code: def create_lazy_tensor(
      self, first_tensor_name: Optional[str] = None
  ) -> str:
      # xla uses an instance method for tensor creation, for the time being
      if self.create_from_first_tensor:
          # TODO(whc) remove this if XLA switches to using static method for creation
          assert (
              first_tensor_name is not None
          ), "Requires first tensor to create lazy tensor"
          return f"{first_tensor_name}.{self.create_tensor}"
      return f"{self.backend_namespace}::{self.create_tensor}"
  
imports: import itertools
  from abc import ABC
  from dataclasses import dataclass
  from typing import Any, Dict, List, Optional, Tuple, Union
  import torchgen.api.dispatcher
  from torchgen.api.lazy import getValueT, isValueType, LazyArgument, LazyIrProperties, LazyIrSchema, tensorListValueT
  from torchgen.api.translate import translate
  from torchgen.api.types import BaseCType, Binding, deviceT, DispatcherSignature, kernel_signature, NativeSignature, OptionalCType, VectorCType
  from torchgen.context import method_with_native_function
  from torchgen.dest.lazy_ts_lowering import ts_lowering_body
  from torchgen.model import Argument, BackendIndex, BackendMetadata, BaseTy, BaseType, FunctionSchema, ListType, NativeFunction, NativeFunctionsGroup
label_desc: Use image node_id 7 for calling the GenLazyNativeFuncDefinition obj's underlying member method code with example usage: obj.create_lazy_tensor(first_tensor_name) and returns: self, str, self, first_tensor_name, str, self