnet-file: resnet18-v2-7.onnx
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jobs:
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build:
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@ -18,6 +21,11 @@ jobs:
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with:
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submodules: recursive
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- name: Set up Python ${{ env.python-version }}
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uses: actions/setup-python@v4
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with:
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python-version: ${{ env.python-version }}
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- name: Install libdw
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run: sudo apt-get update && sudo apt-get install libdw-dev
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@ -25,33 +33,38 @@ jobs:
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id: cache-protobuf
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uses: actions/cache@v3
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with:
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path: protobuf-${{ env.protobuf_version }}
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key: protobuf-${{ env.protobuf_version }}
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path: protobuf-${{ env.protobuf-version }}
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key: protobuf-${{ env.protobuf-version }}
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- name: Download and compile protobuf
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if: steps.cache-protobuf.outputs.cache-hit != 'true'
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run: |
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wget ${{ env.protobuf_download }}
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tar xf protobuf-cpp-${{ env.protobuf_version }}.tar.gz
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cd protobuf-${{ env.protobuf_version }}
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wget ${{ env.protobuf-download }}
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tar xf protobuf-cpp-${{ env.protobuf-version }}.tar.gz
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cd protobuf-${{ env.protobuf-version }}
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./autogen.sh
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./configure CFLAGS="-fPIC" CXXFLAGS="-fPIC"
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make -j2
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make -j8
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- name: Install protobuf
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run: |
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cd protobuf-${{ env.protobuf_version }}
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cd protobuf-${{ env.protobuf-version }}
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sudo make install
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sudo ldconfig
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- name: Build
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run: |
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mkdir build
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cd build
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cmake ..
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make -j2
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run: make
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- name: Test cpu
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run: make test-cpp
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- name: Install python-frontend
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run: |
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cd build
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make test
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python -m pip install --upgrade pip
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make install-python
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- name: Download test model
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run: wget ${{ env.resnet-download }}
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- name: Test onnx frontend
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run: make test-onnx
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@ -1,10 +1,12 @@
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name: clang-format Check
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on:
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pull_request:
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paths-ignore:
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- '**.md'
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- 'LICENSE'
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paths:
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- 'include/**'
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- 'src/**'
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- 'test/**'
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- '3rd-party/**'
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- '.clang-format'
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jobs:
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formatting-check:
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name: Formatting Check
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@ -37,4 +37,8 @@ build_debug/
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.vscode/
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# python
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*.pyc
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*.egg-info
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*.pyc
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# onnx model
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*.onnx
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@ -96,8 +96,8 @@ target_link_libraries(InfiniTensor pybind11::embed)
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# Python bindings
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file(GLOB_RECURSE FFIS src/ffi/ffi_infinitensor.cc)
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pybind11_add_module(pyinfinitensor MODULE ${FFIS})
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target_link_libraries(pyinfinitensor PRIVATE InfiniTensor)
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pybind11_add_module(backend MODULE ${FFIS})
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target_link_libraries(backend PRIVATE InfiniTensor)
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if(USE_BACKTRACE)
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add_definitions(-D BACKWARD_TRACE)
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@ -134,13 +134,13 @@ if(USE_BANG)
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set(NEUWARE_HOME $ENV{NEUWARE_HOME} CACHE STRING "NEUWARE_HOME directory for Cambricon Neuware development")
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endif()
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message(STATUS "NEUWARE_HOME: ${NEUWARE_HOME}")
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include_directories("${NEUWARE_HOME}/include")
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find_library(CAMBRICON_CNNL libcnnl.so "${NEUWARE_HOME}/lib64")
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find_library(CAMBRICON_CNRT libcnrt.so "${NEUWARE_HOME}/lib64")
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find_library(CAMBRICON_CNDRV libcndrv.so "${NEUWARE_HOME}/lib64")
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set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -lstdc++ -Wall -Werror")
