| |
| ''' |
| This script fetches all the models used in the server tests. |
| |
| This is useful for slow tests that use larger models, to avoid them timing out on the model downloads. |
| |
| It is meant to be run from the root of the repository. |
| |
| Example: |
| python scripts/fetch_server_test_models.py |
| ( cd tools/server/tests && ./tests.sh -v -x -m slow ) |
| ''' |
| import ast |
| import glob |
| import logging |
| import os |
| from typing import Generator |
| from pydantic import BaseModel |
| from typing import Optional |
| import subprocess |
|
|
|
|
| class HuggingFaceModel(BaseModel): |
| hf_repo: str |
| hf_file: Optional[str] = None |
|
|
| class Config: |
| frozen = True |
|
|
|
|
| def collect_hf_model_test_parameters(test_file) -> Generator[HuggingFaceModel, None, None]: |
| try: |
| with open(test_file) as f: |
| tree = ast.parse(f.read()) |
| except Exception as e: |
| logging.error(f'collect_hf_model_test_parameters failed on {test_file}: {e}') |
| return |
|
|
| for node in ast.walk(tree): |
| if isinstance(node, ast.FunctionDef): |
| for dec in node.decorator_list: |
| if isinstance(dec, ast.Call) and isinstance(dec.func, ast.Attribute) and dec.func.attr == 'parametrize': |
| param_names = ast.literal_eval(dec.args[0]).split(",") |
| if "hf_repo" not in param_names: |
| continue |
|
|
| raw_param_values = dec.args[1] |
| if not isinstance(raw_param_values, ast.List): |
| logging.warning(f'Skipping non-list parametrize entry at {test_file}:{node.lineno}') |
| continue |
|
|
| hf_repo_idx = param_names.index("hf_repo") |
| hf_file_idx = param_names.index("hf_file") if "hf_file" in param_names else None |
|
|
| for t in raw_param_values.elts: |
| if not isinstance(t, ast.Tuple): |
| logging.warning(f'Skipping non-tuple parametrize entry at {test_file}:{node.lineno}') |
| continue |
| yield HuggingFaceModel( |
| hf_repo=ast.literal_eval(t.elts[hf_repo_idx]), |
| hf_file=ast.literal_eval(t.elts[hf_file_idx]) if hf_file_idx is not None else None) |
|
|
|
|
| if __name__ == '__main__': |
| logging.basicConfig(level=logging.INFO, format='%(levelname)s: %(message)s') |
|
|
| models = sorted(list(set([ |
| model |
| for test_file in glob.glob('tools/server/tests/unit/test_*.py') |
| for model in collect_hf_model_test_parameters(test_file) |
| ])), key=lambda m: (m.hf_repo, m.hf_file)) |
|
|
| logging.info(f'Found {len(models)} models in parameterized tests:') |
| for m in models: |
| logging.info(f' - {m.hf_repo} / {m.hf_file}') |
|
|
| cli_path = os.environ.get( |
| 'LLAMA_CLI_BIN_PATH', |
| os.path.join( |
| os.path.dirname(__file__), |
| '../build/bin/Release/llama-cli.exe' if os.name == 'nt' else '../build/bin/llama-cli')) |
|
|
| for m in models: |
| if '<' in m.hf_repo or (m.hf_file is not None and '<' in m.hf_file): |
| continue |
| if m.hf_file is not None and '-of-' in m.hf_file: |
| logging.warning(f'Skipping model at {m.hf_repo} / {m.hf_file} because it is a split file') |
| continue |
| logging.info(f'Using llama-cli to ensure model {m.hf_repo}/{m.hf_file} was fetched') |
| cmd = [ |
| cli_path, |
| '-hfr', m.hf_repo, |
| *([] if m.hf_file is None else ['-hff', m.hf_file]), |
| '-n', '1', |
| '-p', 'Hey', |
| '--no-warmup', |
| '--log-disable', |
| '-no-cnv'] |
| if m.hf_file != 'tinyllamas/stories260K.gguf' and 'Mistral-Nemo' not in m.hf_repo: |
| cmd.append('-fa') |
| try: |
| subprocess.check_call(cmd) |
| except subprocess.CalledProcessError: |
| logging.error(f'Failed to fetch model at {m.hf_repo} / {m.hf_file} with command:\n {" ".join(cmd)}') |
| exit(1) |
|
|
