



import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple

from transformers import AddedToken, BatchEncoding, PerceiverTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available

from ...test_tokenization_common import TokenizerTesterMixin


if is_torch_available():
							__snake_case				:		Optional[Any]										='pt'
elif is_tf_available():
							__snake_case				:		List[str]										='tf'
else:
							__snake_case				:		Optional[int]										='jax'



class        lowerCamelCase__			(							__snake_case      ,				unittest.TestCase):




		'''simple docstring'''



		snake_case_	=PerceiverTokenizer
		snake_case_	=False



		def 		lowerCAmelCase__      (self )     ->			int:

						"""simple docstring"""






						super().setUp()
						lowerCAmelCase__     :				int												=     PerceiverTokenizer()
						tokenizer.save_pretrained(self.tmpdirname )



		@cached_property
		def 		lowerCAmelCase__      (self )     ->			int:

						"""simple docstring"""






						return PerceiverTokenizer.from_pretrained('''deepmind/language-perceiver''' )



		def 		lowerCAmelCase__      (self		,**__lowerCamelCase )     ->			List[Any]:

						"""simple docstring"""






						return self.tokenizer_class.from_pretrained(self.tmpdirname		,**__lowerCamelCase )



		def 		lowerCAmelCase__      (self		,__lowerCamelCase		,__lowerCamelCase=False		,__lowerCamelCase=20		,__lowerCamelCase=5 )     ->			Dict:

						"""simple docstring"""






						lowerCAmelCase__     :				Dict												=     []
						for i in range(len(__lowerCamelCase ) ):
										try:
														lowerCAmelCase__     :				Dict												=     tokenizer.decode([i]		,clean_up_tokenization_spaces=__lowerCamelCase )
										except UnicodeDecodeError:
														pass
										toks.append((i, tok) )

						lowerCAmelCase__     :				Union[str, Any]												=     list(filter(lambda __lowerCamelCase : re.match(R'''^[ a-zA-Z]+$'''		,t[1] )		,__lowerCamelCase ) )
						lowerCAmelCase__     :				List[str]												=     list(filter(lambda __lowerCamelCase : [t[0]] == tokenizer.encode(t[1]		,add_special_tokens=__lowerCamelCase )		,__lowerCamelCase ) )
						if max_length is not None and len(__lowerCamelCase ) > max_length:
										lowerCAmelCase__     :				Union[str, Any]												=     toks[:max_length]
						if min_length is not None and len(__lowerCamelCase ) < min_length and len(__lowerCamelCase ) > 0:
										while len(__lowerCamelCase ) < min_length:
														lowerCAmelCase__     :				List[str]												=     toks + toks
        # toks_str = [t[1] for t in toks]
						lowerCAmelCase__     :				int												=     [t[0] for t in toks]

						# Ensure consistency
						lowerCAmelCase__     :				List[str]												=     tokenizer.decode(__lowerCamelCase		,clean_up_tokenization_spaces=__lowerCamelCase )
						if " " not in output_txt and len(__lowerCamelCase ) > 1:
										lowerCAmelCase__     :				Union[str, Any]												=     (
										    tokenizer.decode([toks_ids[0]]		,clean_up_tokenization_spaces=__lowerCamelCase )
										    + ' '
										    + tokenizer.decode(toks_ids[1:]		,clean_up_tokenization_spaces=__lowerCamelCase )
										)
						if with_prefix_space:
										lowerCAmelCase__     :				Dict												=     ' ' + output_txt
						lowerCAmelCase__     :				Tuple												=     tokenizer.encode(__lowerCamelCase		,add_special_tokens=__lowerCamelCase )
						return output_txt, output_ids



		def 		lowerCAmelCase__      (self )     ->			Dict:

