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356 lines
14 KiB
Python
356 lines
14 KiB
Python
# SPDX-License-Identifier: AGPL-3.0-only
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# Copyright 2026-present the Unsloth AI Inc. team.
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"""Pinned-symbol + source-pattern transformers compat checks via GitHub raw-fetch + grep.
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Catches breakage classes from unsloth#3998/5036/5155/5259 and
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unsloth-zoo#572/571/549/543/541/495/491/488/472/393/388/583/584/159.
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CPU-only, no install. Anchor versions: transformers 4.57.6, 5.5.0.
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"""
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from __future__ import annotations
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import re
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import pytest
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from tests.version_compat._fetch import fetch_text, first_match, has_def
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# 4.57.6 floor + every 5.x minor since 5.0.0 + main.
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TRANSFORMERS_TAGS = [
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"v4.57.6", # anchor (must work)
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"v5.0.0",
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"v5.1.0",
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"v5.2.0",
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"v5.3.0",
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"v5.4.0",
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"v5.5.0", # anchor (must work)
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"v5.5.4",
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"v5.6.2",
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"v5.7.0",
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"v5.8.0",
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"main",
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]
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# Trainer surface: unsloth/models/_utils.py rewrites Trainer.{__init__, training_step, get_batch_samples, compute_loss}.
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@pytest.mark.parametrize("tag", TRANSFORMERS_TAGS)
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def test_trainer_class_importable_path(tag: str):
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"""transformers.Trainer must remain at trainer.py or trainer/__init__.py."""
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candidates = ["src/transformers/trainer.py", "src/transformers/trainer/__init__.py"]
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hit = first_match("huggingface/transformers", tag, candidates)
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assert hit is not None, f"{tag}: src/transformers/trainer[.py|/__init__.py] both missing"
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_, src = hit
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assert has_def(src, "Trainer", "class"), f"{tag}: class Trainer missing"
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@pytest.mark.parametrize("tag", TRANSFORMERS_TAGS)
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def test_trainer_compute_loss_num_items_in_batch_param(tag: str):
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"""unsloth-zoo#159 + unsloth#4998 + #4616: Trainer.compute_loss must accept num_items_in_batch kwarg."""
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candidates = ["src/transformers/trainer.py", "src/transformers/trainer/__init__.py"]
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hit = first_match("huggingface/transformers", tag, candidates)
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assert hit is not None
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_, src = hit
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m = re.search(r"^\s*def compute_loss\(([^)]*)\)", src, re.MULTILINE | re.DOTALL)
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if m is None:
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pytest.fail(f"{tag}: Trainer.compute_loss not found in source")
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assert "num_items_in_batch" in m.group(1), (
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f"{tag}: Trainer.compute_loss signature missing num_items_in_batch param; "
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f"unsloth grad-accum patches assume this kwarg present"
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)
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@pytest.mark.parametrize("tag", TRANSFORMERS_TAGS)
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def test_trainer_training_step_grad_accum_pattern(tag: str):
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"""unsloth#3598 patches Trainer.training_step source; drift = silent no-op = double-scale loss bug."""
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candidates = ["src/transformers/trainer.py", "src/transformers/trainer/__init__.py"]
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hit = first_match("huggingface/transformers", tag, candidates)
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assert hit is not None
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_, src = hit
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needed = (
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"loss *= self.args.gradient_accumulation_steps",
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"if self.model_accepts_loss_kwargs:",
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"self.accelerator.backward(loss",
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)
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missing = [s for s in needed if s not in src]
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# Hard-fail only when ALL substrings missing; partial drift is informational.
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if len(missing) == len(needed):
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pytest.fail(
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f"{tag}: Trainer.training_step has none of the grad-accum "
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f"fingerprints {needed}; unsloth/models/_utils.py:1689-1791 "
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f"patch silently no-ops -> double-scale loss"
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)
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@pytest.mark.parametrize("tag", TRANSFORMERS_TAGS)
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def test_trainer_get_batch_samples_returns_num_items(tag: str):
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"""unsloth-zoo loss_utils.py:241 replaces Trainer.get_batch_samples; must keep the num_items_in_batch return."""
