code: def _gather_along_first_dim(input_: torch.Tensor) -> torch.Tensor:
      """Gather tensors and concatenate along the first dimension."""
      world_size = get_tensor_model_parallel_world_size()
      # Bypass the function if we are using only 1 GPU.
      if world_size == 1:
          return input_
  
      shape = list(input_.shape)
      shape[0] *= world_size
  
      output = torch.empty(
          shape, dtype=input_.dtype, device=torch.cuda.current_device()
      )
      torch.distributed.all_gather_into_tensor(
          output,
          input_.contiguous(),
          group=get_tensor_model_parallel_group(),
      )
      return output
  
imports: import torch
  from apex.transformer.parallel_state import get_tensor_model_parallel_group
  from apex.transformer.parallel_state import get_tensor_model_parallel_world_size
  from apex.transformer.parallel_state import get_tensor_model_parallel_rank
  from apex.transformer.tensor_parallel.utils import split_tensor_along_last_dim
label_desc: Use image node_id 5 for calling a global function with example usage: _gather_along_first_dim(input_) and returns: output, input_