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if ((NOT DEFINED TARGET_CPU_ARCH) AND (NOT DEFINED ENV{TARGET_CPU_ARCH}))
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execute_process(COMMAND uname -m OUTPUT_VARIABLE _uname_m OUTPUT_STRIP_TRAILING_WHITESPACE)
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set(TARGET_CPU_ARCH "${_uname_m}" CACHE STRING "Target CPU ARCH")
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@ -0,0 +1,22 @@
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.PHONY : build clean install-python test-cpp test-onnx
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TYPE ?= release
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build:
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mkdir -p build/$(TYPE)
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cd build/$(TYPE) && cmake -DCMAKE_BUILD_TYPE=$(TYPE) ../.. && make -j8
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clean:
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rm -rf build
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install-python: build
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cp build/$(TYPE)/backend*.so pyinfinitensor/src/pyinfinitensor
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pip install pyinfinitensor/
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test-cpp: build
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@echo
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cd build/$(TYPE) && make test
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test-onnx:
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@echo
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python3 pyinfinitensor/tests/test_onnx.py
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@ -0,0 +1,44 @@
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#pragma once
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#include "core/graph.h"
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#include "core/runtime.h"
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namespace infini {
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// 借用 onnx 的定义减小传递开销，来自 onnx 但不只用于 onnx。
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//
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// see https://onnx.ai/onnx/intro/concepts.html#element-type
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enum OnnxDType : int {
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UNDEFINED = 0,
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FLOAT,
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UINT8,
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INT8,
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UINT16,
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INT16,
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INT32,
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INT64,
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STRING,
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BOOL,
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FLOAT16,
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DOUBLE,
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UINT32,
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UINT64,
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COMPLEX64,
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COMPLEX128,
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BFLOAT16,
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};
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class GraphHandlerObj {
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Graph g;
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public:
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GraphHandlerObj(Runtime runtime)
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: g(make_ref<GraphObj>(std::move(runtime))) {}
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Tensor tensor(Shape dims, int dtype);
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Tensor matmul(Tensor a, Tensor b, Tensor y, bool transA, bool transB,
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Tensor bias, ActType act);
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};
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} // namespace infini
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@ -10,6 +10,7 @@ class TensorBaseObj;
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class TensorObj;
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class OperatorObj;
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class GraphObj;
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class GraphHandlerObj;
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class RuntimeObj;
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class BlobObj;
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@ -17,6 +18,7 @@ using TensorBase = Ref<TensorBaseObj>;
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using Tensor = Ref<TensorObj>;
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using Operator = Ref<OperatorObj>;
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using Graph = Ref<GraphObj>;
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using GraphHandler = Ref<GraphHandlerObj>;
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using Runtime = Ref<RuntimeObj>;
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using Blob = Ref<BlobObj>;
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enum class OpType;
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@ -0,0 +1,16 @@
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# pyinfinitensor
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InfiniTensor 的 Python 前端。
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- [ ] 从 ONNX 导入模型
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- [ ] 从 Pytorch 导入模型
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- [ ] 从 PaddlePaddle 导入模型
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- [ ] 模型导出到 ONNX
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- [ ] 模型导出到 Pytorch
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- [ ] 模型导出到 PaddlePaddle
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## python 工程结构及打包方法
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本项目使用 [pyproject.toml] 文件定义，目录结构采用 [src 布局](https://setuptools.pypa.io/en/latest/userguide/package_discovery.html#src-layout)，后端库会被[打包](https://setuptools.pypa.io/en/latest/userguide/datafiles.html#package-data)，并支持[自动的依赖安装](https://setuptools.pypa.io/en/latest/userguide/dependency_management.html#declaring-required-dependency)。
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参考 [setuptools 的文档](https://setuptools.pypa.io/en/latest/userguide/index.html)。
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@ -0,0 +1 @@
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@ -0,0 +1,21 @@
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[build-system]
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requires = ["setuptools"]
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build-backend = "setuptools.build_meta"
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[project]
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name = "pyinfinitensor"
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version = "0.0.0"
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authors = [{ name = "YdrMaster", email = "ydrml@hotmail.com" }]
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description = "Python frontend of InfiniTensor"
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readme = "README.md"
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requires-python = ">=3.8"
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keywords = ["optimizer"]
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license = { text = "Apache" }
