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[5/5] megatron_bridge: load the HF model from local disk; Megatron export copies its non-model files - #2610
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[5/5] megatron_bridge: load the HF model from local disk; Megatron export copies its non-model files#2610shengliangxu wants to merge 6 commits into
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Included review availability: This review used your included allowance. Your plan provides up to 12 included reviews per hour; 8 remain after this review. 📝 WalkthroughWalkthroughMegatron Bridge scripts now resolve Hugging Face inputs to local checkpoints for model operations and export. Export paths copy non-model files from local sources. The unified exporter warns when the source is a Hub model ID. The older non-safetensor copy helper emits a deprecation warning. ChangesMegatron HF checkpoint handling
Priority: ⬇️ Low Estimated code review effort: 3 (Moderate) | ~25 minutes Change: Feature Sequence Diagram(s)sequenceDiagram
participant MegatronBridgeScript
participant ensure_local_checkpoint
participant MegatronExporter
participant copy_non_model_files
MegatronBridgeScript->>ensure_local_checkpoint: Resolve Hugging Face input
ensure_local_checkpoint-->>MegatronBridgeScript: Return local path and Hub ID
MegatronBridgeScript->>MegatronExporter: Export using local checkpoint path
MegatronExporter->>copy_non_model_files: Copy non-model files from local directory
Merge Risk: ⚪ Minimal · up to The supplied changes do not establish an outstanding issue that should block merging after normal checks. 🚥 Pre-merge checks | ✅ 5 | ❌ 1❌ Failed checks (1 warning)
✅ Passed checks (5 passed)
✨ Finishing Touches 💡 1📝 Generate docstrings 💡
🧪 Generate unit tests (beta)
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… copy_non_model_files (#2607) ### What does this PR do? Type of change: new feature ### Summary of the series Every pipeline that quantizes, prunes, sparsifies or distills a Hugging Face model now starts the same way: **make the checkpoint local, then load from it**. `ensure_local_checkpoint` returns a local directory as-is and downloads a Hub model ID in full if it is not cached yet -- once, on rank 0 -- and the model, tokenizer and processor are then loaded from that local directory. Before, a Hub ID went straight to `from_pretrained`, which fetched only the files loading needed, so every later step that needed the source as files found its own way back to it: `hf_ptq` through a hand-rolled cache lookup (`_resolve_model_path`, whose `TRANSFORMERS_CACHE` glob picked the lexicographically largest commit hash rather than `refs/main`) and a hardcoded download allowlist, regenerating tokenizer files along the way; the Megatron export by fetching only `*.py` for a Hub ID; other callers of `export_hf_checkpoint` not at all. With the source on local disk, exports follow one rule: an export writes the **model files** -- weights in any format and the metadata describing them -- and carries every other source file (**non-model files**: tokenizer, processor, remote code, chat templates, README, ...) over verbatim, from **local disk only**. Merge in order: 1. #2607 — Add `ensure_local_checkpoint` to load models from local disk, and `copy_non_model_files` ← **this PR** 2. #2608 — HF exporters write off-index safetensors and non-model files 3. #2609 — `hf_ptq`: load the model from local disk, downloading it first if needed 4. #2610 — `megatron_bridge`: load the HF model from local disk; Megatron export copies its non-model files 5. #2611 — `llm_sparsity`: load the model from local disk, downloading it first if needed ### This PR [1/5] Adds the two building blocks to `modelopt/torch/utils/plugins/hf_checkpoint_utils.py`, re-exported from `modelopt.torch.export`. Nothing calls them yet; #2609–#2611 make `ensure_local_checkpoint` the first step of each pipeline. - **`ensure_local_checkpoint(model_name_or_path, group=None) -> (hub_model_id, local_checkpoint_path)`** makes the whole checkpoint local before anything loads it: a local directory as-is, a Hub ID downloaded in full if not cached yet (guessing which files are redundant would risk dropping ones the checkpoint needs). Load the model, tokenizer and processor from `local_checkpoint_path`; `hub_model_id` is the Hub ID, or `None` for a local path, for