code: def linear_with_grad_accumulation_and_async_allreduce(
      input: torch.Tensor,
      weight: torch.Tensor,
      bias: Optional[torch.Tensor],
      gradient_accumulation_fusion: bool,
      async_grad_allreduce: bool,
      sequence_parallel_enabled: bool,
  ) -> torch.Tensor:
      args = _cast_if_autocast_enabled(
          input,
          weight,
          bias,
          gradient_accumulation_fusion,
          async_grad_allreduce,
          sequence_parallel_enabled,
      )
      with torch.cuda.amp.autocast(enabled=False):
          return LinearWithGradAccumulationAndAsyncCommunication.apply(
              *args
          )
  
imports: from typing import Optional, Dict, Tuple, List
  import warnings
  import torch
  import torch.nn.functional
  import torch.nn.init
  from torch.nn.parameter import Parameter
  from apex._autocast_utils import _cast_if_autocast_enabled
  from apex.transformer.parallel_state import get_tensor_model_parallel_group
  from apex.transformer.parallel_state import get_tensor_model_parallel_rank
  from apex.transformer.parallel_state import get_tensor_model_parallel_world_size
  from apex.transformer.utils import divide
  from apex.transformer.tensor_parallel.mappings import copy_to_tensor_model_parallel_region
  from apex.transformer.tensor_parallel.mappings import gather_from_tensor_model_parallel_region
  from apex.transformer.tensor_parallel.mappings import reduce_from_tensor_model_parallel_region
  from apex.transformer.tensor_parallel.mappings import scatter_to_tensor_model_parallel_region
  from apex.transformer.tensor_parallel.mappings import reduce_scatter_to_sequence_parallel_region
  from apex.transformer.tensor_parallel.random import get_cuda_rng_tracker
  from apex.transformer.tensor_parallel.utils import VocabUtility
  from apex.transformer.log_util import get_transformer_logger
label_desc: Use image node_id 7 for calling a global function with example usage: linear_with_grad_accumulation_and_async_allreduce(input, weight, bias, gradient_accumulation_fusion, async_grad_allreduce, sequence_parallel_enabled) and returns: LinearWithGradAccumulationAndAsyncCommunication