* tests: read checked-in files as UTF-8 instead of the platform default Path.read_text() with no encoding uses locale.getpreferredencoding(), which is UTF-8 on the Linux runners and cp1252 on a stock Windows install. Nine module-level reads of checked-in source files were relying on that default. studio/backend/routes/inference.py carries the DeepSeek tool-call token regexes, so it holds U+FF5C and U+2581. Under cp1252 that read raised UnicodeDecodeError on byte 0x81 at position 97806, and because the reads run at import time it took test_cancel_atomicity.py and test_cancel_id_wiring.py out at collection, not as failures. Green on CI, permanently broken for a Windows contributor running the suite locally. Adds a guard: at module scope there is no tmp_path fixture, so a bare read_text()/write_text()/open() there is always touching a checked-in file. That makes the rule mechanical enough to enforce with no allowlist, while staying quiet about temp-dir I/O inside test bodies where the platform default is harmless. The repo already spells this correctly in 464 other places; this only stops the stragglers coming back. * tests: cover import-time helper reads and keep the guard py3.9-safe Follows up on the Codex review: - add `from __future__ import annotations`, since `str | None` in `_offender` is evaluated at import on Python 3.9 and pyproject declares requires-python ">=3.9,<3.15". - widen the guard from module scope to import time. Class bodies and the bodies of module-level helpers called from an executing statement run during collection too, so `CODE = _extract_mixed_precision_code()` was the same hazard as an inline read. `if __name__ == "__main__":` blocks are skipped: pytest never executes them. - scan studio/backend/tests/ as well as tests/. Both trees are collected on Windows by separate CI jobs, and the offender that started this, test_tool_xml_strip.py reading routes/inference.py, lives there. Widening it surfaced seven more import-time reads of checked-in sources; all now name utf-8. * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Harden the import-time encoding guard for PR #7438 Close the detector gaps raised in review, all of which I reproduced against the actual AST before changing anything. False negatives (the guard let a real hazard through): - _is_main_guard ignored the comparison operator, so if __name__ != "__main__" counted as script-only even though its body runs at import. - The else arm of a main guard was discarded with the rest of the If node. - Decorators and argument defaults on a module-level def were skipped with the body, though both are evaluated when the def executes. - Path.open() in text mode was invisible; only builtin open() was matched. - encoding = None and encoding = "locale" both re-select the platform default, but the keyword merely being present counted as pinned. False positives (the guard would have blocked a compliant contributor): - A non-literal mode fell through to the "r" default, so open(p, mode) was flagged even when mode is "rb", where adding encoding= is a ValueError and there is no edit that satisfies the rule. - Same for open(*args) and a **kwargs splat, which hide the mode and can hide an encoding. - Lambda bodies and comprehension elements were walked even though neither runs at definition. Verified: still reports the same 22 offenders on unpatched main, green on this branch and on the tree merged with latest main (557 files), and an adversarial corpus of 33 cases now scores zero false positives and zero false negatives. Also corrected two docstring claims: neither collecting job runs on Windows, and the read is governed by locale.getencoding(). * Walk eager comprehensions and treat io.open as the builtin Two regressions from the previous commit, both reproduced against the AST before changing anything. Lumping list, set and dict comprehensions in with generator expressions was wrong. Only a genexp is lazy; the other three run their element expression, their filters and their nested iterators immediately, so CONTENTS = [p.read_text() for p in PATHS] at module scope is an import-time read the guard was silently missing. Comprehensions are now walked in full and only the genexp keeps the outermost-iterable-only treatment. io was also in the not-a-path-opener list, but io.open is the builtin, with the same mode position and the same platform default. io.open(CHECKED_IN_FILE) is exactly the hazard this guard exists for, so it is matched now, with binary modes and a pinned encoding still exempt. tarfile.open and fitz.open stay exempt since neither has an encoding to name. Verified: 13 targeted cases covering all five eager comprehension forms and io.open in text, binary and pinned shapes all classify correctly; still 22 offenders on unpatched main; green on this branch and on the tree merged with latest main. * Close three more walker gaps in the import-time guard All three reproduced against the AST first. A generator expression handed straight to a call is consumed there, so DATA = "".join(p.read_text() for p in paths) runs its element at import. Only an unconsumed genexp bound to a name stays lazy, so the walker now follows the consumed ones in full and keeps the outermost-iterable-only treatment for the rest. if "__main__" == __name__ is an equivalent and accepted spelling of the main guard, but requiring __name__ on the left meant its body was treated as import-time code. That is a false positive on a block pytest never runs, so both operand orders are recognised now. The helper table was built from module-level defs only, so a def in a class body invoked while the class is constructed was never followed, contradicting the walker's stated coverage of class bodies. Helpers are now collected from the module body and from class bodies at any nesting. Verified: 15 targeted cases including all three fixes and the earlier ones still classify correctly; still 22 offenders on unpatched main; green on this branch and on the tree merged with latest main. * Handle positional read_text encodings, lazy generators and nested helpers * Guard reads reached from test bodies, unbound Path calls and __file__ paths * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Follow derived paths, skip lazy generator helpers, cover compressed openers * Guard the CLI tests, helper parameters and unbound Path arguments * Discover test roots and follow literal, in-place and tuple-derived paths * Identify module openers by import, unwrap starred paths, pin subprocess snippets * Resolve import origins, seed helper locals, follow named generators and parametrize * Scope imports lexically, list tracked test files, bind unpacked names * Resolve aliased openers, keyword-only params, destructured targets, next() * Pin the encoding on subprocess snippets, workflow lint and CLI output for PR #7438 * Harden the CLI encoding guard against detached streams for PR #7438 * Tighten the encoding guard's path and scope analysis for PR #7438 * Resolve path provenance more precisely and keep POSIX stream encodings for PR #7438 * Resolve qualified path classes and scope conditional imports for PR #7438 * Scope CLI stream setup to the entry point and align two encoding pairs for PR #7438 --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: danielhanchen <danielhanchen@gmail.com>
1129 lines
43 KiB
Python
1129 lines
43 KiB
Python
"""E2E sandbox tests for PR #4624: lazy torch imports, CPU fallback, install.sh parsing, NO_TORCH filtering, live server."""
|
|
|
|
from __future__ import annotations
|
|
|
|
import os
|
|
import shutil
|
|
import signal
|
|
import subprocess
|
|
import sys
|
|
import textwrap
|
|
import time
|
|
from pathlib import Path
|
|
from unittest import mock
|
|
|
|
import pytest
|
|
|
|
REPO_ROOT = Path(__file__).resolve().parents[2]
|
|
STUDIO_DIR = REPO_ROOT / "studio"
|
|
BACKEND_DIR = STUDIO_DIR / "backend"
|
|
DATASETS_DIR = BACKEND_DIR / "utils" / "datasets"
|
|
HARDWARE_DIR = BACKEND_DIR / "utils" / "hardware"
|
|
INSTALL_SH = REPO_ROOT / "install.sh"
|
|
INSTALL_PY = STUDIO_DIR / "install_python_stack.py"
|
|
|
|
DATA_COLLATORS = DATASETS_DIR / "data_collators.py"
|
|
CHAT_TEMPLATES = DATASETS_DIR / "chat_templates.py"
|
|
FORMAT_DETECTION = DATASETS_DIR / "format_detection.py"
|
|
MODEL_MAPPINGS = DATASETS_DIR / "model_mappings.py"
|
|
VLM_PROCESSING = DATASETS_DIR / "vlm_processing.py"
|
|
ITERABLE = DATASETS_DIR / "iterable.py"
|
|
HARDWARE_PY = HARDWARE_DIR / "hardware.py"
|
|
|
|
# Unsloth venv for server tests
|
|
STUDIO_VENV = Path.home() / ".unsloth" / "studio" / "unsloth_studio"
|
|
|
|
sys.path.insert(0, str(STUDIO_DIR))
|
|
|
|
|
|
def _venv_python(venv_dir: Path) -> Path:
|
|
"""Return a venv's Python executable path, cross-platform."""