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candidates = ["src/transformers/trainer.py", "src/transformers/trainer/__init__.py"]
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hit = first_match("huggingface/transformers", tag, candidates)
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assert hit is not None
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_, src = hit
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if not has_def(src, "get_batch_samples", "func"):
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pytest.skip(f"{tag}: get_batch_samples not yet on Trainer")
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assert (
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"num_items_in_batch" in src
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), f"{tag}: Trainer.get_batch_samples / num_items_in_batch contract missing"
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@pytest.mark.parametrize("tag", TRANSFORMERS_TAGS)
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def test_trainer_inner_training_loop_inplace_loss_v5(tag: str):
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"""unsloth-zoo#543: transformers 5.0+ switched out-of-place tr_loss add to in-place `self._tr_loss +=`."""
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candidates = ["src/transformers/trainer.py", "src/transformers/trainer/__init__.py"]
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hit = first_match("huggingface/transformers", tag, candidates)
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assert hit is not None
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_, src = hit
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has_inplace = "self._tr_loss +=" in src
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has_outplace = "tr_loss = tr_loss + tr_loss_step" in src
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# Assert ONE form is present so a refactor dropping both is caught.
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assert has_inplace or has_outplace, (
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f"{tag}: Trainer._inner_training_loop has neither "
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f"`tr_loss = tr_loss + tr_loss_step` nor `self._tr_loss +=`; "
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f"unsloth-zoo#543 patch breaks"
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)
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# modeling_utils: checkpoint, PushToHubMixin, ALL_ATTENTION_FUNCTIONS.
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@pytest.mark.parametrize("tag", TRANSFORMERS_TAGS)
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def test_modeling_utils_exposes_checkpoint(tag: str):
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"""unsloth-zoo#549: transformers 5.2+ uses modeling_utils.checkpoint; patch must replace it, not just torch's."""
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src = fetch_text("huggingface/transformers", tag, "src/transformers/modeling_utils.py")
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if src is None:
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pytest.skip(f"{tag}: modeling_utils.py missing")
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# Either a direct import or local rebinding.
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has_import = bool(
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re.search(
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r"^from\s+torch\.utils\.checkpoint\s+import\s+checkpoint",
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src,
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re.MULTILINE,
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)
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or re.search(r"^import\s+torch\.utils\.checkpoint", src, re.MULTILINE)
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or "checkpoint = torch.utils.checkpoint.checkpoint" in src
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)
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assert has_import, (
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f"{tag}: transformers.modeling_utils does not import / re-bind "
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f"torch.utils.checkpoint.checkpoint; unsloth-zoo#549 patch breaks"
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)
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@pytest.mark.parametrize("tag", TRANSFORMERS_TAGS)
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def test_pushtohubmixin_create_repo_status(tag: str):
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"""unsloth-zoo#393: transformers 5.x removed PushToHubMixin._create_repo; snapshot which side."""
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src = fetch_text("huggingface/transformers", tag, "src/transformers/modeling_utils.py")
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if src is None:
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pytest.skip(f"{tag}: modeling_utils.py missing")
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has_create = bool(re.search(r"def _create_repo\b", src) or "_create_repo" in src)
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# Informational only.
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_ = has_create
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# integrations.bitsandbytes: _replace_with_bnb_linear vs new path.
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@pytest.mark.parametrize("tag", TRANSFORMERS_TAGS)
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def test_integrations_bitsandbytes_module_present(tag: str):
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src = fetch_text(
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"huggingface/transformers", tag, "src/transformers/integrations/bitsandbytes.py"
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)
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if src is None:
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pytest.skip(f"{tag}: integrations/bitsandbytes.py missing (legacy layout)")
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assert (
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"Linear4bit" in src or "linear" in src.lower()
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), f"{tag}: integrations/bitsandbytes.py has no Linear4bit reference"
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@pytest.mark.parametrize("tag", TRANSFORMERS_TAGS)
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def test_quantizers_should_convert_module_signature(tag: str):
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"""unsloth-zoo#491/#488: 5.x moved is_replaceable to quantizers_utils.should_convert_module; snapshot its form."""
