wehub-resource-sync
70 lines
2.4 KiB
Python
70 lines
2.4 KiB
Python
import json
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import tempfile
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from pathlib import Path
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import pytest
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from mlc_llm.cli import convert_weight as convert_weight_cli
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pytestmark = [pytest.mark.unittest]
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def test_convert_weight_cli_passes_lora_adapter(monkeypatch):
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with tempfile.TemporaryDirectory() as tmp_dir:
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temp_path = Path(tmp_dir)
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config_path = temp_path / "config.json"
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source_dir = temp_path / "source"
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source_dir.mkdir(parents=True, exist_ok=True)
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source_index = source_dir / "pytorch_model.bin.index.json"
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adapter_dir = temp_path / "adapter"
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adapter_dir.mkdir(parents=True, exist_ok=True)
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output_dir = temp_path / "output"
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config_path.write_text(json.dumps({}), encoding="utf-8")
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source_index.write_text(json.dumps({"weight_map": {}}), encoding="utf-8")
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def _fake_detect_device(device):
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return device
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def _fake_detect_weight(_weight_path, _config_json_path, _weight_format):
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return source_index, "huggingface-torch"
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def _fake_detect_model_type(_model_type, _config):
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return "dummy"
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monkeypatch.setattr(convert_weight_cli, "detect_config", Path)
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monkeypatch.setattr(convert_weight_cli, "detect_device", _fake_detect_device)
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monkeypatch.setattr(convert_weight_cli, "detect_weight", _fake_detect_weight)
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monkeypatch.setattr(convert_weight_cli, "detect_model_type", _fake_detect_model_type)
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monkeypatch.setattr(convert_weight_cli, "MODELS", {"dummy": object()})
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monkeypatch.setattr(convert_weight_cli, "QUANTIZATION", {"q0f16": object()})
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call_args = {}
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def _fake_convert_weight(**kwargs):
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call_args.update(kwargs)
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monkeypatch.setattr(convert_weight_cli, "convert_weight", _fake_convert_weight)
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convert_weight_cli.main(
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[
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str(config_path),
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"--quantization",
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"q0f16",
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"--model-type",
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"dummy",
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"--source",
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str(source_dir),
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"--source-format",
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"auto",
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"--output",
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str(output_dir),
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"--lora-adapter",
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str(adapter_dir),
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]
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)
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assert call_args["lora_adapter"] == adapter_dir
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assert call_args["source"] == source_index
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assert call_args["source_format"] == "huggingface-torch"
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