Update fetch_server_test_models.py
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1 changed files with 72 additions and 52 deletions
82
scripts/fetch_server_test_models.py
Normal file → Executable file
82
scripts/fetch_server_test_models.py
Normal file → Executable file
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@ -1,3 +1,4 @@
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#!/usr/bin/env python
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'''
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This script fetches all the models used in the server tests.
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@ -7,13 +8,14 @@
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Example:
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python scripts/fetch_server_test_models.py
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( cd examples/server/tests && ./tests.sh --tags=slow )
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( cd examples/server/tests && ./tests.sh -v -x -m slow )
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'''
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from behave.parser import Parser
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import ast
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import glob
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import logging
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import os
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from typing import Generator
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from pydantic import BaseModel
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import re
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import subprocess
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import sys
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@ -26,53 +28,71 @@ class HuggingFaceModel(BaseModel):
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frozen = True
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models = set()
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def collect_hf_model_test_parameters(test_file) -> Generator[HuggingFaceModel, None, None]:
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try:
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with open(test_file) as f:
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tree = ast.parse(f.read())
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except Exception as e:
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logging.error(f'collect_hf_model_test_parameters failed on {test_file}: {e}')
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return
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model_file_re = re.compile(r'a model file ([^\s\n\r]+) from HF repo ([^\s\n\r]+)')
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for node in ast.walk(tree):
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if isinstance(node, ast.FunctionDef):
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for dec in node.decorator_list:
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if isinstance(dec, ast.Call) and isinstance(dec.func, ast.Attribute) and dec.func.attr == 'parametrize':
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param_names = ast.literal_eval(dec.args[0]).split(",")
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if not "hf_repo" in param_names or not "hf_file" in param_names:
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continue
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raw_param_values = dec.args[1]
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if not isinstance(raw_param_values, ast.List):
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logging.warning(f'Skipping non-list parametrize entry at {test_file}:{node.lineno}')
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continue
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hf_repo_idx = param_names.index("hf_repo")
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hf_file_idx = param_names.index("hf_file")
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for t in raw_param_values.elts:
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if not isinstance(t, ast.Tuple):
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logging.warning(f'Skipping non-tuple parametrize entry at {test_file}:{node.lineno}')
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continue
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yield HuggingFaceModel(
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hf_repo=ast.literal_eval(t.elts[hf_repo_idx]),
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hf_file=ast.literal_eval(t.elts[hf_file_idx]))
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def process_step(step):
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if (match := model_file_re.search(step.name)):
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(hf_file, hf_repo) = match.groups()
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models.add(HuggingFaceModel(hf_repo=hf_repo, hf_file=hf_file))
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if __name__ == '__main__':
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logging.basicConfig(level=logging.INFO, format='%(levelname)s: %(message)s')
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models = sorted(list(set([
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model
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for test_file in glob.glob('examples/server/tests/unit/test_*.py')
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for model in collect_hf_model_test_parameters(test_file)
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])), key=lambda m: (m.hf_repo, m.hf_file))
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feature_files = glob.glob(
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os.path.join(
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os.path.dirname(__file__),
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'../examples/server/tests/features/*.feature'))
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for feature_file in feature_files:
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with open(feature_file, 'r') as file:
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feature = Parser().parse(file.read())
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if not feature: continue
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if feature.background:
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for step in feature.background.steps:
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process_step(step)
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for scenario in feature.walk_scenarios(with_outlines=True):
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for step in scenario.steps:
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process_step(step)
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logging.info(f'Found {len(models)} models in parameterized tests:')
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for m in models:
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logging.info(f' - {m.hf_repo} / {m.hf_file}')
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cli_path = os.environ.get(
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'LLAMA_SERVER_BIN_PATH',
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os.path.join(
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os.path.dirname(__file__),
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'../build/bin/Release/llama-cli.exe' if os.name == 'nt' else '../build/bin/llama-cli'))
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'../build/bin/Release/llama-cli.exe' if os.name == 'nt' \
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else '../build/bin/llama-cli'))
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for m in sorted(list(models), key=lambda m: m.hf_repo):
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for m in models:
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if '<' in m.hf_repo or '<' in m.hf_file:
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continue
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if '-of-' in m.hf_file:
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print(f'# Skipping model at {m.hf_repo} / {m.hf_file} because it is a split file', file=sys.stderr)
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logging.warning(f'Skipping model at {m.hf_repo} / {m.hf_file} because it is a split file')
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continue
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print(f'# Ensuring model at {m.hf_repo} / {m.hf_file} is fetched')
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logging.info(f'Using llama-cli to ensure model {m.hf_repo}/{m.hf_file} was fetched')
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cmd = [cli_path, '-hfr', m.hf_repo, '-hff', m.hf_file, '-n', '1', '-p', 'Hey', '--no-warmup', '--log-disable']
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if m.hf_file != 'tinyllamas/stories260K.gguf' and not m.hf_file.startswith('Mistral-Nemo'):
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cmd.append('-fa')
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try:
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subprocess.check_call(cmd)
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except subprocess.CalledProcessError:
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print(f'# Failed to fetch model at {m.hf_repo} / {m.hf_file} with command:\n {" ".join(cmd)}', file=sys.stderr)
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logging.error(f'Failed to fetch model at {m.hf_repo} / {m.hf_file} with command:\n {" ".join(cmd)}')
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exit(1)
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