records that must stay valid on other hosts. - Under `torch.distributed`, rank 0 of `group` resolves it and broadcasts the result -- or its error, so a failed download raises everywhere rather than stranding the waiting ranks. Rank 0 decides for local paths too, since ranks checking for themselves could disagree about a node-local directory. Without a `group`, every rank waits on a temporary gloo group whose 24 h timeout outlasts a large download; with one, the caller's group carries the wait. A rank that cannot see the resolved path raises, asking for shared storage. - `snapshot_download` silently returns a possibly incomplete cached snapshot when the Hub is unreachable. With `HF_HUB_OFFLINE` the cache is used quietly (the user's choice); with the Hub unexpectedly unreachable it is used with a warning, or the Hub's error is raised if nothing is cached. An input that is neither a local directory nor a Hub model ID the Hub can access -- a mistyped local path, say -- raises a `ValueError` saying so, chained to the Hub's error; a gated repo still raises `GatedRepoError`. - **`copy_non_model_files(source, export_dir)`** copies every file of a local checkpoint, recursively, except weight files in any format, top-level export metadata (`config.json`, `hf_quant_config.json`, stale quant configs, `.experiment.json`), files the export already wrote, hidden directories (`.git`, `.cache`), and links that resolve outside the checkpoint or its Hub `blobs/` (checked with the existing `resolve_checkpoint_file`). It never writes through a link already in the export, removes a partial copy when one fails, and skips `export_dir` when it lies inside the source (e.g. an earlier export). It returns `/`-separated paths on every platform. **What happens to the existing copy helpers.** `copy_non_model_files` replaces both copy rules the series' callers use today. #2609 moves `hf_ptq` off `copy_non_safetensor_files_from_ckpt`. #2610 moves the Megatron export onto `copy_non_model_files` (dropping its Hub-fetching `copy_hf_ckpt_remote_code` branch), moves `prune_minitron` and `export_distilled_megatron_to_hf` off `copy_hf_ckpt_remote_code`, and deprecates `copy_non_safetensor_files_from_ckpt`. `copy_hf_ckpt_remote_code` stays for now: puzzletron's `init_child_from_parent` still uses it, and migrating puzzletron is out of scope for this series. Also: module constants move to the top next to a note defining model versus non-model files; `off_index_safetensors_files` / `copy_off_index_safetensors` accept a `None` source and report what they copy; comments stop calling off-index weight files "sidecars". ### Usage ```python from modelopt.torch.export import copy_non_model_files, ensure_local_checkpoint hub_model_id, local_checkpoint_path = ensure_local_checkpoint("Qwen/Qwen3-8B") # every rank calls it model = AutoModelForCausalLM.from_pretrained(local_checkpoint_path) ... copy_non_model_files(local_checkpoint_path, export_dir) # after the export wrote its own files ``` ### Testing `pytest tests/unit/torch/utils tests/unit/torch/export tests/examples/hf_ptq` (GPU end-to-end and `test_dataset_utils` excluded): 684 passed. New tests cover the copy rule (weights, owned metadata, subdirectories, hidden dirs, links inside/outside/dangling, Hub `blobs/`), online/offline/unreachable/missing-repo resolution, and -- over two real gloo processes -- rank-0-only download, error propagation, an explicit group, a subgroup without global rank 0, and a local path hidden from one rank. The resolution paths were also checked live against the Hub. CPU only (torch 2.12, transformers 5.9, huggingface_hub 1.19); `transformer_engine` cannot be imported in this environment, so GPU and Megatron tests are left to CI. ### Before your PR is "*Ready for review*" Make sure you read and follow [Contributor guidelines](https://github.com/NVIDIA/Model-Optimizer/blob/main/CONTRIBUTING.md) and your commits are signed (`git commit -s -S`). Make sure you read and follow the [Security Best Practices](https://github.com/NVIDIA/Model-Optimizer/blob/main/SECURITY.md#security-coding-practices-for-contributors) (e.g. avoiding hardcoded `trust_remote_code=True`, `torch.load(..., weights_only=False)`, `pickle`, etc.). - Is this change backward compatible?: ✅ (additive) - If you copied code from any other sources or added a new PIP dependency, did you follow guidance in `CONTRIBUTING.md`: N/A - Did you write any new necessary tests?: ✅ - Did you update [Changelog](https://github.com/NVIDIA/Model-Optimizer/blob/main/CHANGELOG.rst)?: N/A (entries land with the behaviour changes in #2608–#2610) - Did you get Claude approval on this PR?: ❌ ### Additional Information Stacked series; this is the base. <!