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Signed-off-by: seonjinn <sna@nvidia.com>
Signed-off-by: seonjinn <sna@nvidia.com>
Signed-off-by: seonjinn <sna@nvidia.com>
Signed-off-by: seonjinn <sna@nvidia.com>
Signed-off-by: seonjinn <sna@nvidia.com>
Signed-off-by: seonjinn <sna@nvidia.com>
Signed-off-by: seonjinn <sna@nvidia.com>
Signed-off-by: seonjinn <sna@nvidia.com>
Signed-off-by: seonjinn <sna@nvidia.com>
Signed-off-by: seonjinn <sna@nvidia.com>
Signed-off-by: seonjinn <sna@nvidia.com>
Signed-off-by: seonjinn <sna@nvidia.com>
Signed-off-by: seonjinn <sna@nvidia.com>
Signed-off-by: seonjinn <sna@nvidia.com>
Signed-off-by: seonjinn <sna@nvidia.com>
Signed-off-by: seonjinn <sna@nvidia.com>
Signed-off-by: seonjinn <sna@nvidia.com>
Signed-off-by: seonjinn <sna@nvidia.com>
Signed-off-by: seonjinn <sna@nvidia.com>
Signed-off-by: seonjinn <sna@nvidia.com>
Signed-off-by: seonjinn <sna@nvidia.com>
Signed-off-by: seonjinn <sna@nvidia.com>
Signed-off-by: seonjinn <sna@nvidia.com>
Signed-off-by: seonjinn <sna@nvidia.com>
Signed-off-by: seonjinn <sna@nvidia.com>
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Signed-off-by: seonjinn <sna@nvidia.com>
Signed-off-by: seonjinn <sna@nvidia.com>
…0-20260922 Signed-off-by: seonjinn <sna@nvidia.com> # Conflicts: # nemo_rl/weight_sync/nccl_reshard_weight_synchronizer.py
…3908-mcore7300-20260922 Signed-off-by: seonjinn <sna@nvidia.com> # Conflicts: # nemo_rl/models/megatron/setup.py # tests/unit/models/megatron/test_megatron_setup.py # tests/unit/models/policy/test_megatron_worker.py # uv.lock
Signed-off-by: seonjinn <sna@nvidia.com>
Signed-off-by: seonjinn <sna@nvidia.com>
Signed-off-by: seonjinn <sna@nvidia.com>
…0-20260922 Signed-off-by: seonjinn <sna@nvidia.com>
…0-20260922 Signed-off-by: seonjinn <sna@nvidia.com>
…3908-mcore7300-20260922 Signed-off-by: seonjinn <sna@nvidia.com>
Signed-off-by: seonjinn <sna@nvidia.com>
Signed-off-by: seonjinn <sna@nvidia.com>
Signed-off-by: seonjinn <sna@nvidia.com>
Signed-off-by: seonjinn <sna@nvidia.com>
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Exact-head GB200 validation completed on
All 86 selected tests passed. The run used one GB200 node and the current NeMo-RL nightly image. |
Signed-off-by: seonjinn <sna@nvidia.com>
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Summary
Megatron can keep trained parameters in native MXFP8 storage when
fp8_param=true, while refit previously expected one ordinary tensor per parameter. This PR sends Transformer Engine's live E4M3 values and E8M0 scales through the ordered component contract from #3907 without dequantizing the weight.Design
fp8_cfgandte_precision_config_file.Dependencies
Validation
gen_kl_errormean0.001264(range0.000838-0.001549).gen_kl_error=0.00130165at step 2. The nightly used the NCCL Reshard exact-transfer Python fallback, so this is correctness evidence rather than native-op performance evidence.