class_docstr: Custom FX tracer for torchrec
  
  See `Torch.FX documentation <https://pytorch.org/docs/stable/fx.html>`_
  
  We create a custom FX tracer to trace torchrec based models. The custom tracer
  handles python generic types (i.e. NoWait[T], Awaitable[T]) and lower it to
  TorchScript if needed
docstr: Override FX definition to include quantized embedding bags
docstr_tok: ["Override","FX","definition","to","include","quantized","embedding","bags"]
code: def is_leaf_module(
      self, m: torch.nn.Module, module_qualified_name: str
  ) -> bool:
      """
      Override FX definition to include quantized embedding bags
      """
      if type(m).__name__ in self._leaf_modules:
          return True
      return super().is_leaf_module(m, module_qualified_name)
  
file_path: torchrec/torchrec/fx/tracer.py
imports: from typing import Any, Callable, Dict, List, Optional, Union
  import torch
  from torch.fx._compatibility import compatibility
  from torch.fx.graph import Graph
  from torch.fx.node import Argument
  from torchrec.distributed.types import LazyAwaitable, NoWait
  from torchrec.fx.utils import dmp_fx_trace_forward
label_desc: Use image node_id 2 for calling the Tracer obj's underlying member method code with example usage: obj.is_leaf_module(m, module_qualified_name) and returns: super, True