[moe training] default pad_token_groups_for_grouped_mm=False

[danielvegamyhre]

Summary

• Default pad_token_groups_for_grouped_mm to False to avoid surprising users with the extra pad/unpad kernels that incur overhead. This is often handled upstream of the quantization + grouped MM step now, by systems like HybridEP etc, so best for the user to explicitly request the padding via the flag if they need it.
• Update tests and benchmarks accordingly

Tests

• pytest test/prototype/moe_training/test_training.py -s

[pytorch-bot]

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✅ You can merge normally! (2 Unrelated Failures)

As of commit b6bf1a5 with merge base eb64bfb ():

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

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

• Run Regression Tests / test-nightly (CPU Nightly, linux.4xlarge, --pre torch --index-url https://download.pytorch.org/wh... / linux-job (gh) (trunk failure)
  test/quantization/pt2e/test_x86inductor_fusion.py::TestDynamicPatternMatcher::test_q_attention_block
• Run Regression Tests / test-nightly (CUDA Nightly, linux.g5.12xlarge.nvidia.gpu, --pre torch --index-url https://downloa... / linux-job (gh) (trunk failure)
  test/quantization/pt2e/test_x86inductor_fusion.py::TestDynamicPatternMatcher::test_q_attention_block

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