Shaun ZhouandClaude Opus 5
d6c6aca325
CLAUDE.md 已把"只用 convolution 模型"收窄到聚类与数据集生成阶段，检测这一步 不再受限，于是换成最新的 YOLO26：端到端（NMS-free），推理侧少一道后处理。 取最小的 n 档——数据 1.1 万张且标签是弱监督的，模型大了容易把标注噪声学进去。 同时去掉 test_config.py 里"不许用 yolo11/yolo12"的断言，它的依据已随 CLAUDE.md 的改动失效。 Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
190 lines
7.4 KiB
Python
190 lines
7.4 KiB
Python
from pathlib import Path
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import pytest
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pytest.importorskip("yaml")
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from utils.config import Config, apply_overrides, deep_merge, load_config, parse_override # noqa: E402
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def test_deep_merge_is_recursive():
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merged = deep_merge({"a": {"b": 1, "c": 2}}, {"a": {"c": 3}, "d": 4})
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assert merged == {"a": {"b": 1, "c": 3}, "d": 4}
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def test_parse_override_literals():
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assert parse_override("train.lr=1e-3") == ("train.lr", 1e-3)
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assert parse_override("train.amp=False") == ("train.amp", False)
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assert parse_override("model.backbone.name=tiny_conv") == ("model.backbone.name", "tiny_conv")
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assert parse_override("simclr.feature_stages=[5, 6]") == ("simclr.feature_stages", [5, 6])
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def test_parse_override_accepts_yaml_style_scalars():
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"""配置文件里写 null/true/false，命令行上也得能这么写。
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回归测试：只用 ast.literal_eval 时 `false` 会变成字符串 "false"，
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而非空字符串是真值——`--set xxx.enabled=false` 反而把开关打开了。
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"""
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assert parse_override("a=null") == ("a", None)
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assert parse_override("a=~") == ("a", None)
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assert parse_override("a=true") == ("a", True)
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assert parse_override("a=false") == ("a", False)
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assert parse_override("a=false")[1] is False # 不是字符串
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# 路径、模型名这类仍应保持字符串
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assert parse_override("a=resnet18") == ("a", "resnet18")
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assert parse_override("a=runs/x/best.pth") == ("a", "runs/x/best.pth")
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def test_apply_overrides_creates_missing_nodes():
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"""非严格模式下仍可新建嵌套节点；严格模式（load_config 默认）会拦下未知键。"""
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cfg = apply_overrides({}, ["a.b.c=1"], strict=False)
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assert cfg == {"a": {"b": {"c": 1}}}
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with pytest.raises(KeyError, match="不存在"):
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apply_overrides({}, ["a.b.c=1"])
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def test_load_config_with_base(tmp_path):
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(tmp_path / "base.yaml").write_text("train:\n lr: 0.1\n epochs: 10\n", encoding="utf-8")
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(tmp_path / "child.yaml").write_text(
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"_base_: ./base.yaml\ntrain:\n lr: 0.01\nwork_dir: runs/x\n", encoding="utf-8"
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)
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cfg = load_config(tmp_path / "child.yaml", ["train.epochs=2"])
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assert isinstance(cfg, Config)
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assert cfg.train.lr == 0.01
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assert cfg.train.epochs == 2
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assert cfg.get_path("work_dir") == "runs/x"
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def test_load_config_detects_cycle(tmp_path):
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(tmp_path / "a.yaml").write_text("_base_: ./b.yaml\n", encoding="utf-8")
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(tmp_path / "b.yaml").write_text("_base_: ./a.yaml\n", encoding="utf-8")
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with pytest.raises(ValueError, match="循环引用"):
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load_config(tmp_path / "a.yaml")
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def test_project_configs_are_loadable():
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cluster = load_config("configs/cluster/film.yaml")
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assert cluster["dataset"]["name"] == "unlabeled"
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assert cluster["num_clusters"] > 0
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classify = load_config("configs/classify/film.yaml")
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assert classify["model"]["name"] == "classifier"
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assert classify["train"]["monitor"] == "macro_f1"
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def test_replace_key_swaps_a_whole_subdict(tmp_path):
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"""换组件时要能整块替换，否则旧组件的专有字段会残留下来传给新组件。"""
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(tmp_path / "base.yaml").write_text(
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"backbone:\n name: tiny_conv\n widths: [32, 64]\n depths: [1, 2]\n block: dw\n",
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encoding="utf-8",
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)
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(tmp_path / "child.yaml").write_text(
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"_base_: ./base.yaml\nbackbone:\n _replace_: true\n name: torchvision\n arch: resnet18\n",
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encoding="utf-8",
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)
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cfg = load_config(tmp_path / "child.yaml")
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assert cfg["backbone"] == {"name": "torchvision", "arch": "resnet18"}
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assert "_replace_" not in cfg["backbone"] # 标记本身不能漏进构造参数
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def test_without_replace_key_subdicts_still_merge(tmp_path):
