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273 lines
8.8 KiB
Python
273 lines
8.8 KiB
Python
# SPDX-License-Identifier: AGPL-3.0-only
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# Copyright 2026-present the Unsloth AI Inc. team.
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"""Golden-fixture tests for scripts/notebook_validator.py: each reconstructs a broken install cell from an unslothai/notebooks PR and asserts the matching rule fires (and falls silent after the fix).
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Cross-references: PR #258->R-INST-003, #260->R-EXC-001, #261a->R-INST-004,
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#261b/#264->R-INST-005, #221->R-INST-001, 51b1462->R-DRIFT-001.
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"""
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from __future__ import annotations
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import sys
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from pathlib import Path
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import pytest
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HERE = Path(__file__).resolve().parent
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SCRIPTS_DIR = HERE.parent.parent / "scripts"
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sys.path.insert(0, str(SCRIPTS_DIR))
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import notebook_validator as nv # noqa: E402
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# Inline subset of Colab GPU pip-freeze recreating the bug environments (CI uses scripts/data/colab_pip_freeze.gpu.txt).
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COLAB_2026_05 = {
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"torch": "2.10.0+cu128",
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"torchao": "0.10.0",
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"torchcodec": "0.10.0+cu128",
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"transformers": "5.0.0",
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"tokenizers": "0.22.2",
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"peft": "0.19.1",
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"accelerate": "1.13.0",
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"datasets": "4.0.0",
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}
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# ---------- R-INST-001 : forbid git+ HEAD ------------------------------- #
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def test_r_inst_001_fires_on_transformers_git_head():
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cell = """%%capture
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!pip install --force-reinstall git+https://github.com/huggingface/transformers.git
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"""
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findings = nv.rule_inst_001_git_plus(cell, "fixture", 0)
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assert any(f.rule == "R-INST-001" for f in findings)
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def test_r_inst_001_silent_after_pin():
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cell = """%%capture
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!pip install transformers==5.5.0
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"""
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findings = nv.rule_inst_001_git_plus(cell, "fixture", 0)
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assert findings == []
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def test_r_inst_001_allowlist_unsloth_zoo_git():
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cell = """%%capture
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!pip install --no-build-isolation git+https://github.com/state-spaces/mamba.git@main
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!pip install "unsloth_zoo[base] @ git+https://github.com/unslothai/unsloth-zoo"
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"""
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findings = nv.rule_inst_001_git_plus(cell, "fixture", 0)
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assert findings == []
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# ---------- R-INST-003 : peft / torchao floor (PR #258) ------------------ #
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def test_r_inst_003_fires_when_peft_19_with_no_torchao_bump():
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cell = """%%capture
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!pip install --no-deps peft trl unsloth_zoo
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"""
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findings = nv.rule_inst_003_peft_torchao(cell, COLAB_2026_05, "fixture", 0)
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assert any(f.rule == "R-INST-003" for f in findings)
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def test_r_inst_003_silent_when_torchao_bumped():
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cell = """%%capture
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!pip install --no-deps peft trl unsloth_zoo
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!pip install --no-deps --upgrade "torchao>=0.16.0"
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"""
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findings = nv.rule_inst_003_peft_torchao(cell, COLAB_2026_05, "fixture", 0)
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assert findings == []
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def test_r_inst_003_silent_when_torchao_pinned_high():
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cell = """%%capture
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!pip install --no-deps peft trl
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!pip install torchao==0.17.0
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"""
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findings = nv.rule_inst_003_peft_torchao(cell, COLAB_2026_05, "fixture", 0)
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assert findings == []
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# ---------- R-INST-004 : torch / torchcodec ABI (PR #261a) --------------- #
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def test_r_inst_004_fires_torch_2_7_with_torchcodec_0_6():
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cell = """%%capture
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!uv pip install "torch==2.7.1"
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!uv pip install --no-deps "torchcodec==0.6.0"
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"""
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findings = nv.rule_inst_004_torchcodec_torch(cell, COLAB_2026_05, "fixture", 0)
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assert any(f.rule == "R-INST-004" for f in findings)
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def test_r_inst_004_silent_when_torch_2_7_with_torchcodec_0_5():
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cell = """%%capture
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!uv pip install "torch==2.7.1"
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!uv pip install --no-deps "torchcodec==0.5"
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"""
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findings = nv.rule_inst_004_torchcodec_torch(cell, COLAB_2026_05, "fixture", 0)
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assert findings == []
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# ---------- R-INST-005 : transformers + tokenizers window (PRs #261b/#264) -- #
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def test_r_inst_005_fires_no_deps_transformers_55_without_tokenizers_pin(monkeypatch):
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"""PR #264: --no-deps transformers==5.5.0 leaves Colab tokenizers in place; breaks if Colab ships tokenizers > 0.23.0."""
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cell = """%%capture
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!pip install --no-deps transformers==5.5.0
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"""
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# Colab snapshot where tokenizers bumped past transformers 5.5.0's window.
