Revert "Add groups to dynamo benchmarking output data (#103268)"

This reverts commit 455f542ed9.

Reverted https://github.com/pytorch/pytorch/pull/103268 on behalf of https://github.com/drisspg due to no longer needed ([comment](https://github.com/pytorch/pytorch/pull/103268#issuecomment-1591732331))

benchmarks/dynamo/common.py

@@ -15,9 +15,8 @@ import subprocess
 import sys
 import time
 from contextlib import contextmanager
-from dataclasses import dataclass
 
-from typing import Any, List, NamedTuple, Set
+from typing import Any, NamedTuple
 from unittest.mock import MagicMock
 
 import numpy as np
@@ -293,42 +292,6 @@ CI_SKIP_OPTIMIZER = {
 }
 
 
-# Model Groups
-@dataclass(frozen=True)
-class ModelGroup:
-    name: str
-    models: Set[str]
-
-
-BLUEBERRY_MODELS = ModelGroup("Blueberries", {"llama", "nanogpt_generate"})
-
-
-@dataclass(frozen=True)
-class GroupMap:
-    groups: List[ModelGroup]
-
-    def model_group(self, model_name):
-        for group in self.groups:
-            if model_name in group.models:
-                return group.name
-        return None
-
-    @classmethod
-    def assert_single_group(cls, groups: List[ModelGroup]):
-        model_to_group = {}
-        for group in groups:
-            for model in group.models:
-                if model in model_to_group:
-                    raise ValueError(
-                        f"Model {model} appears in multiple groups, {model_to_group[model]} and {group.name}"
-                    )
-                model_to_group[model] = group.name
-        return cls(groups)
-
-
-ALL_MODEL_GROUPS = GroupMap.assert_single_group([BLUEBERRY_MODELS])
-
-
 def model_specified_by_path(path_and_class_str):
     return ":" in path_and_class_str
 
@@ -731,9 +694,8 @@ def speedup_experiment(args, model_iter_fn, model, example_inputs, **kwargs):
             timings,
         )
 
-    current_group = ALL_MODEL_GROUPS.model_group(current_name)
-    first_headers = ["dev", "name", "group", "batch_size"]
-    first_fields = [current_device, current_name, current_group, current_batch_size]
+    first_headers = ["dev", "name", "batch_size"]
+    first_fields = [current_device, current_name, current_batch_size]
     if "tag" in kwargs:
         first_headers.append("tag")
         first_fields.append(kwargs["tag"])