|
|
if sys.platform == "win32":
|
|
return venv_dir / "Scripts" / "python.exe"
|
|
return venv_dir / "bin" / "python"
|
|
|
|
|
|
def _has_uv() -> bool:
|
|
return shutil.which("uv") is not None
|
|
|
|
|
|
def _create_no_torch_venv(venv_dir: Path, python_version: str = "3.12") -> Path | None:
|
|
"""Create a uv venv with no torch. Returns python path or None."""
|
|
result = subprocess.run(
|
|
["uv", "venv", str(venv_dir), "--python", python_version],
|
|
capture_output = True,
|
|
)
|
|
if result.returncode != 0:
|
|
return None
|
|
py = _venv_python(venv_dir)
|
|
if not py.exists():
|
|
return None
|
|
check = subprocess.run([str(py), "-c", "import torch"], capture_output = True)
|
|
if check.returncode == 0:
|
|
return None
|
|
return py
|
|
|
|
|
|
def _run_in_sandbox(
|
|
py: str | Path,
|
|
code: str,
|
|
timeout: int = 60,
|
|
env: dict | None = None,
|
|
) -> subprocess.CompletedProcess:
|
|
"""Run Python code in a sandboxed interpreter."""
|
|
return subprocess.run(
|
|
[str(py), "-c", code],
|
|
capture_output = True,
|
|
timeout = timeout,
|
|
env = env,
|
|
)
|
|
|
|
|
|
def _run_sh(script: str, timeout: int = 30) -> subprocess.CompletedProcess:
|
|
"""Run a bash snippet and return the result."""
|
|
return subprocess.run(
|
|
["bash", "-c", script],
|
|
capture_output = True,
|
|
timeout = timeout,
|
|
)
|
|
|
|
|
|
def _write_loggers_stub(sandbox: Path) -> None:
|
|
"""Create a minimal loggers package stub (replaces the structlog-backed real one)."""
|
|
loggers_dir = sandbox / "loggers"
|
|
loggers_dir.mkdir(exist_ok = True)
|
|
(loggers_dir / "__init__.py").write_text(
|
|
"from .handlers import get_logger\n__all__ = ['get_logger']\n",
|
|
encoding = "utf-8",
|
|
)
|
|
(loggers_dir / "handlers.py").write_text(
|
|
textwrap.dedent("""\
|
|
class _Logger:
|
|
def info(self, msg, *a, **k): pass
|
|
def warning(self, msg, *a, **k): pass
|
|
def debug(self, msg, *a, **k): pass
|
|
def error(self, msg, *a, **k): pass
|
|
def msg(self, msg, *a, **k): pass
|
|
def get_logger(name=None):
|
|
return _Logger()
|
|
"""),
|
|
encoding = "utf-8",
|
|
)
|
|
|
|
|
|
def _write_structlog_stub(sandbox: Path) -> None:
|
|
"""Create a minimal structlog stub."""
|
|
structlog_dir = sandbox / "structlog"
|
|
structlog_dir.mkdir(exist_ok = True)
|
|
(structlog_dir / "__init__.py").write_text(
|
|
textwrap.dedent("""\
|
|
class _Logger:
|
|
def info(self, msg, *a, **k): pass
|
|
def warning(self, msg, *a, **k): pass
|
|
def debug(self, msg, *a, **k): pass
|
|
def error(self, msg, *a, **k): pass
|
|
def msg(self, msg, *a, **k): pass
|
|
def get_logger(name=None):
|
|
return _Logger()
|
|
"""),
|
|
encoding = "utf-8",
|
|
)
|
|
|
|
|
|
def _write_hardware_stub(sandbox: Path) -> None:
|
|
"""Create utils/hardware stub with dataset_map_num_proc."""
|
|
hw_dir = sandbox / "utils" / "hardware"
|
|
hw_dir.mkdir(parents = True, exist_ok = True)
|
|
(sandbox / "utils" / "__init__.py").write_text("", encoding = "utf-8")
|
|
(hw_dir / "__init__.py").write_text(
|
|
"def dataset_map_num_proc(n=None): return n\n",
|
|
encoding = "utf-8",
|
|
)
|
|
|
|
|
|
@pytest.fixture(scope = "session")
|
|
def repo_root():
|
|
return REPO_ROOT
|
|
|
|
|
|
@pytest.fixture
|
|
def sandbox_dir(tmp_path):
|
|
"""Per-test temporary sandbox directory."""
|
|
return tmp_path
|
|
|
|
|
|
@pytest.fixture(params = ["3.12", "3.13"], scope = "module")
|
|
def no_torch_venv(request, tmp_path_factory):
|
|
"""Temporary uv venv with no torch; 3.12 = Intel Mac default, 3.13 = Apple Silicon/Linux."""
|
|
if not _has_uv():
|
|
pytest.skip("uv not available")
|
|
|
|
py_version = request.param
|
|
venv_dir = tmp_path_factory.mktemp(f"e2e_no_torch_{py_version}")
|
|
py = _create_no_torch_venv(venv_dir, py_version)
|
|
if py is None:
|
|
pytest.skip(f"Could not create Python {py_version} no-torch venv")
|
|
return str(py)
|
|
|
|
|
|
# Group 1: BEFORE vs AFTER -- Import Chain
|
|
|
|
|
|
class TestBeforeAfterImportChain:
|
|
"""BEFORE (synthetic top-level torch import) crashes; AFTER (lazy imports) works."""
|
|
|
|
# -- BEFORE: crashes --
|
|
|
|
def test_before_chat_templates_crashes(self, no_torch_venv, sandbox_dir):
|
|
"""BEFORE: chat_templates.py with top-level IterableDataset import crashes without torch."""