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(tmp_path / "base.yaml").write_text("backbone:\n name: tiny_conv\n block: dw\n", encoding="utf-8")
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(tmp_path / "child.yaml").write_text(
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"_base_: ./base.yaml\nbackbone:\n block: res\n", encoding="utf-8"
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)
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cfg = load_config(tmp_path / "child.yaml")
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assert cfg["backbone"] == {"name": "tiny_conv", "block": "res"}
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def test_registry_reports_incompatible_fields_actionably():
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"""--set 只改 name 时旧字段会残留，报错要说清楚是哪些字段、该怎么办。"""
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import pytest
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from models.registry import BACKBONES
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with pytest.raises(TypeError, match=r"不接受的字段.*widths"):
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BACKBONES.build({"name": "torchvision", "arch": "resnet18", "widths": [32]})
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@pytest.mark.parametrize(
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"config_path",
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sorted(str(p) for p in Path("configs").rglob("*.yaml")),
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)
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def test_every_shipped_config_builds_its_components(config_path):
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"""仓库里每个配置都必须能真的构建出组件。
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回归测试：派生配置曾经无法使用——它同时继承两份骨架配置，
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合并后 backbone 混了两边的字段（tiny_conv 的 widths 混进 torchvision），构建时直接报错。
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"""
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pytest.importorskip("torch")
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from models.registry import BACKBONES
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cfg = load_config(config_path)
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# 聚类配置：pretrained 用顶层 backbone，simclr 用 simclr.backbone
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for backbone_cfg in (cfg.get("backbone"), cfg.get_path("simclr.backbone")):
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if not backbone_cfg:
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continue
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backbone_cfg = dict(backbone_cfg)
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if backbone_cfg.get("name") == "torchvision":
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backbone_cfg["pretrained"] = False # 单测里不下载 ImageNet 权重
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backbone = BACKBONES.build(backbone_cfg)
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assert backbone.out_channels > 0
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# 分类配置
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model_cfg = cfg.get("model")
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if model_cfg and "weights" in model_cfg:
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# 检测配置：model 是 ultralytics 的权重名（yolo26n.pt），不走本仓库的注册表，
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# 这里只确认它确实是个权重文件名。
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assert model_cfg["weights"].endswith(".pt")
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elif model_cfg:
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import torch
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from models import build_model
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model_cfg = dict(model_cfg)
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model_cfg.setdefault("num_classes", 3)
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model_cfg["init_from"] = None
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if model_cfg.get("backbone", {}).get("name") == "torchvision":
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model_cfg["backbone"] = {**model_cfg["backbone"], "pretrained": False}
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model = build_model(model_cfg)
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with torch.no_grad():
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assert model(torch.randn(1, 3, 64, 64)).shape[1] == model_cfg["num_classes"]
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@pytest.mark.parametrize(
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"override,expected_hint",
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[
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("simclr.optmizer.weight_decay=0.0", "optimizer"), # 少了个 i
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("simclr.optimizer.lrr=1e-3", "lr"), # 多了个 r
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("num_clusers=4", "num_clusters"), # 少了个 t
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],
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)
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def test_set_rejects_typos_with_suggestion(override, expected_hint):
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"""--set 打错字母会凭空造出没人读的键，训练照跑但改动无效——必须拦下并给出建议。"""
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with pytest.raises(KeyError) as excinfo:
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load_config("configs/cluster/film_simclr_resnet18.yaml", [override])
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assert expected_hint in str(excinfo.value)
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def test_set_accepts_existing_keys():
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cfg = load_config(
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"configs/cluster/film_simclr_resnet18.yaml",
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["simclr.optimizer.lr=0.001", "simclr.optimizer.weight_decay=0.0", "num_clusters=7"],
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)
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assert cfg["simclr"]["optimizer"]["lr"] == 0.001
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assert cfg["simclr"]["optimizer"]["weight_decay"] == 0.0
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assert cfg["num_clusters"] == 7
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def test_apply_overrides_can_add_keys_when_not_strict():
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from utils.config import apply_overrides
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assert apply_overrides({"a": {"b": 1}}, ["a.c=2"], strict=False) == {"a": {"b": 1, "c": 2}}
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