[ci] disable cudagraph for tts_angular on dashboard (#148221)

tts_angular with cudagraph is flaky. Its speedup varies from .05 to 1.01. This PR disables cudagraph for tts_angular to avoid the noise. Since tts_angular shows ~1x speedup while other torchbench models show ~2x speedup, skipping tts_angular would wrongly bump the cudagraph speedup. So this PR only disables cudagraph for tts_angular instead of skipping tts_angular.

[Dashboard ](https://github.com/pytorch/pytorch/actions/runs/13597394087)

Pull Request resolved: https://github.com/pytorch/pytorch/pull/148221
Approved by: https://github.com/eellison

benchmarks/dynamo/common.py

@@ -1824,6 +1824,10 @@ class BenchmarkRunner:
     def skip_models_due_to_control_flow(self):
         return set()
 
+    @property
+    def disable_cudagraph_models(self):
+        return set()
+
     @property
     def guard_on_nn_module_models(self):
         return set()
@@ -3834,6 +3838,9 @@ def run(runner, args, original_dir=None):
         experiment = coverage_experiment
         output_filename = "coverage.csv"
 
+    if args.only in runner.disable_cudagraph_models:
+        args.disable_cudagraphs = True
+
     if args.inductor or args.backend == "inductor" or args.export_aot_inductor:
         inductor_config.triton.cudagraphs = not args.disable_cudagraphs
         inductor_config.triton.persistent_reductions = (

benchmarks/dynamo/torchbench.py

@@ -145,6 +145,10 @@ class TorchBenchmarkRunner(BenchmarkRunner):
     def skip_models_for_freezing_cuda(self):
         return self._skip["freezing"]["cuda"]
 
+    @property
+    def disable_cudagraph_models(self):
+        return self._config["disable_cudagraph"]
+
     @property
     def skip_models_for_freezing_cpu(self):
         return self._skip["freezing"]["cpu"]

benchmarks/dynamo/torchbench.yaml

@@ -111,6 +111,12 @@ non_deterministic:
   - sam_fast
 
 
+disable_cudagraph:
+  # tts_angular is flaky with cudagraphs. Its speedup
+  # oscillates from .05 to 1.05
+  - tts_angular
+
+
 dtype:
   force_amp_for_fp16_bf16_models:
     - DALLE2_pytorch