code: def test_gpu_forward(self):
      parallel_transformer_layer = (
          self.parallel_falcon_transformer_layer
      )
      config: TransformerConfig = parallel_transformer_layer.config
      sequence_length = 32
      micro_batch_size = 2
      parallel_transformer_layer.cuda()
  
      # [sequence length, batch size, hidden size]
      hidden_states = torch.ones(
          (sequence_length, micro_batch_size, config.hidden_size)
      )
      hidden_states = hidden_states.cuda()
  
      attention_mask = torch.ones(
          (1, 1, sequence_length, sequence_length), dtype=bool
      ).cuda()
      hidden_states, context = parallel_transformer_layer(
          hidden_states=hidden_states, attention_mask=attention_mask
      )
      assert hidden_states.shape[0] == sequence_length
      assert hidden_states.shape[1] == micro_batch_size
      assert hidden_states.shape[2] == config.hidden_size
  
imports: import pytest
  import torch
  from nemo.collections.nlp.models.language_modeling.megatron.falcon.falcon_decoder_layer import FalconTransformerLayer
  from nemo.collections.nlp.models.language_modeling.megatron.falcon.falcon_spec import get_falcon_layer_spec
label_desc: Use image node_id 3 for calling the TestParallelFalconTransformerLayer obj's underlying member method code with example usage: obj.test_gpu_forward() without return types