'''simple docstring'''





import unittest

from transformers import ErnieMTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin


UpperCamelCase       :     List[str]			=    get_tests_dir("""fixtures/spiece.model""")



@require_sentencepiece
@require_tokenizers
class   UpperCamelCase					(       a_    ,     unittest.TestCase       ):







    """simple docstring"""





    A     :    Optional[Any]				=			ErnieMTokenizer
    A     :    Tuple				=			False
    A     :    Optional[Any]				=			True
    A     :    Any				=			False
    A     :    List[Any]				=			False





    def    SCREAMING_SNAKE_CASE_     (					self     :						int):


         """simple docstring"""







         super().setUp()

         # We have a SentencePiece fixture for testing
         a					:							Optional[int]							= ErnieMTokenizer(UpperCAmelCase_							,							unk_token='<unk>'							,							pad_token='<pad>')
         tokenizer.save_pretrained(self.tmpdirname)





    def    SCREAMING_SNAKE_CASE_     (					self     :						List[str]							,							UpperCAmelCase_     :						Union[str, Any]):


         """simple docstring"""







         a					:							Optional[Any]							= 'this is a test'
         a					:							int							= 'this is a test'
         return input_text, output_text





    def    SCREAMING_SNAKE_CASE_     (					self     :						str):


         """simple docstring"""







         a					:							List[str]							= '<pad>'
         a					:							List[Any]							= 0

         self.assertEqual(self.get_tokenizer()._convert_token_to_id(UpperCAmelCase_)							,							UpperCAmelCase_)
         self.assertEqual(self.get_tokenizer()._convert_id_to_token(UpperCAmelCase_)							,							UpperCAmelCase_)





    def    SCREAMING_SNAKE_CASE_     (					self     :						Any):


         """simple docstring"""







         a					:							Any							= list(self.get_tokenizer().get_vocab().keys())

         self.assertEqual(vocab_keys[0]							,							'<pad>')
         self.assertEqual(vocab_keys[1]							,							'<unk>')
         self.assertEqual(vocab_keys[-1]							,							'▁eloquent')
         self.assertEqual(len(UpperCAmelCase_)							,							3_0_0_0_0)





    def    SCREAMING_SNAKE_CASE_     (					self     :						Tuple):


         """simple docstring"""







         self.assertEqual(self.get_tokenizer().vocab_size							,							3_0_0_0_0)





    def    SCREAMING_SNAKE_CASE_     (					self     :						int):


         """simple docstring"""







         if not self.test_rust_tokenizer:
              return

         a					:							Union[str, Any]							= self.get_tokenizer()
         a					:							Any							= self.get_rust_tokenizer()

         a					:							Optional[Any]							= 'I was born in 92000, and this is falsé.'

         a					:							Union[str, Any]							= tokenizer.tokenize(UpperCAmelCase_)
         a					:							Union[str, Any]							= rust_tokenizer.tokenize(UpperCAmelCase_)
         self.assertListEqual(UpperCAmelCase_							,							UpperCAmelCase_)

         a					:							Optional[int]							= tokenizer.encode(UpperCAmelCase_							,							add_special_tokens=UpperCAmelCase_)
         a					:							List[str]							= rust_tokenizer.encode(UpperCAmelCase_							,							add_special_tokens=UpperCAmelCase_)
         self.assertListEqual(UpperCAmelCase_							,							UpperCAmelCase_)

         a					:							str							= self.get_rust_tokenizer()
         a					:							str							= tokenizer.encode(UpperCAmelCase_)
         a					:							Dict							= rust_tokenizer.encode(UpperCAmelCase_)
         self.assertListEqual(UpperCAmelCase_							,							UpperCAmelCase_)





    def    SCREAMING_SNAKE_CASE_     (					self     :						Optional[Any]):