|
|
source = CHAT_TEMPLATES.read_text(encoding = "utf-8")
|
|
before_source = "from torch.utils.data import IterableDataset\n" + source
|
|
|
|
before_file = sandbox_dir / "chat_templates_before.py"
|
|
before_file.write_text(before_source, encoding = "utf-8")
|
|
|
|
code = textwrap.dedent(f"""\
|
|
import sys, types
|
|
loggers = types.ModuleType('loggers')
|
|
loggers.get_logger = lambda n: type('L', (), {{'info': lambda s, m: None}})()
|
|
sys.modules['loggers'] = loggers
|
|
fd = types.ModuleType('format_detection')
|
|
fd.detect_dataset_format = fd.detect_multimodal_dataset = fd.detect_custom_format_heuristic = lambda *a, **k: None
|
|
sys.modules['format_detection'] = fd
|
|
mm = types.ModuleType('model_mappings')
|
|
mm.MODEL_TO_TEMPLATE_MAPPER = {{}}
|
|
sys.modules['model_mappings'] = mm
|
|
source = open({str(before_file)!r}, encoding = "utf-8").read()
|
|
source = source.replace('from .format_detection import', 'from format_detection import')
|
|
source = source.replace('from .model_mappings import', 'from model_mappings import')
|
|
exec(source)
|
|
""")
|
|
result = _run_in_sandbox(no_torch_venv, code)
|
|
assert result.returncode != 0, "BEFORE chat_templates.py should crash without torch"
|
|
assert b"ModuleNotFoundError" in result.stderr or b"ImportError" in result.stderr
|
|
|
|
def test_before_data_collators_crashes(self, no_torch_venv, sandbox_dir):
|
|
"""BEFORE: data_collators.py with top-level 'import torch' crashes."""
|
|
source = DATA_COLLATORS.read_text(encoding = "utf-8")
|
|
before_source = "import torch\n" + source
|
|
|
|
before_file = sandbox_dir / "data_collators_before.py"
|
|
before_file.write_text(before_source, encoding = "utf-8")
|
|
|
|
code = textwrap.dedent(f"""\
|
|
import sys, types
|
|
loggers = types.ModuleType('loggers')
|
|
loggers.get_logger = lambda n: None
|
|
sys.modules['loggers'] = loggers
|
|
exec(open({str(before_file)!r}, encoding = "utf-8").read())
|
|
""")
|
|
result = _run_in_sandbox(no_torch_venv, code)
|
|
assert result.returncode != 0, "BEFORE data_collators.py should crash without torch"
|
|
assert b"ModuleNotFoundError" in result.stderr or b"ImportError" in result.stderr
|
|
|
|
def test_before_full_import_chain_crashes(self, no_torch_venv, sandbox_dir):
|
|
"""BEFORE: full utils/datasets/ package with top-level torch imports crashes."""
|
|
_write_loggers_stub(sandbox_dir)
|
|
_write_hardware_stub(sandbox_dir)
|
|
|
|
pkg_dir = sandbox_dir / "utils" / "datasets"
|
|
pkg_dir.mkdir(parents = True, exist_ok = True)
|
|
|
|
# Copy torch-free modules as-is
|
|
shutil.copy2(FORMAT_DETECTION, pkg_dir / "format_detection.py")
|
|
shutil.copy2(MODEL_MAPPINGS, pkg_dir / "model_mappings.py")
|
|
shutil.copy2(VLM_PROCESSING, pkg_dir / "vlm_processing.py")
|
|
|
|
# BEFORE data_collators: prepend top-level 'import torch'
|
|
dc_source = DATA_COLLATORS.read_text(encoding = "utf-8")
|
|
(pkg_dir / "data_collators.py").write_text(
|
|
"import torch\n" + dc_source,
|
|
encoding = "utf-8",
|
|
)
|
|
|
|
# BEFORE chat_templates: prepend top-level IterableDataset import
|
|
ct_source = CHAT_TEMPLATES.read_text(encoding = "utf-8")
|
|
(pkg_dir / "chat_templates.py").write_text(
|
|
"from torch.utils.data import IterableDataset\n" + ct_source,
|
|
encoding = "utf-8",
|
|
)
|
|
|
|
(pkg_dir / "__init__.py").write_text(
|
|
textwrap.dedent("""\
|
|
from .format_detection import detect_dataset_format
|
|
from .data_collators import DataCollatorSpeechSeq2SeqWithPadding
|
|
from .chat_templates import DEFAULT_ALPACA_TEMPLATE
|
|
"""),
|
|
encoding = "utf-8",
|
|
)
|
|
|
|
code = textwrap.dedent(f"""\
|
|
import sys
|
|
sys.path.insert(0, {str(sandbox_dir)!r})
|
|
from utils.datasets import detect_dataset_format
|
|
""")
|
|
result = _run_in_sandbox(no_torch_venv, code)
|
|
assert result.returncode != 0, "BEFORE full import chain should crash without torch"
|
|
assert b"ModuleNotFoundError" in result.stderr or b"ImportError" in result.stderr
|
|
|
|
# -- AFTER: succeeds --
|
|
|
|
def test_after_chat_templates_imports(self, no_torch_venv):
|
|
"""AFTER: PR branch chat_templates.py imports fine without torch."""
|
|
code = textwrap.dedent(f"""\
|
|
import sys, types
|
|
loggers = types.ModuleType('loggers')
|
|
loggers.get_logger = lambda n: type('L', (), {{'info': lambda s, m: None}})()
|
|
sys.modules['loggers'] = loggers
|
|
fd = types.ModuleType('format_detection')
|
|
fd.detect_dataset_format = fd.detect_multimodal_dataset = fd.detect_custom_format_heuristic = lambda *a, **k: None
|
|
sys.modules['format_detection'] = fd
|
|
mm = types.ModuleType('model_mappings')
|
|
mm.MODEL_TO_TEMPLATE_MAPPER = {{}}
|
|
sys.modules['model_mappings'] = mm
|
|
it = types.ModuleType('iterable')
|
|
it.is_streaming_dataset = lambda *a, **k: False
|
|
sys.modules['iterable'] = it
|
|
source = open({str(CHAT_TEMPLATES)!r}, encoding = "utf-8").read()
|
|
source = source.replace('from .format_detection import', 'from format_detection import')
|
|
source = source.replace('from .model_mappings import', 'from model_mappings import')
|
|
source = source.replace('from .iterable import', 'from iterable import')
|
|
exec(source)
|
|
print("OK")
|
|
""")
|
|
result = _run_in_sandbox(no_torch_venv, code)
|
|
assert (
|
|
result.returncode == 0
|
|
), f"AFTER chat_templates.py should work without torch:\n{result.stderr.decode()}"
|
|
assert b"OK" in result.stdout
|
|
|
|
def test_after_data_collators_imports(self, no_torch_venv):
|
|
"""AFTER: PR branch data_collators.py imports fine without torch."""
|
|
code = textwrap.dedent(f"""\
|
|
import sys, types
|
|
loggers = types.ModuleType('loggers')
|
|
loggers.get_logger = lambda n: None
|
|
sys.modules['loggers'] = loggers
|
|
exec(open({str(DATA_COLLATORS)!r}, encoding = "utf-8").read())
|
|
print("OK")
|
|
""")
|
|
result = _run_in_sandbox(no_torch_venv, code)
|
|
assert (
|
|
result.returncode == 0
|
|
), f"AFTER data_collators.py should work without torch:\n{result.stderr.decode()}"
|
|
assert b"OK" in result.stdout
|
|
|
|
def test_after_full_import_chain_imports(self, no_torch_venv, sandbox_dir):
|
|
"""AFTER: full utils/datasets/ package imports fine without torch."""
