08ba6ca0bc
Regression guard for the validator switch to mode="before". Pre-fix, vision_image_size: True was rejected with "must be in [256, 2048] (got 1)" because Pydantic coerced before our check ran. New test asserts the message now reads "integer or null".
122 lines
3.8 KiB
Python
122 lines
3.8 KiB
Python
# SPDX-License-Identifier: AGPL-3.0-only
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# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved.
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"""Pin TrainingStartRequest hyperparameter caps at the at-cap / over-cap boundary."""
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import sys
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from pathlib import Path
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import pytest
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from pydantic import ValidationError
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_BACKEND_ROOT = Path(__file__).resolve().parents[1]
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if str(_BACKEND_ROOT) not in sys.path:
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sys.path.insert(0, str(_BACKEND_ROOT))
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from models.training import (
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_MAX_BATCH_SIZE,
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_MAX_LORA_ALPHA,
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_MAX_LORA_R,
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_MAX_SEQ_LENGTH,
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_MAX_VISION_IMAGE_SIZE,
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_MIN_VISION_IMAGE_SIZE,
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)
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def _check_field(field_name: str, value):
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"""Run the field validator without constructing a full TrainingStartRequest."""
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from models.training import TrainingStartRequest
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schema_field = TrainingStartRequest.model_fields[field_name]
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return TrainingStartRequest.__pydantic_validator__.validate_assignment(
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TrainingStartRequest.model_construct(),
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field_name,
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value,
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)
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class TestSeqLengthCap:
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def test_at_cap_accepts(self):
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_check_field("max_seq_length", _MAX_SEQ_LENGTH)
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assert _MAX_SEQ_LENGTH == 2_000_000
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def test_over_cap_rejects(self):
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with pytest.raises(ValidationError) as exc:
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_check_field("max_seq_length", _MAX_SEQ_LENGTH + 1)
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assert "max_seq_length" in str(exc.value)
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def test_below_min_rejects(self):
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with pytest.raises(ValidationError):
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_check_field("max_seq_length", 0)
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class TestBatchSizeCap:
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def test_at_cap_accepts(self):
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_check_field("batch_size", _MAX_BATCH_SIZE)
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assert _MAX_BATCH_SIZE == 4096
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def test_over_cap_rejects(self):
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with pytest.raises(ValidationError):
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_check_field("batch_size", _MAX_BATCH_SIZE + 1)
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def test_below_min_rejects(self):
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with pytest.raises(ValidationError):
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_check_field("batch_size", 0)
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class TestVisionImageSizeCap:
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def test_none_accepts_model_default(self):
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_check_field("vision_image_size", None)
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@pytest.mark.parametrize(
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"value",
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[_MIN_VISION_IMAGE_SIZE, 640, 1000, _MAX_VISION_IMAGE_SIZE],
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)
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def test_in_range_accepts(self, value):
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_check_field("vision_image_size", value)
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assert _MIN_VISION_IMAGE_SIZE == 256
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assert _MAX_VISION_IMAGE_SIZE == 2048
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@pytest.mark.parametrize(
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"value",
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[_MIN_VISION_IMAGE_SIZE - 1, _MAX_VISION_IMAGE_SIZE + 1, 640.5, True],
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)
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def test_invalid_rejects(self, value):
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with pytest.raises(ValidationError):
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_check_field("vision_image_size", value)
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@pytest.mark.parametrize("value", [True, False])
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def test_bool_error_says_integer_not_range(self, value):
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# Regression guard: pre-fix the bool was coerced to 1/0 and the
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# message read "must be in [256, 2048] (got 1)", which was confusing.
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with pytest.raises(ValidationError) as exc:
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_check_field("vision_image_size", value)
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assert "integer or null" in str(exc.value)
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class TestLoraRCap:
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def test_at_cap_accepts(self):
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_check_field("lora_r", _MAX_LORA_R)
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assert _MAX_LORA_R == 16_384
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def test_over_cap_rejects(self):
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with pytest.raises(ValidationError):
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_check_field("lora_r", _MAX_LORA_R + 1)
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def test_below_min_rejects(self):
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with pytest.raises(ValidationError):
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_check_field("lora_r", 0)
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class TestLoraAlphaCap:
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def test_at_cap_accepts(self):
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_check_field("lora_alpha", _MAX_LORA_ALPHA)
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assert _MAX_LORA_ALPHA == 32_768
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def test_over_cap_rejects(self):
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with pytest.raises(ValidationError):
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_check_field("lora_alpha", _MAX_LORA_ALPHA + 1)
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def test_below_min_rejects(self):
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with pytest.raises(ValidationError):
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_check_field("lora_alpha", 0)
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