         """simple docstring"""







         a					:							Tuple							= ErnieMTokenizer(UpperCAmelCase_							,							do_lower_case=UpperCAmelCase_							,							unk_token='<unk>'							,							pad_token='<pad>')

         a					:							Any							= tokenizer.tokenize('This is a test')
         self.assertListEqual(UpperCAmelCase_							,							['▁this', '▁is', '▁a', '▁test'])

         self.assertListEqual(tokenizer.convert_tokens_to_ids(UpperCAmelCase_)							,							[4_8, 2_5, 2_1, 1_2_8_9])

         a					:							Union[str, Any]							= tokenizer.tokenize('I was born in 92000, and this is falsé.')
         # ErnieMTokenizer(paddlenlp implementation) outputs '9' instead of '_9' so to mimic that '_9' is changed to '9'
         self.assertListEqual(
             UpperCAmelCase_							,							['▁i', '▁was', '▁born', '▁in', '9', '2000', ',', '▁and', '▁this', '▁is', '▁fal', 's', 'é', '.'])
         a					:							List[Any]							= tokenizer.convert_tokens_to_ids(UpperCAmelCase_)
         self.assertListEqual(UpperCAmelCase_							,							[3_1, 2_3, 3_8_6, 1_9, 5_1_8, 3_0_5_0, 1_5, 1_7, 4_8, 2_5, 8_2_5_6, 1_8, 1, 9])

         a					:							List[str]							= tokenizer.convert_ids_to_tokens(UpperCAmelCase_)
         self.assertListEqual(
             UpperCAmelCase_							,							['▁i', '▁was', '▁born', '▁in', '9', '2000', ',', '▁and', '▁this', '▁is', '▁fal', 's', '<unk>', '.']							,							)





    def    SCREAMING_SNAKE_CASE_     (					self     :						int):


         """simple docstring"""







         a					:							str							= ErnieMTokenizer(UpperCAmelCase_							,							unk_token='<unk>'							,							pad_token='<pad>')

         a					:							Dict							= tokenizer.encode('sequence builders')
         a					:							Optional[int]							= tokenizer.encode('multi-sequence build')

         a					:							Dict							= tokenizer.build_inputs_with_special_tokens(UpperCAmelCase_)
         a					:							List[str]							= tokenizer.build_inputs_with_special_tokens(UpperCAmelCase_							,							UpperCAmelCase_)

         assert encoded_sentence == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id]
         assert encoded_pair == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id] + [
             tokenizer.sep_token_id
         ] + text_a + [tokenizer.sep_token_id]







    @slow
    def    SCREAMING_SNAKE_CASE_     (					self     :						Optional[Any]):


         """simple docstring"""







         a					:							Dict							= {'input_ids': [[0, 1_1_0_6_2, 8_2_7_7_2, 7, 1_5, 8_2_7_7_2, 5_3_8, 5_1_5_2_9, 2_3_7, 1_7_1_9_8, 1_2_9_0, 2_0_6, 9, 2_1_5_1_7_5, 1_3_1_4, 1_3_6, 1_7_1_9_8, 1_2_9_0, 2_0_6, 9, 5_6_3_5_9, 4_2, 1_2_2_0_0_9, 9, 1_6_4_6_6, 1_6, 8_7_3_4_4, 4_5_3_7, 9, 4_7_1_7, 7_8_3_8_1, 6, 1_5_9_9_5_8, 7, 1_5, 2_4_4_8_0, 6_1_8, 4, 5_2_7, 2_2_6_9_3, 9, 3_0_4, 4, 2_7_7_7, 2_4_4_8_0, 9_8_7_4, 4, 4_3_5_2_3, 5_9_4, 4, 8_0_3, 1_8_3_9_2, 3_3_1_8_9, 1_8, 4, 4_3_5_2_3, 2_4_4_4_7, 5, 5, 5, 1_6, 1_0_0, 2_4_9_5_5, 8_3_6_5_8, 9_6_2_6, 1_4_4_0_5_7, 1_5, 8_3_9, 2_2_3_3_5, 1_6, 1_3_6, 2_4_9_5_5, 8_3_6_5_8, 8_3_4_7_9, 1_5, 3_9_1_0_2, 7_2_4, 1_6, 6_7_8, 6_4_5, 6_4_6_0, 1_3_2_8, 4_5_8_9, 4_2, 1_2_2_0_0_9, 1_1_5_7_7_4, 2_3, 3_5_5_9, 1_3_2_8, 4_6_8_7_6, 7, 1_3_6, 5_3_8_9_4, 1_9_4_0, 4_2_2_2_7, 4_1_1_5_9, 1_7_7_2_1, 8_2_3, 4_2_5, 4, 2_7_5_1_2, 9_8_7_2_2, 2_0_6, 1_3_6, 5_5_3_1, 4_9_7_0, 9_1_9, 1_7_3_3_6, 5, 2], [0, 2_0_0_8_0, 6_1_8, 8_3, 8_2_7_7_5, 4_7, 4_7_9, 9, 1_5_1_7, 7_3, 5_3_8_9_4, 3_3_3, 8_0_5_8_1, 1_1_0_1_1_7, 1_8_8_1_1, 5_2_5_6, 1_2_9_5, 5_1, 1_5_2_5_2_6, 2_9_7, 7_9_8_6, 3_9_0, 1_2_4_4_1_6, 5_3_8, 3_5_4_3_1, 2_1_4, 9_8, 1_5_0_4_4, 2_5_7_3_7, 1_3_6, 7_1_0_8, 4_3_7_0_1, 2_3, 7_5_6, 1_3_5_3_5_5, 7, 5, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [0, 5_8_1, 6_3_7_7_3, 1_1_9_4_5_5, 6, 1_4_7_7_9_7, 8_8_2_0_3, 7, 6_4_5, 7_0, 2_1, 3_2_8_5, 1_0_2_6_9, 5, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]}
         # fmt: on

