Merge Main (PR #204) and Complete Opset Versioning Implementation

src/qonnx/core/modelwrapper.py

@@ -39,7 +39,7 @@
 import qonnx.util.basic as util
 import qonnx.util.onnx as onnxutil
 from qonnx.core.datatype import DataType
-from qonnx.custom_op.registry import getCustomOp
+from qonnx.custom_op.registry import getCustomOp, is_custom_op
 from qonnx.transformation.double_to_single_float import DoubleToSingleFloat
 from qonnx.transformation.general import (
     RemoveStaticGraphInputs,
@@ -632,11 +632,11 @@ def get_nodes_by_op_type(self, op_type):
 
     def get_finn_nodes(self):
         """Returns a list of nodes where domain == 'qonnx.*'."""
-        return list(filter(lambda x: util.is_finn_op(x.domain), self.graph.node))
+        return list(filter(lambda x: is_custom_op(x.domain), self.graph.node))
 
     def get_non_finn_nodes(self):
         """Returns a list of nodes where domain != 'qonnx.*'."""
-        return list(filter(lambda x: not util.is_finn_op(x.domain), self.graph.node))
+        return list(filter(lambda x: not is_custom_op(x.domain), self.graph.node))
 
     def get_node_index(self, node):
         """Returns current index of given node, or None if not found."""

src/qonnx/core/onnx_exec.py

@@ -35,10 +35,10 @@
 
 import qonnx.analysis.topology as ta
 import qonnx.core.execute_custom_node as ex_cu_node
+from qonnx.custom_op.registry import is_custom_op
 from qonnx.util.basic import (
     get_preferred_qonnx_opset,
     get_sanitize_quant_tensors,
-    is_finn_op,
     qonnx_make_model,
     sanitize_quant_values,
 )
@@ -49,7 +49,7 @@ def execute_node(node, context, graph, opset_version, return_full_exec_context=F
 
     Input/output provided via context."""
 
-    if is_finn_op(node.domain):
+    if is_custom_op(node.domain, node.op_type):
         ex_cu_node.execute_custom_node(node, context, graph, onnx_opset_version=opset_version)
     else:
         # onnxruntime unfortunately does not implement run_node as defined by ONNX,

src/qonnx/custom_op/base.py

@@ -36,7 +36,27 @@
 class CustomOp(ABC):
     """CustomOp class all custom op nodes are based on. Contains different functions
     every custom node should have. Some as abstract methods, these have to be
-    filled when writing a new custom op node."""
+    filled when writing a new custom op node.
+
+    Opset Version Support:
+        CustomOp classes use "since version" semantics matching ONNX operators.
+        Version is determined by the class name using _vN suffix convention:
+
+        - No suffix (e.g., IntQuant): Version 1 (default)
+        - _vN suffix (e.g., IntQuant_v2): Version N
+
+        The registry automatically selects the highest version <= requested opset.
+
+        Example:
+            class IntQuant(CustomOp):
+                pass  # Version 1 (no suffix)
+
+            class IntQuant_v2(CustomOp):
+                pass  # Version 2, covers opset v2-v3 (if no v3 exists)
+
+            class IntQuant_v4(CustomOp):
+                pass  # Version 4, covers opset v4+
+    """
 
     def __init__(self, onnx_node, onnx_opset_version=get_preferred_qonnx_opset()):
         super().__init__()

src/qonnx/custom_op/channels_last/__init__.py

@@ -1,29 +1,6 @@
+# Importing registers CustomOps in qonnx.custom_op.channels_last domain
 from qonnx.custom_op.channels_last.batch_normalization import BatchNormalization
 from qonnx.custom_op.channels_last.conv import Conv
 from qonnx.custom_op.channels_last.max_pool import MaxPool
 
-# channels-last ops are defined by the underlying ONNX standard op
-# thus, we can define them for any version of the original op
-# so we emulate a custom op dictionary that mimics the support for any
-# {ChannelsLastOp}_vX instead of hardcoding what versions are supported
-
-
-class ChannelsLastCustomOpDict(dict):
-    def __init__(self):
-        self._custom_ops = {"Conv": Conv, "MaxPool": MaxPool, "BatchNormalization": BatchNormalization}
-
-    def __getitem__(self, key):
-        base_key = key.split("_v")[0]  # Extract base key (e.g., Conv from Conv_v13)
-        if base_key in self._custom_ops:
-            return self._custom_ops[base_key]
-        raise KeyError(f"Channels-last CustomOp '{key}' not found.")
-
-    def __contains__(self, key):
-        base_key = key.split("_v")[0]
-        return base_key in self._custom_ops
-
-    def keys(self):
-        return self._custom_ops.keys()
-
-
-custom_op = ChannelsLastCustomOpDict()
+__all__ = ["Conv", "MaxPool", "BatchNormalization"]