-- This is an auto-generated comment: release notes by coderabbit.ai --> ## Summary by CodeRabbit * **New Features** * Checkpoint exports can resolve local and Hub-hosted checkpoints, using cached snapshots when offline or Hub access is unavailable. Missing offline cache entries are reported as errors. * Exports can copy eligible non-model checkpoint files without overwriting existing export files. Hidden directories and unsafe or dangling links are excluded. * Distributed exports coordinate checkpoint resolution across processes and report failures, including when other processes cannot access the resolved path. * Safetensors files not listed in an index are treated as standalone weight files and can be copied into exports when eligible. <!-- end of auto-generated comment: release notes by coderabbit.ai --> --------- Signed-off-by: Shengliang Xu <shengliangx@nvidia.com>
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Review comments at @modelopt/torch/export/unified_export_megatron.py:
- Line 42: Update the API documentation for pretrained_model_name_or_path to
clarify that Hub model IDs do not copy non-model files, including tokenizer,
processor, generation configuration, and remote code; direct callers to
ensure_local_checkpoint when those files are needed.
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examples/megatron_bridge/export_distilled_megatron_to_hf.pyexamples/megatron_bridge/export_quantized_megatron_to_hf.pyexamples/megatron_bridge/prune_minitron.pyexamples/megatron_bridge/quantize.pymodelopt/torch/export/unified_export_megatron.pytests/unit/torch/utils/test_hf_checkpoint_utils.py
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… needed (#2609) ### What does this PR do? Type of change: bug fix ### Summary of the series Every pipeline that quantizes, prunes, sparsifies or distills a Hugging Face model now starts the same way: **make the checkpoint local, then load from it**. `ensure_local_checkpoint` returns a local directory as-is and downloads a Hub model ID in full if it is not cached yet -- once, on rank 0 -- and the model, tokenizer and processor are then loaded from that local directory. Before, a Hub ID went straight to `from_pretrained`, which fetched only the files loading needed, so every later step that needed the source as files found its own way back to it: `hf_ptq` through a hand-rolled cache lookup (`_resolve_model_path`, whose `TRANSFORMERS_CACHE` glob picked the lexicographically largest commit hash rather than `refs/main`) and a hardcoded download allowlist, regenerating tokenizer files along the way; the Megatron export by fetching only `*.py` for a Hub ID; other callers of `export_hf_checkpoint` not at all. With the source on local disk, exports follow one rule: an export writes the **model files** -- weights in any format and the metadata describing them -- and carries every other source file (**non-model files**: tokenizer, processor, remote code, chat templates, README, ...) over verbatim, from **local disk only**. Merge in order: 1. #2607 — Add `ensure_local_checkpoint` to load models from local disk, and `copy_non_model_files` 2. #2608 — HF exporters write off-index safetensors and non-model files 3. #2609 — `hf_ptq`: load the model from local disk, downloading it first if needed ← **this PR** 4. #2610 — `megatron_bridge`: load the HF model from local disk; Megatron export copies its non-model files 5. #2611 — `llm_sparsity`: load the model from local disk, downloading it first if needed ### This PR [3/5] **Loading.** `main()` now makes the model local before anything else: `ensure_local_checkpoint(--pyt_ckpt_path)` returns a local directory as-is or downloads a Hub ID once, and every later step -- loading the model, tokenizer and processor, the MXFP4 cast, and the export's copy of the source's files -- reads that local copy. `--pyt_ckpt_path` stays as given; the local directory is `args.local_checkpoint_path`, and `args.hub_model_id` (the Hub ID, or `None`) still names the layerwise resume directory. This replaces the per-step ways back to the source -- `_resolve_model_path`, a hardcoded sidecar allowlist, `_resolved_local_dir`, `hf_hub_download` fallbacks. **Exporting.