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77 lines
2.5 KiB
Python
77 lines
2.5 KiB
Python
"""RaiseUninitialized must ignore a checkpoint that only re-initializes deterministic
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position_ids buffers, but still raise when a real weight is missing -- even if the same
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HF record also lists a benign position_ids buffer.
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"""
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from __future__ import annotations
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import logging
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import pytest
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from unsloth.models._utils import (
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_all_missing_keys_are_position_ids,
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_RaiseUninitialized,
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)
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_TEMPLATE = (
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"Some weights of DeepseekOCRForCausalLM were not initialized from the model "
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"checkpoint at unsloth/DeepSeek-OCR and are newly initialized: {keys}\n"
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"You should probably TRAIN this model on a down-stream task."
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)
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def _record(keys_repr: str) -> logging.LogRecord:
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return logging.LogRecord(
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name = "transformers.modeling_utils",
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level = logging.WARNING,
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pathname = "modeling_utils.py",
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lineno = 1,
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msg = _TEMPLATE.format(keys = keys_repr),
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args = None,
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exc_info = None,
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)
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@pytest.mark.parametrize(
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"keys_repr, expected",
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[
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("['model.vision_model.embeddings.position_ids']", True),
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(
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"['model.vision_model.embeddings.position_ids', "
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"'vision_model.encoder.layers.0.position_ids']",
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True,
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),
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# A real missing weight alongside position_ids must NOT be suppressed.
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(
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"['model.vision_model.embeddings.position_ids', 'model.layers.5.mlp.weight']",
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False,
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),
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("['model.layers.5.mlp.weight']", False),
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("[]", False),
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],
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)
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def test_all_missing_keys_are_position_ids(keys_repr, expected):
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assert _all_missing_keys_are_position_ids(_TEMPLATE.format(keys = keys_repr)) is expected
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def test_emit_suppresses_position_ids_only_record():
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# A record listing only position_ids buffers loads cleanly (no raise).
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handler = _RaiseUninitialized()
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handler.emit(_record("['model.vision_model.embeddings.position_ids']"))
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def test_emit_raises_when_real_weight_missing_alongside_position_ids():
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# The core fix: one benign position_ids key must not mask a real missing weight.
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handler = _RaiseUninitialized()
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with pytest.raises(Exception, match = "some weights are not initialized"):
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handler.emit(
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_record("['model.vision_model.embeddings.position_ids', 'model.layers.5.mlp.weight']")
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)
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def test_emit_raises_on_real_missing_weight():
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handler = _RaiseUninitialized()
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with pytest.raises(Exception, match = "some weights are not initialized"):
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handler.emit(_record("['model.layers.5.mlp.weight']"))
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