Raise ruff line-length to 100 and extend the local pre-commit format pipeline (def-signature magic-comma normalization, short multi-line assert collapse, kwarg '=' spacing, blank-line-after-short-import removal, adjacent string-literal / f-string+plain merge, redundant-pass pruning). Every transform re-checks the file AST and is dropped if it would differ; the whole-repo reformat is verified AST-identical per file and idempotent.
161 lines
5.7 KiB
Python
161 lines
5.7 KiB
Python
# SPDX-License-Identifier: AGPL-3.0-only
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# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved.
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"""GPU-free test harness.
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unsloth's import chain hits unsloth_zoo.device_type, which calls
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get_device_type() at import time and raises NotImplementedError on CI
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runners with no CUDA / XPU / HIP visible. Pre-load the real
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unsloth_zoo.device_type under a temporarily-mocked
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torch.cuda.is_available() so its @cache permanently captures "cuda".
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On a real accelerator the pre-load is skipped and detection runs
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normally.
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Mirrors the conftest harness in unslothai/unsloth-zoo PR #624.
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"""
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from __future__ import annotations
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import importlib.util
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import os
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import sys
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import types
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def _has_real_accelerator() -> bool:
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try:
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import torch
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except Exception:
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return False
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for probe in (
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lambda: hasattr(torch, "cuda") and torch.cuda.is_available(),
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lambda: hasattr(torch, "xpu") and torch.xpu.is_available(),
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lambda: hasattr(torch, "accelerator") and torch.accelerator.is_available(),
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):
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try:
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if probe():
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return True
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except Exception:
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pass
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return False
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def _preload_device_type(package: str, prereqs: tuple[str, ...] = ()) -> bool:
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"""Pre-load <package>.device_type under a mocked
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torch.cuda.is_available() == True so its @cache permanently
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captures "cuda". prereqs lists submodule names of <package> that
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must be loaded first (e.g. 'utils' for unsloth_zoo). Returns False
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if the package or any prerequisite cannot be imported, in which
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case the caller falls back to a stub."""
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target = f"{package}.device_type"
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if target in sys.modules:
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return True
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pkg_spec = importlib.util.find_spec(package)
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if pkg_spec is None or not pkg_spec.submodule_search_locations:
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return False
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pkg_path = pkg_spec.submodule_search_locations[0]
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skeleton_already = package in sys.modules
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if not skeleton_already:
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skel = types.ModuleType(package)
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skel.__path__ = [pkg_path]
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skel.__spec__ = pkg_spec
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skel.__package__ = package
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sys.modules[package] = skel
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try:
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for prereq in prereqs:
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full = f"{package}.{prereq}"
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if full in sys.modules:
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continue
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prereq_path = os.path.join(pkg_path, f"{prereq}.py")
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prereq_spec = importlib.util.spec_from_file_location(full, prereq_path)
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prereq_mod = importlib.util.module_from_spec(prereq_spec)
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sys.modules[full] = prereq_mod
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prereq_spec.loader.exec_module(prereq_mod)
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device_type_path = os.path.join(pkg_path, "device_type.py")
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dt_spec = importlib.util.spec_from_file_location(target, device_type_path)
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dt_mod = importlib.util.module_from_spec(dt_spec)
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sys.modules[target] = dt_mod
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import torch
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_orig_is_avail = torch.cuda.is_available
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torch.cuda.is_available = lambda: True # type: ignore[assignment]
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try:
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dt_spec.loader.exec_module(dt_mod)
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finally:
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torch.cuda.is_available = _orig_is_avail
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except Exception:
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sys.modules.pop(target, None)
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return False
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finally:
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if not skeleton_already:
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sys.modules.pop(package, None)
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return True
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def _patch_torch_cuda_for_import() -> None:
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"""Stub torch.cuda.* probes that fire at IMPORT time of unsloth /
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unsloth_zoo when DEVICE_TYPE was forced to "cuda" above. These are
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queries, not real GPU work, so returning plausible Ampere values
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lets the import chain finish; tests that touch real tensors run on
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CPU like normal."""
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try:
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import torch.cuda.memory as _cuda_memory # type: ignore
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_cuda_memory.mem_get_info = lambda *a, **k: (0, 80 * 1024**3)
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except Exception:
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pass
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try:
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import torch
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torch.cuda.get_device_capability = lambda *a, **k: (8, 0)
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torch.cuda.is_bf16_supported = lambda *a, **k: True
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except Exception:
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pass
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def _install_device_type_stub(name: str) -> None:
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stub = types.ModuleType(name)
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stub.DEVICE_TYPE = "cuda"
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stub.DEVICE_TYPE_TORCH = "cuda"
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stub.DEVICE_COUNT = 1
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stub.ALLOW_PREQUANTIZED_MODELS = False
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stub.is_hip = lambda: False
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stub.get_device_type = lambda: "cuda"
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stub.get_device_count = lambda: 1
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stub.device_synchronize = lambda *a, **k: None
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stub.device_empty_cache = lambda *a, **k: None
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stub.device_is_bf16_supported = lambda *a, **k: False
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sys.modules[name] = stub
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if not _has_real_accelerator():
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if not _preload_device_type("unsloth_zoo", prereqs = ("utils",)):
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_install_device_type_stub("unsloth_zoo.device_type")
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if not _preload_device_type("unsloth"):
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_install_device_type_stub("unsloth.device_type")
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_patch_torch_cuda_for_import()
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# ---------------------------------------------------------------------------
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# Apply ALL upstream-drift fixes (vllm GuidedDecodingParams alias, triton
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# CompiledKernel attr wrap, peft transformers_weight_conversion stub, etc.)
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# by triggering ``import unsloth``. Fixes live on ``unsloth/import_fixes.py``
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# and apply at unsloth import time. The GPU-free harness above pre-spoofs
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# the device-type chain so ``import unsloth`` survives on a CPU-only runner.
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# Suites without unsloth installed (e.g. security-only) keep passing --
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# the ImportError is swallowed and the drift detectors will surface any
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# pathology the missing patches would have hidden.
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# ---------------------------------------------------------------------------
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def _apply_upstream_import_fixes_for_tests() -> None:
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try:
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import unsloth # noqa: F401 # runs unsloth/import_fixes.py
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except Exception:
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pass
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_apply_upstream_import_fixes_for_tests()
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