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

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

from ...test_tokenization_common import TokenizerTesterMixin


if is_torch_available():
						__a         =   'pt'
elif is_tf_available():
						__a         =   'tf'
else:
						__a         =   'jax'
class 					lowercase__(							UpperCAmelCase					,		unittest.TestCase				):



	"""simple docstring"""




	a     :List[str]       	=      ByTaTokenizer
	a     :Optional[int]       	=      False
	def 		_lowercase    (			self    :     List[Any]			)			->	int:
					super().setUp()
					lowercase_	    =   ByTaTokenizer()
					tokenizer.save_pretrained(self.tmpdirname			)
	@cached_property
	def 		_lowercase    (			self    :     str			)			->	Tuple:
					return ByTaTokenizer.from_pretrained('''google/byt5-small'''			)
	def 		_lowercase    (			self    :     str			,				**SCREAMING_SNAKE_CASE_    :     List[Any]			)			->	ByTaTokenizer:
					return self.tokenizer_class.from_pretrained(self.tmpdirname			,				**SCREAMING_SNAKE_CASE_			)
	def 		_lowercase    (			self    :     Union[str, Any]			,				SCREAMING_SNAKE_CASE_    :     int			,				SCREAMING_SNAKE_CASE_    :     List[str]=False			,				SCREAMING_SNAKE_CASE_    :     Dict=2_0			,				SCREAMING_SNAKE_CASE_    :     Tuple=5			)			->	Tuple[str, list]:
					# XXX The default common tokenizer tests assume that every ID is decodable on its own.
					# This assumption is invalid for ByT5 because single bytes might not be
					# valid utf-8 (byte 128 for instance).
					# Here we're overriding the smallest possible method to provide
					# a clean sequence without making the same assumption.

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

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

					# Ensure consistency
					lowercase_	    =   tokenizer.decode(SCREAMING_SNAKE_CASE_			,				clean_up_tokenization_spaces=SCREAMING_SNAKE_CASE_			)
					if " " not in output_txt and len(SCREAMING_SNAKE_CASE_			) > 1:
									lowercase_	    =   (
									    tokenizer.decode([toks_ids[0]]			,				clean_up_tokenization_spaces=SCREAMING_SNAKE_CASE_			)
									    + ''' '''
									    + tokenizer.decode(toks_ids[1:]			,				clean_up_tokenization_spaces=SCREAMING_SNAKE_CASE_			)
									)
					if with_prefix_space:
									lowercase_	    =   ''' ''' + output_txt
					lowercase_	    =   tokenizer.encode(SCREAMING_SNAKE_CASE_			,				add_special_tokens=SCREAMING_SNAKE_CASE_			)
					return output_txt, output_ids
	def 		_lowercase    (			self    :     Union[str, Any]			)			->	Tuple:
					lowercase_	    =   self.ta_base_tokenizer
					lowercase_	    =   tokenizer(['''hi</s>''', '''I went to the gym</s>''', '''</s>''']			)
					lowercase_	    =   tokenizer(['''hi''', '''I went to the gym''', '''''']			)
					self.assertListEqual(batch_with_eos_added['''input_ids''']			,				batch_without_eos_added['''input_ids''']			)
	def 		_lowercase    (			self    :     Dict			)			->	List[Any]:
					lowercase_	    =   self.ta_base_tokenizer
					lowercase_	    =   '''Unicode €.'''
					lowercase_	    =   tokenizer(SCREAMING_SNAKE_CASE_			)
					lowercase_	    =   [8_8, 1_1_3, 1_0_8, 1_0_2, 1_1_4, 1_0_3, 1_0_4, 3_5, 2_2_9, 1_3_3, 1_7_5, 4_9, 1]
					self.assertEqual(encoded['''input_ids''']			,				SCREAMING_SNAKE_CASE_			)

					# decoding
					lowercase_	    =   tokenizer.decode(SCREAMING_SNAKE_CASE_			)
					self.assertEqual(SCREAMING_SNAKE_CASE_			,				'''Unicode €.</s>'''			)

					lowercase_	    =   tokenizer('''e è é ê ë'''			)
					lowercase_	    =   [1_0_4, 3_5, 1_9_8, 1_7_1, 3_5, 1_9_8, 1_7_2, 3_5, 1_9_8, 1_7_3, 3_5, 1_9_8, 1_7_4, 1]
					self.assertEqual(encoded['''input_ids''']			,				SCREAMING_SNAKE_CASE_			)
					# decoding
					lowercase_	    =   tokenizer.decode(SCREAMING_SNAKE_CASE_			)
					self.assertEqual(SCREAMING_SNAKE_CASE_			,				'''e è é ê ë</s>'''			)

