code: def test_forward(self, falcon_gpt_model, test_text):
      dtype = falcon_gpt_model.torch_dtype
  
      falcon_gpt_model.eval()
  
      ids = [
          falcon_gpt_model.tokenizer.text_to_ids(text)
          for text in test_text
      ]
  
      id_tensors = [
          torch.unsqueeze(torch.LongTensor(id_list), dim=0)
          for id_list in ids
      ]
  
      masks_and_position_ids = [
          get_ltor_masks_and_position_ids(
              id_tensor,
              falcon_gpt_model.tokenizer.eos_id,
              False,
              False,
              False,
          )
          for id_tensor in id_tensors
      ]
      output_tensors = []
      with torch.no_grad():
          for tokens, attn_mask_and_pos_ids in zip(
              id_tensors, masks_and_position_ids
          ):
              attn_mask, _, pos_ids = attn_mask_and_pos_ids
              assert tokens.shape == pos_ids.shape
              assert (
                  attn_mask.shape[2]
                  == attn_mask.shape[3]
                  == tokens.shape[1]
                  == pos_ids.shape[1]
              )
              with torch.autocast("cuda", dtype=dtype):
                  output_tensor = falcon_gpt_model.forward(
                      tokens=tokens.cuda(),
                      text_position_ids=pos_ids.cuda(),
                      attention_mask=attn_mask.cuda(),
                      labels=None,
                  )
              # output is [b s h]
              assert output_tensor.shape[0] == 1
              assert output_tensor.shape[1] == tokens.shape[1]
              assert (
                  output_tensor.shape[2]
                  == falcon_gpt_model.padded_vocab_size
              )
              assert output_tensor.dtype == dtype
              output_tensors.append(output_tensor)
  
file_path: NeMo/tests/collections/nlp/test_falcon_model.py
imports: import pytest
  import torch
  from omegaconf import DictConfig
  from pytorch_lightning import Trainer
  from nemo.collections.common.tokenizers.huggingface.auto_tokenizer import AutoTokenizer
  from nemo.collections.nlp.models.language_modeling.megatron_gpt_model import MegatronGPTModel
  from nemo.collections.nlp.modules.common.megatron.utils import get_ltor_masks_and_position_ids
  from nemo.collections.nlp.parts.nlp_overrides import NLPDDPStrategy
label_desc: Use image node_id 3 for calling the TestFalconGPTModel obj's underlying member method code with example usage: obj.test_forward(falcon_gpt_model, test_text) without return types