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| #!/usr/bin/env python3 | |
| """ | |
| Tests for scripts/push_to_huggingface.py focusing on model card creation/upload. | |
| We mock Hugging Face Hub interactions and create dummy model folders to verify: | |
| - Repo id resolution via whoami | |
| - Repository creation call | |
| - README.md upload with expected content (fallback simple card path) | |
| - Uploading of model files from the directory | |
| """ | |
| import sys | |
| import types | |
| from pathlib import Path | |
| def _repo_root() -> Path: | |
| return Path(__file__).resolve().parents[1] | |
| def _add_scripts_to_path() -> None: | |
| scripts_dir = _repo_root() / "scripts" | |
| if str(scripts_dir) not in sys.path: | |
| sys.path.insert(0, str(scripts_dir)) | |
| def _make_full_model_dir(base: Path) -> Path: | |
| model_dir = base / "full_model" | |
| model_dir.mkdir(parents=True, exist_ok=True) | |
| (model_dir / "config.json").write_text("{}", encoding="utf-8") | |
| # Create an empty weight file to satisfy validation | |
| (model_dir / "model.safetensors").write_bytes(b"") | |
| return model_dir | |
| def _make_lora_model_dir(base: Path) -> Path: | |
| model_dir = base / "lora_model" | |
| model_dir.mkdir(parents=True, exist_ok=True) | |
| (model_dir / "adapter_config.json").write_text("{}", encoding="utf-8") | |
| (model_dir / "adapter_model.bin").write_bytes(b"\x00") | |
| return model_dir | |
| def test_push_model_card_full_model(monkeypatch, tmp_path): | |
| _add_scripts_to_path() | |
| import push_to_huggingface as mod | |
| # Ensure module thinks HF is available and patch API + functions | |
| monkeypatch.setattr(mod, "HF_AVAILABLE", True, raising=False) | |
| create_repo_calls = [] | |
| upload_file_calls = [] | |
| class DummyHfApi: | |
| def __init__(self, token=None): | |
| self.token = token | |
| def whoami(self): | |
| return {"name": "testuser"} | |
| def fake_create_repo(*, repo_id, token=None, private=False, exist_ok=False, repo_type=None): | |
| create_repo_calls.append({ | |
| "repo_id": repo_id, | |
| "token": token, | |
| "private": private, | |
| "exist_ok": exist_ok, | |
| "repo_type": repo_type, | |
| }) | |
| def fake_upload_file(*, path_or_fileobj, path_in_repo, repo_id, token, repo_type=None): | |
| path = Path(path_or_fileobj) | |
| content = None | |
| if path.exists() and path.is_file(): | |
| try: | |
| content = path.read_text(encoding="utf-8") | |
| except Exception: | |
| content = None | |
| upload_file_calls.append({ | |
| "path_in_repo": path_in_repo, | |
| "repo_id": repo_id, | |
| "token": token, | |
| "repo_type": repo_type, | |
| "content": content, | |
| "local_path": str(path), | |
| }) | |
| monkeypatch.setattr(mod, "HfApi", DummyHfApi, raising=False) | |
| monkeypatch.setattr(mod, "create_repo", fake_create_repo, raising=False) | |
| monkeypatch.setattr(mod, "upload_file", fake_upload_file, raising=False) | |
| # Prepare dummy full model directory | |
| model_dir = _make_full_model_dir(tmp_path) | |
| pusher = mod.HuggingFacePusher( | |
| model_path=str(model_dir), | |
| repo_name="my-repo", | |
| token="fake-token", | |
| private=True, | |
| author_name="Tester", | |
| model_description="Desc", | |
| model_name="BaseModel", | |
| dataset_name="DatasetX", | |
| ) | |
| # Execute push (this should use fallback simple model card) | |
| ok = pusher.push_model( | |
| training_config={"param": 1}, | |
| results={"train_loss": 0.1, "eval_loss": 0.2, "perplexity": 9.9}, | |
| ) | |
| assert ok is True | |
| # Repo creation was called with resolved user prefix | |
| assert any(c["repo_id"] == "testuser/my-repo" for c in create_repo_calls) | |
