Added import of quantized modules so they get registered

src/super_gradients/modules/__init__.py

@@ -3,7 +3,7 @@
 from .repvgg_block import RepVGGBlock
 from .se_blocks import SEBlock, EffectiveSEBlock
 from .skip_connections import Residual, SkipConnection, CrossModelSkipConnection, BackboneInternalSkipConnection, HeadInternalSkipConnection
-
+from super_gradients.common.abstractions.abstract_logger import get_logger
 
 __all__ = [
     "ConvBNAct",
@@ -17,3 +17,30 @@
     "BackboneInternalSkipConnection",
     "HeadInternalSkipConnection",
 ]
+
+logger = get_logger(__name__)
+try:
+    # flake8 respects only the first occurence of __all__ defined in the module's root
+    from .quantization import QuantBottleneck  # noqa: F401
+    from .quantization import QuantResidual  # noqa: F401
+    from .quantization import QuantSkipConnection  # noqa: F401
+    from .quantization import QuantCrossModelSkipConnection  # noqa: F401
+    from .quantization import QuantBackboneInternalSkipConnection  # noqa: F401
+    from .quantization import QuantHeadInternalSkipConnection  # noqa: F401
+
+    quant_extensions = [
+        "QuantBottleneck",
+        "QuantResidual",
+        "QuantSkipConnection",
+        "QuantCrossModelSkipConnection",
+        "QuantBackboneInternalSkipConnection",
+        "QuantHeadInternalSkipConnection",
+    ]
+
+except (ImportError, NameError, ModuleNotFoundError) as import_err:
+    logger.warning(f"Failed to import pytorch_quantization: {import_err}")
+    quant_extensions = None
+
+
+if quant_extensions is not None:
+    __all__.extend(quant_extensions)