** The unified exporters copy the source's non-model files themselves (#2608), so the example no longer does -- except after the deprecated TensorRT-LLM export, which does not. It also stops regenerating tokenizer and processor files: the source's are carried over verbatim. So a `pad_token` that `get_tokenizer` sets for calibration (the EOS token, for a model without one) no longer leaks into the exported tokenizer; #2597 already stopped it overwriting an existing pad token. It also removes the default padding side and pad token threaded through six functions only to undo that before saving. The three notebooks do the same: make the model local first, load from it, and leave the tokenizer files to the export. Mostly deletions (+84 / −466). ### Usage No flag change. `--pyt_ckpt_path org/model` downloads the whole repo once before loading; to skip files, download it yourself (e.g. `hf download org/model --exclude 'original/*'`) and pass the local path. ### Testing Same suite as #2607: 685 passed (the `hf_ptq` tests moved to the library in #2607 or were dropped with the code they covered). Notebooks validated as JSON. CPU only (torch 2.12, transformers 5.9, huggingface_hub 1.19); `transformer_engine` cannot be imported in this environment, so GPU and Megatron tests are left to CI. ### Before your PR is "*Ready for review*" Make sure you read and follow [Contributor guidelines](https://github.com/NVIDIA/Model-Optimizer/blob/main/CONTRIBUTING.md) and your commits are signed (`git commit -s -S`). Make sure you read and follow the [Security Best Practices](https://github.com/NVIDIA/Model-Optimizer/blob/main/SECURITY.md#security-coding-practices-for-contributors) (e.g. avoiding hardcoded `trust_remote_code=True`, `torch.load(..., weights_only=False)`, `pickle`, etc.). - Is this change backward compatible?: ✅ (`--pyt_ckpt_path` unchanged; exports carry the source's files as-is) - If you copied code from any other sources or added a new PIP dependency, did you follow guidance in `CONTRIBUTING.md`: N/A - Did you write any new necessary tests?: N/A (removes code; the new helpers are tested in #2607/#2608) - Did you update [Changelog](https://github.com/NVIDIA/Model-Optimizer/blob/main/CHANGELOG.rst)?: N/A (the `pad_token` fix is #2597's entry; the verbatim copy is #2608's) - Did you get Claude approval on this PR?: ❌ ### Additional Information Stacked on #2608. <!-- This is an auto-generated comment: release notes by coderabbit.ai --> ## Summary by CodeRabbit * **Updates** * Models and tokenizers are loaded from a locally resolved checkpoint, which is reused across quantization and export steps. * TensorRT-LLM exports include non-model files from the local checkpoint, and multimodal exports save the source configuration. * Quantized exports no longer separately save tokenizer files or restore tokenizer padding settings. Local checkpoint paths are also used when restoring compressed weights and resolving source configurations. <!-- end of auto-generated comment: release notes by coderabbit.ai --> --------- Signed-off-by: Shengliang Xu <shengliangx@nvidia.com>
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Changes requested: the shared distillation export helpers now reject Hub IDs still passed by distill.py, breaking its post-training HF export.
Needs action:
- Fix the
distill.pycallers ofexport_llm_to_hfandsave_vlm_to_hfto resolve the student checkpoint locally before export; preserve the original CLI identifier. - Add Hub-ID regression tests for both distillation export branches, plus assertions that Megatron loading/export uses the resolved directory and saved tokenizer references retain the Hub ID.
No action needed:
- Reusing
ensure_local_checkpointandcopy_non_model_filesis justified over partial Hub fetches and artifact regeneration in the PR body. - Existing test edits are justified: they assert the new deprecation warning without removing copying assertions.
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@cjluo-nv bot review: both items are addressed in e8e3d5a.
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Changes requested: the distillation caller bug is fixed, but the new regression test patches the wrong binding when the example module is cached.
