Update for transformers 5.0

[pstjohn]

Currently blocked by huggingface/transformers#43510

Summary by CodeRabbit

• New Features

  • Added checkpoint loading validation test.
  • Enhanced distributed testing infrastructure with improved port configuration.

• Improvements

  • Removed upper-bound version constraints on the transformer library for broader compatibility.
  • Improved weight initialization and checkpoint state management for TransformerEngine-optimized models.

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📝 Walkthrough

Walkthrough

This pull request relaxes transformers version constraints across multiple projects, introduces weight initialization and state management improvements for TransformerEngine-backed models, updates weight tying declarations from tuples to typed class variable mappings, and adds TCP port fixture infrastructure to distributed tests for rendezvous configuration.

Changes

Cohort / File(s)	Summary
Transformers dependency relaxation .devcontainer/recipes/requirements.txt, bionemo-recipes/models/amplify/pyproject.toml, bionemo-recipes/models/esm2/pyproject.toml, bionemo-recipes/models/llama3/requirements.txt, bionemo-recipes/recipes/esm2_accelerate_te/requirements.txt, bionemo-recipes/recipes/esm2_native_te/requirements.txt, bionemo-recipes/recipes/esm2_peft_te/requirements.txt, bionemo-recipes/recipes/geneformer_native_te_mfsdp_fp8/requirements.txt, bionemo-recipes/recipes/llama3_native_te/requirements.txt	Removes upper bound constraint on transformers dependency, changing from transformers<5.0 to transformers across all dependency files.
ESM2 weight initialization and state management bionemo-recipes/models/esm2/src/esm/modeling_esm_te.py	Introduces _init_weights() method to skip TransformerEngine modules, adds state_dict() override to filter TE-specific _extra_state entries, updates get_init_context() signature to accept dtype parameter, changes _tied_weights_keys from tuple to ClassVar[dict[str, str]] mapping, and removes explicit init_weights() call from initialization sequence.
ESM2 model conversion bionemo-recipes/models/esm2/src/esm/convert.py	Replaces tie_weights() with post_init() as final post-processing step in ESM TE to HF model conversion.
ESM2 test infrastructure bionemo-recipes/models/esm2/tests/conftest.py, bionemo-recipes/models/esm2/tests/test_convert.py	Adds unused_tcp_port fixture for acquiring ephemeral ports; introduces new test for checkpoint loading verification.
ESM2 distributed tests bionemo-recipes/models/esm2/tests/test_distributed_fp8.py, bionemo-recipes/models/esm2/tests/test_distributed_strategies.py	Updates test signatures to accept unused_tcp_port parameter, adds rendezvous backend/endpoint configuration to torchrun commands, refactors FP8 extra state collection from state_dict keys to direct module inspection, adds cross-rank FP8 extra state synchronization validation, and includes seed initialization for reproducibility.
Llama3 weight initialization and state management bionemo-recipes/models/llama3/modeling_llama_te.py, bionemo-recipes/recipes/llama3_native_te/modeling_llama_te.py	Adds state_dict() override to filter TE-specific _extra_state keys, implements get_init_context() classmethod for empty context initialization, updates _tied_weights_keys from tuple to ClassVar[dict[str, str]] mapping, and adjusts typing imports to include ClassVar.
Llama3 test infrastructure bionemo-recipes/models/llama3/tests/conftest.py, bionemo-recipes/models/llama3/tests/test_cp_bshd.py, bionemo-recipes/models/llama3/tests/test_cp_thd.py, bionemo-recipes/models/llama3/tests/test_meta_device_init.py	Adds unused_tcp_port fixture, updates test signatures to accept fixture parameter, configures rendezvous backend/endpoint in torchrun commands, and fixes model loading to use local NVEsmForMaskedLM import instead of remote AutoModel loading.
Recipe example files bionemo-recipes/recipes/esm2_accelerate_te/example_8m_checkpoint/esm_nv.py, bionemo-recipes/recipes/esm2_native_te/example_8m_checkpoint/esm_nv.py, bionemo-recipes/recipes/esm2_peft_te/example_8m_checkpoint/esm_nv.py	Introduces identical weight initialization, state management, and weight tying declaration patterns as in main model files, including _init_weights(), state_dict() overrides, updated get_init_context() signatures, and _tied_weights_keys ClassVar dict mappings.

