Fix non-existing parameters in docstrings in benchmarks (#91115)

This is a continuation of https://github.com/pytorch/pytorch/pull/90505
Pull Request resolved: https://github.com/pytorch/pytorch/pull/91115
Approved by: https://github.com/clee2000

benchmarks/distributed/rpc/parameter_server/launcher.py

@@ -117,7 +117,7 @@ def run_trainer(
         extra_args (dict): configurations added by the user
         data (list): training samples
         rank (int): process number in the world
-        server_rrefs (dict): a dictionary containing server RRefs
+        server_rref (dict): a dictionary containing server RRefs
     """
     trainer_class = trainer_map[args.trainer]
     if extra_args is not None:

benchmarks/distributed/rpc/parameter_server/trainer/ddp_models.py

@@ -11,7 +11,7 @@ def basic_ddp_model(self, rank, model, process_group, hook_state, hook):
         rank (int): worker rank
         model (nn.Module): neural network model
         process_group (ProcessGroup): distributed process group
-        HookState (class): class that will be used to keep track of state
+        hook_state (class): class that will be used to keep track of state
             during training.
         hook (function): ddp communication hook
     """

benchmarks/operator_benchmark/benchmark_core.py

@@ -47,7 +47,7 @@ def _create_test(bench_op_obj, orig_test_attrs, tags, OperatorTestCase, run_back
             bench_op_obj: an object which instantiated from a subclass of
                 Caffe2BenchmarkBase/TorchBenchmarkBase which includes tensor
                 creation and operator execution.
-            test_attrs: a dictionary includes test configs.
+            orig_test_attrs: a dictionary includes test configs.
             tags: a attribute in test config to filter inputs
             OperatorTestCase: a named tuple to save the metadata of an test
             run_backward: a bool parameter indicating backward path