Merge pull request #5 from Joejiong/add-op-benchmark

Add conv2d mlir files and with naive implementation nchw& nhwc 

benchmarks/DeepLearning/CMakeLists.txt

 add_subdirectory(Models)
 add_subdirectory(Ops)
+

benchmarks/DeepLearning/Ops/CMakeLists.txt

 add_subdirectory(DepthwiseConv2DNhwcHwcOp)
+add_subdirectory(Conv2DNhwcHwcfOp)
+add_subdirectory(Conv2DNchwFchwOp)

benchmarks/DeepLearning/Ops/Conv2DNchwFchwOp/CMakeLists.txt

+set(BUDDY_OPT_ATTR avx512f)
+set(LLVM_MLIR_BINARY_DIR ${BUDDY_OPT_BUILD_DIR}/../llvm/build/bin)
+
+add_custom_command(OUTPUT conv-2d-nchw-fchw.o
+  COMMAND ${LLVM_MLIR_BINARY_DIR}/mlir-opt ${BUDDY_SOURCE_DIR}/benchmarks/DeepLearning/Ops/Conv2DNchwFchwOp/Conv2DNchwFchw.mlir 
+              -convert-linalg-to-loops 
+              -convert-scf-to-std 
+              -convert-linalg-to-llvm 
+              -lower-affine 
+              --convert-memref-to-llvm 
+              -convert-std-to-llvm='emit-c-wrappers=1' 
+              -reconcile-unrealized-casts| 
+                ${LLVM_MLIR_BINARY_DIR}/mlir-translate --mlir-to-llvmir |
+                ${LLVM_MLIR_BINARY_DIR}/llc -mtriple=x86_64-unknown-linux-gnu -mattr=${BUDDY_OPT_ATTR} 
+              --filetype=obj -o ${BUDDY_BINARY_DIR}/../benchmarks/DeepLearning/Ops/Conv2DNchwFchwOp/conv-2d-nchw-fchw.o
+)
+
+add_library(Conv2DNchwFchw conv-2d-nchw-fchw.o)
+
+set_target_properties(Conv2DNchwFchw PROPERTIES LINKER_LANGUAGE CXX)
+
+add_executable(conv-2d-nchw-fchw-benchmark Main.cpp MLIROptBenchmark.cpp)
+
+target_link_libraries(conv-2d-nchw-fchw-benchmark
+  GoogleBenchmark
+  Conv2DNchwFchw
+  Container
+)

benchmarks/DeepLearning/Ops/Conv2DNchwFchwOp/Conv2DNchwFchw.mlir

+// generate from iree processed alexnet or lenet mlir file
+func @conv_2d_nchw_fchw(%input: memref<?x?x?x?xf32>, %filter: memref<?x?x?x?xf32>, %output: memref<?x?x?x?xf32>) {
+    linalg.conv_2d_nchw_fchw 
+    {dilations = dense<1> : tensor<2xi64>, strides = dense<1> : tensor<2xi64>} 
+    ins(%input, %filter : memref<?x?x?x?xf32>, memref<?x?x?x?xf32>) 
+    outs(%output : memref<?x?x?x?xf32>)
+    return
+}