|
|
_write_loggers_stub(sandbox_dir)
|
|
_write_hardware_stub(sandbox_dir)
|
|
|
|
pkg_dir = sandbox_dir / "utils" / "datasets"
|
|
pkg_dir.mkdir(parents = True, exist_ok = True)
|
|
|
|
# Copy AFTER versions (PR branch -- no top-level torch)
|
|
for src in [
|
|
FORMAT_DETECTION,
|
|
MODEL_MAPPINGS,
|
|
VLM_PROCESSING,
|
|
DATA_COLLATORS,
|
|
CHAT_TEMPLATES,
|
|
ITERABLE,
|
|
]:
|
|
if src.exists():
|
|
shutil.copy2(src, pkg_dir / src.name)
|
|
|
|
(pkg_dir / "__init__.py").write_text(
|
|
textwrap.dedent("""\
|
|
from .format_detection import detect_dataset_format, detect_custom_format_heuristic
|
|
from .model_mappings import MODEL_TO_TEMPLATE_MAPPER
|
|
from .chat_templates import DEFAULT_ALPACA_TEMPLATE, get_dataset_info_summary
|
|
from .data_collators import (
|
|
DataCollatorSpeechSeq2SeqWithPadding,
|
|
DeepSeekOCRDataCollator,
|
|
VLMDataCollator,
|
|
)
|
|
from .vlm_processing import generate_smart_vlm_instruction
|
|
"""),
|
|
encoding = "utf-8",
|
|
)
|
|
|
|
code = textwrap.dedent(f"""\
|
|
import sys
|
|
sys.path.insert(0, {str(sandbox_dir)!r})
|
|
from utils.datasets import (
|
|
detect_dataset_format,
|
|
DEFAULT_ALPACA_TEMPLATE,
|
|
DataCollatorSpeechSeq2SeqWithPadding,
|
|
DeepSeekOCRDataCollator,
|
|
VLMDataCollator,
|
|
generate_smart_vlm_instruction,
|
|
)
|
|
assert 'Instruction' in DEFAULT_ALPACA_TEMPLATE
|
|
print("OK: full import chain succeeded")
|
|
""")
|
|
result = _run_in_sandbox(no_torch_venv, code)
|
|
assert (
|
|
result.returncode == 0
|
|
), f"AFTER full import chain should work:\n{result.stderr.decode()}"
|
|
assert b"OK: full import chain succeeded" in result.stdout
|
|
|
|
|
|
# Group 2: Dataclass Instantiation
|
|
|
|
|
|
class TestDataclassInstantiation:
|
|
"""Dataclass collators instantiate and constants are accessible without torch."""
|
|
|
|
def test_speech_collator_instantiate(self, no_torch_venv):
|
|
"""DataCollatorSpeechSeq2SeqWithPadding(processor=None) succeeds."""
|
|
code = textwrap.dedent(f"""\
|
|
import sys, types
|
|
loggers = types.ModuleType('loggers')
|
|
loggers.get_logger = lambda n: None
|
|
sys.modules['loggers'] = loggers
|
|
exec(open({str(DATA_COLLATORS)!r}, encoding = "utf-8").read())
|
|
obj = DataCollatorSpeechSeq2SeqWithPadding(processor=None)
|
|
assert obj.processor is None
|
|
print("OK")
|
|
""")
|
|
result = _run_in_sandbox(no_torch_venv, code)
|
|
assert result.returncode == 0, f"Failed:\n{result.stderr.decode()}"
|
|
|
|
def test_deepseek_ocr_collator_instantiate(self, no_torch_venv):
|
|
"""DeepSeekOCRDataCollator has correct default field values."""
|
|
code = textwrap.dedent(f"""\
|
|
import sys, types
|
|
loggers = types.ModuleType('loggers')
|
|
loggers.get_logger = lambda n: None
|
|
sys.modules['loggers'] = loggers
|
|
exec(open({str(DATA_COLLATORS)!r}, encoding = "utf-8").read())
|
|
obj = DeepSeekOCRDataCollator(processor=None)
|
|
assert obj.processor is None
|
|
assert obj.max_length == 2048
|
|
assert obj.ignore_index == -100
|
|
print("OK")
|
|
""")
|
|
result = _run_in_sandbox(no_torch_venv, code)
|
|
assert result.returncode == 0, f"Failed:\n{result.stderr.decode()}"
|
|
|
|
def test_vlm_collator_instantiate(self, no_torch_venv):
|
|
"""VLMDataCollator has correct default field values."""
|
|
code = textwrap.dedent(f"""\
|
|
import sys, types
|
|
loggers = types.ModuleType('loggers')
|
|
loggers.get_logger = lambda n: None
|
|
sys.modules['loggers'] = loggers
|
|
exec(open({str(DATA_COLLATORS)!r}, encoding = "utf-8").read())
|
|
obj = VLMDataCollator(processor=None)
|
|
assert obj.processor is None
|
|
assert obj.max_length == 2048
|
|
assert obj.mask_input_tokens is True
|
|
print("OK")
|
|
""")
|
|
result = _run_in_sandbox(no_torch_venv, code)
|
|
assert result.returncode == 0, f"Failed:\n{result.stderr.decode()}"
|
|
|
|
def test_alpaca_template_accessible(self, no_torch_venv):
|
|
"""DEFAULT_ALPACA_TEMPLATE constant is accessible and contains 'Instruction'."""
|
|
code = textwrap.dedent(f"""\
|
|
import sys, types
|
|
loggers = types.ModuleType('loggers')
|
|
loggers.get_logger = lambda n: type('L', (), {{'info': lambda s, m: None}})()
|
|
sys.modules['loggers'] = loggers
|
|
fd = types.ModuleType('format_detection')
|
|
fd.detect_dataset_format = fd.detect_multimodal_dataset = fd.detect_custom_format_heuristic = lambda *a, **k: None
|
|
sys.modules['format_detection'] = fd
|
|
mm = types.ModuleType('model_mappings')
|
|
mm.MODEL_TO_TEMPLATE_MAPPER = {{}}
|
|
sys.modules['model_mappings'] = mm
|
|
it = types.ModuleType('iterable')
|
|
it.is_streaming_dataset = lambda *a, **k: False
|
|
sys.modules['iterable'] = it
|
|
ns = {{}}
|
|
source = open({str(CHAT_TEMPLATES)!r}, encoding = "utf-8").read()
|
|
source = source.replace('from .format_detection import', 'from format_detection import')
|
|
source = source.replace('from .model_mappings import', 'from model_mappings import')
|
|
source = source.replace('from .iterable import', 'from iterable import')
|
|
exec(source, ns)
|
|
assert 'Instruction' in ns['DEFAULT_ALPACA_TEMPLATE']
|
|
print("OK")
|
|
""")
|
|
result = _run_in_sandbox(no_torch_venv, code)
|
|
assert result.returncode == 0, f"Failed:\n{result.stderr.decode()}"
|
|
|
|
|
|
# Group 3: Edge Cases -- Partial/Broken Torch
|
|
|
|
|
|
class TestEdgeCasesBrokenTorch:
|
|
"""Behavior with fake or broken torch modules on sys.path."""
|
|
|
|
def test_fake_broken_torch_module(self, no_torch_venv, sandbox_dir):
|
|
"""Fake torch raising RuntimeError on import: data_collators.py (no top-level torch) still loads."""
