Max/hotfixes

_version.py

@@ -28,7 +28,7 @@
 commit_id: COMMIT_ID
 __commit_id__: COMMIT_ID
 
-__version__ = version = '0.1.dev140+ge3e4fd1c6.d20260301'
-__version_tuple__ = version_tuple = (0, 1, 'dev140', 'ge3e4fd1c6.d20260301')
+__version__ = version = '0.1.dev161+g47a99b31a.d20260304'
+__version_tuple__ = version_tuple = (0, 1, 'dev161', 'g47a99b31a.d20260304')
 
-__commit_id__ = commit_id = 'ge3e4fd1c6'
+__commit_id__ = commit_id = 'g47a99b31a'

negate/__init__.py

@@ -1,29 +1,99 @@
 # SPDX-License-Identifier: MPL-2.0 AND LicenseRef-Commons-Clause-License-Condition-1.0
 # <!-- // /*  d a r k s h a p e s */ -->
-# ruff: noqa
-
-from datasets import logging as ds_logging, disable_progress_bars as ds_disable_progress_bars
-from huggingface_hub import logging as hf_logging
-from huggingface_hub.utils.tqdm import disable_progress_bars as hf_disable_progress_bars
-from transformers import logging as tf_logging
-from diffusers.utils import logging as df_logging
-from timm.utils.log import setup_default_logging
+
+from __future__ import annotations
+
+import importlib
 import logging
 import warnings
+from typing import Any
+
+__all__ = [
+    "Blurb",
+    "InferContext",
+    "Spec",
+    "build_train_call",
+    "chart_decompositions",
+    "compute_weighted_certainty",
+    "configure_runtime_logging",
+    "end_processing",
+    "infer_origin",
+    "load_metadata",
+    "load_spec",
+    "pretrain",
+    "root_folder",
+    "run_training_statistics",
+    "save_features",
+    "save_train_result",
+    "train_model",
+    "training_loop",
+]
+
+_ATTR_SOURCES = {
+    "Blurb": ("negate.io.blurb", "Blurb"),
+    "InferContext": ("negate.inference", "InferContext"),
+    "Spec": ("negate.io.spec", "Spec"),
+    "build_train_call": ("negate.train", "build_train_call"),
+    "chart_decompositions": ("negate.metrics.track", "chart_decompositions"),
+    "compute_weighted_certainty": ("negate.metrics.heuristics", "compute_weighted_certainty"),
+    "end_processing": ("negate.io.save", "end_processing"),
+    "infer_origin": ("negate.inference", "infer_origin"),
+    "load_metadata": ("negate.io.spec", "load_metadata"),
+    "load_spec": ("negate.io.spec", "load_spec"),
+    "pretrain": ("negate.train", "pretrain"),
+    "root_folder": ("negate.io.config", "root_folder"),
+    "run_training_statistics": ("negate.metrics.track", "run_training_statistics"),
+    "save_features": ("negate.io.save", "save_features"),
+    "save_train_result": ("negate.io.save", "save_train_result"),
+    "train_model": ("negate.train", "train_model"),
+    "training_loop": ("negate.train", "training_loop"),
+}
+
+_LOGGING_CONFIGURED = False
+
+
+def configure_runtime_logging() -> None:
+    """Apply quiet logging defaults for third-party ML stacks."""
+
+    global _LOGGING_CONFIGURED
+    if _LOGGING_CONFIGURED:
+        return
+
+    warnings.filterwarnings("ignore", category=UserWarning)
+    warnings.filterwarnings("ignore", category=DeprecationWarning)
+
+    try:
+        from datasets import logging as ds_logging, disable_progress_bars as ds_disable_progress_bars
+        from diffusers.utils import logging as df_logging
+        from huggingface_hub import logging as hf_logging
+        from huggingface_hub.utils.tqdm import disable_progress_bars as hf_disable_progress_bars
+        from timm.utils.log import setup_default_logging
+        from transformers import logging as tf_logging
+    except Exception:
+        # Keep startup resilient when optional deps are absent.
+        _LOGGING_CONFIGURED = True
+        return
+
+    setup_default_logging(logging.ERROR)
+    for logger in [df_logging, ds_logging, hf_logging, tf_logging]:
+        logger.set_verbosity_error()
 
-warnings.filterwarnings("ignore", category=UserWarning)
-warnings.filterwarnings("ignore", category=DeprecationWarning)
-setup_default_logging(logging.ERROR)
-for logger in [df_logging, ds_logging, hf_logging, tf_logging]:
-    logger.set_verbosity_error()
     ds_disable_progress_bars()
     hf_disable_progress_bars()
+    _LOGGING_CONFIGURED = True
+
+
+def __getattr__(name: str) -> Any:
+    source = _ATTR_SOURCES.get(name)
+    if source is None:
+        raise AttributeError(name)
+
+    module_name, attr_name = source
+    module = importlib.import_module(module_name)
+    value = getattr(module, attr_name)
+    globals()[name] = value
+    return value
+
 
-from negate.io.blurb import Blurb
-from negate.io.config import root_folder
-from negate.io.spec import Spec, load_spec, load_metadata
-from negate.metrics.track import chart_decompositions, run_training_statistics
-from negate.train import build_train_call, pretrain, train_model, training_loop
-from negate.io.save import save_train_result, end_processing, save_features
-from negate.metrics.heuristics import compute_weighted_certainty
-from negate.inference import infer_origin, InferContext
+def __dir__() -> list[str]:
+    return sorted(set(globals()) | set(__all__))