A fuse ops test

examples/BuddyFusedLeNet/CMakeLists.txt

@@ -0,0 +1,83 @@
+file(GLOB SUBGRAPH_FILES "${CMAKE_CURRENT_SOURCE_DIR}/subgraph*.mlir")
+
+add_custom_command(
+  OUTPUT ${BUDDY_EXAMPLES_DIR}/BuddyFusedLeNet/arg0.data
+         ${BUDDY_EXAMPLES_DIR}/BuddyFusedLeNet/forward.mlir
+         ${SUBGRAPH_FILES}
+  COMMAND python3 ${BUDDY_EXAMPLES_DIR}/BuddyFusedLeNet/buddy-lenet-import.py
+  COMMENT "Generating forward.mlir, subgraph*.mlir and parameter files"
+)
+
+set(SUBGRAPH_OBJECTS "")
+foreach(SUBGRAPH_FILE ${SUBGRAPH_FILES})
+  get_filename_component(SUBGRAPH_NAME ${SUBGRAPH_FILE} NAME_WE)
+  set(OBJECT_FILE ${BUDDY_BINARY_DIR}/../examples/BuddyFusedLeNet/${SUBGRAPH_NAME}.o)
+  list(APPEND SUBGRAPH_OBJECTS ${OBJECT_FILE})
+
+  add_custom_command(
+    OUTPUT ${OBJECT_FILE}
+    COMMAND ${BUDDY_BINARY_DIR}/buddy-opt ${SUBGRAPH_FILE}
+              -pass-pipeline
+              "builtin.module(func.func(tosa-to-linalg-named, tosa-to-arith, tosa-to-linalg, tosa-to-tensor))" |
+            ${BUDDY_BINARY_DIR}/buddy-opt
+              -convert-elementwise-to-linalg
+              -func-bufferize-dynamic-offset
+              -arith-bufferize
+              -func-bufferize
+              -tensor-bufferize
+              -linalg-bufferize
+              -finalizing-bufferize
+              -convert-linalg-to-loops
+              -lower-affine
+              -convert-scf-to-cf
+              -llvm-request-c-wrappers
+              -convert-math-to-llvm
+              -convert-math-to-libm
+              -convert-arith-to-llvm
+              -convert-func-to-llvm
+              -expand-strided-metadata
+              -finalize-memref-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 -O3
+              -o ${OBJECT_FILE}
+    DEPENDS ${SUBGRAPH_FILE} buddy-opt
+    COMMENT "Building ${SUBGRAPH_NAME}.o"
+    VERBATIM
+  )
+endforeach()
+
+add_custom_command(
+  OUTPUT forward.o
+  COMMAND ${LLVM_TOOLS_BINARY_DIR}/mlir-opt ${BUDDY_EXAMPLES_DIR}/BuddyFusedLeNet/forward.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 -O3
+            -o ${BUDDY_BINARY_DIR}/../examples/BuddyFusedLeNet/forward.o
+  DEPENDS ${BUDDY_EXAMPLES_DIR}/BuddyFusedLeNet/forward.mlir
+  COMMENT "Building forward.o"
+  VERBATIM
+)
+
+add_library(FUSED_LENET STATIC ${SUBGRAPH_OBJECTS} forward.o)
+
+SET_TARGET_PROPERTIES(FUSED_LENET PROPERTIES LINKER_LANGUAGE C)
+
+add_executable(buddy-fused-lenet-run buddy-lenet-main.cpp)
+target_link_directories(buddy-fused-lenet-run PRIVATE ${LLVM_LIBRARY_DIR})
+
+set(BUDDY_LENET_LIBS FUSED_LENET mlir_c_runner_utils ${PNG_LIBRARIES})
+
+target_link_libraries(buddy-fused-lenet-run ${BUDDY_LENET_LIBS})

examples/BuddyFusedLeNet/README.md

@@ -0,0 +1,47 @@
+# Buddy Compiler Fuse Ops Example
+
+## Fused LeNet Model Inference
+
+0. Activate your python environment.
+
+1. Build buddy-mlir
+
+```bash
+$ 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
+```
+
+2. 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:${PYTHONPATH}
+```
+
+3. Set the `FUSED_LENET_EXAMPLE_PATH` environment variable.
+
+```bash
+$ export FUSED_LENET_EXAMPLE_PATH=${BUDDY_MLIR_BUILD_DIR}/../examples/BuddyFusedLeNet/
+```
+
+4. Build and run the Fused LeNet example
+
+```bash
+$ cmake -G Ninja .. -DBUDDY_FUSED_LENET_EXAMPLES=ON
+$ ninja buddy-fused-lenet-run
+$ cd bin
+$ ./buddy-fused-lenet-run
+```

