Update fetch_server_test_models.py

scripts/fetch_server_test_models.py

@@ -1,3 +1,4 @@
+#!/usr/bin/env python
 '''
     This script fetches all the models used in the server tests.
 
@@ -7,13 +8,14 @@
 
     Example:
         python scripts/fetch_server_test_models.py
-        ( cd examples/server/tests && ./tests.sh --tags=slow )
+        ( cd examples/server/tests && ./tests.sh -v -x -m slow )
 '''
-from behave.parser import Parser
+import ast
 import glob
+import logging
 import os
+from typing import Generator
 from pydantic import BaseModel
-import re
 import subprocess
 import sys
 
@@ -26,53 +28,71 @@ class Config:
         frozen = True
 
 
-models = set()
-
-model_file_re = re.compile(r'a model file ([^\s\n\r]+) from HF repo ([^\s\n\r]+)')
-
-
-def process_step(step):
-    if (match := model_file_re.search(step.name)):
-        (hf_file, hf_repo) = match.groups()
-        models.add(HuggingFaceModel(hf_repo=hf_repo, hf_file=hf_file))
-
-
-feature_files = glob.glob(
-    os.path.join(
-        os.path.dirname(__file__),
-        '../examples/server/tests/features/*.feature'))
-
-for feature_file in feature_files:
-    with open(feature_file, 'r') as file:
-        feature = Parser().parse(file.read())
-        if not feature: continue
-
-    if feature.background:
-        for step in feature.background.steps:
-            process_step(step)
-
-    for scenario in feature.walk_scenarios(with_outlines=True):
-        for step in scenario.steps:
-            process_step(step)
-
-cli_path = os.environ.get(
-    'LLAMA_SERVER_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 sorted(list(models), key=lambda m: m.hf_repo):
-    if '<' in m.hf_repo or '<' in m.hf_file:
-        continue
-    if '-of-' in m.hf_file:
-        print(f'# Skipping model at {m.hf_repo} / {m.hf_file} because it is a split file', file=sys.stderr)
-        continue
-    print(f'# Ensuring model at {m.hf_repo} / {m.hf_file} is fetched')
-    cmd = [cli_path, '-hfr', m.hf_repo, '-hff', m.hf_file, '-n', '1', '-p', 'Hey', '--no-warmup', '--log-disable']
-    if m.hf_file != 'tinyllamas/stories260K.gguf' and not m.hf_file.startswith('Mistral-Nemo'):
-        cmd.append('-fa')
+def collect_hf_model_test_parameters(test_file) -> Generator[HuggingFaceModel, None, None]:
     try:
-        subprocess.check_call(cmd)
-    except subprocess.CalledProcessError:
-        print(f'# Failed to fetch model at {m.hf_repo} / {m.hf_file} with command:\n  {" ".join(cmd)}', file=sys.stderr)
-        exit(1)
+        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 not "hf_repo" in param_names or not "hf_file" 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")
+
+                    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 __name__ == '__main__':
+    logging.basicConfig(level=logging.INFO, format='%(levelname)s: %(message)s')
+
+    models = sorted(list(set([
+        model
+        for test_file in glob.glob('examples/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_SERVER_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 '<' in m.hf_file:
+            continue
+        if '-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, '-hff', m.hf_file, '-n', '1', '-p', 'Hey', '--no-warmup', '--log-disable']
+        if m.hf_file != 'tinyllamas/stories260K.gguf' and not m.hf_file.startswith('Mistral-Nemo'):
+            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)