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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def make_tensor_value_info( name, # type: Text elem_type, # type: int shape, # type: Optional[Sequence[Union[Text, int]]] doc_string="", # type: Text shape_denotation=None, # type: Optional[List[Text]] """Makes a ValueInfoProto based on the data type and shape."""

    value_info_proto = ValueInfoProto()
    value_info_proto.name = name
    if doc_string:
        value_info_proto.doc_string = doc_string

    tensor_type_proto = value_info_proto.type.tensor_type
    tensor_type_proto.elem_type = elem_type

    tensor_shape_proto = tensor_type_proto.shape

    if shape is not None:
        # You might think this is a no-op (extending a normal Python
        # list by [] certainly is), but protobuf lists work a little
        # differently; if a field is never set, it is omitted from the
        # resulting protobuf; a list that is explicitly set to be
        # empty will get an (empty) entry in the protobuf. This
        # difference is visible to our consumers, so make sure we emit
        # an empty shape!
        tensor_shape_proto.dim.extend([])

        if shape_denotation:
            if len(shape_denotation) != len(shape):
                raise ValueError(
                    'Invalid shape_denotation. '
                    'Must be of the same length as shape.')

        for i, d in enumerate(shape):
            dim = tensor_shape_proto.dim.add()
            if d is None:
                pass
            elif isinstance(d, integer_types):
                dim.dim_value = d
            elif isinstance(d, text_type):
                dim.dim_param = d
            else:
                raise ValueError(
                    'Invalid item in shape: {}. '
                    'Needs to of integer_types or text_type.'.format(d))

            if shape_denotation:
                dim.denotation = shape_denotation[i]

    return value_info_proto