





'''simple docstring'''




import unittest

from transformers import AutoConfig, AutoTokenizer, BertConfig, TensorType, is_flax_available
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, require_flax, slow


if is_flax_available():
    import jax

    from transformers.models.auto.modeling_flax_auto import FlaxAutoModel
    from transformers.models.bert.modeling_flax_bert import FlaxBertModel
    from transformers.models.roberta.modeling_flax_roberta import FlaxRobertaModel






@require_flax
class UpperCAmelCase							(		unittest.TestCase							):



    @slow
    def 					__lowerCamelCase						(  self					):







     for model_name in ["bert-base-cased", "bert-large-uncased"]:
      with self.subTest(lowerCAmelCase_					):
       __UpperCAmelCase					=   AutoConfig.from_pretrained(lowerCAmelCase_					)
       self.assertIsNotNone(lowerCAmelCase_					)
       self.assertIsInstance(lowerCAmelCase_     ,			lowerCAmelCase_					)

       __UpperCAmelCase					=   FlaxAutoModel.from_pretrained(lowerCAmelCase_					)
       self.assertIsNotNone(lowerCAmelCase_					)
       self.assertIsInstance(lowerCAmelCase_     ,			lowerCAmelCase_					)



    @slow
    def 					__lowerCamelCase						(  self					):







     for model_name in ["roberta-base", "roberta-large"]:
      with self.subTest(lowerCAmelCase_					):
       __UpperCAmelCase					=   AutoConfig.from_pretrained(lowerCAmelCase_					)
       self.assertIsNotNone(lowerCAmelCase_					)
       self.assertIsInstance(lowerCAmelCase_     ,			lowerCAmelCase_					)

       __UpperCAmelCase					=   FlaxAutoModel.from_pretrained(lowerCAmelCase_					)
       self.assertIsNotNone(lowerCAmelCase_					)
       self.assertIsInstance(lowerCAmelCase_     ,			lowerCAmelCase_					)



    @slow
    def 					__lowerCamelCase						(  self					):







     for model_name in ["bert-base-cased", "bert-large-uncased"]:
      __UpperCAmelCase					=   AutoTokenizer.from_pretrained(lowerCAmelCase_					)
      __UpperCAmelCase					=   FlaxBertModel.from_pretrained(lowerCAmelCase_					)
      __UpperCAmelCase					=   tokenizer('Do you support jax jitted function?'     ,			return_tensors=TensorType.JAX					)

      @jax.jit
      def eval(**__A					):
       return model(**lowerCAmelCase_					)

      eval(**lowerCAmelCase_					).block_until_ready()



    @slow
    def 					__lowerCamelCase						(  self					):







     for model_name in ["roberta-base", "roberta-large"]:
      __UpperCAmelCase					=   AutoTokenizer.from_pretrained(lowerCAmelCase_					)
      __UpperCAmelCase					=   FlaxRobertaModel.from_pretrained(lowerCAmelCase_					)
      __UpperCAmelCase					=   tokenizer('Do you support jax jitted function?'     ,			return_tensors=TensorType.JAX					)

      @jax.jit
      def eval(**__A					):
       return model(**lowerCAmelCase_					)

      eval(**lowerCAmelCase_					).block_until_ready()



    def 					__lowerCamelCase						(  self					):







     with self.assertRaisesRegex(
         lowerCAmelCase_     ,			'bert-base is not a local folder and is not a valid model identifier'					):
      __UpperCAmelCase					=   FlaxAutoModel.from_pretrained('bert-base'					)



    def 					__lowerCamelCase						(  self					):







     with self.assertRaisesRegex(
         lowerCAmelCase_     ,			r'aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)'					):
      __UpperCAmelCase					=   FlaxAutoModel.from_pretrained(lowerCAmelCase_     ,			revision='aaaaaa'					)



    def 					__lowerCamelCase						(  self					):







     with self.assertRaisesRegex(
         lowerCAmelCase_     ,			'hf-internal-testing/config-no-model does not appear to have a file named flax_model.msgpack'     ,			):
      __UpperCAmelCase					=   FlaxAutoModel.from_pretrained('hf-internal-testing/config-no-model'					)




    def 					__lowerCamelCase						(  self					):







     with self.assertRaisesRegex(lowerCAmelCase_     ,			'Use `from_pt=True` to load this model'					):
      __UpperCAmelCase					=   FlaxAutoModel.from_pretrained('hf-internal-testing/tiny-bert-pt-only'					)







