Add --benchmark_dispatches option to pytest. (#800)

* Add --benchmark_dispatches option to pytest.

* Update README.md and fix filepath for dispatch benchmarks

README.md

@@ -215,14 +215,14 @@ python -m  shark.examples.shark_inference.resnet50_script --device="cpu" # Use g
 pytest tank/test_models.py -k "MiniLM"
 ```
   
-
+### How to use your locally built IREE / Torch-MLIR with SHARK
 If you are a *Torch-mlir developer or an IREE developer* and want to test local changes you can uninstall
 the provided packages with `pip uninstall torch-mlir` and / or `pip uninstall iree-compiler iree-runtime` and build locally
 with Python bindings and set your PYTHONPATH as mentioned [here](https://github.com/iree-org/iree/tree/main/docs/api_docs/python#install-iree-binaries)
 for IREE and [here](https://github.com/llvm/torch-mlir/blob/main/development.md#setup-python-environment-to-export-the-built-python-packages)
 for Torch-MLIR.
 
-### How to use your locally built Torch-MLIR with SHARK
+How to use your locally built Torch-MLIR with SHARK:
 ```shell
 1.) Run `./setup_venv.sh in SHARK` and activate `shark.venv` virtual env.
 2.) Run `pip uninstall torch-mlir`.
@@ -240,9 +240,15 @@ Now the SHARK will use your locally build Torch-MLIR repo.
 
 ## Benchmarking Dispatches
 
-To produce benchmarks of individual dispatches, you can add `--dispatch_benchmarks=All --dispatch_benchmarks_dir=<output_dir>` to your command line argument.  
+To produce benchmarks of individual dispatches, you can add `--dispatch_benchmarks=All --dispatch_benchmarks_dir=<output_dir>` to your pytest command line argument.  
 If you only want to compile specific dispatches, you can specify them with a space seperated string instead of `"All"`.  E.G. `--dispatch_benchmarks="0 1 2 10"`
 
+For example, to generate and run dispatch benchmarks for MiniLM on CUDA:
+```
+pytest -k "MiniLM and torch and static and cuda" --benchmark_dispatches=All -s --dispatch_benchmarks_dir=./my_dispatch_benchmarks                                                                                
+```
+The given command will populate `<dispatch_benchmarks_dir>/<model_name>/` with an `ordered_dispatches.txt` that lists and orders the dispatches and their latencies, as well as folders for each dispatch that contain .mlir, .vmfb, and results of the benchmark for that dispatch.
+
 if you want to instead incorporate this into a python script, you can pass the `dispatch_benchmarks` and `dispatch_benchmarks_dir` commands when initializing `SharkInference`, and the benchmarks will be generated when compiled.  E.G:
 
 ```
@@ -266,7 +272,7 @@ Output will include:
 - A .txt file containing benchmark output
 
 
-See tank/README.md for instructions on how to run model tests and benchmarks from the SHARK tank.
+See tank/README.md for further instructions on how to run model tests and benchmarks from the SHARK tank.
 
 </details>
 

conftest.py

@@ -60,3 +60,13 @@ def pytest_addoption(parser):
         default="gs://shark_tank/latest",
         help="URL to bucket from which to download SHARK tank artifacts. Default is gs://shark_tank/latest",
     )
+    parser.addoption(
+        "--benchmark_dispatches",
+        default=None,
+        help="Benchmark individual dispatch kernels produced by IREE compiler. Use 'All' for all, or specific dispatches e.g. '0 1 2 10'",
+    )
+    parser.addoption(
+        "--dispatch_benchmarks_dir",
+        default="./temp_dispatch_benchmarks",
+        help="Directory in which dispatch benchmarks are saved.",
+    )

shark/iree_utils/benchmark_utils.py

@@ -139,9 +139,14 @@ def run_benchmark_module(benchmark_cl):
         benchmark_path
     ), "Cannot find benchmark_module, Please contact SHARK maintainer on discord."
     bench_result = run_cmd(" ".join(benchmark_cl))
-    print(bench_result)
-    regex_split = re.compile("(\d+[.]*\d*)(  *)([a-zA-Z]+)")
-    match = regex_split.search(bench_result)
-    time = float(match.group(1))
-    unit = match.group(3)
+    try:
+        regex_split = re.compile("(\d+[.]*\d*)(  *)([a-zA-Z]+)")
+        match = regex_split.search(bench_result)
+        time = float(match.group(1))
+        unit = match.group(3)
+    except AttributeError:
+        regex_split = re.compile("(\d+[.]*\d*)([a-zA-Z]+)")
+        match = regex_split.search(bench_result)
+        time = float(match.group(1))
+        unit = match.group(2)
     return 1.0 / (time * 0.001)

tank/test_models.py

@@ -137,6 +137,19 @@ class SharkModuleTester:
     def create_and_check_module(self, dynamic, device):
         shark_args.local_tank_cache = self.local_tank_cache
         shark_args.force_update_tank = self.update_tank
+        shark_args.dispatch_benchmarks = self.benchmark_dispatches
+        if self.benchmark_dispatches is not None:
+            _m = self.config["model_name"].split("/")
+            _m.extend([self.config["framework"], str(dynamic), device])
+            _m = "_".join(_m)
+            shark_args.dispatch_benchmarks_dir = os.path.join(
+                self.dispatch_benchmarks_dir,
+                _m,
+            )
+            if not os.path.exists(self.dispatch_benchmarks_dir):
+                os.mkdir(self.dispatch_benchmarks_dir)
+            if not os.path.exists(shark_args.dispatch_benchmarks_dir):
+                os.mkdir(shark_args.dispatch_benchmarks_dir)
         if "nhcw-nhwc" in self.config["flags"] and not os.path.isfile(
             ".use-iree"
         ):
@@ -278,6 +291,12 @@ class SharkModuleTest(unittest.TestCase):
             "update_tank"
         )
         self.module_tester.tank_url = self.pytestconfig.getoption("tank_url")
+        self.module_tester.benchmark_dispatches = self.pytestconfig.getoption(
+            "benchmark_dispatches"
+        )
+        self.module_tester.dispatch_benchmarks_dir = (
+            self.pytestconfig.getoption("dispatch_benchmarks_dir")
+        )
 
         if config["xfail_cpu"] == "True" and device == "cpu":
             pytest.xfail(reason=config["xfail_reason"])