code: def test_decoder_rnn():
      """Test for Decoder Layer of SeqToSeq Model"""
      embedding_dimensions = 5
      num_output_tokens = 7
      max_length = 4
      batch_size = 2
      n_layers = 9
      layer = torch_layers.DecoderRNN(
          embedding_dimensions,
          num_output_tokens,
          n_layers,
          max_length,
          batch_size,
      )
      embeddings = torch.randn(batch_size, embedding_dimensions)
      output, hidden = layer([embeddings, None])
      assert output.shape == (batch_size, max_length, num_output_tokens)
      assert hidden.shape == (
          n_layers,
          batch_size,
          embedding_dimensions,
      )
  
imports: import deepchem
  import numpy
  import pytest
  import os
label_desc: Use image node_id 58 for calling a global function with example usage: test_decoder_rnn() without return types