Needs action:
- 💬 Author added both export regressions in
e8e3d5a7e1— fix the cached-module monkeypatch intest_distill.py(inline comment) and verify both cases pass in the full suite. - Add mocked quantize/prune regressions asserting loading and export use the resolved directory while saved
hf_tokenizer_pathretains the Hub ID; these previously requested assertions are still absent.
No action needed:
- ✔️ Resolved since the last review: both
distill.pyexport callers now receive the local source, and both unified-export API docstrings describe the Hub-ID limitation. - Shared checkpoint utilities are justified over partial Hub downloads and artifact regeneration. Deprecation test edits retain the existing copy assertions.
| resolved_from.append(str(model_name_or_path)) | ||
| return "org/tiny-student", str(resolved) | ||
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| monkeypatch.setattr(modelopt.torch.export, "ensure_local_checkpoint", ensure_local_checkpoint) |
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This patches modelopt.torch.export.ensure_local_checkpoint, but distill.py imports that function into its own module namespace. The in-process runner's _load_example_module() caches _modelopt_example_megatron_bridge_distill in sys.modules; earlier tests such as test_distill_llm_hf_export already load it. Consequently the cached module retains the original function, resolved_from stays empty, and the marker is not copied. The second parameterized case can likewise retain the first case's mock. Patch ensure_local_checkpoint on the actual example module used by the runner (loading it before patching), rather than only the exporting package. Run both parameterized cases together and after an existing distillation test to cover the cached-module path.
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Right, _load_example_module returns the cached module, so the patch on modelopt.torch.export never reached it. Fixed in 3dc0f25: the test loads the module the runner caches and patches ensure_local_checkpoint on it, and monkeypatch restores it between the two cases.
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@cjluo-nv bot review, both items:
All of these run single-rank so the in-process runner sees the patch. |
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Nudge: prior correctness and coverage concerns are resolved, but embedded agent directives in previous bot comments require human review.
Needs action:
- Confirm this review manually; previous CodeRabbit comments contain embedded agent instructions, which were ignored as untrusted input.
- Confirm the new distillation, quantize/export, and prune regressions pass in Megatron CI, including both cached-module distillation cases; GPU tests could not be executed here.
No action needed:
- ✔️ Resolved since the last review: local-source distillation callers, cached-module monkeypatching, quantize/prune Hub-ID and saved-tokenizer regressions, and Hub-ID API documentation.
- Shared checkpoint utilities are justified over partial Hub downloads and Transformers artifact regeneration in the PR body; no second production subsystem is introduced.
- Existing deprecation test edits are justified and retain all copying assertions.
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…rst if needed (#2611) ### What does this PR do? Type of change: bug fix ### Summary of the series Every pipeline that quantizes, prunes, sparsifies or distills a Hugging Face model now starts the same way: **make the checkpoint local, then load from it**. `ensure_local_checkpoint` returns a local directory as-is and downloads a Hub model ID in full if it is not cached yet -- once, on rank 0 -- and the model, tokenizer and processor are then loaded from that local directory. Before, a Hub ID went straight to `from_pretrained`, which fetched only the files loading needed, so every later step that needed the source as files found its own way back to it: `hf_ptq` through a hand-rolled cache lookup (`_resolve_model_path`, whose `TRANSFORMERS_CACHE` glob picked the lexicographically largest commit hash rather than `refs/main`) and a hardcoded download allowlist, regenerating tokenizer files along the way; the Megatron export by fetching only `*.py` for a Hub ID; other callers of `export_hf_checkpoint` not at all. With the source on local disk, exports follow one rule: an export writes the **model files** -- weights in any format and the metadata describing them -- and carries every other source file (**non-model files**: tokenizer, processor, remote code, chat templates, README, ...) over verbatim, from **local disk only**. Merge in order: 1. #2607 — Add `ensure_local_checkpoint` to load models from local disk, and `copy_non_model_files` 2. #2608 — HF exporters write off-index safetensors and non-model files 3. #2609 — `hf_ptq`: load the model from local disk, downloading it first if needed 4. #2611 — `llm_sparsity`: load the model from local disk, downloading it first if needed ← **this PR** 5. #2610 — `megatron_bridge`: load the HF model from local disk; Megatron export copies its non-model files ### This PR [4/5] **Loading.