'''simple docstring'''


import unittest
from pathlib import Path
from tempfile import TemporaryDirectory

from transformers import AutoConfig, TFAutoModel, is_tensorflow_text_available, is_tf_available
from transformers.models.bert.tokenization_bert import BertTokenizer
from transformers.testing_utils import require_tensorflow_text, require_tf, slow


if is_tf_available():
       import tensorflow as tf

if is_tensorflow_text_available():
       from transformers.models.bert import TFBertTokenizer


__snake_case						  =		["""bert-base-uncased""", """bert-base-cased"""]
__snake_case						  =		"""hf-internal-testing/tiny-bert-tf-only"""

if is_tf_available():





       class       _a    (		tf.keras.Model      ):


         """simple docstring"""

         def __init__(		self      :       str   ,				lowercase_      :       int      ):







           '''simple docstring'''


           super().__init__()
           lowercase_     =       tokenizer
           lowercase_     =       AutoConfig.from_pretrained(SCREAMING_SNAKE_CASE_      )
           lowercase_     =       TFAutoModel.from_config(SCREAMING_SNAKE_CASE_      )





         def 		lowerCamelCase__  (		self      :       Union[str, Any]   ,				lowercase_      :       str      ):







           '''simple docstring'''


           lowercase_     =       self.tokenizer(SCREAMING_SNAKE_CASE_      )
           lowercase_     =       self.bert(**SCREAMING_SNAKE_CASE_      )
           return out["pooler_output"]





@require_tf
@require_tensorflow_text
class       _a    (		unittest.TestCase      ):


  """simple docstring"""

  def 		lowerCamelCase__  (		self      :       Union[str, Any]      ):







    '''simple docstring'''


    super().setUp()

    lowercase_     =       [
        BertTokenizer.from_pretrained(SCREAMING_SNAKE_CASE_      ) for checkpoint in (TOKENIZER_CHECKPOINTS * 2)
    ]  # repeat for when fast_bert_tokenizer=false
    lowercase_     =       [TFBertTokenizer.from_pretrained(SCREAMING_SNAKE_CASE_      ) for checkpoint in TOKENIZER_CHECKPOINTS] + [
        TFBertTokenizer.from_pretrained(SCREAMING_SNAKE_CASE_   ,				use_fast_bert_tokenizer=SCREAMING_SNAKE_CASE_      )
        for checkpoint in TOKENIZER_CHECKPOINTS
    ]
    assert len(self.tokenizers      ) == len(self.tf_tokenizers      )

    lowercase_     =       [
        'This is a straightforward English test sentence.',
        'This one has some weird characters\rto\nsee\r\nif  those\u00E9break things.',
        'Now we\'re going to add some Chinese: 一 二 三 一二三',
        'And some much more rare Chinese: 齉 堃 齉堃',
        'Je vais aussi écrire en français pour tester les accents',
        'Classical Irish also has some unusual characters, so in they go: Gaelaċ, ꝼ',
    ]
    lowercase_     =       list(zip(self.test_sentences   ,				self.test_sentences[::-1]      )      )




  def 		lowerCamelCase__  (		self      :       int      ):







    '''simple docstring'''


    for tokenizer, tf_tokenizer in zip(self.tokenizers   ,				self.tf_tokenizers      ):
      for test_inputs in (self.test_sentences, self.paired_sentences):
        lowercase_     =       tokenizer(SCREAMING_SNAKE_CASE_   ,				return_tensors="""tf"""   ,				padding="""longest"""      )
        lowercase_     =       tf_tokenizer(SCREAMING_SNAKE_CASE_      )

        for key in python_outputs.keys():
          self.assertTrue(tf.reduce_all(python_outputs[key].shape == tf_outputs[key].shape      )      )
          self.assertTrue(tf.reduce_all(tf.cast(python_outputs[key]   ,				tf.intaa      ) == tf_outputs[key]      )      )




  @slow
  def 		lowerCamelCase__  (		self      :       List[Any]      ):







    '''simple docstring'''


    for tf_tokenizer in self.tf_tokenizers:
      lowercase_     =       tf_tokenizer(self.paired_sentences      )
      lowercase_     =       tf_tokenizer(
          text=[sentence[0] for sentence in self.paired_sentences]   ,				text_pair=[sentence[1] for sentence in self.paired_sentences]   ,				)
      for key in merged_outputs.keys():
        self.assertTrue(tf.reduce_all(tf.cast(merged_outputs[key]   ,				tf.intaa      ) == separated_outputs[key]      )      )




  @slow
  def 		lowerCamelCase__  (		self      :       Any      ):







    '''simple docstring'''


    for tf_tokenizer in self.tf_tokenizers:
      lowercase_     =       tf.function(SCREAMING_SNAKE_CASE_      )
      for test_inputs in (self.test_sentences, self.paired_sentences):
        lowercase_     =       tf.constant(SCREAMING_SNAKE_CASE_      )
        lowercase_     =       compiled_tokenizer(SCREAMING_SNAKE_CASE_      )
        lowercase_     =       tf_tokenizer(SCREAMING_SNAKE_CASE_      )

        for key in eager_outputs.keys():
          self.assertTrue(tf.reduce_all(eager_outputs[key] == compiled_outputs[key]      )      )