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src = fetch_text(
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"huggingface/transformers",
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tag,
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"src/transformers/quantizers/quantizers_utils.py",
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)
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if src is None:
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pytest.skip(f"{tag}: quantizers/quantizers_utils.py missing")
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if not has_def(src, "should_convert_module", "func"):
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pytest.skip(f"{tag}: should_convert_module not yet present (4.x)")
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# Catch substring matching in `.{key}.` form.
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has_dot_form = ".{key}." in src or "f'.{key}.'" in src or 'f".{key}."' in src
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# Informational only.
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_ = has_dot_form
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# integrations.finegrained_fp8.FP8Linear: bias/has_bias rename in v5.
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@pytest.mark.parametrize("tag", TRANSFORMERS_TAGS)
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def test_fp8linear_init_param_names(tag: str):
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"""unsloth-zoo#572: transformers 5.x renamed FP8Linear.__init__ `bias` -> `has_bias`."""
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src = fetch_text(
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"huggingface/transformers",
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tag,
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"src/transformers/integrations/finegrained_fp8.py",
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)
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if src is None:
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pytest.skip(f"{tag}: integrations/finegrained_fp8.py missing")
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if not has_def(src, "FP8Linear", "class"):
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pytest.skip(f"{tag}: FP8Linear not yet defined")
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has_bias_kw = re.search(r"def __init__\([^)]*\bbias\b", src) is not None
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has_has_bias_kw = re.search(r"def __init__\([^)]*\bhas_bias\b", src) is not None
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assert (
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has_bias_kw or has_has_bias_kw
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), f"{tag}: FP8Linear.__init__ has neither `bias` nor `has_bias` param"
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# processing_utils: Unpack importable.
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@pytest.mark.parametrize("tag", TRANSFORMERS_TAGS)
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def test_processing_utils_unpack_importable(tag: str):
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"""unsloth-zoo#583/584: transformers.processing_utils.Unpack must keep importing."""
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src = fetch_text("huggingface/transformers", tag, "src/transformers/processing_utils.py")
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if src is None:
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pytest.skip(f"{tag}: processing_utils.py missing")
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has_unpack = bool(re.search(r"^Unpack\b\s*=", src, re.MULTILINE) or "Unpack" in src)
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assert has_unpack, (
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f"{tag}: transformers.processing_utils.Unpack missing; "
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f"unsloth-zoo#583/584 import guard breaks"
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)
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# Models: gemma3, gpt_oss forward signature drift.
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@pytest.mark.parametrize("tag", TRANSFORMERS_TAGS)
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def test_gemma3_attention_forward_present(tag: str):
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src = fetch_text(
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"huggingface/transformers",
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tag,
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"src/transformers/models/gemma3/modeling_gemma3.py",
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)
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if src is None:
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pytest.skip(f"{tag}: modeling_gemma3.py missing")
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assert has_def(src, "Gemma3Attention", "class"), f"{tag}: class Gemma3Attention missing"
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@pytest.mark.parametrize("tag", TRANSFORMERS_TAGS)
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def test_gpt_oss_model_forward_present(tag: str):
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src = fetch_text(
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"huggingface/transformers",
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tag,
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"src/transformers/models/gpt_oss/modeling_gpt_oss.py",
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)
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if src is None:
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pytest.skip(f"{tag}: modeling_gpt_oss.py missing (legacy)")
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assert has_def(src, "GptOssModel", "class"), f"{tag}: class GptOssModel missing"
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# auto_factory: unsloth#5155 _LazyAutoMapping private API.
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@pytest.mark.parametrize("tag", TRANSFORMERS_TAGS)
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def test_auto_factory_lazy_mapping_private_api(tag: str):
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"""unsloth#5155: resolve_model_class needs all four _LazyAutoMapping private attrs to remain."""
