'''simple docstring'''

from __future__ import annotations

import unittest

from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow


if is_tf_available():
  import numpy as np
  import tensorflow as tf

  from transformers import TFCamembertModel


@require_tf
@require_sentencepiece
@require_tokenizers
class 				_lowercase	(      unittest.TestCase   ):
      '''simple docstring'''


      @slow
      def 		lowerCAmelCase__					(				self							)			->			List[Any]:



         '''simple docstring'''



         UpperCAmelCase__							:				str   				=  TFCamembertModel.from_pretrained('''jplu/tf-camembert-base'''							)

         UpperCAmelCase__							:				str   				=  tf.convert_to_tensor(
             [[5, 121, 11, 660, 16, 730, 25543, 110, 83, 6]]					,dtype=tf.intaa					,)  # J'aime le camembert !"

         UpperCAmelCase__							:				Union[str, Any]   				=  model(lowerCamelCase_							)['''last_hidden_state''']
         UpperCAmelCase__							:				Any   				=  tf.TensorShape((1, 10, 768)							)
         self.assertEqual(output.shape					,lowerCamelCase_							)
         # compare the actual values for a slice.
         UpperCAmelCase__							:				str   				=  tf.convert_to_tensor(
             [[[-0.0254, 0.0235, 0.1027], [0.0606, -0.1811, -0.0418], [-0.1561, -0.1127, 0.2687]]]					,dtype=tf.floataa					,)
         # camembert = torch.hub.load('pytorch/fairseq', 'camembert.v0')
         # camembert.eval()
         # expected_slice = roberta.model.forward(input_ids)[0][:, :3, :3].detach()

         self.assertTrue(np.allclose(output[:, :3, :3].numpy()					,expected_slice.numpy()					,atol=1e-4							)							)





'''simple docstring'''

import json
import os
from typing import Optional, Tuple

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


UpperCamelCase__     :	int				=			logging.get_logger(__name__)

UpperCamelCase__     :	Optional[Any]				=			{'vocab_file': 'vocab.json'}

UpperCamelCase__     :	Tuple				=			{
    'vocab_file': {
        'mgp-str': 'https://huggingface.co/alibaba-damo/mgp-str-base/blob/main/vocab.json',
    }
}

UpperCamelCase__     :	List[Any]				=			{'mgp-str': 27}


class 				_lowercase	(      lowerCAmelCase   ):
      '''simple docstring'''


      UpperCAmelCase_      :      Any      							=   VOCAB_FILES_NAMES
      UpperCAmelCase_      :      Dict      							=   PRETRAINED_VOCAB_FILES_MAP
      UpperCAmelCase_      :      int      							=   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES




      def __init__(				self					,lowerCamelCase_					,lowerCamelCase_="[GO]"					,lowerCamelCase_="[GO]"					,lowerCamelCase_="[s]"					,lowerCamelCase_="[GO]"					,**lowerCamelCase_							)			->			str:



         '''simple docstring'''



         super().__init__(
             unk_token=lowerCamelCase_					,bos_token=lowerCamelCase_					,eos_token=lowerCamelCase_					,pad_token=lowerCamelCase_					,**lowerCamelCase_					,)

         with open(lowerCamelCase_					,encoding='''utf-8'''							) as vocab_handle:
            UpperCAmelCase__							:				Optional[Any]   				=  json.load(lowerCamelCase_							)
         UpperCAmelCase__							:				Any   				=  {v: k for k, v in self.vocab.items()}




      @property
      def 		lowerCAmelCase__					(				self							)			->			Tuple:



         '''simple docstring'''



         return len(self.vocab							)




      def 		lowerCAmelCase__					(				self							)			->			Dict:



         '''simple docstring'''



         return dict(self.vocab					,**self.added_tokens_encoder							)




      def 		lowerCAmelCase__					(				self					,lowerCamelCase_							)			->			Any:



         '''simple docstring'''



         UpperCAmelCase__							:				List[Any]   				=  []
         for s in text:
            char_tokens.extend(lowerCamelCase_							)
         return char_tokens




      def 		lowerCAmelCase__					(				self					,lowerCamelCase_							)			->			str:



         '''simple docstring'''



         return self.vocab.get(lowerCamelCase_					,self.vocab.get(self.unk_token							)							)




      def 		lowerCAmelCase__					(				self					,lowerCamelCase_							)			->			Any:



         '''simple docstring'''



         return self.decoder.get(lowerCamelCase_							)




      def 		lowerCAmelCase__					(				self					,lowerCamelCase_					,lowerCamelCase_ = None							)			->			Tuple[str]:



         '''simple docstring'''



         if not os.path.isdir(lowerCamelCase_							):
            logger.error('''Vocabulary path ({}) should be a directory'''.format(lowerCamelCase_							)							)
            return
         UpperCAmelCase__							:				Union[str, Any]   				=  os.path.join(
             lowerCamelCase_					,(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']							)

         with open(lowerCamelCase_					,'''w'''					,encoding='''utf-8'''							) as f:
            f.write(json.dumps(self.vocab					,indent=2					,sort_keys=lowerCamelCase_					,ensure_ascii=lowerCamelCase_							) + '''\n'''							)

         return (vocab_file,)