src/qonnx/custom_op/channels_last/batch_normalization.py

@@ -33,6 +33,7 @@
 
 
 class BatchNormalization(ChannelsLastWrappedOp):
+
     def get_nodeattr_types(self):
         """Returns a dict of permitted attributes for node, where:
         ret_dict[attribute_name] = (dtype, require, default_value, <allowed_values>)

src/qonnx/custom_op/channels_last/conv.py

@@ -34,6 +34,7 @@
 
 
 class Conv(ChannelsLastWrappedOp):
+
     def get_nodeattr_types(self):
         """Returns a dict of permitted attributes for node, where:
         ret_dict[attribute_name] = (dtype, require, default_value, <allowed_values>)

src/qonnx/custom_op/channels_last/max_pool.py

@@ -34,6 +34,7 @@
 
 
 class MaxPool(ChannelsLastWrappedOp):
+
     def get_nodeattr_types(self):
         """Returns a dict of permitted attributes for node, where:
         ret_dict[attribute_name] = (dtype, require, default_value, <allowed_values>)

src/qonnx/custom_op/general/__init__.py

@@ -26,6 +26,7 @@
 # OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
 # OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
 
+# Importing registers CustomOps in qonnx.custom_op.general domain
 from qonnx.custom_op.general.bipolar_quant import BipolarQuant
 from qonnx.custom_op.general.debugmarker import DebugMarker
 from qonnx.custom_op.general.floatquant import FloatQuant
@@ -35,33 +36,21 @@
 from qonnx.custom_op.general.maxpoolnhwc import MaxPoolNHWC
 from qonnx.custom_op.general.multithreshold import MultiThreshold
 from qonnx.custom_op.general.quantavgpool2d import QuantAvgPool2d
+from qonnx.custom_op.general.quant import Quant
 from qonnx.custom_op.general.trunc import Trunc
 from qonnx.custom_op.general.xnorpopcount import XnorPopcountMatMul
 
-custom_op = dict()
-
-custom_op["DebugMarker"] = DebugMarker
-custom_op["QuantAvgPool2d"] = QuantAvgPool2d
-custom_op["MaxPoolNHWC"] = MaxPoolNHWC
-custom_op["GenericPartition"] = GenericPartition
-custom_op["MultiThreshold"] = MultiThreshold
-custom_op["XnorPopcountMatMul"] = XnorPopcountMatMul
-custom_op["Im2Col"] = Im2Col
-custom_op["IntQuant"] = IntQuant
-custom_op["Quant"] = IntQuant
-custom_op["Trunc"] = Trunc
-custom_op["BipolarQuant"] = BipolarQuant
-custom_op["FloatQuant"] = FloatQuant
-
-custom_op["DebugMarker_v1"] = DebugMarker
-custom_op["QuantAvgPool2d_v1"] = QuantAvgPool2d
-custom_op["MaxPoolNHWC_v1"] = MaxPoolNHWC
-custom_op["GenericPartition_v1"] = GenericPartition
-custom_op["MultiThreshold_v1"] = MultiThreshold
-custom_op["XnorPopcountMatMul_v1"] = XnorPopcountMatMul
-custom_op["Im2Col_v1"] = Im2Col
-custom_op["IntQuant_v1"] = IntQuant
-custom_op["Quant_v1"] = IntQuant
-custom_op["Trunc_v1"] = Trunc
-custom_op["BipolarQuant_v1"] = BipolarQuant
-custom_op["FloatQuant_v1"] = FloatQuant
+__all__ = [
+    "BipolarQuant",
+    "DebugMarker",
+    "FloatQuant",
+    "GenericPartition",
+    "Im2Col",
+    "IntQuant",
+    "MaxPoolNHWC",
+    "MultiThreshold",
+    "Quant",
+    "QuantAvgPool2d",
+    "Trunc",
+    "XnorPopcountMatMul",
+]

src/qonnx/custom_op/general/debugmarker.py

@@ -32,6 +32,7 @@
 
 
 class DebugMarker(CustomOp):
+
     def get_nodeattr_types(self):
         return {"export_debug_name": ("s", True, "")}
 

src/qonnx/custom_op/general/im2col.py

@@ -141,6 +141,7 @@ def im2col_indices_nchw(
 
 
 class Im2Col(CustomOp):
+
     def get_nodeattr_types(self):
         return {
             # stride and shape of convolution kernel