					# encode/decode, but with `encode` instead of `__call__`
					self.assertEqual(tokenizer.decode(tokenizer.encode('''e è é ê ë'''			)			)			,				'''e è é ê ë</s>'''			)
	def 		_lowercase    (			self    :     int			)			->	List[Any]:
					lowercase_	    =   self.ta_base_tokenizer
					lowercase_	    =   ['''A long paragraph for summarization.''', '''Another paragraph for summarization.''']
					# fmt: off
					lowercase_	    =   [6_8, 3_5, 1_1_1, 1_1_4, 1_1_3, 1_0_6, 3_5, 1_1_5, 1_0_0, 1_1_7, 1_0_0, 1_0_6, 1_1_7, 1_0_0, 1_1_5, 1_0_7, 3_5, 1_0_5, 1_1_4, 1_1_7, 3_5, 1_1_8, 1_2_0, 1_1_2, 1_1_2, 1_0_0, 1_1_7, 1_0_8, 1_2_5, 1_0_0, 1_1_9, 1_0_8, 1_1_4, 1_1_3, 4_9, 1, 0]
					# fmt: on
					lowercase_	    =   tokenizer(SCREAMING_SNAKE_CASE_			,				padding=SCREAMING_SNAKE_CASE_			,				return_tensors=SCREAMING_SNAKE_CASE_			)
					self.assertIsInstance(SCREAMING_SNAKE_CASE_			,				SCREAMING_SNAKE_CASE_			)

					if FRAMEWORK != "jax":
									lowercase_	    =   list(batch.input_ids.numpy()[0]			)
					else:
									lowercase_	    =   list(batch.input_ids.tolist()[0]			)

					self.assertListEqual(SCREAMING_SNAKE_CASE_			,				SCREAMING_SNAKE_CASE_			)

					self.assertEqual((2, 3_7)			,				batch.input_ids.shape			)
					self.assertEqual((2, 3_7)			,				batch.attention_mask.shape			)
	def 		_lowercase    (			self    :     int			)			->	List[str]:
					lowercase_	    =   self.ta_base_tokenizer
					lowercase_	    =   ['''A long paragraph for summarization.''', '''Another paragraph for summarization.''']
					lowercase_	    =   tokenizer(SCREAMING_SNAKE_CASE_			,				padding=SCREAMING_SNAKE_CASE_			,				return_tensors=SCREAMING_SNAKE_CASE_			)
					# check if input_ids are returned and no decoder_input_ids
					self.assertIn('''input_ids'''			,				SCREAMING_SNAKE_CASE_			)
					self.assertIn('''attention_mask'''			,				SCREAMING_SNAKE_CASE_			)
					self.assertNotIn('''decoder_input_ids'''			,				SCREAMING_SNAKE_CASE_			)
					self.assertNotIn('''decoder_attention_mask'''			,				SCREAMING_SNAKE_CASE_			)
	def 		_lowercase    (			self    :     List[str]			)			->	Any:
					lowercase_	    =   self.ta_base_tokenizer
					lowercase_	    =   [
					    '''Summary of the text.''',
					    '''Another summary.''',
					]
					lowercase_	    =   tokenizer(
					    text_target=SCREAMING_SNAKE_CASE_			,				max_length=3_2			,				padding='''max_length'''			,				truncation=SCREAMING_SNAKE_CASE_			,				return_tensors=SCREAMING_SNAKE_CASE_			)
					self.assertEqual(3_2			,				targets['''input_ids'''].shape[1]			)
	def 		_lowercase    (			self    :     int			)			->	Any:
					lowercase_	    =   self.ta_base_tokenizer
					lowercase_	    =   ['''A long paragraph for summarization. </s>''']
					lowercase_	    =   ['''Summary of the text. </s>''']
					# fmt: off
					lowercase_	    =   [6_8, 3_5, 1_1_1, 1_1_4, 1_1_3, 1_0_6, 3_5, 1_1_5, 1_0_0, 1_1_7, 1_0_0, 1_0_6, 1_1_7, 1_0_0, 1_1_5, 1_0_7, 3_5, 1_0_5, 1_1_4, 1_1_7, 3_5, 1_1_8, 1_2_0, 1_1_2, 1_1_2, 1_0_0, 1_1_7, 1_0_8, 1_2_5, 1_0_0, 1_1_9, 1_0_8, 1_1_4, 1_1_3, 4_9, 3_5, 1]
					lowercase_	    =   [8_6, 1_2_0, 1_1_2, 1_1_2, 1_0_0, 1_1_7, 1_2_4, 3_5, 1_1_4, 1_0_5, 3_5, 1_1_9, 1_0_7, 1_0_4, 3_5, 1_1_9, 1_0_4, 1_2_3, 1_1_9, 4_9, 3_5, 1]
					# fmt: on

