class_docstr: Gather the input from model parallel region and concatenate.
  
  Args:
      input_: input matrix.
      parallel_mode: parallel mode.
      dim: dimension
class_docstr_tok: ["Gather","the","input","from","model","parallel","region","and","concatenate",".","Args",":","input_",":","input","matrix",".","parallel_mode",":","parallel","mode",".","dim",":","dimension"]
code: def forward(ctx, input_, dim, process_group):
      ctx.process_group = process_group
      ctx.dim = dim
      return _gather(input_, dim, process_group)
  
imports: import torch
  import torch.distributed
  import torch.nn.functional
label_desc: Use image node_id 1 for calling the _GatherForwardSplitBackward obj's underlying member method code with example usage: obj.forward(ctx, input_, dim, process_group) and returns: _gather