Estimated code review effort

🎯 3 (Moderate) | ⏱️ ~20 minutes

Poem

🐰 Hopping through transformers, we loosen the reins,
TransformerEngine now flows through our veins,
Weight tying maps grow, state dicts now clean,
Port-finding sockets ensure tests convene,
With dtype in context, our models take flight—
A refactored foundation, now sparkling bright! ✨

🚥 Pre-merge checks | ✅ 2 | ❌ 1

❌ Failed checks (1 warning)

Check name	Status	Explanation	Resolution
Description check	⚠️ Warning	The pull request description is incomplete. It only contains a single line referencing a blocked upstream PR, lacking any of the required template sections such as Description, Usage, Type of changes, CI Pipeline Configuration, or Pre-submit Checklist.	Complete the pull request description using the provided template. Include detailed description of changes, usage examples, type of changes, CI configuration labels, and pre-submit checklist items.

✅ Passed checks (2 passed)

Check name	Status	Explanation
Title check	✅ Passed	The title 'Update for transformers 5.0' clearly and concisely describes the main objective of the pull request - updating the codebase for transformers v5.0 compatibility.
Docstring Coverage	✅ Passed	Docstring coverage is 84.00% which is sufficient. The required threshold is 80.00%.

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[pstjohn]

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Actionable comments posted: 0

Caution

Some comments are outside the diff and can’t be posted inline due to platform limitations.

⚠️ Outside diff range comments (2)

bionemo-recipes/models/esm2/src/esm/convert.py (1)

122-135: ⚠️ Potential issue | 🟡 Minor

Remove redundant post_init() call; apply_transforms() already calls tie_weights().

Testing confirms the current code is safe—weight values are preserved correctly through the post_init() call (test_convert.py validates roundtrip conversion with strict tolerances). However, apply_transforms() already invokes tie_weights() before returning, making the subsequent post_init() call redundant. Also note that convert_esm_hf_to_te() does not call post_init(), creating an inconsistency.

Suggested fix

-    output_model.post_init()

bionemo-recipes/models/esm2/tests/conftest.py (1)

16-43: ⚠️ Potential issue | 🟡 Minor

Add a second blank line after the import block.

Ruff/isort will flag a single blank line before the module-level TRITON env block.

🧹 Suggested fix

-from esm.convert import convert_esm_hf_to_te
-
-# Fix Triton UTF-8 decoding issue by setting CUDA library path
+from esm.convert import convert_esm_hf_to_te
+
+
+# Fix Triton UTF-8 decoding issue by setting CUDA library path

As per coding guidelines, Follow import sorting configuration as per isort with 2 lines after imports.

🧹 Nitpick comments (3)

bionemo-recipes/models/amplify/pyproject.toml (1)

21-21: Confirm whether AMPLIFY should stay capped at Transformers <5.0.

If AMPLIFY is now v5-compatible, aligning this constraint (e.g., transformers>=5.0,<6) would prevent users from staying on v4. If not, the TODO is fine but this will keep the package incompatible with v5 installs.

💡 Optional alignment with v5 support

-    "transformers<5.0",                  # TODO(BIO-143): update AMPLIFY to support Transformers v5
+    "transformers>=5.0,<6",              # TODO(BIO-143): update AMPLIFY to support Transformers v5

bionemo-recipes/recipes/geneformer_native_te_mfsdp_fp8/requirements.txt (1)

9-9: Add an explicit v5 lower bound to avoid silently running v4.

An unconstrained transformers can be satisfied by an already-installed v4, which defeats the v5 migration and risks runtime mismatches. Consider transformers>=5.0,<6 to lock the supported major.

♻️ Suggested constraint

-transformers
+transformers>=5.0,<6

bionemo-recipes/recipes/esm2_native_te/requirements.txt (1)

11-11: Consider bounding transformers to the v5 major line.

Leaving this unbounded can allow v6+ upgrades with breaking changes. A constrained range still permits v5 updates while preventing accidental major bumps.

🔧 Suggested constraint

-transformers
+transformers>=5.0,<6.0