code: def dummy_inputs(cls, params, init_case):
      n_unique_src_words = 13
      scores = torch.randn(
          (
              params["batch_size"] * params["tgt_max_len"],
              init_case["vocab_size"] + n_unique_src_words,
          )
      )
      scores = softmax(scores, dim=1)
      align = torch.randint(
          0,
          n_unique_src_words,
          (params["batch_size"] * params["tgt_max_len"],),
      )
      target = torch.randint(
          0,
          init_case["vocab_size"],
          (params["batch_size"] * params["tgt_max_len"],),
      )
      target[0] = init_case["unk_index"]
      target[1] = init_case["ignore_index"]
      return scores, align, target
  
imports: import unittest
  from onmt.modules.copy_generator import CopyGenerator, CopyGeneratorLoss
  import itertools
  from copy import deepcopy
  import torch
  from torch.nn.functional import softmax
  from onmt.tests.utils_for_tests import product_dict
label_desc: Use image node_id 1 for calling the TestCopyGeneratorLoss obj's underlying member method code with example usage: obj.dummy_inputs(cls, params, init_case) and returns: scores,  align,  target