						"""simple docstring"""






						lowerCAmelCase__     :				Union[str, Any]												=     self.perceiver_tokenizer
						lowerCAmelCase__     :				List[Any]												=     'Unicode €.'
						lowerCAmelCase__     :				Optional[int]												=     tokenizer(__lowerCamelCase )
						lowerCAmelCase__     :				List[Any]												=     [4, 91, 1_16, 1_11, 1_05, 1_17, 1_06, 1_07, 38, 2_32, 1_36, 1_78, 52, 5]
						self.assertEqual(encoded['''input_ids''']		,__lowerCamelCase )

						# decoding
						lowerCAmelCase__     :				Tuple												=     tokenizer.decode(__lowerCamelCase )
						self.assertEqual(__lowerCamelCase		,'''[CLS]Unicode €.[SEP]''' )

						lowerCAmelCase__     :				Dict												=     tokenizer('''e è é ê ë''' )
						lowerCAmelCase__     :				Dict												=     [4, 1_07, 38, 2_01, 1_74, 38, 2_01, 1_75, 38, 2_01, 1_76, 38, 2_01, 1_77, 5]
						self.assertEqual(encoded['''input_ids''']		,__lowerCamelCase )
						# decoding
						lowerCAmelCase__     :				Optional[int]												=     tokenizer.decode(__lowerCamelCase )
						self.assertEqual(__lowerCamelCase		,'''[CLS]e è é ê ë[SEP]''' )

						# encode/decode, but with `encode` instead of `__call__`
						self.assertEqual(tokenizer.decode(tokenizer.encode('''e è é ê ë''' ) )		,'''[CLS]e è é ê ë[SEP]''' )



		def 		lowerCAmelCase__      (self )     ->			Any:

						"""simple docstring"""






						lowerCAmelCase__     :				List[Any]												=     self.perceiver_tokenizer
						lowerCAmelCase__     :				Union[str, Any]												=     ['A long paragraph for summarization.', 'Another paragraph for summarization.']
						# fmt: off
						lowerCAmelCase__     :				Union[str, Any]												=     [4, 71, 38, 1_14, 1_17, 1_16, 1_09, 38, 1_18, 1_03, 1_20, 1_03, 1_09, 1_20, 1_03, 1_18, 1_10, 38, 1_08, 1_17, 1_20, 38, 1_21, 1_23, 1_15, 1_15, 1_03, 1_20, 1_11, 1_28, 1_03, 1_22, 1_11, 1_17, 1_16, 52, 5, 0]
						# fmt: on
						lowerCAmelCase__     :				str												=     tokenizer(__lowerCamelCase		,padding=__lowerCamelCase		,return_tensors=__lowerCamelCase )
						self.assertIsInstance(__lowerCamelCase		,__lowerCamelCase )

						if FRAMEWORK != "jax":
										lowerCAmelCase__     :				List[Any]												=     list(batch.input_ids.numpy()[0] )
						else:
										lowerCAmelCase__     :				Dict												=     list(batch.input_ids.tolist()[0] )

						self.assertListEqual(__lowerCamelCase		,__lowerCamelCase )

						self.assertEqual((2, 38)		,batch.input_ids.shape )
						self.assertEqual((2, 38)		,batch.attention_mask.shape )



		def 		lowerCAmelCase__      (self )     ->			Tuple:

						"""simple docstring"""






						lowerCAmelCase__     :				int												=     self.perceiver_tokenizer
						lowerCAmelCase__     :				Optional[Any]												=     ['A long paragraph for summarization.', 'Another paragraph for summarization.']
						lowerCAmelCase__     :				int												=     tokenizer(__lowerCamelCase		,padding=__lowerCamelCase		,return_tensors=__lowerCamelCase )
						# check if input_ids are returned and no decoder_input_ids
						self.assertIn('''input_ids'''		,__lowerCamelCase )
						self.assertIn('''attention_mask'''		,__lowerCamelCase )
						self.assertNotIn('''decoder_input_ids'''		,__lowerCamelCase )
						self.assertNotIn('''decoder_attention_mask'''		,__lowerCamelCase )



		def 		lowerCAmelCase__      (self )     ->			Optional[int]:

						"""simple docstring"""






						lowerCAmelCase__     :				str												=     self.perceiver_tokenizer
						lowerCAmelCase__     :				List[Any]												=     [
						    'Summary of the text.',
						    'Another summary.',
						]
						lowerCAmelCase__     :				List[Any]												=     tokenizer(
						    text_target=__lowerCamelCase		,max_length=32		,padding='''max_length'''		,truncation=__lowerCamelCase		,return_tensors=__lowerCamelCase )
						self.assertEqual(32		,targets['''input_ids'''].shape[1] )



		def 		lowerCAmelCase__      (self )     ->			Tuple:

						"""simple docstring"""






						lowerCAmelCase__     :				str												=     self.get_tokenizers()
						for tokenizer in tokenizers:
										with self.subTest(f"""{tokenizer.__class__.__name__}""" ):
														self.assertNotEqual(tokenizer.model_max_length		,42 )

        # Now let's start the test
						lowerCAmelCase__     :				Tuple												=     self.get_tokenizers()
						for tokenizer in tokenizers:
										with self.subTest(f"""{tokenizer.__class__.__name__}""" ):
														# Isolate this from the other tests because we save additional tokens/etc
														lowerCAmelCase__     :				Tuple												=     tempfile.mkdtemp()

														lowerCAmelCase__     :				Optional[Any]												=     ' He is very happy, UNwant\u00E9d,running'
														lowerCAmelCase__     :				Optional[int]												=     tokenizer.encode(__lowerCamelCase		,add_special_tokens=__lowerCamelCase )
														tokenizer.save_pretrained(__lowerCamelCase )

														lowerCAmelCase__     :				str												=     tokenizer.__class__.from_pretrained(__lowerCamelCase )
														lowerCAmelCase__     :				Optional[Any]												=     after_tokenizer.encode(__lowerCamelCase		,add_special_tokens=__lowerCamelCase )
														self.assertListEqual(__lowerCamelCase		,__lowerCamelCase )

														shutil.rmtree(__lowerCamelCase )

						lowerCAmelCase__     :				Optional[Any]												=     self.get_tokenizers(model_max_length=42 )
						for tokenizer in tokenizers:
										with self.subTest(f"""{tokenizer.__class__.__name__}""" ):
														# Isolate this from the other tests because we save additional tokens/etc
														lowerCAmelCase__     :				Optional[Any]												=     tempfile.mkdtemp()

														lowerCAmelCase__     :				Dict												=     ' He is very happy, UNwant\u00E9d,running'
														tokenizer.add_tokens(['''bim''', '''bambam'''] )
														lowerCAmelCase__     :				List[str]												=     tokenizer.additional_special_tokens
														additional_special_tokens.append('''new_additional_special_token''' )
														tokenizer.add_special_tokens({'''additional_special_tokens''': additional_special_tokens} )
														lowerCAmelCase__     :				int												=     tokenizer.encode(__lowerCamelCase		,add_special_tokens=__lowerCamelCase )
														tokenizer.save_pretrained(__lowerCamelCase )

														lowerCAmelCase__     :				Dict												=     tokenizer.__class__.from_pretrained(__lowerCamelCase )
														lowerCAmelCase__     :				str												=     after_tokenizer.encode(__lowerCamelCase		,add_special_tokens=__lowerCamelCase )
														self.assertListEqual(__lowerCamelCase		,__lowerCamelCase )
														self.assertIn('''new_additional_special_token'''		,after_tokenizer.additional_special_tokens )
														self.assertEqual(after_tokenizer.model_max_length		,42 )

														lowerCAmelCase__     :				Union[str, Any]												=     tokenizer.__class__.from_pretrained(__lowerCamelCase		,model_max_length=43 )
														self.assertEqual(tokenizer.model_max_length		,43 )

														shutil.rmtree(__lowerCamelCase )



		def 		lowerCAmelCase__      (self )     ->			Any:

						"""simple docstring"""






						lowerCAmelCase__     :				List[str]												=     []
						if self.test_slow_tokenizer:
										tokenizer_list.append((self.tokenizer_class, self.get_tokenizer()) )

						if self.test_rust_tokenizer:
										tokenizer_list.append((self.rust_tokenizer_class, self.get_rust_tokenizer()) )

						for tokenizer_class, tokenizer_utils in tokenizer_list:
										with tempfile.TemporaryDirectory() as tmp_dir:
														tokenizer_utils.save_pretrained(__lowerCamelCase )

														with open(os.path.join(__lowerCamelCase		,'''special_tokens_map.json''' )		,encoding='''utf-8''' ) as json_file:
																		lowerCAmelCase__     :				Tuple												=     json.load(__lowerCamelCase )

														with open(os.path.join(__lowerCamelCase		,'''tokenizer_config.json''' )		,encoding='''utf-8''' ) as json_file:
																		lowerCAmelCase__     :				Union[str, Any]												=     json.load(__lowerCamelCase )

														lowerCAmelCase__     :				List[str]												=     [f"""<extra_id_{i}>""" for i in range(1_25 )]

														lowerCAmelCase__     :				Dict												=     added_tokens_extra_ids + [
														    'an_additional_special_token'
														]
														lowerCAmelCase__     :				Tuple												=     added_tokens_extra_ids + [
														    'an_additional_special_token'
														]

														with open(os.path.join(__lowerCamelCase		,'''special_tokens_map.json''' )		,'''w'''		,encoding='''utf-8''' ) as outfile:
																		json.dump(__lowerCamelCase		,__lowerCamelCase )
														with open(os.path.join(__lowerCamelCase		,'''tokenizer_config.json''' )		,'''w'''		,encoding='''utf-8''' ) as outfile:
																		json.dump(__lowerCamelCase		,__lowerCamelCase )

														# the following checks allow us to verify that our test works as expected, i.e. that the tokenizer takes
														# into account the new value of additional_special_tokens given in the "tokenizer_config.json" and
														# "special_tokens_map.json" files
														lowerCAmelCase__     :				Any												=     tokenizer_class.from_pretrained(
														    __lowerCamelCase		,)
														self.assertIn(
														    '''an_additional_special_token'''		,tokenizer_without_change_in_init.additional_special_tokens )
														self.assertEqual(
														    ['''an_additional_special_token''']		,tokenizer_without_change_in_init.convert_ids_to_tokens(
														        tokenizer_without_change_in_init.convert_tokens_to_ids(['''an_additional_special_token'''] ) )		,)

														# Now we test that we can change the value of additional_special_tokens in the from_pretrained
														lowerCAmelCase__     :				str												=     added_tokens_extra_ids + [AddedToken('''a_new_additional_special_token'''		,lstrip=__lowerCamelCase )]
														lowerCAmelCase__     :				List[str]												=     tokenizer_class.from_pretrained(
														    __lowerCamelCase		,additional_special_tokens=__lowerCamelCase		,)

														self.assertIn('''a_new_additional_special_token'''		,tokenizer.additional_special_tokens )
														self.assertEqual(
														    ['''a_new_additional_special_token''']		,tokenizer.convert_ids_to_tokens(
														        tokenizer.convert_tokens_to_ids(['''a_new_additional_special_token'''] ) )		,)



		def 		lowerCAmelCase__      (self )     ->			str:

						"""simple docstring"""






						lowerCAmelCase__     :				Tuple												=     self.perceiver_tokenizer
						self.assertEqual(tokenizer.decode([1_78] )		,'''�''' )



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

						"""simple docstring"""






						pass



		def 		lowerCAmelCase__      (self )     ->			List[str]:

						"""simple docstring"""






						pass



		def 		lowerCAmelCase__      (self )     ->			Any:

						"""simple docstring"""






						pass



		def 		lowerCAmelCase__      (self )     ->			List[str]:

