tune down batch-size for res2net to avoid OOM

[shunting314]

Stack from ghstack (oldest at bottom):

• -> tune down batch-size for res2net to avoid OOM #122977

The batch-size for this model is 64 previously. Later on we change that to 256 and cause OOM in cudagraphs setting. This PR tune the batch size down to 128.

Share more logs from my local run

cuda,res2net101_26w_4s,128,1.603578,110.273572,335.263494,1.042566,11.469964,11.001666,807,2,7,6,0,0
cuda,res2net101_26w_4s,256,1.714980,207.986155,344.013071,1.058278,22.260176,21.034332,807,2,7,6,0,0

The log shows that torch.compile uses 11GB for 128 batch size and 21GB for 256 batch size. I guess the benchmark script has extra overhead cause the model OOM for 256 batch size in the dashboard run.

cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang

[pytorch-bot]

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✅ You can merge normally! (3 Unrelated Failures)

As of commit 767ca08 with merge base 57a9a64 ():

FLAKY - The following jobs failed but were likely due to flakiness present on trunk:

• inductor / rocm6.0-py3.8-inductor / test (inductor, 1, 1, linux.rocm.gpu.2) (gh)
  test/distributed/test_c10d_functional_native.py::TestWithNCCL::test_unwaited
• pull / linux-focal-cuda12.1-py3.10-gcc9 / test (default, 4, 5, linux.4xlarge.nvidia.gpu) (gh)
  test_foreach.py::TestForeachCUDA::test_binary_op_list_error_cases__foreach_add_cuda_complex128

BROKEN TRUNK - The following job failed but were present on the merge base:

👉 Rebase onto the `viable/strict` branch to avoid these failures

• pull / linux-jammy-py3.8-gcc11 / test (docs_test, 1, 1, linux.2xlarge) (gh)
  Process completed with exit code 2.

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[shunting314]

@pytorchbot merge -i

[pytorchmergebot]

Merge started

Your change will be merged while ignoring the following 2 checks: pull / linux-jammy-py3.8-gcc11 / test (docs_test, 1, 1, linux.2xlarge), pull / linux-focal-cuda12.1-py3.10-gcc9 / test (default, 4, 5, linux.4xlarge.nvidia.gpu)

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