Enable dedicated MMSeg full mmcv runtime
This commit is contained in:
@@ -13,20 +13,53 @@ from typing import Any
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from .config import settings
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def _run_command(command: list[str], cwd: Path | None = None, timeout: int = 60) -> dict[str, Any]:
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try:
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result = subprocess.run(
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command,
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cwd=str(cwd or settings.project_root),
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capture_output=True,
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text=True,
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timeout=timeout,
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)
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return {
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"passed": result.returncode == 0,
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"returncode": result.returncode,
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"stdout": result.stdout[-4000:],
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"stderr": result.stderr[-4000:],
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}
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except subprocess.TimeoutExpired as exc:
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return {
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"passed": False,
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"returncode": None,
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"stdout": (exc.stdout or "")[-4000:] if isinstance(exc.stdout, str) else "",
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"stderr": (exc.stderr or "")[-4000:] if isinstance(exc.stderr, str) else "",
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"error": f"command timed out after {timeout}s",
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}
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except Exception as exc:
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return {"passed": False, "returncode": None, "stdout": "", "stderr": "", "error": str(exc)}
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def _run_snippet(code: str, cwd: Path | None = None, timeout: int = 60) -> dict[str, Any]:
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result = subprocess.run(
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[sys.executable, "-c", code],
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cwd=str(cwd or settings.project_root),
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capture_output=True,
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text=True,
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timeout=timeout,
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)
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return {
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"passed": result.returncode == 0,
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"returncode": result.returncode,
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"stdout": result.stdout[-4000:],
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"stderr": result.stderr[-4000:],
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}
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return _run_command([sys.executable, "-c", code], cwd=cwd, timeout=timeout)
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def _run_conda_snippet(env_name: str, code: str, cwd: Path | None = None, timeout: int = 60) -> dict[str, Any]:
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detail = _run_command(["conda", "run", "-n", env_name, "python", "-c", code], cwd=cwd, timeout=timeout)
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detail["env"] = env_name
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return detail
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MMSEG_FULL_BUILD_SNIPPET = (
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"from mmseg.utils import register_all_modules; "
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"register_all_modules(init_default_scope=True); "
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"from mmengine.config import Config; "
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"from mmseg.registry import MODELS; "
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"import mmcv._ext; "
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"cfg=Config.fromfile({config_path!r}); "
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"model=MODELS.build(cfg.model); "
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"print(type(model).__name__)"
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)
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def _request_json(method: str, url: str, payload: dict[str, Any] | None = None, timeout: int = 10) -> dict[str, Any]:
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@@ -182,13 +215,23 @@ def run_model_family_readiness() -> dict[str, Any]:
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"required": True,
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"detail": {"passed": mmseg_pretrained.exists(), "path": str(mmseg_pretrained), "size": mmseg_pretrained.stat().st_size if mmseg_pretrained.exists() else 0},
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},
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{
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"name": "mmseg_full_env_imports",
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"required": True,
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"detail": _run_conda_snippet(
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settings.mmseg_conda_env,
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"import torch, cv2, mmcv, mmengine, mmseg; "
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"import mmcv._ext; "
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"print(torch.__version__, torch.version.cuda, cv2.__version__, mmcv.__version__, mmseg.__version__)",
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timeout=90,
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),
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},
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{
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"name": "mmseg_full_model_build",
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"required": False,
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"detail": _run_snippet(
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"from mmengine.config import Config; from mmseg.registry import MODELS; "
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f"cfg=Config.fromfile({str(mmseg_config)!r}); "
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"model=MODELS.build(cfg.model); print(type(model).__name__)",
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"required": True,
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"detail": _run_conda_snippet(
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settings.mmseg_conda_env,
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MMSEG_FULL_BUILD_SNIPPET.format(config_path=str(mmseg_config)),
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timeout=90,
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),
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},
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@@ -55,21 +55,36 @@ def validate_project(run_build: bool = False) -> dict:
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checks.append({"name": "weights_manifest_present", "passed": manifest.get("count", 0) >= 1})
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checks.append({"name": "gpus_query", "passed": bool(get_gpus().get("available"))})
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env_names = [item["name"] for item in get_conda_envs().get("envs", [])]
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checks.append({"name": "seg_smp_env_exists", "passed": "seg_smp" in env_names})
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checks.append({"name": "task_env_exists", "passed": settings.task_conda_env in env_names, "detail": {"env": settings.task_conda_env}})
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checks.append({"name": "mmseg_env_exists", "passed": settings.mmseg_conda_env in env_names, "detail": {"env": settings.mmseg_conda_env}})
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smoke = _run(
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[
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"conda",
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"run",
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"-n",
