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chore: import upstream snapshot with attribution
2026-07-13 13:23:58 +08:00

69 lines
2.1 KiB
Python

from pathlib import Path
from typing import Union
import pytest
import tvm
from mlc_llm.loader import HuggingFaceLoader
from mlc_llm.model import MODELS
from mlc_llm.support import logging, tqdm
logging.enable_logging()
@pytest.mark.parametrize(
"base_path",
[
"./dist/models/Llama-2-7b-hf",
"./dist/models/Llama-2-13b-hf",
"./dist/models/Llama-2-70b-hf",
],
)
def test_load_torch_llama(base_path: Union[str, Path]):
base_path = Path(base_path)
path_config = base_path / "config.json"
path_params = base_path / "pytorch_model.bin.index.json"
model = MODELS["llama"]
config = model.config.from_file(path_config)
loader = HuggingFaceLoader(
path=path_params,
extern_param_map=model.source["huggingface-torch"](config, None),
)
with tqdm.redirect():
for _name, _param in loader.load(device=tvm.device("cpu")):
return # To reduce the time of the test
@pytest.mark.parametrize(
"base_path",
[
"./dist/models/Llama-2-7b-hf",
"./dist/models/Llama-2-13b-hf",
"./dist/models/Llama-2-70b-hf",
],
)
def test_load_safetensor_llama(base_path: Union[str, Path]):
base_path = Path(base_path)
path_config = base_path / "config.json"
path_params = base_path / "model.safetensors.index.json"
model = MODELS["llama"]
config = model.config.from_file(path_config)
loader = HuggingFaceLoader(
path=path_params,
extern_param_map=model.source["huggingface-safetensor"](config, None),
)
with tqdm.redirect():
for _name, _param in loader.load(device=tvm.device("cpu")):
return # To reduce the time of the test
if __name__ == "__main__":
test_load_torch_llama(base_path="./dist/models/Llama-2-7b-hf")
test_load_torch_llama(base_path="./dist/models/Llama-2-13b-hf")
test_load_torch_llama(base_path="./dist/models/Llama-2-70b-hf")
test_load_safetensor_llama(base_path="./dist/models/Llama-2-7b-hf")
test_load_safetensor_llama(base_path="./dist/models/Llama-2-13b-hf")
test_load_safetensor_llama(base_path="./dist/models/Llama-2-70b-hf")