Increase multiplier to 3 for Inductor AMP FP16 benchmark correctness …

…check (#135932)

Summary:
Fix pytorch/pytorch#135657.
Aligned with AMP BF16, using multiplier 3 for Inductor AMP FP16 benchmark correctness check

X-link: pytorch/pytorch#135932
Approved by: https://github.com/CaoE, https://github.com/jgong5, https://github.com/jansel

Reviewed By: jeanschmidt

Differential Revision: D62980154

fbshipit-source-id: e7fb9cd8faea933ff85fb1173620bf0d54ebf9f1

userbenchmark/dynamo/dynamobench/_dynamo/utils.py

@@ -1787,7 +1787,9 @@ def to_tensor(t):
  # accuracy when comparing AMP with FP32 is within a difference of less than 0.1%.
  # Thus, it's possible that the correctness check failures for these models are
  # false alarms. We use multiplier of 3 instead of 2 to avoid these false alarms.
- multiplier = 3.0 if res.dtype == torch.bfloat16 else 2.0
+ multiplier = (
+ 3.0 if res.dtype in (torch.float16, torch.bfloat16) else 2.0
+ )
 
  if use_larger_multiplier_for_smaller_tensor and (
  fp64_ref.numel() <= 10 and tol >= 4 * 1e-2