** `hf_sa.py` and `export_hf_ckpt.py` now make the model local first with `ensure_local_checkpoint` -- a local directory as-is, a Hub ID downloaded once -- and load the model and tokenizer from that copy (`args.local_checkpoint_path`), keeping their argument as given. That is also what lets `export_hf_checkpoint`, which carries the source's non-model files only from local disk (#2608), include them. **Exporting.** `hf_sa.py` no longer saves its tokenizer into the export: it sets `pad_token` to EOS only for generation, so the source's files are the right ones. `export_hf_ckpt.py` keeps its save, after the export, because it can add a pad token and resize the embeddings. ### Usage No flag change. ### Testing Both scripts byte-compile; their end-to-end tests need a GPU and are left to CI. No library code changes in this PR. ### Before your PR is "*Ready for review*" Make sure you read and follow [Contributor guidelines](https://github.com/NVIDIA/Model-Optimizer/blob/main/CONTRIBUTING.md) and your commits are signed (`git commit -s -S`). Make sure you read and follow the [Security Best Practices](https://github.com/NVIDIA/Model-Optimizer/blob/main/SECURITY.md#security-coding-practices-for-contributors) (e.g. avoiding hardcoded `trust_remote_code=True`, `torch.load(..., weights_only=False)`, `pickle`, etc.). - Is this change backward compatible?: ✅ - If you copied code from any other sources or added a new PIP dependency, did you follow guidance in `CONTRIBUTING.md`: N/A - Did you write any new necessary tests?: N/A - Did you update [Changelog](https://github.com/NVIDIA/Model-Optimizer/blob/main/CHANGELOG.rst)?: N/A (no user-facing change beyond the series' entries in #2608 and #2610) - Did you get Claude approval on this PR?: ❌ ### Additional Information Based on `main` (#2607–#2609 are merged); #2610 is stacked on it. <!-- This is an auto-generated comment: release notes by coderabbit.ai --> ## Summary by CodeRabbit * **Improvements** * Model export examples load checkpoints from a local copy while retaining the original model reference and, when available, its Hub ID. * Weight-sparsity exports save tokenizer updates, including padding-token changes. Attention-sparsity exports no longer save the tokenizer separately. * Attention-sparsity exports run the model in inference mode. <!-- end of auto-generated comment: release notes by coderabbit.ai --> --------- Signed-off-by: Shengliang Xu <shengliangx@nvidia.com>
The Megatron unified HF export copied every top-level non-safetensors file of a local source -- *.bin weights included -- but only *.py of a Hub ID, then regenerated the generation config, tokenizer and image processor. Now it writes its config and copies the source's non-model files with copy_non_model_files, from a local source only; a Hub ID gets a warning, as in the HF exporters. That is a breaking change for callers passing a Hub ID, who no longer get those files. The megatron_bridge quantize, export, prune and distillation-export scripts therefore make the HF model local first with ensure_local_checkpoint, keeping their argument as given and reading from hf_model_path. The tokenizer path recorded in saved Megatron checkpoints stays the Hub ID, which remains valid on other hosts. prune_minitron and the distillation VLM export -- which every rank reaches -- copy the non-model files from the main rank only, and the distillation LLM export now copies them too. copy_non_safetensor_files_from_ckpt lost its last internal user and is deprecated in favour of copy_non_model_files. Signed-off-by: Shengliang Xu <shengliangx@nvidia.com>
…D as hub_model_id As in hf_ptq: name the local checkpoint directory and the Hub identifier for what they are, with a student_ prefix in the distillation export. Signed-off-by: Shengliang Xu <shengliangx@nvidia.com>
…model ID Signed-off-by: Shengliang Xu <shengliangx@nvidia.com>
export_llm_to_hf and save_vlm_to_hf now copy the source's non-model files, which reads the student from local disk only, but distill.py still passed --student_hf_path unresolved: a Hub ID would fail the export after training. Resolve it with ensure_local_checkpoint at the start of main() and build, probe and export the student from that local copy; --student_hf_path stays as given. Signed-off-by: Shengliang Xu <shengliangx@nvidia.com>
Signed-off-by: Shengliang Xu <shengliangx@nvidia.com>
Signed-off-by: Shengliang Xu <shengliangx@nvidia.com>
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What does this PR do?
