def dynamic_inputs_outputs()

in python/graph_util.py [0:0]

• 65 lines of code
• 40 McCabe index (conditional complexity)

    def dynamic_inputs_outputs(self, op):
        if op.type in DynamicBatchSizeHelper.unary_ops:
            return list(op.inputs), op.outputs
        elif op.type in DynamicBatchSizeHelper.binary_broadcast_ops:
            shape0, shape1 = [ts.shape for ts in op.inputs]
            if shape0.rank is None or shape1.rank is None:
                return [], []
            if shape0.rank > shape1.rank:
                return [op.inputs[0]], op.outputs
            elif shape0.rank < shape1.rank:
                return [op.inputs[1]], op.outputs
            else:  # same rank
                inputs = []
                if len(shape0) > 0 and shape0.as_list()[0] is None:
                    inputs.append(op.inputs[0])
                if len(shape1) > 0 and shape0.as_list()[0] is None:
                    inputs.append(op.inputs[1])
                return inputs, op.outputs
        elif op.type in DynamicBatchSizeHelper.reduce_axis_ops:
            axis_op = op.inputs[-1].op
            if axis_op.type == 'Const':
                axis_list = _get_int32_values(axis_op)
                if axis_list and 0 not in axis_list:
                    return list(op.inputs[:-1]), op.outputs
        elif op.type in DynamicBatchSizeHelper.pseudo_unary_ops:
            return list(op.inputs[:1]), op.outputs
        elif op.type in {'Concat', 'ConcatV2'}:
            axis_op = op.inputs[-1].op
            if axis_op.type == 'Const':
                axis_list = _get_int32_values(axis_op)
                if any(axis < 0 for axis in axis_list):
                    rank = op.inputs[0].shape.rank
                    if rank is None:
                        return [], []
                    axis_list = [axis if axis >= 0 else (axis + rank) for axis in axis_list]
                if axis_list and 0 not in axis_list:
                    return list(op.inputs[:-1]), op.outputs
        elif op.type == 'ExpandDims':
            pass
        elif op.type == 'Stack':
            pass
        elif op.type in {'BatchMatMul', 'BatchMatMulV2'}:
            pass
        elif op.type == 'Cumprod':
            pass
        elif op.type == 'Cumsum':
            pass
        elif op.type == 'MatMul':
            if not op.node_def.attr['transpose_a'].b:
                return list(op.inputs[:1]), op.outputs
        elif op.type == 'Slice':
            pass
        elif op.type == 'StridedSlice':
            pass
        elif op.type == 'Shape':
            pass
        elif op.type == 'Reshape':
            pass
        elif op.type == 'Squeeze':
            pass
        elif op.type == 'Transpose':
            pass
        elif op.type == 'Unstack':
            pass
        return [], []