|
|
torch_dir = sandbox_dir / "torch"
|
|
torch_dir.mkdir()
|
|
(torch_dir / "__init__.py").write_text(
|
|
'raise RuntimeError("CUDA not found")\n',
|
|
encoding = "utf-8",
|
|
)
|
|
_write_loggers_stub(sandbox_dir)
|
|
shutil.copy2(DATA_COLLATORS, sandbox_dir / "data_collators.py")
|
|
|
|
code = textwrap.dedent(f"""\
|
|
import sys
|
|
sys.path.insert(0, {str(sandbox_dir)!r})
|
|
exec(open({str(sandbox_dir / 'data_collators.py')!r}, encoding = "utf-8").read())
|
|
obj = DataCollatorSpeechSeq2SeqWithPadding(processor=None)
|
|
print("OK: data_collators works despite broken torch on sys.path")
|
|
""")
|
|
result = _run_in_sandbox(no_torch_venv, code)
|
|
assert result.returncode == 0, f"Should work with broken torch:\n{result.stderr.decode()}"
|
|
assert b"OK:" in result.stdout
|
|
|
|
def test_torch_import_error_hardware_fallback(self, no_torch_venv, sandbox_dir):
|
|
"""Fake torch raising ImportError: detect_hardware() falls back to CPU."""
|
|
torch_dir = sandbox_dir / "torch"
|
|
torch_dir.mkdir()
|
|
(torch_dir / "__init__.py").write_text(
|
|
'raise ImportError("No torch binary")\n',
|
|
encoding = "utf-8",
|
|
)
|
|
_write_loggers_stub(sandbox_dir)
|
|
_write_structlog_stub(sandbox_dir)
|
|
|
|
code = textwrap.dedent(f"""\
|
|
import sys
|
|
sys.path.insert(0, {str(sandbox_dir)!r})
|
|
source = open({str(HARDWARE_PY)!r}, encoding = "utf-8").read()
|
|
ns = {{'__name__': '__test__'}}
|
|
exec(source, ns)
|
|
result = ns['detect_hardware']()
|
|
assert result == ns['DeviceType'].CPU, f"Expected CPU, got {{result}}"
|
|
print("OK: detect_hardware returned CPU")
|
|
""")
|
|
result = _run_in_sandbox(no_torch_venv, code)
|
|
assert (
|
|
result.returncode == 0
|
|
), f"detect_hardware should fallback to CPU:\n{result.stderr.decode()}"
|
|
assert b"OK: detect_hardware returned CPU" in result.stdout
|
|
|
|
def test_fake_torch_no_cuda(self, no_torch_venv, sandbox_dir):
|
|
"""Fake torch imports OK but cuda.is_available() is False: detect_hardware() falls back to CPU."""
|
|
torch_dir = sandbox_dir / "torch"
|
|
torch_dir.mkdir()
|
|
(torch_dir / "__init__.py").write_text(
|
|
textwrap.dedent("""\
|
|
class _Cuda:
|
|
@staticmethod
|
|
def is_available():
|
|
return False
|
|
cuda = _Cuda()
|
|
class version:
|
|
cuda = None
|
|
"""),
|
|
encoding = "utf-8",
|
|
)
|
|
_write_loggers_stub(sandbox_dir)
|
|
_write_structlog_stub(sandbox_dir)
|
|
|
|
code = textwrap.dedent(f"""\
|
|
import sys
|
|
sys.path.insert(0, {str(sandbox_dir)!r})
|
|
source = open({str(HARDWARE_PY)!r}, encoding = "utf-8").read()
|
|
ns = {{'__name__': '__test__'}}
|
|
exec(source, ns)
|
|
result = ns['detect_hardware']()
|
|
assert result == ns['DeviceType'].CPU, f"Expected CPU, got {{result}}"
|
|
print("OK: detect_hardware returned CPU with fake torch (no CUDA)")
|
|
""")
|
|
result = _run_in_sandbox(no_torch_venv, code)
|
|
assert result.returncode == 0, f"Should fall back to CPU:\n{result.stderr.decode()}"
|
|
assert b"OK:" in result.stdout
|
|
|
|
def test_lazy_torch_fails_at_call_time_not_import_time(self, no_torch_venv, sandbox_dir):
|
|
"""apply_chat_template_to_dataset imports without torch; the lazy import fails at call time, not import time."""
|
|
_write_loggers_stub(sandbox_dir)
|
|
|
|
code = textwrap.dedent(f"""\
|
|
import sys, types
|
|
sys.path.insert(0, {str(sandbox_dir)!r})
|
|
fd = types.ModuleType('format_detection')
|
|
fd.detect_dataset_format = fd.detect_multimodal_dataset = fd.detect_custom_format_heuristic = lambda *a, **k: None
|
|
sys.modules['format_detection'] = fd
|
|
mm = types.ModuleType('model_mappings')
|
|
mm.MODEL_TO_TEMPLATE_MAPPER = {{}}
|
|
sys.modules['model_mappings'] = mm
|
|
it = types.ModuleType('iterable')
|
|
it.is_streaming_dataset = lambda *a, **k: False
|
|
sys.modules['iterable'] = it
|
|
|
|
ns = {{}}
|
|
source = open({str(CHAT_TEMPLATES)!r}, encoding = "utf-8").read()
|
|
source = source.replace('from .format_detection import', 'from format_detection import')
|
|
source = source.replace('from .model_mappings import', 'from model_mappings import')
|
|
source = source.replace('from .iterable import', 'from iterable import')
|
|
exec(source, ns)
|
|
|
|
# Import succeeds -- this is the fix
|
|
assert 'apply_chat_template_to_dataset' in ns
|
|
print("OK: import succeeded")
|
|
|
|
# Calling alpaca branch triggers lazy torch import inside the try block.
|
|
# The function catches the error and returns it in the errors list.
|
|
dataset_info = {{
|
|
'dataset': type('D', (), {{'map': lambda *a, **k: None}})(),
|
|
'final_format': 'alpaca',
|
|
'chat_column': None,
|
|
'is_standardized': True,
|
|
'warnings': [],
|
|
}}
|
|
result = ns['apply_chat_template_to_dataset'](dataset_info, None)
|
|
# The function has a try/except that catches the error gracefully
|
|
if not result['success']:
|
|
print("OK: call-time failure caught gracefully")
|
|
else:
|
|
print("OK: call succeeded (unexpected but not a crash)")
|
|
""")
|
|
result = _run_in_sandbox(no_torch_venv, code)
|
|
assert result.returncode == 0, f"Should not crash at import time:\n{result.stderr.decode()}"
|
|
assert b"OK: import succeeded" in result.stdout
|
|
|
|
|
|
# Group 4: Hardware Detection Without Torch
|
|
|
|
|
|
class TestHardwareDetectionNoTorch:
|
|
"""Hardware module works without torch, falling back to CPU."""
|
|
|
|
def test_detect_hardware_no_torch(self, no_torch_venv, sandbox_dir):
|
|
"""detect_hardware() returns CPU when torch is not installed."""