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colab = dict(COLAB_2026_05, tokenizers = "0.23.5")
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def fake_meta(name, version):
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if name.lower() == "transformers" and version == "5.5.0":
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return {"info": {"requires_dist": ["tokenizers (>=0.22.0,<=0.23.0)"]}}
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return None
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monkeypatch.setattr(nv, "pypi_metadata", fake_meta)
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findings = nv.rule_inst_005_transformers_tokenizers(cell, colab, "fixture", 0)
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assert any(f.rule == "R-INST-005" for f in findings)
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def test_r_inst_005_silent_when_no_deps_pins_tokenizers(monkeypatch):
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cell = """%%capture
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!pip install --no-deps transformers==5.5.0 "tokenizers>=0.22.0,<=0.23.0"
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"""
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def fake_meta(name, version):
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if name.lower() == "transformers" and version == "5.5.0":
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return {"info": {"requires_dist": ["tokenizers (>=0.22.0,<=0.23.0)"]}}
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return None
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monkeypatch.setattr(nv, "pypi_metadata", fake_meta)
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# Cell wins over Colab; resolved tokenizers will be 0.23.0.
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colab = dict(COLAB_2026_05, tokenizers = "0.23.5")
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findings = nv.rule_inst_005_transformers_tokenizers(cell, colab, "fixture", 0)
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assert findings == []
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def test_r_inst_005_silent_without_no_deps(monkeypatch):
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"""Without --no-deps, pip resolves tokenizers transitively; rule must NOT fire (false-positive case from e.g. Whisper.ipynb)."""
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cell = """%%capture
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!pip install transformers==4.51.3
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"""
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def fake_meta(name, version):
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if name.lower() == "transformers" and version == "4.51.3":
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return {"info": {"requires_dist": ["tokenizers (>=0.21,<0.22)"]}}
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return None
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monkeypatch.setattr(nv, "pypi_metadata", fake_meta)
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colab = COLAB_2026_05
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findings = nv.rule_inst_005_transformers_tokenizers(cell, colab, "fixture", 0)
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assert findings == []
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# ---------- R-API-003 : suboptimal optim warning (PR #221, partial) ------ #
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import json
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from pathlib import Path as _P
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def _nb_with_code(*sources: str) -> dict:
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return {
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"cells": [{"cell_type": "code", "source": s} for s in sources],
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"metadata": {},
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"nbformat": 4,
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"nbformat_minor": 5,
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}
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def test_r_api_003_fires_on_adamw_torch_fused():
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nb = _nb_with_code(
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"%%capture\n!pip install unsloth\n",
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'from trl import SFTConfig\ntrainer = SFTConfig(optim="adamw_torch_fused")\n',
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)
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findings = nv.scan_user_cells(nb, "fixture")
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assert any(f.rule == "R-API-003" for f in findings)
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def test_r_api_003_silent_on_adamw_8bit():
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nb = _nb_with_code(
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"%%capture\n!pip install unsloth\n",
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'from trl import SFTConfig\ntrainer = SFTConfig(optim="adamw_8bit")\n',
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)
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findings = nv.scan_user_cells(nb, "fixture")
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assert findings == []
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# ---------- Environment classifier --------------------------------------- #
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@pytest.mark.parametrize(
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"path,expected",
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[
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("nb/Llama3.1_(8B)-Alpaca.ipynb", "colab"),
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("nb/Kaggle-Llama3.1_(8B)-Alpaca.ipynb", "kaggle"),
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("kaggle/Gemma4_(31B)-Text.ipynb", "kaggle"),
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("nb/AMD-Llama3.1_(8B)-Alpaca.ipynb", "amd"),
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("nb/HuggingFace Course-Qwen3_(4B)-GRPO.ipynb", "colab"),
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(
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"nb/gpt_oss_(20B)_Reinforcement_Learning_2048_Game_DGX_Spark.ipynb",
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"dgx_spark",
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),
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],
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)
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def test_environment_classifier(path, expected):
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assert nv.target_environment(path) == expected
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# ---------- Integration: walk the live notebooks repo (skipped if absent) -- #
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def _live_notebooks_dir() -> Path | None:
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candidates = [
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Path(__file__).resolve().parents[3] / "notebooks", # workspace sibling
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Path("/mnt/disks/unslothai/ubuntu/workspace_12/notebooks"),
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]
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for p in candidates:
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if (p / "update_all_notebooks.py").is_file():
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return p
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return None
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@pytest.mark.skipif(
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_live_notebooks_dir() is None,
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reason = "unslothai/notebooks not cloned at sibling path",
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)
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def test_exceptions_passes_on_head():
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"""L1.2 must be silent on live unslothai/notebooks HEAD; a fire means a DONT_UPDATE_EXCEPTIONS notebook lost its policy clause or the clause set is stale."""
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findings = nv.rule_l12_exceptions_coverage(_live_notebooks_dir())
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assert findings == [], findings
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@pytest.mark.skipif(
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_live_notebooks_dir() is None,
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reason = "unslothai/notebooks not cloned at sibling path",
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)
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def test_lint_smoke_no_module_errors():
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"""The lint subcommand walks every nb/kaggle without crashing (findings are fine)."""
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import subprocess
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rc = subprocess.run(
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[
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sys.executable,
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str(SCRIPTS_DIR / "notebook_validator.py"),
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"lint",
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"--no-pypi",
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"--notebooks-dir",
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str(_live_notebooks_dir()),
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"--colab-pin",
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str(SCRIPTS_DIR / "data" / "colab_pip_freeze.gpu.txt"),
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],
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capture_output = True,
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text = True,
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timeout = 120,
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)
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# rc=0 means clean, rc=1 means findings reported, rc=2 means crash.
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assert rc.returncode in (0, 1), rc.stderr[-2000:]
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