					lowercase_	    =   tokenizer(SCREAMING_SNAKE_CASE_			,				text_target=SCREAMING_SNAKE_CASE_			)

					self.assertEqual(SCREAMING_SNAKE_CASE_			,				batch['''input_ids'''][0]			)
					self.assertEqual(SCREAMING_SNAKE_CASE_			,				batch['''labels'''][0]			)
	def 		_lowercase    (			self    :     List[str]			)			->	Optional[int]:
					# safety check on max_len default value so we are sure the test works
					lowercase_	    =   self.get_tokenizers()
					for tokenizer in tokenizers:
									with self.subTest(f'''{tokenizer.__class__.__name__}'''			):
													self.assertNotEqual(tokenizer.model_max_length			,				4_2			)

        # Now let's start the test
					lowercase_	    =   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
													lowercase_	    =   tempfile.mkdtemp()

													lowercase_	    =   ''' He is very happy, UNwant\u00E9d,running'''
													lowercase_	    =   tokenizer.encode(SCREAMING_SNAKE_CASE_			,				add_special_tokens=SCREAMING_SNAKE_CASE_			)
													tokenizer.save_pretrained(SCREAMING_SNAKE_CASE_			)

													lowercase_	    =   tokenizer.__class__.from_pretrained(SCREAMING_SNAKE_CASE_			)
													lowercase_	    =   after_tokenizer.encode(SCREAMING_SNAKE_CASE_			,				add_special_tokens=SCREAMING_SNAKE_CASE_			)
													self.assertListEqual(SCREAMING_SNAKE_CASE_			,				SCREAMING_SNAKE_CASE_			)

													shutil.rmtree(SCREAMING_SNAKE_CASE_			)

					lowercase_	    =   self.get_tokenizers(model_max_length=4_2			)
					for tokenizer in tokenizers:
									with self.subTest(f'''{tokenizer.__class__.__name__}'''			):
													# Isolate this from the other tests because we save additional tokens/etc
													lowercase_	    =   tempfile.mkdtemp()

													lowercase_	    =   ''' He is very happy, UNwant\u00E9d,running'''
													tokenizer.add_tokens(['''bim''', '''bambam''']			)
													lowercase_	    =   tokenizer.additional_special_tokens
													additional_special_tokens.append('''new_additional_special_token'''			)
													tokenizer.add_special_tokens({'''additional_special_tokens''': additional_special_tokens}			)
													lowercase_	    =   tokenizer.encode(SCREAMING_SNAKE_CASE_			,				add_special_tokens=SCREAMING_SNAKE_CASE_			)
													tokenizer.save_pretrained(SCREAMING_SNAKE_CASE_			)

													lowercase_	    =   tokenizer.__class__.from_pretrained(SCREAMING_SNAKE_CASE_			)
													lowercase_	    =   after_tokenizer.encode(SCREAMING_SNAKE_CASE_			,				add_special_tokens=SCREAMING_SNAKE_CASE_			)
													self.assertListEqual(SCREAMING_SNAKE_CASE_			,				SCREAMING_SNAKE_CASE_			)
													self.assertIn('''new_additional_special_token'''			,				after_tokenizer.additional_special_tokens			)
													self.assertEqual(after_tokenizer.model_max_length			,				4_2			)

													lowercase_	    =   tokenizer.__class__.from_pretrained(SCREAMING_SNAKE_CASE_			,				model_max_length=4_3			)
													self.assertEqual(tokenizer.model_max_length			,				4_3			)

													shutil.rmtree(SCREAMING_SNAKE_CASE_			)
	def 		_lowercase    (			self    :     List[Any]			)			->	Optional[int]:
					lowercase_	    =   []
					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(SCREAMING_SNAKE_CASE_			)