|
|
_write_loggers_stub(sandbox_dir)
|
|
_write_structlog_stub(sandbox_dir)
|
|
|
|
code = textwrap.dedent(f"""\
|
|
import sys
|
|
sys.path.insert(0, {str(sandbox_dir)!r})
|
|
source = open({str(HARDWARE_PY)!r}, encoding = "utf-8").read()
|
|
ns = {{'__name__': '__test__'}}
|
|
exec(source, ns)
|
|
device = ns['detect_hardware']()
|
|
assert device == ns['DeviceType'].CPU
|
|
assert ns['CHAT_ONLY'] is True
|
|
print("OK: detect_hardware returned CPU, CHAT_ONLY=True")
|
|
""")
|
|
result = _run_in_sandbox(no_torch_venv, code)
|
|
assert result.returncode == 0, f"Failed:\n{result.stderr.decode()}"
|
|
assert b"OK:" in result.stdout
|
|
|
|
def test_get_package_versions_no_torch(self, no_torch_venv, sandbox_dir):
|
|
"""get_package_versions() returns torch=None, cuda=None without torch."""
|
|
_write_loggers_stub(sandbox_dir)
|
|
_write_structlog_stub(sandbox_dir)
|
|
|
|
code = textwrap.dedent(f"""\
|
|
import sys
|
|
sys.path.insert(0, {str(sandbox_dir)!r})
|
|
source = open({str(HARDWARE_PY)!r}, encoding = "utf-8").read()
|
|
ns = {{'__name__': '__test__'}}
|
|
exec(source, ns)
|
|
versions = ns['get_package_versions']()
|
|
assert versions['torch'] is None, f"Expected torch=None, got {{versions['torch']}}"
|
|
assert versions['cuda'] is None, f"Expected cuda=None, got {{versions['cuda']}}"
|
|
print("OK: torch=None, cuda=None")
|
|
""")
|
|
result = _run_in_sandbox(no_torch_venv, code)
|
|
assert result.returncode == 0, f"Failed:\n{result.stderr.decode()}"
|
|
assert b"OK:" in result.stdout
|
|
|
|
def test_hardware_module_import_no_torch(self, no_torch_venv, sandbox_dir):
|
|
"""Hardware module imports and detect_hardware is callable without torch."""
|
|
_write_loggers_stub(sandbox_dir)
|
|
_write_structlog_stub(sandbox_dir)
|
|
_write_hardware_stub(sandbox_dir)
|
|
|
|
# Copy the real hardware module into a sandbox package
|
|
hw_sandbox = sandbox_dir / "hw_pkg"
|
|
hw_sandbox.mkdir()
|
|
(hw_sandbox / "__init__.py").write_text("", encoding = "utf-8")
|
|
shutil.copy2(HARDWARE_PY, hw_sandbox / "hardware.py")
|
|
|
|
code = textwrap.dedent(f"""\
|
|
import sys
|
|
sys.path.insert(0, {str(sandbox_dir)!r})
|
|
source = open({str(hw_sandbox / 'hardware.py')!r}, encoding = "utf-8").read()
|
|
ns = {{'__name__': '__test__'}}
|
|
exec(source, ns)
|
|
assert callable(ns['detect_hardware'])
|
|
assert callable(ns['get_package_versions'])
|
|
assert callable(ns['is_apple_silicon'])
|
|
print("OK: all hardware functions accessible")
|
|
""")
|
|
result = _run_in_sandbox(no_torch_venv, code)
|
|
assert result.returncode == 0, f"Failed:\n{result.stderr.decode()}"
|
|
assert b"OK:" in result.stdout
|
|
|
|
|
|
# Group 5: install.sh Logic (via bash subprocess)
|
|
|
|
|
|
class TestInstallShLogic:
|
|
"""install.sh flag parsing, platform detection, and guard logic."""
|
|
|
|
@pytest.fixture(autouse = True)
|
|
def _check_install_sh(self):
|
|
if not INSTALL_SH.is_file():
|
|
pytest.skip("install.sh not found")
|
|
|
|
def test_python_flag_parsing(self):
|
|
"""--python flag correctly sets _USER_PYTHON."""
|
|
script = textwrap.dedent("""\
|
|
_USER_PYTHON=""
|
|
_next_is_python=false
|
|
for arg in "$@"; do
|
|
if [ "$_next_is_python" = true ]; then
|
|
_USER_PYTHON="$arg"
|
|
_next_is_python=false
|
|
continue
|
|
fi
|
|
case "$arg" in
|
|
--python) _next_is_python=true ;;
|
|
esac
|
|
done
|
|
echo "$_USER_PYTHON"
|
|
""")
|
|
# --python 3.12
|
|
r = _run_sh(f"{script}" + "\n", timeout = 10)
|
|
r = subprocess.run(
|
|
["bash", "-c", script + "\n", "_", "--python", "3.12"],
|
|
capture_output = True,
|
|
timeout = 10,
|
|
)
|
|
assert r.stdout.strip() == b"3.12"
|
|
|
|
# --local --python 3.11
|
|
r = subprocess.run(
|
|
["bash", "-c", script + "\n", "_", "--local", "--python", "3.11"],
|
|
capture_output = True,
|
|
timeout = 10,
|
|
)
|
|
assert r.stdout.strip() == b"3.11"
|
|
|
|
# no --python flag
|
|
r = subprocess.run(
|
|
["bash", "-c", script + "\n", "_", "--local"],
|
|
capture_output = True,
|
|
timeout = 10,
|
|
)
|
|
assert r.stdout.strip() == b""
|
|
|
|
def test_python_flag_missing_arg_errors(self):
|
|
"""--python without a version argument triggers an error."""
|
|
script = textwrap.dedent("""\
|
|
set -e
|
|
_USER_PYTHON=""
|
|
_next_is_python=false
|
|
for arg in "$@"; do
|
|
if [ "$_next_is_python" = true ]; then
|
|
_USER_PYTHON="$arg"
|
|
_next_is_python=false
|
|
continue
|
|
fi
|
|
case "$arg" in
|
|
--python) _next_is_python=true ;;
|
|
esac
|
|
done
|
|
if [ "$_next_is_python" = true ]; then
|
|
echo "ERROR: --python requires a version argument" >&2
|
|
exit 1
|
|
fi
|
|
echo "$_USER_PYTHON"
|
|
""")
|
|
r = subprocess.run(
|
|
["bash", "-c", script + "\n", "_", "--python"],
|
|
capture_output = True,
|
|
timeout = 10,
|
|
)
|
|
assert r.returncode != 0
|
|
assert b"ERROR" in r.stderr
|
|
|
|
def test_python_version_resolution(self):
|
|
"""Python version defaults to 3.12 on Intel Mac, 3.13 elsewhere.
|
|
--python overrides both."""