| # README upload occurred and contains either generator or fallback content (full model) | |
| readme_calls = [c for c in upload_file_calls if c["path_in_repo"] == "README.md"] | |
| assert readme_calls, "README.md was not uploaded" | |
| readme_content = readme_calls[-1]["content"] or "" | |
| assert ( | |
| "fine-tuned Voxtral ASR model" in readme_content | |
| or "SmolLM3" in readme_content | |
| or "Model Details" in readme_content | |
| ) | |
| assert "DatasetX" in readme_content or "Training Configuration" in readme_content | |
| # Model files were uploaded (config and weights) | |
| uploaded_paths = {c["path_in_repo"] for c in upload_file_calls} | |
| assert "config.json" in uploaded_paths | |
| assert "model.safetensors" in uploaded_paths | |
| def test_push_model_card_lora_model_fallback(monkeypatch, tmp_path): | |
| _add_scripts_to_path() | |
| import push_to_huggingface as mod | |
| # Ensure module thinks HF is available and patch API + functions | |
| monkeypatch.setattr(mod, "HF_AVAILABLE", True, raising=False) | |
| upload_file_calls = [] | |
| class DummyHfApi: | |
| def __init__(self, token=None): | |
| self.token = token | |
| def whoami(self): | |
| return {"username": "anotheruser"} | |
| def fake_create_repo(*, repo_id, token=None, private=False, exist_ok=False, repo_type=None): | |
| return None | |
| def fake_upload_file(*, path_or_fileobj, path_in_repo, repo_id, token, repo_type=None): | |
| path = Path(path_or_fileobj) | |
| content = None | |
| if path.exists() and path.is_file(): | |
| try: | |
| content = path.read_text(encoding="utf-8") | |
| except Exception: | |
| content = None | |
| upload_file_calls.append({ | |
| "path_in_repo": path_in_repo, | |
| "repo_id": repo_id, | |
| "content": content, | |
| }) | |
| monkeypatch.setattr(mod, "HfApi", DummyHfApi, raising=False) | |
| monkeypatch.setattr(mod, "create_repo", fake_create_repo, raising=False) | |
| monkeypatch.setattr(mod, "upload_file", fake_upload_file, raising=False) | |
| # Insert a dummy generate_model_card module that raises in generate to force fallback | |
| dummy_mod = types.ModuleType("generate_model_card") | |
| class RaisingGen: | |
| def __init__(self, *args, **kwargs): | |
| pass | |
| def generate_model_card(self, variables): | |
| raise RuntimeError("force fallback") | |
| def default_vars(): | |
| return {} | |
| dummy_mod.ModelCardGenerator = RaisingGen | |
| dummy_mod.create_default_variables = default_vars | |
| sys.modules["generate_model_card"] = dummy_mod | |
| # Prepare dummy lora model directory | |
| model_dir = _make_lora_model_dir(tmp_path) | |
| pusher = mod.HuggingFacePusher( | |
| model_path=str(model_dir), | |
| repo_name="my-lora-repo", | |
| token="fake-token", | |
| private=False, | |
| author_name="Tester", | |
| model_description="Desc", | |
| model_name="BaseModel", | |
| dataset_name="DatasetY", | |
| ) | |
| ok = pusher.push_model(training_config={}, results={}) | |
| assert ok is True | |
| # README upload occurred and contains either generator or fallback content (LoRA) | |
| readme_calls = [c for c in upload_file_calls if c["path_in_repo"] == "README.md"] | |
| assert readme_calls, "README.md was not uploaded" | |
| readme_content = readme_calls[-1]["content"] or "" | |
| assert ( | |
| "LoRA adapter for Voxtral ASR" in readme_content | |
| or "SmolLM3" in readme_content | |
| or "Model Details" in readme_content | |
| ) | |
| assert "DatasetY" in readme_content or "Training Configuration" in readme_content | |
| # LoRA files uploaded | |
| uploaded_paths = {Path(c.get("local_path", "")).name for c in upload_file_calls if c.get("local_path")} | |
| assert any(name.startswith("adapter_") for name in uploaded_paths) | |