         self.tokenizer_integration_test_util(
             expected_encoding=UpperCAmelCase_							,							model_name='susnato/ernie-m-base_pytorch'							,							sequences=[
                 'Transformers (formerly known as pytorch-transformers and pytorch-pretrained-bert) provides '
                 'general-purpose architectures (BERT, GPT-2, RoBERTa, XLM, DistilBert, XLNet...) for Natural '
                 'Language Understanding (NLU) and Natural Language Generation (NLG) with over32+ pretrained '
                 'models in100+ languages and deep interoperability between Jax, PyTorch and TensorFlow.',
                 'BERT is designed to pre-train deep bidirectional representations from unlabeled text by jointly '
                 'conditioning on both left and right context in all layers.',
                 'The quick brown fox jumps over the lazy dog.',
             ]							,							)


'''simple docstring'''





import glob
import os

from get_test_info import get_tester_classes


if __name__ == "__main__":
      UpperCamelCase       :     List[Any]			=    []

      UpperCamelCase       :     Tuple			=    os.path.join("""tests""", """models""", """**""", """test_modeling_*.py""")
      UpperCamelCase       :     List[str]			=    glob.glob(pattern)
      # TODO: deal with TF/Flax too
      UpperCamelCase       :     List[Any]			=    [
          x for x in test_files if not (x.startswith("""test_modeling_tf_""") or x.startswith("""test_modeling_flax_"""))
      ]

      for test_file in test_files:
            UpperCamelCase       :     List[str]			=    get_tester_classes(test_file)
            for tester_class in tester_classes:
                  # A few tester classes don't have `parent` parameter in `__init__`.
                  # TODO: deal this better
                  try:
                        UpperCamelCase       :     int			=    tester_class(parent=None)
                  except Exception:
                        continue
                  if hasattr(tester, """get_config"""):
                        UpperCamelCase       :     Union[str, Any]			=    tester.get_config()
                        for k, v in config.to_dict().items():
                              if isinstance(v, int):
                                    UpperCamelCase       :     List[Any]			=    None
                                    if k in ["vocab_size"]:
                                          UpperCamelCase       :     List[Any]			=    100
                                    elif k in ["max_position_embeddings"]:
                                          UpperCamelCase       :     Tuple			=    128
                                    elif k in ["hidden_size", "d_model"]:
                                          UpperCamelCase       :     Any			=    40
                                    elif k == ["num_layers", "num_hidden_layers", "num_encoder_layers", "num_decoder_layers"]:
                                          UpperCamelCase       :     Tuple			=    5
                                    if target is not None and v > target:
                                          failures.append(
                                              f'''{tester_class.__name__} will produce a `config` of type `{config.__class__.__name__}`'''
                                              f''' with config["{k}"] = {v} which is too large for testing! Set its value to be smaller'''
                                              f''' than {target}.'''
                                          )

      if len(failures) > 0:
            raise Exception(f'''There were {len(failures)} failures:\n''' + """\n""".join(failures))