|
|
script = textwrap.dedent("""\
|
|
MAC_INTEL="$1"
|
|
_USER_PYTHON="$2"
|
|
|
|
if [ -n "$_USER_PYTHON" ]; then
|
|
PYTHON_VERSION="$_USER_PYTHON"
|
|
elif [ "$MAC_INTEL" = true ]; then
|
|
PYTHON_VERSION="3.12"
|
|
else
|
|
PYTHON_VERSION="3.13"
|
|
fi
|
|
echo "$PYTHON_VERSION"
|
|
""")
|
|
# Intel Mac, no override
|
|
r = subprocess.run(
|
|
["bash", "-c", script + "\n", "_", "true", ""],
|
|
capture_output = True,
|
|
timeout = 10,
|
|
)
|
|
assert r.stdout.strip() == b"3.12"
|
|
|
|
# non-Intel, no override
|
|
r = subprocess.run(
|
|
["bash", "-c", script + "\n", "_", "false", ""],
|
|
capture_output = True,
|
|
timeout = 10,
|
|
)
|
|
assert r.stdout.strip() == b"3.13"
|
|
|
|
# Intel Mac with --python override
|
|
r = subprocess.run(
|
|
["bash", "-c", script + "\n", "_", "true", "3.11"],
|
|
capture_output = True,
|
|
timeout = 10,
|
|
)
|
|
assert r.stdout.strip() == b"3.11"
|
|
|
|
def test_mac_intel_detection_snippet(self):
|
|
"""Architecture detection sets MAC_INTEL correctly for different platforms."""
|
|
script = textwrap.dedent("""\
|
|
OS="$1"
|
|
_ARCH="$2"
|
|
MAC_INTEL=false
|
|
if [ "$OS" = "macos" ] && [ "$_ARCH" = "x86_64" ]; then
|
|
MAC_INTEL=true
|
|
fi
|
|
echo "$MAC_INTEL"
|
|
""")
|
|
cases = [
|
|
(("macos", "x86_64"), b"true"),
|
|
(("macos", "arm64"), b"false"),
|
|
(("linux", "x86_64"), b"false"),
|
|
(("linux", "aarch64"), b"false"),
|
|
]
|
|
for (os_val, arch), expected in cases:
|
|
r = subprocess.run(
|
|
["bash", "-c", script + "\n", "_", os_val, arch],
|
|
capture_output = True,
|
|
timeout = 10,
|
|
)
|
|
assert r.stdout.strip() == expected, (
|
|
f"MAC_INTEL for ({os_val}, {arch}): "
|
|
f"expected {expected!r}, got {r.stdout.strip()!r}"
|
|
)
|
|
|
|
def test_stale_venv_guard_respects_override(self):
|
|
"""When _USER_PYTHON is set, the stale venv recreation guard is skipped."""
|
|
script = textwrap.dedent("""\
|
|
MAC_INTEL=true
|
|
_USER_PYTHON="$1"
|
|
_VENV_EXISTS=true # simulate existing venv
|
|
|
|
SHOULD_RECREATE=false
|
|
if [ "$MAC_INTEL" = true ] && [ -z "$_USER_PYTHON" ] && [ "$_VENV_EXISTS" = true ]; then
|
|
SHOULD_RECREATE=true
|
|
fi
|
|
echo "$SHOULD_RECREATE"
|
|
""")
|
|
# with override: should NOT recreate
|
|
r = subprocess.run(
|
|
["bash", "-c", script + "\n", "_", "3.11"],
|
|
capture_output = True,
|
|
timeout = 10,
|
|
)
|
|
assert r.stdout.strip() == b"false"
|
|
|
|
# without override: SHOULD recreate
|
|
r = subprocess.run(
|
|
["bash", "-c", script + "\n", "_", ""],
|
|
capture_output = True,
|
|
timeout = 10,
|
|
)
|
|
assert r.stdout.strip() == b"true"
|
|
|
|
|
|
# Group 6: install_python_stack.py NO_TORCH Filtering
|
|
|
|
|
|
class TestInstallPythonStackFiltering:
|
|
"""NO_TORCH filtering logic in install_python_stack.py."""
|
|
|
|
@pytest.fixture(autouse = True)
|
|
def _check_install_py(self):
|
|
if not INSTALL_PY.is_file():
|
|
pytest.skip("install_python_stack.py not found")
|
|
|
|
def test_filter_requirements_removes_torch_deps(self):
|
|
"""_filter_requirements removes all NO_TORCH_SKIP_PACKAGES from a real extras file."""
|
|
import install_python_stack as ips
|
|
|
|
extras = STUDIO_DIR / "backend" / "requirements" / "extras.txt"
|
|
if not extras.is_file():
|
|
pytest.skip("extras.txt not found")
|
|
|
|
result_path = ips._filter_requirements(extras, ips.NO_TORCH_SKIP_PACKAGES)
|
|
filtered = Path(result_path).read_text(encoding = "utf-8").lower()
|
|
lines = [
|
|
l.strip() for l in filtered.splitlines() if l.strip() and not l.strip().startswith("#")
|
|
]
|
|
|
|
for pkg in ips.NO_TORCH_SKIP_PACKAGES:
|
|
assert not any(
|
|
l.startswith(pkg) for l in lines
|
|
), f"{pkg} should be removed from extras.txt"
|
|
|
|
def test_filter_requirements_preserves_non_torch(self):
|
|
"""Non-torch packages survive NO_TORCH filtering."""
|
|
import install_python_stack as ips
|
|
|
|
extras = STUDIO_DIR / "backend" / "requirements" / "extras.txt"
|
|
if not extras.is_file():
|
|
pytest.skip("extras.txt not found")
|
|
|
|
result_path = ips._filter_requirements(extras, ips.NO_TORCH_SKIP_PACKAGES)
|
|
filtered_text = Path(result_path).read_text(encoding = "utf-8").lower()
|
|
|
|
must_survive = ["scikit-learn", "loguru", "tiktoken", "einops"]
|
|
original_text = extras.read_text(encoding = "utf-8").lower()
|
|
for pkg in must_survive:
|
|
if pkg in original_text:
|
|
assert pkg in filtered_text, f"{pkg} should survive NO_TORCH filtering"
|
|
|
|
def test_infer_no_torch_env_var_overrides_platform(self):
|
|
"""UNSLOTH_NO_TORCH=true on Linux -> True; =false on Intel Mac -> False."""
|
|
import install_python_stack as ips
|
|
|
|
# Explicit true on Linux
|
|
with (
|
|
mock.patch.dict(os.environ, {"UNSLOTH_NO_TORCH": "true"}),
|
|
mock.patch.object(ips, "IS_MAC_INTEL", False),
|
|
):
|
|
assert ips._infer_no_torch() is True
|
|
|
|
# explicit false on Intel Mac
|
|
with (
|
|
mock.patch.dict(os.environ, {"UNSLOTH_NO_TORCH": "false"}),
|
|
mock.patch.object(ips, "IS_MAC_INTEL", True),
|
|
):
|
|
assert ips._infer_no_torch() is False
|
|
|
|
# Unset on Intel Mac -> True (platform fallback)
|
|
env = os.environ.copy()
|
|
env.pop("UNSLOTH_NO_TORCH", None)
|
|
with (
|
|
mock.patch.dict(os.environ, env, clear = True),
|
|
mock.patch.object(ips, "IS_MAC_INTEL", True),
|
|
):
|
|
assert ips._infer_no_torch() is True
|
|
|
|
def test_no_torch_skips_overrides_and_triton(self):
|
|
"""When NO_TORCH=True, overrides.txt and triton are skipped (source guard check)."""