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"seg_smp",
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settings.task_conda_env,
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"python",
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"-c",
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"import fastapi, uvicorn, torch, cv2, segmentation_models_pytorch, ultralytics, albumentations, mmengine, mmseg, mmcv; print(torch.__version__, torch.cuda.is_available())",
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],
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cwd=settings.project_root,
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)
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checks.append({"name": "seg_smp_backend_smoke", "passed": smoke["passed"], "detail": smoke})
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checks.append({"name": "task_env_backend_smoke", "passed": smoke["passed"], "detail": smoke})
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mmseg_smoke = _run(
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[
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"conda",
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"run",
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"-n",
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settings.mmseg_conda_env,
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"python",
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"-c",
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"import torch, cv2, mmcv, mmengine, mmseg; import mmcv._ext; print(torch.__version__, torch.version.cuda, cv2.__version__, mmcv.__version__, mmseg.__version__)",
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],
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cwd=settings.project_root,
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)
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checks.append({"name": "mmseg_env_full_mmcv_smoke", "passed": mmseg_smoke["passed"], "detail": mmseg_smoke})
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no_weight = _run(["bash", "scripts/check_no_weight_git.sh"], cwd=settings.project_root)
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checks.append({"name": "no_weight_in_git", "passed": no_weight["passed"], "detail": no_weight})
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@@ -20,6 +20,7 @@ class Settings:
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log_dir: Path
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weights_root: Path
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task_conda_env: str
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mmseg_conda_env: str
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backend_conda_env: str
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weight_mode: str
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enable_shell_tasks: bool
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@@ -46,6 +47,7 @@ def get_settings() -> Settings:
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log_dir=log_dir,
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weights_root=weights_root,
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task_conda_env=os.getenv("SEG_TASK_CONDA_ENV", "seg_smp"),
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mmseg_conda_env=os.getenv("SEG_MMSEG_CONDA_ENV", "seg_mmcv"),
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backend_conda_env=os.getenv("SEG_BACKEND_CONDA_ENV", "seg_smp"),
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weight_mode=os.getenv("SEG_WEIGHT_MODE", "copy"),
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enable_shell_tasks=os.getenv("SEG_ENABLE_SHELL_TASKS", "1") == "1",
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@@ -157,7 +157,8 @@ def build_task_checks() -> list[dict[str, Any]]:
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for task in TASK_TYPES:
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params = TASK_DEFAULTS.get(task, {})
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try:
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spec = build_module_task(task, dict(params), settings.task_conda_env)
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conda_env = settings.mmseg_conda_env if task.startswith("mmseg.") else settings.task_conda_env
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spec = build_module_task(task, dict(params), conda_env)
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script_path = _command_script_path(spec.command) if spec else None
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checks.append(
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{
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@@ -17,8 +17,14 @@ _running: dict[str, subprocess.Popen] = {}
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_lock = threading.Lock()
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def default_conda_env_for_job(job_type: str) -> str:
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if job_type.startswith("mmseg."):
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return settings.mmseg_conda_env
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return settings.task_conda_env
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def _build_task(request: JobCreate) -> CommandSpec:
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conda_env = request.conda_env or settings.task_conda_env
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conda_env = request.conda_env or default_conda_env_for_job(request.type)
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spec = build_module_task(request.type, request.params, conda_env)
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if spec is None:
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raise ValueError(f"unsupported job type: {request.type}")
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@@ -113,4 +119,3 @@ def cancel_job(job_id: str) -> dict | None:
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except ProcessLookupError:
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pass
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return db.get_job(job_id)
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@@ -60,7 +60,7 @@ def get_conda_envs() -> dict:
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parts = raw.replace("*", " ").split()
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if len(parts) >= 2:
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envs.append({"name": parts[0], "path": parts[-1], "active": marker})
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return {"available": True, "envs": envs, "task_default": settings.task_conda_env}
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return {"available": True, "envs": envs, "task_default": settings.task_conda_env, "mmseg_default": settings.mmseg_conda_env}
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def disk_usage() -> dict:
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@@ -103,4 +103,3 @@ def scan_results() -> list[dict]:
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continue
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results.sort(key=lambda item: item["modified"], reverse=True)
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return results[:1000]
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@@ -23,6 +23,7 @@ def test_project_var_artifact_path_is_served(tmp_path, monkeypatch):
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log_dir=original.log_dir,
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weights_root=original.weights_root,
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task_conda_env=original.task_conda_env,
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mmseg_conda_env=original.mmseg_conda_env,
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backend_conda_env=original.backend_conda_env,
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weight_mode=original.weight_mode,
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enable_shell_tasks=original.enable_shell_tasks,
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6
backend/tests/test_jobs.py
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6
backend/tests/test_jobs.py
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@@ -0,0 +1,6 @@
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from app.jobs import default_conda_env_for_job
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def test_mmseg_jobs_use_mmseg_conda_env_by_default():
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assert default_conda_env_for_job("mmseg.train") == "seg_mmcv"
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assert default_conda_env_for_job("segmodel.train") == "seg_smp"
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