test: benchgc: initial commit for benchgc

Author: WangJialei-A

test/benchgc/.gitignore

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+dist/
+src/benchgc.egg-info/
+build

test/benchgc/README.md

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+# benchgc - benchmark tool for graph compiler

test/benchgc/cases/add.mlir

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+module {
+  func.func @f32(%arg0: tensor<128x256xf32>, %arg1: tensor<128x256xf32>) -> tensor<128x256xf32> {
+    %0 = onednn_graph.add %arg0, %arg1 : (tensor<128x256xf32>, tensor<128x256xf32>) -> tensor<128x256xf32>
+    return %0 : tensor<128x256xf32>
+  }
+}

test/benchgc/cases/mlp.mlir

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+module {
+  func.func @bf16_layer2(%in: tensor<128x512xbf16>, 
+                 %weight0: tensor<512x256xbf16>, %bias0: tensor<256xbf16>, 
+                 %weight1: tensor<256x64xbf16>, %bias1: tensor<64xbf16>) -> tensor<128x64xbf16> {
+    // layer 0
+    %0 = onednn_graph.matmul %in, %weight0, %bias0 : (tensor<128x512xbf16>, tensor<512x256xbf16>, tensor<256xbf16>) -> tensor<128x256xbf16>
+    %1 = onednn_graph.relu %0 : (tensor<128x256xbf16>) -> tensor<128x256xbf16>
+    // layer 1
+    %2 = onednn_graph.matmul %1, %weight1, %bias1 : (tensor<128x256xbf16>, tensor<256x64xbf16>, tensor<64xbf16>) -> tensor<128x64xbf16>
+    %3 = onednn_graph.relu %2 : (tensor<128x64xbf16>) -> tensor<128x64xbf16>
+    return %3 : tensor<128x64xbf16>
+  }
+}

test/benchgc/setup.py

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+################################################################################
+# Copyright 2024 Intel Corporation
+#
+# 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.
+################################################################################
+
+import pathlib
+import sys
+import setuptools
+import os
+import subprocess
+from typing import List
+
+build_dir: pathlib.Path = pathlib.Path.cwd() / "build_temp"
+if not build_dir.exists():
+    build_dir.mkdir(parents=True)
+
+cmake_args: List[str] = [
+    f"-DPYTHON_EXECUTABLE={sys.executable}",
+    "-DCMAKE_BUILD_TYPE=Debug",
+    "-DMLIR_ENABLE_BINDINGS_PYTHON=ON",
+]
+if "SC_MLIR" in os.environ:
+    cmake_args.append(f"-DMLIR_DIR={os.environ['SC_MLIR']}")
+
+subprocess.run(["cmake", "../../../mlir", *cmake_args], cwd=build_dir, check=True)
+subprocess.run(["make", "-j"], cwd=build_dir, check=True)
+
+setuptools.setup(
+    name="benchgc",
+    description="benchmark tool for graph compiler",
+    package_dir={
+        "benchgc": "src/benchgc",
+        "gcext": "build_temp/python_packages/gcext_core/gcext",
+    },
+    packages=setuptools.find_packages("src")
+    + setuptools.find_packages("build_temp/python_packages/gcext_core"),
+    package_data={"gcext": ["_mlir_libs/*.so"]},
+    install_requires=["torch", "numpy"],
+)

test/benchgc/src/benchgc/__init__.py

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+################################################################################
+# Copyright 2024 Intel Corporation
+#
+# 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.
+################################################################################
+
+import sys
+import pathlib
+
+# add the path to $PYTHONPATH where pysc shared object is located
+sys.path.append(pathlib.Path(__file__).parent.resolve().__str__())

test/benchgc/src/benchgc/__main__.py

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+################################################################################
+# Copyright 2024 Intel Corporation
+#
+# 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.
+################################################################################
+
+
+import json
+import sys
+import argparse
+import gcext.ir
+import gcext.dialects.onednn_graph
+from . import graph, runner, gapi, util
+
+try:
+    parser = argparse.ArgumentParser(prog="benchmark tool for graph compiler")
+    parser.add_argument("--mlir", required=True, help="a mlir case file", type=str)
+    parser.add_argument("--entry", required=True, help="main entry function", type=str)
+    parser.add_argument(
+        "--json",
+        default=None,
+        help="dump graph api json file into the specified file name",
+        type=str,
+    )
+    parser.add_argument(
+        "--seed",
+        required=False,
+        default=0,
+        type=int,
+        help="a seed value to generate data filling",
+    )
+    parser.add_argument(
+        "--verbose",
+        type=int,
+        default=util.NO_VERBOSE,
+        help="verbose level",
+        choices=[
+            util.NO_VERBOSE,
+            util.COMPARE_VERBOSE,
+            util.ERROR_OUTPUT_VERBOSE,
+            util.OUTPUT_VERBOSE,
+            util.INPUT_VERBOSE,
+        ],
+    )
+
+    args = parser.parse_args()
+    util.set_seed(args.seed)
+except argparse.ArgumentError:
+    sys.stderr.write("Argument parse failed\n")
+    sys.exit(1)
+
+with open(args.mlir, "r") as mlir_file:
+    with gcext.ir.Context() as ctx:
+        gcext.dialects.onednn_graph.register_dialect()
+        module = gcext.ir.Module.parse(mlir_file.read())
+        g = gapi.MLIRGraph(module)
+        graph_object = g.convert_to_json('"' + args.entry + '"')
+        if args.json is not None:
+            with open(args.json, "w") as json_file:
+                json.dump(graph_object, json_file)