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

													with open(os.path.join(SCREAMING_SNAKE_CASE_			,				'''tokenizer_config.json'''			)			,				encoding='''utf-8'''			) as json_file:
																	lowercase_	    =   json.load(SCREAMING_SNAKE_CASE_			)

													lowercase_	    =   [f'''<extra_id_{i}>''' for i in range(1_2_5			)]

													lowercase_	    =   added_tokens_extra_ids + [
													    '''an_additional_special_token'''
													]
													lowercase_	    =   added_tokens_extra_ids + [
													    '''an_additional_special_token'''
													]

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

													# 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
													lowercase_	    =   tokenizer_class.from_pretrained(
													    SCREAMING_SNAKE_CASE_			,				)
													self.assertIn(
													    '''an_additional_special_token'''			,				tokenizer_without_change_in_init.additional_special_tokens			)
													# self.assertIn("an_additional_special_token",tokenizer_without_change_in_init.get_vocab()) # ByT5Tokenization no vocab
													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
													lowercase_	    =   added_tokens_extra_ids + [AddedToken('''a_new_additional_special_token'''			,				lstrip=SCREAMING_SNAKE_CASE_			)]
													lowercase_	    =   tokenizer_class.from_pretrained(
													    SCREAMING_SNAKE_CASE_			,				additional_special_tokens=SCREAMING_SNAKE_CASE_			,				)

													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 		_lowercase    (			self    :     Union[str, Any]			)			->	Optional[Any]:
					lowercase_	    =   []
					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(SCREAMING_SNAKE_CASE_			)

													lowercase_	    =   tokenizer_class.from_pretrained(SCREAMING_SNAKE_CASE_			)

													self.assertTrue(tokenizer.decode([2_5_5]			) == ''''''			)
	def 		_lowercase    (			self    :     List[Any]			)			->	Dict:
					pass
	def 		_lowercase    (			self    :     Union[str, Any]			)			->	Any:
					pass
	def 		_lowercase    (			self    :     Optional[Any]			)			->	str:
					pass
	def 		_lowercase    (			self    :     Optional[int]			)			->	Any:
					pass
	def 		_lowercase    (			self    :     str			)			->	str:
					# The default common tokenizer tests uses invalid tokens for ByT5 that can only accept one-character strings
					# and special added tokens as tokens
					lowercase_	    =   self.get_tokenizers(fast=SCREAMING_SNAKE_CASE_			,				do_lower_case=SCREAMING_SNAKE_CASE_			)
					for tokenizer in tokenizers:
									with self.subTest(f'''{tokenizer.__class__.__name__}'''			):
													lowercase_	    =   ['''t''', '''h''', '''i''', '''s''', ''' ''', '''i''', '''s''', ''' ''', '''a''', ''' ''', '''t''', '''e''', '''x''', '''t''', '''</s>''']
													lowercase_	    =   tokenizer.convert_tokens_to_string(SCREAMING_SNAKE_CASE_			)

													self.assertIsInstance(SCREAMING_SNAKE_CASE_			,				SCREAMING_SNAKE_CASE_			)




	def 		_lowercase    (			self    :     str			)			->	Dict:
					lowercase_	    =   self.get_tokenizers()
					for tokenizer in tokenizers:
									with self.subTest(f'''{tokenizer.__class__.__name__}'''			):
													lowercase_	    =   [
													    '''bos_token''',
													    '''eos_token''',
													    '''unk_token''',
													    '''sep_token''',
													    '''pad_token''',
													    '''cls_token''',
													    '''mask_token''',
													]

													lowercase_	    =   0
													lowercase_	    =   tokenizer.convert_ids_to_tokens(
													    SCREAMING_SNAKE_CASE_			,				skip_special_tokens=SCREAMING_SNAKE_CASE_			)