benchmarks/DeepLearning/Ops/Conv2DNchwFchwOp/MLIROptBenchmark.cpp

+//===- MLIROptBenchmark.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.
+//
+//===----------------------------------------------------------------------===//
+//
+// This file implements the benchmark for conv2d(nchw-fchw) operation.
+//
+//===----------------------------------------------------------------------===//
+
+#include "Utils/Container.h"
+#include <benchmark/benchmark.h>
+
+namespace
+{
+
+    // Declare the mobilenet C interface.
+    extern "C"
+    {
+        void _mlir_ciface_conv_2d_nchw_fchw(MemRef<float, 4> *input,
+                                            MemRef<float, 4> *filter,
+                                            MemRef<float, 4> *output);
+    }
+
+    intptr_t sizesInput[4] = {1, 2, 3, 3};
+    intptr_t sizesFilter[4] = {2, 2, 2, 2};
+    intptr_t sizesOutput[4] = {1, 2, 2, 2};
+
+    // Create input, filter, and output.
+    MemRef<float, 4> inputMemRef(sizesInput, 2.0);
+    MemRef<float, 4> filterMemRef(sizesFilter, 3.0);
+    MemRef<float, 4> outputMemRef(sizesOutput, 0.0);
+
+    // Define benchmark function.
+    void BM_Conv2DNchwFchw(benchmark::State &state)
+    {
+        for (auto _ : state)
+        {
+            for (int i = 0; i < state.range(0); ++i)
+            {
+                _mlir_ciface_conv_2d_nchw_fchw(&inputMemRef, &filterMemRef,
+                                               &outputMemRef);
+            }
+        }
+    }
+
+} // namespace
+
+// Register benchmarking function with different arguments.
+BENCHMARK(BM_Conv2DNchwFchw)->Arg(1);
+BENCHMARK(BM_Conv2DNchwFchw)->Arg(4);
+
+// Print result function.
+void printResult()
+{
+    // Clear the output memref.
+    MemRef<float, 4> outputMemRef(sizesOutput, 0.0);
+    // Run the mlir function.
+    _mlir_ciface_conv_2d_nchw_fchw(&inputMemRef, &filterMemRef,
+                                   &outputMemRef);
+    // Print the output.
+    std::cout << "Output: [ ";
+    for (int i = 0; i < 8; ++i)
+        std::cout << outputMemRef[i] << " ";
+    std::cout << "]" << std::endl;
+}

benchmarks/DeepLearning/Ops/Conv2DNchwFchwOp/Main.cpp

+//===- 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.
+//
+//===----------------------------------------------------------------------===//
+//
+// This is the main file of the conv2d(nchw_filter_fchw) benchmark.
+//
+//===----------------------------------------------------------------------===//
+
+#include <benchmark/benchmark.h>
+
+void printResult();
+
+int main(int argc, char **argv)
+{
+    // Run benchmark.
+    ::benchmark::Initialize(&argc, argv);
+    ::benchmark::RunSpecifiedBenchmarks();
+    // Print result.
+    printResult();
+
+    return 0;
+}
\ No newline at end of file

benchmarks/DeepLearning/Ops/Conv2DNhwcHwcfOp/CMakeLists.txt

+set(BUDDY_OPT_ATTR avx512f)
+set(LLVM_MLIR_BINARY_DIR ${BUDDY_OPT_BUILD_DIR}/../llvm/build/bin)
+
+add_custom_command(OUTPUT conv-2d-nhwc-hwcf.o
+  COMMAND ${LLVM_MLIR_BINARY_DIR}/mlir-opt ${BUDDY_SOURCE_DIR}/benchmarks/DeepLearning/Ops/Conv2DNhwcHwcfOp/Conv2DNhwcHwcf.mlir 
+              -convert-linalg-to-loops 
+              -convert-scf-to-std 
+              -convert-linalg-to-llvm 
+              -lower-affine 
+              --convert-memref-to-llvm 
+              -convert-std-to-llvm='emit-c-wrappers=1' 
+              -reconcile-unrealized-casts| 
+                ${LLVM_MLIR_BINARY_DIR}/mlir-translate --mlir-to-llvmir |
+                ${LLVM_MLIR_BINARY_DIR}/llc 
+              -mtriple=x86_64-unknown-linux-gnu 
+              -mattr=${BUDDY_OPT_ATTR} 
+              --filetype=obj 
+              -o ${BUDDY_BINARY_DIR}/../benchmarks/DeepLearning/Ops/Conv2DNhwcHwcfOp/conv-2d-nhwc-hwcf.o
+)
+
+add_library(Conv2DNhwcHwcf conv-2d-nhwc-hwcf.o)
+
+set_target_properties(Conv2DNhwcHwcf PROPERTIES LINKER_LANGUAGE CXX)
+
+add_executable(conv-2d-nhwc-hwcf-benchmark Main.cpp MLIROptBenchmark.cpp)
+
+target_link_libraries(conv-2d-nhwc-hwcf-benchmark
+  GoogleBenchmark
+  Conv2DNhwcHwcf
+  Container
+)