'''simple docstring'''




import json
import os
import unittest

from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin






@require_tokenizers
class UpperCAmelCase							(		UpperCAmelCase_					,			unittest.TestCase							):
    _A :			List[str]						   =       MgpstrTokenizer
    _A :			Any						   =       False
    _A :			List[Any]						   =       {}
    _A :			int						   =       False



    def 					__lowerCamelCase						(  self					):
     super().setUp()

     # fmt: off
     __UpperCAmelCase					=   ['[GO]', '[s]', '0', '1', '2', '3', '4', '5', '6', '7', '8', '9', 'a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j', 'k', 'l', 'm', 'n', 'o', 'p', 'q', 'r', 's', 't', 'u', 'v', 'w', 'x', 'y', 'z']
     # fmt: on
     __UpperCAmelCase					=   dict(zip(__A     ,			range(len(__A					)					)					)					)

     __UpperCAmelCase					=   os.path.join(self.tmpdirname     ,			VOCAB_FILES_NAMES['vocab_file']					)
     with open(self.vocab_file     ,			'w'     ,			encoding='utf-8'					) as fp:
      fp.write(json.dumps(__A					) + '\n'					)



    def 					__lowerCamelCase						(  self     ,			**__A					):
     return MgpstrTokenizer.from_pretrained(self.tmpdirname     ,			**__A					)



    def 					__lowerCamelCase						(  self     ,			__A					):
     __UpperCAmelCase					=   'tester'
     __UpperCAmelCase					=   'tester'
     return input_text, output_text



    @unittest.skip('MGP-STR always lower cases letters.'					)
    def 					__lowerCamelCase						(  self					):
     pass



    def 					__lowerCamelCase						(  self					):
     __UpperCAmelCase					=   self.get_tokenizers(do_lower_case=__A					)
     for tokenizer in tokenizers:
      with self.subTest(f'{tokenizer.__class__.__name__}'					):
       __UpperCAmelCase					=   '[SPECIAL_TOKEN]'

       tokenizer.add_special_tokens({'cls_token': special_token}					)
       __UpperCAmelCase					=   tokenizer.encode([special_token]     ,			add_special_tokens=__A					)
       self.assertEqual(len(__A					)     ,			1					)

       __UpperCAmelCase					=   tokenizer.decode(__A     ,			skip_special_tokens=__A					)
       self.assertTrue(special_token not in decoded					)



    def 					__lowerCamelCase						(  self					):
     __UpperCAmelCase					=   self.get_tokenizers()
     for tokenizer in tokenizers:
      with self.subTest(f'{tokenizer.__class__.__name__}'					):
       __UpperCAmelCase					,    __UpperCAmelCase					=   self.get_input_output_texts(__A					)

       __UpperCAmelCase					=   tokenizer.tokenize(__A					)
       __UpperCAmelCase					=   tokenizer.convert_tokens_to_ids(__A					)
       __UpperCAmelCase					=   tokenizer.encode(__A     ,			add_special_tokens=__A					)
       self.assertListEqual(__A     ,			__A					)

       __UpperCAmelCase					=   tokenizer.convert_ids_to_tokens(__A					)
       self.assertNotEqual(len(__A					)     ,			0					)
       __UpperCAmelCase					=   tokenizer.decode(__A					)
       self.assertIsInstance(__A     ,			__A					)

       self.assertEqual(text_a.replace(' '     ,			''					)     ,			__A					)



    @unittest.skip('MGP-STR tokenizer only handles one sequence.'					)
    def 					__lowerCamelCase						(  self					):
     pass




    @unittest.skip('inputs cannot be pretokenized in MgpstrTokenizer'					)
    def 					__lowerCamelCase						(  self					):
     pass





