Fix unused Python variables outside torch/ and test/ (#136359)

Summary:
X-link: pytorch/pytorch#136359
Approved by: https://github.com/albanD

Reviewed By: clee2000

Differential Revision: D67115192

fbshipit-source-id: 65e4ccafac9046d78e1de4234d5aa00894274c81

userbenchmark/dynamo/dynamobench/common.py

@@ -671,7 +671,7 @@ def print_summary_table(data, print_dataframe=False):
                     col.ljust(width),
                     f"gmean={gmean(cdata):.2f}x mean={cdata.mean():.3f}x",
                 )
-        except Exception as e:
+        except Exception:
             pass
 
 
@@ -3018,7 +3018,7 @@ def record_status(accuracy_status, dynamo_start_stats):
                     )
                 ):
                     is_same = False
-            except Exception as e:
+            except Exception:
                 # Sometimes torch.allclose may throw RuntimeError
                 is_same = False
 
@@ -3110,7 +3110,7 @@ def record_status(accuracy_status, dynamo_start_stats):
                     tol=tolerance,
                 ):
                     is_same = False
-            except Exception as e:
+            except Exception:
                 # Sometimes torch.allclose may throw RuntimeError
                 is_same = False
 
@@ -3157,7 +3157,7 @@ def check_tolerance(
                 self.init_optimizer(name, current_device, model.parameters())
                 optimized_model_iter_fn = optimize_ctx(self.run_n_iterations)
                 new_result = optimized_model_iter_fn(model, example_inputs)
-            except Exception as e:
+            except Exception:
                 log.exception("")
                 print(
                     "TorchDynamo optimized model failed to run because of following error"
@@ -3542,7 +3542,7 @@ def minify_model(
 
         try:
             shutil.move("repro.py", f"{repro_dir}/{name}_repro.py")
-        except OSError as e:
+        except OSError:
             logging.error("Could not find repro script for model %s", name)
         else:
             logging.info(
@@ -4369,9 +4369,6 @@ def run(runner, args, original_dir=None):
             # Set translation validation on by default on CI accuracy runs.
             torch.fx.experimental._config.translation_validation = True
 
-        ci = functools.partial(
-            CI, args.backend, training=args.training, dynamic=args.dynamic_shapes
-        )
     if args.ddp:
         assert args.training, "DDP benchmark requires --training mode"
         torch._dynamo.config.optimize_ddp = args.optimize_ddp_mode

userbenchmark/dynamo/dynamobench/torchbench.py

@@ -236,7 +236,6 @@ def load_model(
             )
         is_training = self.args.training
         use_eval_mode = self.args.use_eval_mode
-        dynamic_shapes = self.args.dynamic_shapes
         candidates = [
             f"torchbenchmark.models.{model_name}",
             f"torchbenchmark.canary_models.{model_name}",