													for attr in attributes_list:
																	setattr(SCREAMING_SNAKE_CASE_			,				attr + '''_id'''			,				SCREAMING_SNAKE_CASE_			)
																	self.assertEqual(getattr(SCREAMING_SNAKE_CASE_			,				SCREAMING_SNAKE_CASE_			)			,				SCREAMING_SNAKE_CASE_			)
																	self.assertEqual(getattr(SCREAMING_SNAKE_CASE_			,				attr + '''_id'''			)			,				SCREAMING_SNAKE_CASE_			)

																	setattr(SCREAMING_SNAKE_CASE_			,				attr + '''_id'''			,				SCREAMING_SNAKE_CASE_			)
																	self.assertEqual(getattr(SCREAMING_SNAKE_CASE_			,				SCREAMING_SNAKE_CASE_			)			,				SCREAMING_SNAKE_CASE_			)
																	self.assertEqual(getattr(SCREAMING_SNAKE_CASE_			,				attr + '''_id'''			)			,				SCREAMING_SNAKE_CASE_			)

													setattr(SCREAMING_SNAKE_CASE_			,				'''additional_special_tokens_ids'''			,				[]			)
													self.assertListEqual(getattr(SCREAMING_SNAKE_CASE_			,				'''additional_special_tokens'''			)			,				[]			)
													self.assertListEqual(getattr(SCREAMING_SNAKE_CASE_			,				'''additional_special_tokens_ids'''			)			,				[]			)

													setattr(SCREAMING_SNAKE_CASE_			,				'''additional_special_tokens_ids'''			,				[token_id_to_test_setters]			)
													self.assertListEqual(getattr(SCREAMING_SNAKE_CASE_			,				'''additional_special_tokens'''			)			,				[token_to_test_setters]			)
													self.assertListEqual(getattr(SCREAMING_SNAKE_CASE_			,				'''additional_special_tokens_ids'''			)			,				[token_id_to_test_setters]			)






from collections import OrderedDict
from typing import Mapping

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


__a         =   logging.get_logger(__name__)

__a         =   {
    'xlm-mlm-en-2048': 'https://huggingface.co/xlm-mlm-en-2048/resolve/main/config.json',
    'xlm-mlm-ende-1024': 'https://huggingface.co/xlm-mlm-ende-1024/resolve/main/config.json',
    'xlm-mlm-enfr-1024': 'https://huggingface.co/xlm-mlm-enfr-1024/resolve/main/config.json',
    'xlm-mlm-enro-1024': 'https://huggingface.co/xlm-mlm-enro-1024/resolve/main/config.json',
    'xlm-mlm-tlm-xnli15-1024': 'https://huggingface.co/xlm-mlm-tlm-xnli15-1024/resolve/main/config.json',
    'xlm-mlm-xnli15-1024': 'https://huggingface.co/xlm-mlm-xnli15-1024/resolve/main/config.json',
    'xlm-clm-enfr-1024': 'https://huggingface.co/xlm-clm-enfr-1024/resolve/main/config.json',
    'xlm-clm-ende-1024': 'https://huggingface.co/xlm-clm-ende-1024/resolve/main/config.json',
    'xlm-mlm-17-1280': 'https://huggingface.co/xlm-mlm-17-1280/resolve/main/config.json',
    'xlm-mlm-100-1280': 'https://huggingface.co/xlm-mlm-100-1280/resolve/main/config.json',
}
class 					lowercase__(							UpperCAmelCase				):



	"""simple docstring"""