						"""simple docstring"""






						pass



		def 		lowerCAmelCase__      (self )     ->			Tuple:

						"""simple docstring"""






						lowerCAmelCase__     :				Any												=     self.get_tokenizers(fast=__lowerCamelCase		,do_lower_case=__lowerCamelCase )
						for tokenizer in tokenizers:
										with self.subTest(f"""{tokenizer.__class__.__name__}""" ):
														lowerCAmelCase__     :				Optional[Any]												=     ['[CLS]', 't', 'h', 'i', 's', ' ', 'i', 's', ' ', 'a', ' ', 't', 'e', 's', 't', '[SEP]']
														lowerCAmelCase__     :				Any												=     tokenizer.convert_tokens_to_string(__lowerCamelCase )

														self.assertIsInstance(__lowerCamelCase		,__lowerCamelCase )




from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


snake_case_			  = logging.get_logger(__name__)

snake_case_			  = {
    '''distilbert-base-uncased''': '''https://huggingface.co/distilbert-base-uncased/resolve/main/config.json''',
    '''distilbert-base-uncased-distilled-squad''': (
        '''https://huggingface.co/distilbert-base-uncased-distilled-squad/resolve/main/config.json'''
    ),
    '''distilbert-base-cased''': '''https://huggingface.co/distilbert-base-cased/resolve/main/config.json''',
    '''distilbert-base-cased-distilled-squad''': (
        '''https://huggingface.co/distilbert-base-cased-distilled-squad/resolve/main/config.json'''
    ),
    '''distilbert-base-german-cased''': '''https://huggingface.co/distilbert-base-german-cased/resolve/main/config.json''',
    '''distilbert-base-multilingual-cased''': (
        '''https://huggingface.co/distilbert-base-multilingual-cased/resolve/main/config.json'''
    ),
    '''distilbert-base-uncased-finetuned-sst-2-english''': (
        '''https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-english/resolve/main/config.json'''
    ),
}


class       SCREAMING_SNAKE_CASE__					(__snake_case     ):
    __lowerCamelCase						:       Any														=     """distilbert"""
    __lowerCamelCase						:       List[Any]														=     {
        """hidden_size""": """dim""",
        """num_attention_heads""": """n_heads""",
        """num_hidden_layers""": """n_layers""",
    }





    def __init__(      self						,   a=3_0522						,   a=512						,   a=False						,   a=6						,   a=12						,   a=768						,   a=4 * 768						,   a=0.1						,   a=0.1						,   a="gelu"						,   a=0.02						,   a=0.1						,   a=0.2						,   a=0						,   **a						,   ):
         lowercase__    :   int      =       vocab_size
         lowercase__    :   int      =       max_position_embeddings
         lowercase__    :   List[str]      =       sinusoidal_pos_embds
         lowercase__    :   Tuple      =       n_layers
         lowercase__    :   Optional[int]      =       n_heads
         lowercase__    :   List[Any]      =       dim
         lowercase__    :   Any      =       hidden_dim
         lowercase__    :   Union[str, Any]      =       dropout
         lowercase__    :   Optional[int]      =       attention_dropout
         lowercase__    :   List[Any]      =       activation
         lowercase__    :   Union[str, Any]      =       initializer_range
         lowercase__    :   Dict      =       qa_dropout
         lowercase__    :   Tuple      =       seq_classif_dropout
         super().__init__(**a						,   pad_token_id=a)



class       SCREAMING_SNAKE_CASE__					(__snake_case     ):





    @property
    def       snake_case_				(      self):
         if self.task == "multiple-choice":
              lowercase__    :   List[str]      =       {0: 'batch', 1: 'choice', 2: 'sequence'}
         else:
              lowercase__    :   Tuple      =       {0: 'batch', 1: 'sequence'}
         return OrderedDict(
             [
                 ('input_ids', dynamic_axis),
                 ('attention_mask', dynamic_axis),
             ])

