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- Added comments to clarify file purposes in example_commands.sh, inference_wan.py, pretrain_wan.py, wan_provider.py, wan_step.py, and wan.py. - Introduced EnergonMultiModalDataModule for handling multimodal datasets in nemo_vfm. - Created SequentialMegatronSampler for efficient sequential sampling in large datasets. - Added new files for DIT attention and base data handling. This commit enhances documentation and introduces new functionalities for better data management and processing.
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/ok to test 04f6c14 |
Signed-off-by: Parth Mannan <pmannan@nvidia.com>
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/ok to test 7247bc7 |
Signed-off-by: Parth Mannan <pmannan@nvidia.com>
Signed-off-by: Parth Mannan <pmannan@nvidia.com>
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/ok to test 7fedda7 |
abhinavg4
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Nov 21, 2025
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Looks good. Thanks a ton for your help.
lbliii
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Dec 3, 2025
* first commit * workable code * workable thd * clean up, remove all CP for sbhd, CP now is only for thd * run outside of Mbridge * Update example scripts and add new data module for multimodal datasets - Added comments to clarify file purposes in example_commands.sh, inference_wan.py, pretrain_wan.py, wan_provider.py, wan_step.py, and wan.py. - Introduced EnergonMultiModalDataModule for handling multimodal datasets in nemo_vfm. - Created SequentialMegatronSampler for efficient sequential sampling in large datasets. - Added new files for DIT attention and base data handling. This commit enhances documentation and introduces new functionalities for better data management and processing. * workable code before refactoring * refactor attention submodules + reorder files locations * update refactor * update refactor * reorganize files * reorganize files * refactoring code * add README for perf test * using vae, t5, scheduler from Diffusers * update repo, remove Wan's Github moduels * fix Ruff * fix ruff + copyright * fix Ruff + Lint * fix Ruff + Lint * fix Ruff + Lint * fix Ruff + Lint * fix Ruff + Lint * fix Ruff + Lint * fix Ruff + Lint * fix Ruff + Lint * merged main + address comments * remove example_commands.md, Google waits until mid Nov * refactor inference_configs + mockdatamodule * add dit_embeddings.py * fix lint ruff * add 'average_gradients_across_tp_domain' to torch.nn for when running sequence_parallelism * add english negative prompt * fix ruff lint * Update uv.lock for deps: diffusers==0.35.1, easydict, imageio * update dfm/src/megatron/data/dit * change english negative prompt * seem to workable seq_packing * refactor with Sajad's PR - DiT data to common dir * fix Ruff, lint * fix Ruff, lint * fix Ruff, lint * workable mock datamodule (doesn't need setting path); updated training algo + hyper-parameters aligning with Linnan; tested training with anime dataset finetung * bring wan_task encoders features to common, sharing with dit * lint, ruff * lint, ruff * lint, ruff * fix CP error (input of thd_split_inputs_cp to be cu_seqlens_q_padded instead of cu_seqlens_q) * udpate README_perf_test.md * fix lint, ruff * update uv.lock, merge main * uv.lock * uv.lock * uv.lock * update uv.lock [using ci] * Performance improvements to Wan * Perf optimizations * Tiny fix * Remove CP disable as packed sequences not supported * Fix comment * Minor fixes. Revert video_latent comparison * Fix missed check * Lint fix * H100 mock pretraining perf config * Rename config file * Lint check Signed-off-by: Parth Mannan <pmannan@nvidia.com> * Adding GB200 perf config Signed-off-by: Parth Mannan <pmannan@nvidia.com> * GB300 perf config Signed-off-by: Parth Mannan <pmannan@nvidia.com> * Refactor Energon data module to return wrapped dataloaders and add EnergonDataloader class for cyclic iteration. Introduce WAN pretrain mock data configuration for testing. * Enhance DiffusionTaskEncoder to handle None attributes in stacking and concatenation methods. Add WAN pretrain mock data configuration for testing purposes. * Refactor data processing in dit_data_step to simplify batch retrieval and update WAN pretrain configuration to include train_iters. * Add op fusions Signed-off-by: Parth Mannan <pmannan@nvidia.com> * Update H100 config Signed-off-by: Parth Mannan <pmannan@nvidia.com> * Fix lint Signed-off-by: Parth Mannan <pmannan@nvidia.com> * Resolve conflict Signed-off-by: Parth Mannan <pmannan@nvidia.com> * Fix for mock dataloader test Signed-off-by: Parth Mannan <pmannan@nvidia.com> * Fix Dummyiter Signed-off-by: Parth Mannan <pmannan@nvidia.com> * Fix test Signed-off-by: Parth Mannan <pmannan@nvidia.com> * Make RoPE test only GPU Signed-off-by: Parth Mannan <pmannan@nvidia.com> * Rope cuda fix Signed-off-by: Parth Mannan <pmannan@nvidia.com> --------- Signed-off-by: Parth Mannan <pmannan@nvidia.com> Co-authored-by: Huy Vu2 <huvu@login-eos02.eos.clusters.nvidia.com> Co-authored-by: Abhinav Garg <abhinavg@stanford.edu> Co-authored-by: root <root@eos0025.eos.clusters.nvidia.com> Co-authored-by: root <root@eos0558.eos.clusters.nvidia.com> Co-authored-by: Pablo Garay <pagaray@nvidia.com> Signed-off-by: Lawrence Lane <llane@nvidia.com>