	a     :List[Any]       	=      'xlm'
	a     :Dict       	=      {
	    'hidden_size': 'emb_dim',
	    'num_attention_heads': 'n_heads',
	    'num_hidden_layers': 'n_layers',
	    'n_words': 'vocab_size',  # For backward compatibility
	}
	def __init__(			self    :     List[Any]			,				SCREAMING_SNAKE_CASE_    :     Dict=3_0_1_4_5			,				SCREAMING_SNAKE_CASE_    :     Dict=2_0_4_8			,				SCREAMING_SNAKE_CASE_    :     Optional[int]=1_2			,				SCREAMING_SNAKE_CASE_    :     Optional[int]=1_6			,				SCREAMING_SNAKE_CASE_    :     Dict=0.1			,				SCREAMING_SNAKE_CASE_    :     str=0.1			,				SCREAMING_SNAKE_CASE_    :     Any=True			,				SCREAMING_SNAKE_CASE_    :     Any=False			,				SCREAMING_SNAKE_CASE_    :     str=False			,				SCREAMING_SNAKE_CASE_    :     Optional[Any]=False			,				SCREAMING_SNAKE_CASE_    :     Optional[Any]=1			,				SCREAMING_SNAKE_CASE_    :     Dict=True			,				SCREAMING_SNAKE_CASE_    :     Dict=5_1_2			,				SCREAMING_SNAKE_CASE_    :     Optional[int]=2_0_4_8**-0.5			,				SCREAMING_SNAKE_CASE_    :     Dict=1e-12			,				SCREAMING_SNAKE_CASE_    :     Any=0.02			,				SCREAMING_SNAKE_CASE_    :     str=0			,				SCREAMING_SNAKE_CASE_    :     List[Any]=1			,				SCREAMING_SNAKE_CASE_    :     List[Any]=2			,				SCREAMING_SNAKE_CASE_    :     int=3			,				SCREAMING_SNAKE_CASE_    :     Dict=5			,				SCREAMING_SNAKE_CASE_    :     int=True			,				SCREAMING_SNAKE_CASE_    :     List[Any]="first"			,				SCREAMING_SNAKE_CASE_    :     Any=True			,				SCREAMING_SNAKE_CASE_    :     List[Any]=None			,				SCREAMING_SNAKE_CASE_    :     str=True			,				SCREAMING_SNAKE_CASE_    :     Union[str, Any]=0.1			,				SCREAMING_SNAKE_CASE_    :     Optional[Any]=5			,				SCREAMING_SNAKE_CASE_    :     List[str]=5			,				SCREAMING_SNAKE_CASE_    :     Any=0			,				SCREAMING_SNAKE_CASE_    :     str=0			,				SCREAMING_SNAKE_CASE_    :     Optional[Any]=2			,				SCREAMING_SNAKE_CASE_    :     Tuple=0			,				**SCREAMING_SNAKE_CASE_    :     Dict			,				)			->	List[Any]:
					lowercase_	    =   vocab_size
					lowercase_	    =   emb_dim
					lowercase_	    =   n_layers
					lowercase_	    =   n_heads
					lowercase_	    =   dropout
					lowercase_	    =   attention_dropout
					lowercase_	    =   gelu_activation
					lowercase_	    =   sinusoidal_embeddings
					lowercase_	    =   causal
					lowercase_	    =   asm
					lowercase_	    =   n_langs
					lowercase_	    =   use_lang_emb
					lowercase_	    =   layer_norm_eps
					lowercase_	    =   bos_index
					lowercase_	    =   eos_index
					lowercase_	    =   pad_index
					lowercase_	    =   unk_index
					lowercase_	    =   mask_index
					lowercase_	    =   is_encoder
					lowercase_	    =   max_position_embeddings
					lowercase_	    =   embed_init_std
					lowercase_	    =   init_std
					lowercase_	    =   summary_type
					lowercase_	    =   summary_use_proj
					lowercase_	    =   summary_activation
					lowercase_	    =   summary_proj_to_labels
					lowercase_	    =   summary_first_dropout
					lowercase_	    =   start_n_top
					lowercase_	    =   end_n_top
					lowercase_	    =   mask_token_id
					lowercase_	    =   lang_id

					if "n_words" in kwargs:
									lowercase_	    =   kwargs['''n_words''']

					super().__init__(pad_token_id=SCREAMING_SNAKE_CASE_			,				bos_token_id=SCREAMING_SNAKE_CASE_			,				**SCREAMING_SNAKE_CASE_			)

class 					lowercase__(							UpperCAmelCase				):



	"""simple docstring"""




	@property
	def 		_lowercase    (			self    :     int			)			->	Mapping[str, Mapping[int, str]]:
					if self.task == "multiple-choice":
									lowercase_	    =   {0: '''batch''', 1: '''choice''', 2: '''sequence'''}
					else:
									lowercase_	    =   {0: '''batch''', 1: '''sequence'''}
					return OrderedDict(
					    [
					        ('''input_ids''', dynamic_axis),
					        ('''attention_mask''', dynamic_axis),
					        ('''token_type_ids''', dynamic_axis),
					    ]			)