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src = fetch_text(
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"huggingface/transformers",
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tag,
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"src/transformers/models/auto/auto_factory.py",
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)
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if src is None:
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pytest.skip(f"{tag}: auto/auto_factory.py missing")
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needed = (
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"_model_mapping",
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"_config_mapping",
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"_extra_content",
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"_load_attr_from_module",
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)
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missing = [n for n in needed if n not in src]
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assert not missing, (
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f"{tag}: _LazyAutoMapping private API missing {missing}; "
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f"unsloth/models/_utils.py:resolve_model_class breaks (unsloth#5155)"
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)
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# configuration_utils: PreTrainedConfig vs PretrainedConfig in 5.x.
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@pytest.mark.parametrize("tag", TRANSFORMERS_TAGS)
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def test_configuration_utils_alias(tag: str):
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"""transformers 5.x renamed PretrainedConfig -> PreTrainedConfig; unsloth-zoo imports both defensively."""
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src = fetch_text(
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"huggingface/transformers",
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tag,
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"src/transformers/configuration_utils.py",
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)
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if src is None:
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pytest.skip(f"{tag}: configuration_utils.py missing")
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has_old = has_def(src, "PretrainedConfig", "class")
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has_new = has_def(src, "PreTrainedConfig", "class")
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assert has_old or has_new, (
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f"{tag}: neither PretrainedConfig (4.x) nor PreTrainedConfig (5.x) "
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f"defined in configuration_utils.py"
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)
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# tokenization: apply_chat_template return_dict default flip in v5.
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@pytest.mark.parametrize("tag", TRANSFORMERS_TAGS)
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def test_apply_chat_template_signature_present(tag: str):
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"""unsloth-zoo#572: apply_chat_template `return_dict` default flipped False -> True in transformers 5.x."""
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src = fetch_text(
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"huggingface/transformers",
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tag,
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"src/transformers/tokenization_utils_base.py",
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)
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if src is None:
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pytest.skip(f"{tag}: tokenization_utils_base.py missing")
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assert has_def(
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src, "apply_chat_template", "func"
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), f"{tag}: apply_chat_template missing in tokenization_utils_base.py"
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# Generic-importability sweep: every transformers symbol unsloth/zoo imports must stay reachable.
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@pytest.mark.parametrize("tag", TRANSFORMERS_TAGS)
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def test_modeling_attn_mask_utils_symbols(tag: str):
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"""_prepare_4d_attention_mask_for_sdpa is imported by unsloth/models/llama.py + sentence_transformer.py."""
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src = fetch_text(
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"huggingface/transformers",
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tag,
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"src/transformers/modeling_attn_mask_utils.py",
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)
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if src is None:
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pytest.skip(f"{tag}: modeling_attn_mask_utils.py missing")
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assert has_def(src, "AttentionMaskConverter", "class"), f"{tag}: AttentionMaskConverter missing"
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assert (
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has_def(src, "_prepare_4d_attention_mask_for_sdpa", "func")
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or "_prepare_4d_attention_mask_for_sdpa" in src
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), f"{tag}: _prepare_4d_attention_mask_for_sdpa missing"
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@pytest.mark.parametrize("tag", TRANSFORMERS_TAGS)
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def test_cache_utils_classes(tag: str):
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src = fetch_text("huggingface/transformers", tag, "src/transformers/cache_utils.py")
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if src is None:
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pytest.skip(f"{tag}: cache_utils.py missing")
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needed = ("Cache", "DynamicCache")
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for cls in needed:
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assert has_def(src, cls, "class"), f"{tag}: transformers.cache_utils.{cls} missing"
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@pytest.mark.parametrize("tag", TRANSFORMERS_TAGS)
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def test_training_args_parallel_mode_importable(tag: str):
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src = fetch_text("huggingface/transformers", tag, "src/transformers/training_args.py")
|
|
if src is None:
|
|
pytest.skip(f"{tag}: training_args.py missing")
|
|
assert "ParallelMode" in src, (
|
|
f"{tag}: transformers.training_args.ParallelMode missing; "
|
|
f"unsloth-zoo loss_utils.py:232 ImportError"
|
|
)
|