code: def torch_trace_handler():
      """Create a trace handler for traces generated by the profiler.
  
       Provide as an argument to `torch.profiler.profile`:
       ```python
       torch.profiler.profile(..., on_trace_ready=wandb.profiler.torch_trace_handler())
       ```
  
      Calling this function ensures that profiler charts & tables can be viewed in your run dashboard
      on wandb.ai.
  
      Please note that `wandb.init()` must be called before this function is invoked.
      The PyTorch (torch) version must also be at least 1.9, in order to ensure stability
      of their Profiler API.
  
      Args:
          None
  
      Returns:
          None
  
      Raises:
          UsageError if wandb.init() hasn't been called before profiling.
          Error if torch version is less than 1.9.0.
  
      Examples:
      ```python
      run = wandb.init()
      run.config.id = "profile_code"
  
      with torch.profiler.profile(
          schedule=torch.profiler.schedule(wait=1, warmup=1, active=3, repeat=1),
          on_trace_ready=wandb.profiler.torch_trace_handler(),
          record_shapes=True,
          with_stack=True,
      ) as prof:
          for i, batch in enumerate(dataloader):
              if step >= 5:
                  break
              train(batch)
              prof.step()
      ```
      """
      from pkg_resources import parse_version
  
      torch = wandb.util.get_module(PYTORCH_MODULE, required=True)
      torch_profiler = wandb.util.get_module(
          PYTORCH_PROFILER_MODULE, required=True
      )
  
      if parse_version(torch.__version__) < parse_version("1.9.0"):
          raise Error(
              f"torch version must be at least 1.9 in order to use the PyTorch Profiler API.\
              \nVersion of torch currently installed: {torch.__version__}"
          )
  
      try:
          logdir = os.path.join(wandb.run.dir, "pytorch_traces")  # type: ignore
          os.mkdir(logdir)
      except AttributeError:
          raise UsageError(
              "Please call `wandb.init()` before `wandb.profiler.torch_trace_handler()`"
          ) from None
  
      with telemetry.context() as tel:
          tel.feature.torch_profiler_trace = True
  
      return torch_profiler.tensorboard_trace_handler(logdir)
  
imports: import os
  import wandb
  from wandb.errors import Error, UsageError
  from wandb.sdk.lib import telemetry
label_desc: Use image node_id 1 for calling a global function with example usage: torch_trace_handler() and returns: torch_profiler