Type of change: new feature (with a backward breaking change and a deprecation)
Summary of the series
Every pipeline that quantizes, prunes, sparsifies or distills a Hugging Face model now starts the same way: make the checkpoint local, then load from it.
ensure_local_checkpointreturns a local directory as-is and downloads a Hub model ID in full if it is not cached yet -- once, on rank 0 -- and the model, tokenizer and processor are then loaded from that local directory.Before, a Hub ID went straight to
from_pretrained, which fetched only the files loading needed, so every later step that needed the source as files found its own way back to it:hf_ptqthrough a hand-rolled cache lookup (_resolve_model_path, whoseTRANSFORMERS_CACHEglob picked the lexicographically largest commit hash rather thanrefs/main) and a hardcoded download allowlist, regenerating tokenizer files along the way; the Megatron export by fetching only*.pyfor a Hub ID; other callers ofexport_hf_checkpointnot at all.With the source on local disk, exports follow one rule: an export writes the model files -- weights in any format and the metadata describing them -- and carries every other source file (non-model files: tokenizer, processor, remote code, chat templates, README, ...) over verbatim, from local disk only.
Merge in order:
ensure_local_checkpointto load models from local disk, andcopy_non_model_fileshf_ptq: load the model from local disk, downloading it first if neededllm_sparsity: load the model from local disk, downloading it first if neededmegatron_bridge: load the HF model from local disk; Megatron export copies its non-model files ← this PRThis PR [5/5]
Loading. The
megatron_bridgequantize, export, prune and distillation-export scripts now make the HF model local first withensure_local_checkpoint-- a local directory as-is, a Hub ID downloaded once -- and load the model, tokenizer and processor from that copy (args.local_checkpoint_path;student_local_checkpoint_pathin the distillation export).--hf_model_name_or_path/--student_hf_pathstay as given, and the tokenizer path recorded in saved Megatron checkpoints stays the Hub ID, which remains valid on other hosts.Exporting. The Megatron unified HF export copied every top-level non-safetensors file of a local source --
*.binweights included -- but only*.pyof a Hub ID, then regenerated the generation config, tokenizer and image processor. Now it writes its config and copies the source's non-model files withcopy_non_model_files, from a local source only; a Hub ID gets a warning, as in the HF exporters. Breaking: callers passing a Hub ID no longer get those files (CHANGELOG entry with the fix: pass the path fromensure_local_checkpoint).prune_minitronand the distillation VLM export -- which every rank reaches -- copy from the main rank only, and the distillation LLM export now copies the files too.copy_non_safetensor_files_from_ckptlost its last internal user and is deprecated in favour ofcopy_non_model_files.Usage
Testing
Same suite as #2607: 685 passed, including the deprecation test. The
megatron_bridgescripts andunified_export_megatron.pybyte-compile; the Megatron tests cannot run here, sincetransformer_enginecannot be imported, so they rely on CI. CPU only (torch 2.12, transformers 5.9, huggingface_hub 1.19).Before your PR is "Ready for review"
Make sure you read and follow Contributor guidelines and your commits are signed (
git commit -s -S).Make sure you read and follow the Security Best Practices (e.g. avoiding hardcoded
trust_remote_code=True,torch.load(..., weights_only=False),pickle, etc.).export_mcore_gpt_to_hfwith a Hub-ID source no longer writes tokenizer, processor, generation config or remote-code files; pass a local directory (e.g. fromensure_local_checkpoint).copy_non_safetensor_files_from_ckptis deprecated but still works.CONTRIBUTING.md: N/AAdditional Information
Stacked on #2611; last of the series.
Summary by CodeRabbit