huvunvidia
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Feb 12, 2026
* first commit * workable code * workable thd * clean up, remove all CP for sbhd, CP now is only for thd * run outside of Mbridge * Update example scripts and add new data module for multimodal datasets - Added comments to clarify file purposes in example_commands.sh, inference_wan.py, pretrain_wan.py, wan_provider.py, wan_step.py, and wan.py. - Introduced EnergonMultiModalDataModule for handling multimodal datasets in nemo_vfm. - Created SequentialMegatronSampler for efficient sequential sampling in large datasets. - Added new files for DIT attention and base data handling. This commit enhances documentation and introduces new functionalities for better data management and processing. * workable code before refactoring * refactor attention submodules + reorder files locations * update refactor * update refactor * reorganize files * reorganize files * refactoring code * add README for perf test * using vae, t5, scheduler from Diffusers * update repo, remove Wan's Github moduels * fix Ruff * fix ruff + copyright * fix Ruff + Lint * fix Ruff + Lint * fix Ruff + Lint * fix Ruff + Lint * fix Ruff + Lint * fix Ruff + Lint * fix Ruff + Lint * fix Ruff + Lint * merged main + address comments * remove example_commands.md, Google waits until mid Nov * refactor inference_configs + mockdatamodule * add dit_embeddings.py * fix lint ruff * add 'average_gradients_across_tp_domain' to torch.nn for when running sequence_parallelism * add english negative prompt * fix ruff lint * Update uv.lock for deps: diffusers==0.35.1, easydict, imageio * update dfm/src/megatron/data/dit * change english negative prompt * seem to workable seq_packing * refactor with Sajad's PR - DiT data to common dir * fix Ruff, lint * fix Ruff, lint * fix Ruff, lint * workable mock datamodule (doesn't need setting path); updated training algo + hyper-parameters aligning with Linnan; tested training with anime dataset finetung * bring wan_task encoders features to common, sharing with dit * lint, ruff * lint, ruff * lint, ruff * fix CP error (input of thd_split_inputs_cp to be cu_seqlens_q_padded instead of cu_seqlens_q) * udpate README_perf_test.md * fix lint, ruff * update uv.lock, merge main * uv.lock * uv.lock * uv.lock * update uv.lock [using ci] * Performance improvements to Wan * Perf optimizations * Tiny fix * Remove CP disable as packed sequences not supported * Fix comment * Minor fixes. Revert video_latent comparison * Fix missed check * Lint fix * H100 mock pretraining perf config * Rename config file * Lint check Signed-off-by: Parth Mannan <pmannan@nvidia.com> * Adding GB200 perf config Signed-off-by: Parth Mannan <pmannan@nvidia.com> * GB300 perf config Signed-off-by: Parth Mannan <pmannan@nvidia.com> * Refactor Energon data module to return wrapped dataloaders and add EnergonDataloader class for cyclic iteration. Introduce WAN pretrain mock data configuration for testing. * Enhance DiffusionTaskEncoder to handle None attributes in stacking and concatenation methods. Add WAN pretrain mock data configuration for testing purposes. * Refactor data processing in dit_data_step to simplify batch retrieval and update WAN pretrain configuration to include train_iters. * Add op fusions Signed-off-by: Parth Mannan <pmannan@nvidia.com> * Update H100 config Signed-off-by: Parth Mannan <pmannan@nvidia.com> * Fix lint Signed-off-by: Parth Mannan <pmannan@nvidia.com> * Resolve conflict Signed-off-by: Parth Mannan <pmannan@nvidia.com> * Fix for mock dataloader test Signed-off-by: Parth Mannan <pmannan@nvidia.com> * Fix Dummyiter Signed-off-by: Parth Mannan <pmannan@nvidia.com> * Fix test Signed-off-by: Parth Mannan <pmannan@nvidia.com> * Make RoPE test only GPU Signed-off-by: Parth Mannan <pmannan@nvidia.com> * Rope cuda fix Signed-off-by: Parth Mannan <pmannan@nvidia.com> --------- Signed-off-by: Parth Mannan <pmannan@nvidia.com> Co-authored-by: Huy Vu2 <huvu@login-eos02.eos.clusters.nvidia.com> Co-authored-by: Abhinav Garg <abhinavg@stanford.edu> Co-authored-by: root <root@eos0025.eos.clusters.nvidia.com> Co-authored-by: root <root@eos0558.eos.clusters.nvidia.com> Co-authored-by: Pablo Garay <pagaray@nvidia.com>
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