code: def gather(cls, comm, in_array, out_array, root=0, stream=None):
      # TODO(ecastill) out_array needs to have comm size in shape[0]
      if out_array.shape[0] != comm._n_devices:
          raise RuntimeError(
              f"gather requires out_array to have {comm._n_devices}"
              f"elements in its first dimension, found {out_array.shape}"
          )
      comm._check_contiguous(in_array)
      comm._check_contiguous(out_array)
      stream = comm._get_stream(stream)
      nccl.groupStart()
      if root == comm.rank:
          for i in range(comm._n_devices):
              array = out_array[i]
              odtype, ocount = _get_nccl_dtype_and_count(array)
              cls._recv(comm, array, i, odtype, ocount, stream)
      dtype, count = _get_nccl_dtype_and_count(in_array)
      cls._send(comm, in_array, root, dtype, count, stream)
      nccl.groupEnd()
  
imports: import numpy
  import warnings
  import cupy
  from cupy.cuda import nccl
  from cupyx.distributed import _store
  from cupyx.distributed._comm import _Backend
  from cupyx.scipy import sparse
label_desc: Use image node_id 12 for calling the _DenseNCCLCommunicator obj's underlying member method code with example usage: obj.gather(cls, comm, in_array, out_array, root, stream) without return types