Function func

python/paddle/tensor/layer_function_generator.py:132–162

(*args, **kwargs)

        return dtype

    def func(*args, **kwargs) -> Tensor:
        helper = LayerHelper(op_type, **kwargs)

        dtype = infer_and_check_dtype(op_proto, *args, **kwargs)

        inputs = {}
        for ipt in op_proto.inputs:
            name = _convert_(ipt.name)
            val = kwargs.pop(name, [])
            if not isinstance(val, list) and not isinstance(val, tuple):
                val = [val]
            if len(val) == 0 and len(args) != 0:
                val = args[0]
                args = args[1:]
            inputs[ipt.name] = val

        outputs = {}
        out = kwargs.pop(_convert_(o_name), [])
        if out:
            out_var = out[0] if isinstance(out, (list, tuple)) else out
        else:
            out_var = helper.create_variable_for_type_inference(dtype=dtype)
        outputs[o_name] = [out_var]
        for name in intermediate_output_names:
            outputs[name] = [
                helper.create_variable_for_type_inference(dtype=dtype)
            ]
        helper.append_op(
            type=op_type, inputs=inputs, outputs=outputs, attrs=kwargs
        )
        return helper.append_activation(out_var)

    func.__name__ = op_type
    return func