Merge pull request #7 from clang-ykt/setup-buildbot

Set up CI build process

.circleci/config.yml

@@ -2,15 +2,59 @@ version: 2
 jobs:
   build:
     docker:
-      - image: debian:stretch
+      - image: circleci/python
 
     steps:
       - checkout
-
       - run:
-          name: Greeting
+          name: "Pull Submodules"
-          command: echo Hello, world.
+          command: |
+            git submodule update --init --recursive
+      - run:
+          name: Check current directory
+          command: pwd
+      - run:
+          name: Check current directory content
+          command: ls
+      - run:
+          name: Installing GCC
+          command: 'sudo apt-get update && sudo apt-get install -y gcc g++'
+      - run:
+          name: Install CMAKE
+          command: 'sudo apt-get update && sudo apt-get install -y cmake ninja-build'
+      - run:
+          name: Install Protobuf
+          command: 'sudo apt-get update && sudo apt-get install -y protobuf-compiler'
+      - run:
+          name: Check gcc version
+          command: gcc --version
 
+      - restore_cache:
+          key: ONNF-MLIR-{{ arch }}
+      - run:
+          name: Install MLIR
+          command: |
+            if [ ! -f llvm-project/build/bin/mlir-opt ]; then
+              git clone https://github.com/llvm/llvm-project.git  
+              cd llvm-project && git checkout 9b6ad8466bb8b97082b705270603ad7f4559e931 && cd ..
+              git clone https://github.com/tensorflow/mlir llvm-project/llvm/projects/mlir 
+              cd llvm-project/llvm/projects/mlir && git checkout 0710266d0f56cf6ab0f437badbd7416b6cecdf5f && cd ../../../..
+              mkdir llvm-project/build 
+              cd llvm-project/build 
+              cmake -G Ninja ../llvm -DLLVM_ENABLE_RTTI=ON  -DLLVM_BUILD_EXAMPLES=OFF -DLLVM_TARGETS_TO_BUILD="host" -DCMAKE_BUILD_TYPE=Release
+              CMAKE_EXE_LINKER_FLAGS="-Wl,--reduce-memory-overheads -Wl,--hash-size=512" cmake --build . --target check-mlir -- -j 4
+            fi
+      - save_cache:
+          key: ONNF-MLIR-{{ arch }}
+          paths:
+            - llvm-project
+      - run:
+          name: Install ONNF
+          command: |
+            mkdir build && cd build
+            LLVM_SRC=$(pwd)/../llvm-project/llvm LLVM_BUILD=$(pwd)/../llvm-project/build cmake ..
+            make all
+            LIT_OPTS=-v make check-mlir-lit
       - run:
           name: Print the Current Time
           command: date

README.md

@@ -1,2 +1,66 @@
 # ONNF
-Open Neural Network Frontend
+Open Neural Network Frontend : an ONNX frontend for MLIR.
+
+[![CircleCI](https://circleci.com/gh/clang-ykt/ONNF.svg?style=svg)](https://circleci.com/gh/clang-ykt/ONNF)
+
+## Installation
+
+We assume an existing installation of MLIR. The LLVM-Project repo commit hash we used to test against is 9b6ad8466bb8b97082b705270603ad7f4559e931 and the MLIR repo commit hash we used is 0710266d0f56cf6ab0f437badbd7416b6cecdf5f. 
+
+Two environment variables need to be set:
+- LLVM_SRC should point to the llvm src directory (e.g., llvm-project/llvm).
+- LLVM_BUILD should point to the llvm build directory (e.g., llvm-project/build).
+
+To build ONNF, use the following command:
+```
+git clone --recursive git@github.com:clang-ykt/ONNF.git
+mkdir build
+cd build
+cmake ..
+cmake --build . --target all
+```
+
+After the above commands succeed, an `onnf` executable should appear in the `bin` directory. 
+
+## Using ONNF
+
+The usage of `onnf` is as such:
+```
+OVERVIEW: ONNF MLIR modular optimizer driver
+
+USAGE: onnf [options] <input file>
+
+OPTIONS:
+
+Generic Options:
+
+  --help        - Display available options (--help-hidden for more)
+  --help-list   - Display list of available options (--help-list-hidden for more)
+  --version     - Display the version of this program
+
+ONNF Options:
+These are frontend options.
+
+  Choose target to emit:
+      --EmitONNXIR - Ingest ONNX and emit corresponding ONNX dialect.
+      --EmitMLIR   - Lower model to MLIR built-in transformation dialect.
+      --EmitLLVMIR - Lower model to LLVM IR (LLVM dialect).
+      --EmitLLVMBC - Lower model to LLVM IR and emit (to file) LLVM bitcode for model.
+```
+
+## Example
+
+For example, to lower an ONNX model (e.g., add.onnx) to ONNX dialect, use the following command:
+```
+./onnf --EmitONNXIR add.onnx
+```
+The output should look like:
+```
+module {
+  func @main_graph(%arg0: tensor<10x10x10xf32>, %arg1: tensor<10x10x10xf32>) -> tensor<10x10x10xf32> {
+    %0 = "onnx.Add"(%arg0, %arg1) : (tensor<10x10x10xf32>, tensor<10x10x10xf32>) -> tensor<10x10x10xf32>
+    return %0 : tensor<10x10x10xf32>
+  }
+}
+```
+

