code: def meta_cuda_rnn(
      input,
      weight,
      weight_stride0,
      weight_buf,
      hx,
      cx,
      mode,
      hidden_size,
      proj_size,
      num_layers,
      batch_first,
      dropout,
      train,
      bidirectional,
      batch_sizes,
      dropout_state,
  ):
      is_input_packed = len(batch_sizes) != 0
      if is_input_packed:
          seq_length = len(batch_sizes)
          mini_batch = batch_sizes[0]
          batch_sizes_sum = input.shape[0]
      else:
          seq_length = input.shape[1] if batch_first else input.shape[0]
          mini_batch = input.shape[0] if batch_first else input.shape[1]
          batch_sizes_sum = -1
  
      num_directions = 2 if bidirectional else 1
      out_size = proj_size if proj_size != 0 else hidden_size
      if is_input_packed:
          out_shape = [batch_sizes_sum, out_size * num_directions]
      else:
          out_shape = (
              [mini_batch, seq_length, out_size * num_directions]
              if batch_first
              else [seq_length, mini_batch, out_size * num_directions]
          )
      output = input.new_empty(out_shape)
  
      cell_shape = [
          num_layers * num_directions,
          mini_batch,
          hidden_size,
      ]
      cy = torch.empty(0) if cx is None else cx.new_empty(cell_shape)
  
      hy = hx.new_empty(
          [num_layers * num_directions, mini_batch, out_size]
      )
  
      # TODO: Query cudnnGetRNNTrainingReserveSize (expose to python)
      reserve_shape = 0 if train else 0
      reserve = input.new_empty(reserve_shape, dtype=torch.uint8)
  
      return output, hy, cy, reserve, weight_buf
  
imports: from typing import List, Optional, Union
  import torch
  from torch.utils._pytree import tree_map
label_desc: Use image node_id 6 for calling a global function with example usage: meta_cuda_rnn(input, weight, weight_stride0, weight_buf, hx, cx, mode, hidden_size, proj_size, num_layers, batch_first, dropout, train, bidirectional, batch_sizes, dropout_state) and returns: output,  hy,  cy,  reserve,  weight_buf