[e2e] add profiler entry for single stablehlo/mhlo file

frontends/torch-frontend/torch-frontend/python/torch_frontend/byteir_backend/inner_compile.py

@@ -95,8 +95,7 @@ def inner_compile(gm: torch.fx.GraphModule,
             module = torch_frontend.compile_dynamo_model(
                 gm,
                 output_type="stablehlo",
-                backend_legal_ops=BACKEND_LEGAL_OPS,
-                debug=DebugType.PRINT_AFTER_FALIURE)
+                backend_legal_ops=BACKEND_LEGAL_OPS)
             with open(stablehlo_file, "w") as f:
                 print(module.operation.get_asm(), file=f)
         if not os.path.exists(byre_file):

tests/numerical_test/execute.py

@@ -223,7 +223,7 @@ def profile(self, inputs, outputs, warmup_trials=10, run_trials=50):
         return ((end - start) * 1000) / run_trials
 
 
-def compile_and_run_mlir(mhlo_file, target, verbose, mode="numerical", **kwargs):
+def compile_and_run_mlir(mhlo_file, target, verbose, mode="numerical", workdir="./local_test", unique_name=None, **kwargs):
     try:
         data_generator = MLIRDataGenerator(mhlo_file, target)
         entry_func_name = data_generator.entry_func_name
@@ -236,12 +236,12 @@ def compile_and_run_mlir(mhlo_file, target, verbose, mode="numerical", **kwargs)
             interp = Interpreter.load_from_file(mhlo_file, is_stablehlo=True)
             golden_outputs = interp.call_function(entry_func_name, np_inputs)
 
-        unique_name = os.path.basename(mhlo_file).split(".")[0] + "." + target
+        if unique_name is None:
+            unique_name = os.path.basename(mhlo_file).split(".")[0] + "." + target
         # byteir compile
-        TEMP_FOLDER = "./local_test"
-        os.makedirs(TEMP_FOLDER, exist_ok=True)
-        os.makedirs(TEMP_FOLDER + f"/{unique_name}", exist_ok=True)
-        output_mlir_file_name = f"{TEMP_FOLDER}/{unique_name}/{unique_name}.rt.mlir"
+        os.makedirs(workdir, exist_ok=True)
+        os.makedirs(workdir + f"/{unique_name}", exist_ok=True)
+        output_mlir_file_name = f"{workdir}/{unique_name}/{unique_name}.rt.mlir"
         byteir.compile(
             mhlo_file,
             output_mlir_file_name,
@@ -317,7 +317,7 @@ def compile_and_run_mlir(mhlo_file, target, verbose, mode="numerical", **kwargs)
     )
 
 
-def compile_and_run_torch(test, target, verbose, mode="numerical"):
+def compile_and_run_torch(test, target, verbose, mode="numerical", workdir="./local_test"):
     import torch_frontend
 
     cur_device = get_target_device(target)
@@ -339,11 +339,10 @@ def compile_and_run_torch(test, target, verbose, mode="numerical"):
 
         unique_name = test.unique_name + "." + target
         # byteir compile
-        TEMP_FOLDER = "./local_test"
-        os.makedirs(TEMP_FOLDER, exist_ok=True)
-        os.makedirs(TEMP_FOLDER + f"/{unique_name}", exist_ok=True)
-        mlir_file_name = f"{TEMP_FOLDER}/{unique_name}/{unique_name}.stablehlo.mlir"
-        output_mlir_file_name = f"{TEMP_FOLDER}/{unique_name}/{unique_name}.rt.mlir"
+        os.makedirs(workdir, exist_ok=True)
+        os.makedirs(workdir + f"/{unique_name}", exist_ok=True)
+        mlir_file_name = f"{workdir}/{unique_name}/{unique_name}.stablehlo.mlir"
+        output_mlir_file_name = f"{workdir}/{unique_name}/{unique_name}.rt.mlir"
         with open(mlir_file_name, "w+") as fout:
             compiled_graph.operation.print(file=fout, large_elements_limit=None)
         byteir.compile(

tests/numerical_test/profiler.py

@@ -0,0 +1,34 @@
+# Copyright 2022 ByteDance Ltd. and/or its affiliates. All rights reserved.
+# 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 argparse
+
+from execute import compile_and_run_mlir
+from reporting import report_results
+
+def parse_args():
+    parser = argparse.ArgumentParser()
+    parser.add_argument("input_mlir_path")
+    parser.add_argument("--workdir", type=str, default="./profiling", help="workspace directory")
+    parser.add_argument("--name", type=str, default="model")
+    parser.add_argument("--target", type=str, default="cuda", choices=["cpu", "cuda", "cuda_with_ait"])
+    parser.add_argument("--mode", type=str, default="profile", choices=["numerical", "profile"])
+    parser.add_argument("-v", "--verbose", default=False, action="store_true")
+    return parser.parse_args()
+
+if __name__ == "__main__":
+    args = parse_args()
+
+    result = compile_and_run_mlir(args.input_mlir_path, args.target, args.verbose, mode=args.mode, workdir=args.workdir, unique_name=args.name)
+    report_results([result])