src/CMakeLists.txt

@@ -7,11 +7,9 @@ add_library(compiler
         dialect/onnx/onnx_ops.hpp
         dialect/krnl/krnl_helper.cpp
         dialect/krnl/krnl_helper.hpp
-        pass/shape_inference_pass.cpp
         pass/shape_inference_interface.hpp
         dialect/onnx/onnxop.inc
         pass/onnx_combine.cpp
-        pass/lower_frontend_to_krnl.cpp
         pass/passes.hpp)
 
 # Include root src directory.
@@ -70,7 +68,7 @@ add_subdirectory(runtime)
 
 add_executable(onnf main.cpp)
 
-target_link_libraries(onnf builder ${MLIRLibs} onnf_transform)
+target_link_libraries(onnf builder ${MLIRLibs} onnf_transform onnf_shape_inference onnf_lower_frontend)
 set_target_properties(onnf PROPERTIES LINK_FLAGS "-lz")
 whole_archive_link_mlir(onnf ${MLIRWholeArchiveLibs})
 

src/pass/lower_frontend_to_krnl.cpp

@@ -331,9 +331,9 @@ Value *mapToLowerScalarOp<ONNXTanhOp>(Operation *op,
   auto neg = rewriter.create<SubFOp>(loc, zero, operand);
   auto exp = rewriter.create<ExpOp>(loc, operand);
   auto negExp = rewriter.create<ExpOp>(loc, neg);
-  auto result =
+  auto diff = rewriter.create<SubFOp>(loc, exp, negExp);
-      rewriter.create<DivFOp>(loc, rewriter.create<SubFOp>(loc, exp, negExp),
+  auto sum = rewriter.create<AddFOp>(loc, exp, negExp);
-                              rewriter.create<AddFOp>(loc, exp, negExp));
+  auto result = rewriter.create<DivFOp>(loc, diff, sum);
 
   return result;
 }

src/tool/onnf_opt/CMakeLists.txt

@@ -4,9 +4,6 @@ add_dependencies(onnf-opt gen_krnl_ops)
 target_include_directories(onnf-opt PRIVATE ${ONNF_SRC_ROOT})
 target_include_directories(onnf-opt PRIVATE ${ONNF_BIN_ROOT})
 
-target_link_libraries(onnf-opt compiler ${MLIRLibs})
+target_link_libraries(onnf-opt ${MLIRLibs} curses)
 whole_archive_link_mlir(onnf-opt ${MLIRWholeArchiveLibs})
-whole_archive_link_onnf(onnf-opt onnf_transform onnf_lower_frontend onnf_shape_inference)
+whole_archive_link_onnf(onnf-opt compiler onnf_transform onnf_lower_frontend onnf_shape_inference)
-
-# TODO: need to investigate how to whole-archive link compiler pass to onnf-opt.
-target_link_libraries(onnf-opt compiler)