  @slow
  def 		lowerCamelCase__  (		self      :       str      ):







    '''simple docstring'''


    for tf_tokenizer in self.tf_tokenizers:
      lowercase_     =       ModelToSave(tokenizer=SCREAMING_SNAKE_CASE_      )
      lowercase_     =       tf.convert_to_tensor(self.test_sentences      )
      lowercase_     =       model(SCREAMING_SNAKE_CASE_      )  # Build model with some sample inputs
      with TemporaryDirectory() as tempdir:
        lowercase_     =       Path(SCREAMING_SNAKE_CASE_      ) / 'saved.model'
        model.save(SCREAMING_SNAKE_CASE_      )
        lowercase_     =       tf.keras.models.load_model(SCREAMING_SNAKE_CASE_      )
      lowercase_     =       loaded_model(SCREAMING_SNAKE_CASE_      )
      # We may see small differences because the loaded model is compiled, so we need an epsilon for the test
      self.assertLessEqual(tf.reduce_max(tf.abs(out - loaded_output      )      )   ,				1e-5      )





'''simple docstring'''



from ...configuration_utils import PretrainedConfig
from ...utils import logging


A__						:   Tuple				=    logging.get_logger(__name__)

A__						:   Dict				=    {
    """RWKV/rwkv-4-169m-pile""": """https://huggingface.co/RWKV/rwkv-4-169m-pile/resolve/main/config.json""",
    """RWKV/rwkv-4-430m-pile""": """https://huggingface.co/RWKV/rwkv-4-430m-pile/resolve/main/config.json""",
    """RWKV/rwkv-4-1b5-pile""": """https://huggingface.co/RWKV/rwkv-4-1b5-pile/resolve/main/config.json""",
    """RWKV/rwkv-4-3b-pile""": """https://huggingface.co/RWKV/rwkv-4-3b-pile/resolve/main/config.json""",
    """RWKV/rwkv-4-7b-pile""": """https://huggingface.co/RWKV/rwkv-4-7b-pile/resolve/main/config.json""",
    """RWKV/rwkv-4-14b-pile""": """https://huggingface.co/RWKV/rwkv-4-14b-pile/resolve/main/config.json""",
    """RWKV/rwkv-raven-1b5""": """https://huggingface.co/RWKV/rwkv-raven-1b5/resolve/main/config.json""",
    """RWKV/rwkv-raven-3b""": """https://huggingface.co/RWKV/rwkv-raven-3b/resolve/main/config.json""",
    """RWKV/rwkv-raven-7b""": """https://huggingface.co/RWKV/rwkv-raven-7b/resolve/main/config.json""",
    """RWKV/rwkv-raven-14b""": """https://huggingface.co/RWKV/rwkv-raven-14b/resolve/main/config.json""",
}





class   UpperCAmelCase_    (_UpperCAmelCase    ):





    """simple docstring"""






    lowerCamelCase    :   List[Any]					=     'rwkv'
    lowerCamelCase    :   Any					=     {'max_position_embeddings': 'context_length'}







    def __init__(				self     ,	SCREAMING_SNAKE_CASE_=5_02_77     ,	SCREAMING_SNAKE_CASE_=10_24     ,	SCREAMING_SNAKE_CASE_=40_96     ,	SCREAMING_SNAKE_CASE_=32     ,	SCREAMING_SNAKE_CASE_=None     ,	SCREAMING_SNAKE_CASE_=None     ,	SCREAMING_SNAKE_CASE_=1E-5     ,	SCREAMING_SNAKE_CASE_=0     ,	SCREAMING_SNAKE_CASE_=0     ,	SCREAMING_SNAKE_CASE_=6     ,	SCREAMING_SNAKE_CASE_=False     ,	SCREAMING_SNAKE_CASE_=True     ,	**SCREAMING_SNAKE_CASE_     ,	)							->	Optional[Any]:
         __lowerCamelCase  :      Optional[int]														=						vocab_size
         __lowerCamelCase  :      Tuple														=						context_length
         __lowerCamelCase  :      str														=						hidden_size
         __lowerCamelCase  :      List[str]														=						num_hidden_layers
         __lowerCamelCase  :      Any														=						attention_hidden_size if attention_hidden_size is not None else hidden_size
         __lowerCamelCase  :      Optional[int]														=						intermediate_size if intermediate_size is not None else 4 * hidden_size
         __lowerCamelCase  :      Optional[Any]														=						layer_norm_epsilon
         __lowerCamelCase  :      int														=						rescale_every
         __lowerCamelCase  :      Tuple														=						use_cache

         __lowerCamelCase  :      int														=						bos_token_id
         __lowerCamelCase  :      Optional[Any]														=						eos_token_id

         super().__init__(
             tie_word_embeddings=SCREAMING_SNAKE_CASE_     ,	bos_token_id=SCREAMING_SNAKE_CASE_     ,	eos_token_id=SCREAMING_SNAKE_CASE_     ,	**SCREAMING_SNAKE_CASE_      )