examples/BuddyFusedLeNet/buddy-lenet-import.py

@@ -0,0 +1,79 @@
+# ===- 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 numpy as np
+import torch
+from torch._inductor.decomposition import decompositions as inductor_decomp
+
+from buddy.compiler.frontend import DynamoCompiler
+from buddy.compiler.graph import GraphDriver
+from buddy.compiler.graph.transform import simply_fuse, my_fuse_ops_test
+from buddy.compiler.ops import tosa
+from model import LeNet
+
+# Retrieve the LeNet model path from environment variables.
+model_path = os.environ.get("FUSED_LENET_EXAMPLE_PATH")
+if model_path is None:
+    raise EnvironmentError(
+        "The environment variable 'LENET_MODEL_PATH' is not set or is invalid."
+    )
+
+model = LeNet()
+model = torch.load(model_path + "/lenet-model.pth")
+model = model.eval()
+
+# Initialize Dynamo Compiler with specific configurations as an importer.
+dynamo_compiler = DynamoCompiler(
+    primary_registry=tosa.ops_registry,
+    aot_autograd_decomposition=inductor_decomp,
+)
+
+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)
+
+assert len(graphs) == 1
+graph = graphs[0]
+params = dynamo_compiler.imported_params[graph]
+pattern_list = [my_fuse_ops_test]
+graph.fuse_ops(pattern_list)
+driver = GraphDriver(graph)
+path_prefix = os.path.dirname(os.path.abspath(__file__))
+
+for i in range(len(driver.subgraphs)):
+    driver.subgraphs[i].lower_to_top_level_ir()
+    with open(os.path.join(path_prefix, f"subgraph{i}.mlir"), "w") as module_file:
+        print(driver.subgraphs[i]._imported_module, file=module_file)
+
+with open(os.path.join(path_prefix, "forward.mlir"), "w") as module_file:
+    print(driver.construct_main_graph(True), file=module_file)
+
+params = dynamo_compiler.imported_params[graph]
+current_path = os.path.dirname(os.path.abspath(__file__))
+
+float32_param = np.concatenate(
+    [param.detach().numpy().reshape([-1]) for param in params]
+)
+
+float32_param.tofile(Path(current_path) / "arg0.data")

examples/BuddyFusedLeNet/buddy-lenet-main.cpp

@@ -0,0 +1,133 @@
+//===- 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 <buddy/Core/Container.h>
+#include <buddy/DIP/ImgContainer.h>
+#include <chrono>
+#include <cmath>
+#include <cstdlib>
+#include <filesystem>
+#include <fstream>
+#include <limits>
+#include <string>
+#include <utility>
+#include <vector>
+
+constexpr size_t ParamsSize = 44426;
+const std::string ImgName = "1-28*28.png";
+
+/// Declare LeNet forward function.
+extern "C" void _mlir_ciface_forward(MemRef<float, 2> *output,
+                                     MemRef<float, 1> *arg0,
+                                     dip::Image<float, 4> *input);
+
+/// 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 &paramFilePath,
+                    MemRef<float, 1> &params) {
+  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<char *>(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<double, std::milli> 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 = "Fused 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};
+
+  // Create input and output containers for the image and model output.
+  std::string lenetDir = getenv("FUSED_LENET_EXAMPLE_PATH");
+  std::string imgPath = lenetDir + "/images/" + ImgName;
+  dip::Image<float, 4> input(imgPath, dip::DIP_GRAYSCALE, true /* norm */);
+  MemRef<float, 2> output(sizesOutput);
+
+  // Load model parameters from the specified file.
+  std::string paramsDir = lenetDir + "/arg0.data";
+  MemRef<float, 1> paramsContainer({ParamsSize});
+  loadParameters(paramsDir, paramsContainer);
+
+  // Call the forward function of the model.
+  _mlir_ciface_forward(&output, &paramsContainer, &input);
+
+  // 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;
+}

examples/BuddyFusedLeNet/model.py

@@ -0,0 +1,41 @@
+# ===- model.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 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

examples/CMakeLists.txt

@@ -16,6 +16,10 @@ if (BUDDY_LENET_EXAMPLES)
   add_subdirectory(BuddyLeNet)
 endif()
 
+if (BUDDY_FUSED_LENET_EXAMPLES)
+  add_subdirectory(BuddyFusedLeNet)
+endif()
+
 if(BUDDY_WHISPER_EXAMPLES)
   add_subdirectory(BuddyWhisper)
 endif()