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classifiers = ["Programming Language :: Python :: 3"]
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dependencies = ["onnx"]
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[tool.setuptools.packages.find]
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where = ["src"]
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[tool.setuptools.package-data]
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pyinfinitensor = ["*.so"]
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@ -0,0 +1,8 @@
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import sys
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from pathlib import Path
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sys.path.append(str(Path(str(__file__)).parent))
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import backend
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print("import backend: {}".format(backend))
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@ -0,0 +1,66 @@
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import onnx
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import backend
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runtime = backend.cpu_runtime()
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def from_onnx(model: onnx.ModelProto):
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handler = backend.GraphHandlerObj(runtime)
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tensors = dict()
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for input in model.graph.input:
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dims = [d.dim_value for d in input.type.tensor_type.shape.dim]
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tensors[input.name] = handler.tensor(dims, input.type.tensor_type.elem_type)
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for output in model.graph.output:
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dims = [d.dim_value for d in output.type.tensor_type.shape.dim]
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tensors[output.name] = handler.tensor(dims, output.type.tensor_type.elem_type)
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for node in model.graph.node:
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if node.op_type == "MatMul":
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handler.matmul(
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tensors[node.input[0]],
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tensors[node.input[1]],
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tensors[node.output[0]],
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False,
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False,
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None,
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backend.ActType.Linear,
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)
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def parse_onnx(model: onnx.ModelProto):
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print()
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for field in [
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"doc_string",
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"domain",
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"functions",
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"metadata_props",
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"model_version",
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"producer_name",
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"producer_version",
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"training_info",
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]:
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print("{}: {}".format(field, getattr(model, field)))
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print("ir_version:", model.ir_version)
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for opset in model.opset_import:
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print("opset domain={} version={}".format(opset.domain, opset.version))
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print("layout:")
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for node in model.graph.node:
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print(
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' {o} <- {op}"{name}"{a} <- {i}'.format(
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name=node.name,
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op=node.op_type,
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i=node.input,
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o=node.output,
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a=[a.name for a in node.attribute],
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)
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)
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print("weight:")
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for node in model.graph.initializer:
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print(" {}".format(node.name))
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@ -0,0 +1,43 @@
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import os, onnx, unittest
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from onnx import TensorProto
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from onnx.helper import make_model, make_node, make_graph, make_tensor_value_info
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from onnx.checker import check_model
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from pyinfinitensor.onnx import from_onnx, parse_onnx, backend, runtime
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class TestStringMethods(unittest.TestCase):
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def test_load(self):
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model_file = next(
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(name for name in os.listdir() if name.endswith(".onnx")), None
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)
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if model_file != None:
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print(
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"model: {file}({size:.2f} MiB)".format(
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file=model_file, size=os.path.getsize(model_file) / 1024 / 1024
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)
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)
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parse_onnx(onnx.load(model_file))
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def test_import(self):
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i = make_tensor_value_info("i", TensorProto.FLOAT, [1, 2, 3])
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w = make_tensor_value_info("w", TensorProto.FLOAT, [1, 3, 4])
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o = make_tensor_value_info("o", TensorProto.FLOAT, [1, 2, 4])
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matmul = make_node("MatMul", ["i", "w"], ["o"], name="matmul")
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graph = make_graph([matmul], "mm", [i, w], [o])
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model = make_model(graph)
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check_model(model)
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print(model)
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from_onnx(model)
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parse_onnx(model)
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def test_frontend(self):
