Benchmarks: Add Feature - Add interface to get all predefine parameters of all benchmarks. (#56)

* Benchmarks: Add Feature - Add interface to get all predefine parameters of all benchmarks.

superbench/benchmarks/base.py

@@ -23,7 +23,7 @@ def __init__(self, name, parameters=''):
             parameters (str): benchmark parameters.
         """
         self._name = name
-        self._argv = list(filter(None, parameters.split(' ')))
+        self._argv = list(filter(None, parameters.split(' '))) if parameters is not None else list()
         self._benchmark_type = None
         self._parser = argparse.ArgumentParser(
             add_help=False,

superbench/benchmarks/registry.py

@@ -23,7 +23,7 @@ class BenchmarkRegistry:
     benchmarks: Dict[str, dict] = dict()
 
     @classmethod
-    def register_benchmark(cls, name, class_def, parameters=None, platform=None):
+    def register_benchmark(cls, name, class_def, parameters='', platform=None):
         """Register new benchmark, key is the benchmark name.
 
         Args:
@@ -67,6 +67,18 @@ def register_benchmark(cls, name, class_def, parameters=None, platform=None):
 
                 cls.benchmarks[name][p] = (class_def, parameters)
 
+        benchmark = class_def(name, parameters)
+        benchmark.add_parser_arguments()
+        ret, args, unknown = benchmark.parse_args()
+        if not ret or len(unknown) >= 1:
+            logger.log_and_raise(
+                TypeError,
+                'Registered benchmark has invalid arguments - benchmark: {}, parameters: {}'.format(name, parameters)
+            )
+        else:
+            cls.benchmarks[name]['predefine_param'] = vars(args)
+            logger.info('Benchmark registration - benchmark: {}, predefine_parameters: {}'.format(name, vars(args)))
+
     @classmethod
     def is_benchmark_context_valid(cls, benchmark_context):
         """Check wether the benchmark context is valid or not.
@@ -143,6 +155,19 @@ def get_benchmark_configurable_settings(cls, benchmark_context):
         else:
             return None
 
+    @classmethod
+    def get_all_benchmark_predefine_settings(cls):
+        """Get all registered benchmarks' predefine settings.
+
+        Return:
+            benchmark_params (dict[str, dict]): key is benchmark name,
+              value is the dict with structure: {'parameter': default_value}.
+        """
+        benchmark_params = dict()
+        for name in cls.benchmarks:
+            benchmark_params[name] = cls.benchmarks[name]['predefine_param']
+        return benchmark_params
+
     @classmethod
     def launch_benchmark(cls, benchmark_context):
         """Select and Launch benchmark.

tests/benchmarks/test_registry.py

@@ -7,6 +7,7 @@
 
 from superbench.benchmarks import Platform, Framework, BenchmarkType, BenchmarkRegistry, ReturnCode
 from superbench.benchmarks.micro_benchmarks import MicroBenchmark
+from superbench.benchmarks.micro_benchmarks.sharding_matmul import ShardingMode
 
 
 class AccumulationBenchmark(MicroBenchmark):
@@ -196,3 +197,20 @@ def test_launch_benchmark():
     benchmark = BenchmarkRegistry.launch_benchmark(context)
     assert (benchmark)
     assert (benchmark.return_code == ReturnCode.INVALID_ARGUMENT)
+
+
+def test_get_all_benchmark_predefine_settings():
+    """Test interface BenchmarkRegistry.get_all_benchmark_predefine_settings()."""
+    benchmark_params = BenchmarkRegistry.get_all_benchmark_predefine_settings()
+
+    # Choose benchmark 'pytorch-sharding-matmul' for testing.
+    benchmark_name = 'pytorch-sharding-matmul'
+    assert (benchmark_name in benchmark_params)
+    assert (benchmark_params[benchmark_name]['run_count'] == 1)
+    assert (benchmark_params[benchmark_name]['duration'] == 0)
+    assert (benchmark_params[benchmark_name]['n'] == 4096)
+    assert (benchmark_params[benchmark_name]['k'] == 4096)
+    assert (benchmark_params[benchmark_name]['m'] == 4096)
+    assert (benchmark_params[benchmark_name]['mode'] == [ShardingMode.ALLREDUCE, ShardingMode.ALLGATHER])
+    assert (benchmark_params[benchmark_name]['num_warmup'] == 10)
+    assert (benchmark_params[benchmark_name]['num_steps'] == 500)