benchmarks/DeepLearning/Ops/Conv2DNhwcHwcfOp/Conv2DNhwcHwcf.mlir

+// generate from iree processed mobilenet mlir file
+func @conv_2d_nhwc_hwcf(%input: memref<?x?x?x?xf32>, %filter: memref<?x?x?x?xf32>, %output: memref<?x?x?x?xf32>) {
+    linalg.conv_2d_nhwc_hwcf 
+    {dilations = dense<1> : tensor<2xi64>, strides = dense<1> : tensor<2xi64>} 
+    ins(%input, %filter : memref<?x?x?x?xf32>, memref<?x?x?x?xf32>) 
+    outs(%output : memref<?x?x?x?xf32>) 
+    return
+}

benchmarks/DeepLearning/Ops/Conv2DNhwcHwcfOp/MLIROptBenchmark.cpp

+//===- MLIROptBenchmark.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.
+//
+//===----------------------------------------------------------------------===//
+//
+// This file implements the benchmark for conv2d(nhwc-hwcf) operation.
+//
+//===----------------------------------------------------------------------===//
+
+#include "Utils/Container.h"
+#include <benchmark/benchmark.h>
+
+namespace
+{
+
+    // Declare the mobilenet C interface.
+    extern "C"
+    {
+        void _mlir_ciface_conv_2d_nhwc_hwcf(MemRef<float, 4> *input,
+                                            MemRef<float, 4> *filter,
+                                            MemRef<float, 4> *output);
+    }
+
+    intptr_t sizesInput[4] = {1, 3, 3, 2};
+    intptr_t sizesFilter[4] = {2, 2, 2, 2};
+    intptr_t sizesOutput[4] = {1, 2, 2, 2};
+
+    // Create input, filter, and output.
+    MemRef<float, 4> inputMemRef(sizesInput, 2.0);
+    MemRef<float, 4> filterMemRef(sizesFilter, 3.0);
+    MemRef<float, 4> outputMemRef(sizesOutput, 0.0);
+
+    // Define benchmark function.
+    void BM_Conv2DNhwcHwcf(benchmark::State &state)
+    {
+        for (auto _ : state)
+        {
+            for (int i = 0; i < state.range(0); ++i)
+            {
+                _mlir_ciface_conv_2d_nhwc_hwcf(&inputMemRef, &filterMemRef,
+                                               &outputMemRef);
+            }
+        }
+    }
+
+} // namespace
+
+// Register benchmarking function with different arguments.
+BENCHMARK(BM_Conv2DNhwcHwcf)->Arg(1);
+BENCHMARK(BM_Conv2DNhwcHwcf)->Arg(4);
+
+// Print result function.
+void printResult()
+{
+    // Clear the output memref.
+    MemRef<float, 4> outputMemRef(sizesOutput, 0.0);
+    // Run the mlir function.
+    _mlir_ciface_conv_2d_nhwc_hwcf(&inputMemRef, &filterMemRef,
+                                   &outputMemRef);
+    // Print the output.
+    std::cout << "Output: [ ";
+    for (int i = 0; i < 8; ++i)
+        std::cout << outputMemRef[i] << " ";
+    std::cout << "]" << std::endl;
+}

benchmarks/DeepLearning/Ops/Conv2DNhwcHwcfOp/Main.cpp

+//===- 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.
+//
+//===----------------------------------------------------------------------===//
+//
+// This is the main file of the conv2d(nhwc_filter_hwcf) benchmark.
+//
+//===----------------------------------------------------------------------===//
+
+#include <benchmark/benchmark.h>
+
+void printResult();
+
+int main(int argc, char **argv) 
+{
+    // Run benchmark.
+    ::benchmark::Initialize(&argc, argv);
+    ::benchmark::RunSpecifiedBenchmarks();
+    // Print result.
+    printResult();
+
+    return 0;
+}
\ No newline at end of file