code: def test_encoder_rnn():
      """Test for Encoder Layer of SeqToSeq Model"""
      hidden_size = 7
      num_input_token = 4
      n_layers = 5
      input = torch.tensor(
          [[1, 0, 2, 3, 0], [0, 0, 0, 0, 0], [0, 0, 0, 0, 0]]
      )
      layer = torch_layers.EncoderRNN(
          num_input_token, hidden_size, n_layers
      )
      emb, hidden = layer(input)
  
      assert (
          emb.shape
          == emb.shape
          == (input.shape[0], input.shape[1], hidden_size)
      )
      assert hidden.shape == (input.shape[0], hidden_size)
  
imports: import deepchem
  import numpy
  import pytest
  import os
label_desc: Use image node_id 57 for calling a global function with example usage: test_encoder_rnn() without return types