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handler = backend.GraphHandlerObj(runtime)
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i = handler.tensor([1, 2, 3], 12)
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w = handler.tensor([1, 3, 4], 12)
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o = handler.tensor([1, 2, 4], 12)
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handler.matmul(i, w, o, False, False, None, backend.ActType.Relu)
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if __name__ == "__main__":
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unittest.main()
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@ -0,0 +1,37 @@
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#include "core/graph_handler.h"
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#include "operators/matmul.h"
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namespace infini {
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static DataType dtype_repr_convert(int);
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Tensor GraphHandlerObj::tensor(Shape dims, int dtype) {
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return g->addTensor(std::move(dims), dtype_repr_convert(dtype));
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}
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Tensor GraphHandlerObj::matmul(Tensor a, Tensor b, Tensor y, bool transA,
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bool transB, Tensor bias, ActType act) {
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if (y) {
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g->addOpWithOutputs<MatmulObj>(std::move(a), std::move(b), y, transA,
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transB, std::move(bias), act);
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return y;
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} else {
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return g
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->addOp<MatmulObj>(std::move(a), std::move(b), y, transA, transB,
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std::move(bias), act)
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->getOutput();
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}
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}
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static DataType dtype_repr_convert(int dtype) {
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switch ((OnnxDType)dtype) {
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case OnnxDType::FLOAT:
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return DataType::Float32;
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case OnnxDType::UINT32:
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return DataType::UInt32;
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default:
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IT_ASSERT(false, "Unsupported data type");
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}
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}
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} // namespace infini
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@ -1,7 +1,10 @@
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#include "core/graph_handler.h"
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#include <pybind11/stl.h>
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#ifdef USE_CUDA
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#include "cuda/operator_timer.h"
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#endif
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namespace py = pybind11;
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namespace infini {
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@ -18,6 +21,34 @@ void register_operator_timer(py::module &m) {
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#endif
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}
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void init_graph_builder(py::module &m) {
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m.def("cpu_runtime", &CpuRuntimeObj::getInstance);
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py::class_<RuntimeObj, std::shared_ptr<RuntimeObj>>(m, "RuntimeObj");
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py::class_<CpuRuntimeObj, std::shared_ptr<CpuRuntimeObj>, RuntimeObj>(
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m, "CpuRuntimeObj");
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py::class_<Shape>(m, "Shape");
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py::class_<TensorObj, std::shared_ptr<TensorObj>>(m, "TensorObj");
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py::class_<Tensor>(m, "Tensor");
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py::enum_<ActType>(m, "ActType")
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.value("Linear", ActType::None) // None 是 Python 关键字，不能用
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.value("Relu", ActType::Relu)
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.value("Sigmoid", ActType::Sigmoid)
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.value("Tanh", ActType::Tanh)
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.export_values();
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py::class_<GraphHandler>(m, "GraphHandler");
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py::class_<GraphHandlerObj>(m, "GraphHandlerObj")
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.def(py::init<Runtime>())
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.def("tensor", py::overload_cast<Shape, int>(&GraphHandlerObj::tensor),
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policy::reference_internal)
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.def("matmul",
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py::overload_cast<Tensor, Tensor, Tensor, bool, bool, Tensor,
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ActType>(&GraphHandlerObj::matmul),
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policy::reference_internal);
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}
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} // namespace infini
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PYBIND11_MODULE(pyinfinitensor, m) { infini::register_operator_timer(m); }
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PYBIND11_MODULE(backend, m) {
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infini::register_operator_timer(m);
|
||||
infini::init_graph_builder(m);
|
||||
}
|
||||
|
|
|
|||
|
|
@ -0,0 +1,2 @@
|
|||
def inc(x: int) -> int:
|
||||
return x + 1
|
||||
|
|
@ -0,0 +1,16 @@
|
|||
#include "core/graph_handler.h"
|
||||
#include "core/runtime.h"
|
||||
#include <test.h>
|
||||
|
||||
namespace infini {
|
||||
|
||||
TEST(Handler, matmul) {
|
||||
auto runtime = CpuRuntimeObj::getInstance();
|
||||
auto handler = make_ref<GraphHandlerObj>(runtime);
|
||||
auto i = handler->tensor({1, 2, 3}, OnnxDType::UINT32);
|
||||
auto w = handler->tensor({1, 3, 4}, OnnxDType::UINT32);
|
||||
auto o = handler->tensor({1, 2, 4}, OnnxDType::UINT32);
|
||||
handler->matmul(i, w, o, false, false, nullptr, ActType::None);
|
||||
}
|
||||
|
||||
} // namespace infini
|
||||
|
|
@ -0,0 +1,16 @@
|
|||
#include <filesystem>
|
||||
#include <pybind11/embed.h>
|
||||
#include <test.h>
|
||||
|
||||
TEST(Python, pybind) {
|
||||
namespace fs = std::filesystem;
|
||||
namespace py = pybind11;
|
||||
using mod = py::module;
|
||||
|
||||
py::scoped_interpreter _python;
|
||||
|
||||
auto sys_path_append = mod::import("sys").attr("path").attr("append");
|
||||
sys_path_append(fs::path(__FILE__).parent_path().c_str());
|
||||
auto ans = mod::import("python").attr("inc")(1);
|
||||
EXPECT_EQ(ans.cast<int>(), 2);
|
||||
}
|
||||
Loading…
Reference in New Issue