diff --git a/src/finn/custom_op/fpgadataflow/eltwise.py b/src/finn/custom_op/fpgadataflow/eltwise.py index a7b9c814e274e3df87fdcbc04ec9ca36ba1076e0..d6284750c73026c09fb7986ffc2517ed9ae3b153 100644 --- a/src/finn/custom_op/fpgadataflow/eltwise.py +++ b/src/finn/custom_op/fpgadataflow/eltwise.py @@ -42,21 +42,25 @@ class StreamingEltwise(HLSCustomOp): super().__init__(onnx_node) def get_nodeattr_types(self): - my_attrs = { - "NumChannels": ("i", True, ""), - "PE": ("i", True, ""), - # FINN DataTypes for inputs; output datatype inferred from input - "inputDataType0": ("s", True, ""), - "inputDataType1": ("s", True, ""), - # type of EltwiseFunction for the operation - "eltwiseOp": ("s", True, "", ["Add", "Sub", "AbsDiff"]), - # number of input vectors, examples: - # [1] is a single vector (like a FC layer with batch=1) - # [4] is four vectors (like a FC layer with batch=4) - # [1, 4, 4] is four * four vectors (like a conv layer with batch=1) - "numInputVectors": ("ints", False, [1]), - } - my_attrs.update(super().get_nodeattr_types()) + + my_attrs = super().get_nodeattr_types() + my_attrs.update( + { + "NumChannels": ("i", True, ""), + "PE": ("i", True, ""), + # FINN DataTypes for inputs; output datatype inferred from input + "inputDataType0": ("s", True, ""), + "inputDataType1": ("s", True, ""), + # type of EltwiseFunction for the operation + "eltwiseOp": ("s", True, "", ["Add", "Sub", "AbsDiff"]), + # number of input vectors, examples: + # [1] is a single vector (like a FC layer with batch=1) + # [4] is four vectors (like a FC layer with batch=4) + # [1, 4, 4] is four * four vectors (like a conv layer with batch=1) + "numInputVectors": ("ints", False, [1]), + "inFIFODepths": ("ints", False, [2, 2]), + } + ) return my_attrs def get_eltwise_op_lambda(self):