def binary_op(op_str, a, b):
if op_str == "+":
return a + b
elif op_str == "Add":
return ng.add(a, b)
elif op_str == "-":
return a - b
elif op_str == "Sub":
return ng.subtract(a, b)
elif op_str == "*":
return a * b
elif op_str == "Mul":
return ng.multiply(a, b)
elif op_str == "/":
return a / b
elif op_str == "Div":
return ng.divide(a, b)
elif op_str == "Equal":
return ng.equal(a, b)
elif op_str == "Greater":
return ng.greater(a, b)
elif op_str == "GreaterEq":
return ng.greater_equal(a, b)
elif op_str == "Less":
return ng.less(a, b)
elif op_str == "LessEq":
return ng.less_equal(a, b)
elif op_str == "Maximum":
return ng.maximum(a, b)
elif op_str == "Minimum":
return ng.minimum(a, b)
elif op_str == "NotEqual":
return ng.not_equal(a, b)
elif op_str == "Power":
return ng.power(a, b)
def Equal(onnx_node, ng_inputs): # type: (NodeWrapper, List[NgraphNode]) -> NgraphNode
"""Perform the `equal` logical operation elementwise on two input tensors."""
left, right = broadcast_for_binary_operation(onnx_node, ng_inputs)
return ng.equal(left, right)
def Not(onnx_node, ng_inputs): # type: (NodeWrapper, List[TensorOp]) -> Op
return ng.equal(ng_inputs[0] + 1, 1)
def Equal(onnx_node, ng_inputs): # type: (NodeWrapper, List[TensorOp]) -> Op
left, right = cast_axes_for_binary_broadcast(onnx_node, ng_inputs)
return ng.equal(left, right)