|
|
import install_python_stack as ips
|
|
|
|
source = Path(ips.__file__).read_text(encoding = "utf-8")
|
|
|
|
assert "if NO_TORCH:" in source, "NO_TORCH guard not found in install_python_stack.py"
|
|
|
|
# macOS guard for triton
|
|
assert (
|
|
"not IS_WINDOWS and not IS_MACOS" in source
|
|
), "'not IS_WINDOWS and not IS_MACOS' guard for triton not found"
|
|
|
|
|
|
# Group 7: Live Server Startup -- Heavyweight
|
|
|
|
|
|
def _studio_venv_python() -> Path | None:
|
|
"""Return the studio venv Python path, or None if not found."""
|
|
py = _venv_python(STUDIO_VENV)
|
|
if py.exists():
|
|
return py
|
|
return None
|
|
|
|
|
|
def _server_port() -> int:
|
|
"""Find an available port for the test server."""
|
|
import socket
|
|
with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s:
|
|
s.bind(("", 0))
|
|
return s.getsockname()[1]
|
|
|
|
|
|
server = pytest.mark.server
|
|
|
|
|
|
@server
|
|
class TestLiveServerStartup:
|
|
"""Live server startup against the existing Unsloth venv with torch made unimportable (pytest -m server)."""
|
|
|
|
@pytest.fixture(autouse = True)
|
|
def _check_studio_venv(self):
|
|
py = _studio_venv_python()
|
|
if py is None:
|
|
pytest.skip("Unsloth venv not found at ~/.unsloth/studio/unsloth_studio")
|
|
|
|
@pytest.fixture(scope = "class")
|
|
def server_process(self):
|
|
"""Start the studio backend server without torch, yield (proc, port), then stop."""
|
|
py = _studio_venv_python()
|
|
if py is None:
|
|
pytest.skip("Unsloth venv not found")
|
|
|
|
port = _server_port()
|
|
backend_dir = BACKEND_DIR
|
|
|
|
check = subprocess.run(
|
|
[str(py), "-c", "import torch; print(torch.__version__)"],
|
|
capture_output = True,
|
|
)
|
|
torch_was_installed = check.returncode == 0
|
|
torch_version = check.stdout.decode().strip() if torch_was_installed else None
|
|
|
|
if torch_was_installed:
|
|
subprocess.run(
|
|
[
|
|
str(py),
|
|
"-m",
|
|
"pip",
|
|
"uninstall",
|
|
"-y",
|
|
"torch",
|
|
"torchvision",
|
|
"torchaudio",
|
|
],
|
|
capture_output = True,
|
|
timeout = 120,
|
|
)
|
|
|
|
env = os.environ.copy()
|
|
env["PYTHONPATH"] = str(backend_dir)
|
|
proc = subprocess.Popen(
|
|
[str(py), str(backend_dir / "run.py"), "--port", str(port)],
|
|
env = env,
|
|
stdout = subprocess.PIPE,
|
|
stderr = subprocess.PIPE,
|
|
cwd = str(backend_dir),
|
|
)
|
|
|
|
# Wait for server to be ready (poll /api/health)
|
|
import urllib.request
|
|
import urllib.error
|
|
|
|
ready = False
|
|
for _ in range(30):
|
|
time.sleep(1)
|
|
try:
|
|
resp = urllib.request.urlopen(f"http://127.0.0.1:{port}/api/health", timeout = 2)
|
|
if resp.status == 200:
|
|
ready = True
|
|
break
|
|
except (urllib.error.URLError, ConnectionRefusedError, OSError):
|
|
continue
|
|
|
|
if not ready:
|
|
stdout, stderr = proc.communicate(timeout = 5)
|
|
if torch_was_installed and torch_version:
|
|
subprocess.run(
|
|
[
|
|
str(py),
|
|
"-m",
|
|
"pip",
|
|
"install",
|
|
f"torch=={torch_version}",
|
|
"torchvision",
|
|
"torchaudio",
|
|
],
|
|
capture_output = True,
|
|
timeout = 300,
|
|
)
|
|
server_output = stdout.decode(errors = "replace") + stderr.decode(errors = "replace")
|
|
pytest.skip(f"Server failed to start within 30 seconds. Output:\n{server_output}")
|
|
|
|
yield proc, port
|
|
|
|
# Cleanup: stop server, reinstall torch
|
|
proc.terminate()
|
|
try:
|
|
proc.wait(timeout = 10)
|
|
except subprocess.TimeoutExpired:
|
|
proc.kill()
|
|
proc.wait(timeout = 5)
|
|
|
|
if torch_was_installed and torch_version:
|
|
subprocess.run(
|
|
[
|
|
str(py),
|
|
"-m",
|
|
"pip",
|
|
"install",
|
|
f"torch=={torch_version}",
|
|
"torchvision",
|
|
"torchaudio",
|
|
],
|
|
capture_output = True,
|
|
timeout = 300,
|
|
)
|
|
|
|
def test_server_starts_without_torch(self, server_process):
|
|
"""Server responds to /api/health with chat_only: true."""
|
|
import json
|
|
import urllib.request
|
|
|
|
_, port = server_process
|
|
resp = urllib.request.urlopen(f"http://127.0.0.1:{port}/api/health", timeout = 5)
|
|
data = json.loads(resp.read())
|
|
assert data["status"] == "healthy"
|
|
assert data["chat_only"] is True
|
|
|
|
def test_all_routes_registered(self, server_process):
|
|
"""OpenAPI spec shows >= 20 paths (server started fully)."""
|
|
import json
|
|
import urllib.request
|
|
|
|
_, port = server_process
|
|
resp = urllib.request.urlopen(f"http://127.0.0.1:{port}/openapi.json", timeout = 5)
|
|
spec = json.loads(resp.read())
|
|
assert (
|
|
len(spec.get("paths", {})) >= 20
|
|
), f"Expected >= 20 routes, got {len(spec.get('paths', {}))}"
|
|
|
|
def test_hardware_endpoint_no_torch(self, server_process):
|
|
"""GET /api/system/hardware returns torch=null, gpu_name=null."""
|
|
import json
|
|
import urllib.request
|
|
|
|
_, port = server_process
|
|
resp = urllib.request.urlopen(
|
|
f"http://127.0.0.1:{port}/api/system/hardware",
|
|
timeout = 5,
|
|
)
|
|
data = json.loads(resp.read())
|
|
versions = data.get("versions", {})
|
|
assert versions.get("torch") is None
|
|
assert versions.get("cuda") is None
|
|
|
|
def test_server_survives_multiple_requests(self, server_process):
|
|
"""Hit 5 different endpoints. Server PID should still be alive after."""
|
|
import urllib.request
|
|
import urllib.error
|
|
|
|
proc, port = server_process
|
|
endpoints = [
|
|
"/api/health",
|
|
"/openapi.json",
|
|
"/api/system/hardware",
|
|
"/api/health",
|
|
"/docs",
|
|
]
|
|
for ep in endpoints:
|
|
try:
|
|
urllib.request.urlopen(f"http://127.0.0.1:{port}{ep}", timeout = 5)
|
|
except urllib.error.HTTPError:
|
|
pass # 4xx/5xx fine -- server didn't crash
|
|
except urllib.error.URLError:
|
|
pytest.fail(f"Server stopped responding at {ep}")
|
|
|
|
assert proc.poll() is None, "Server process should still be running"
|