




'''simple docstring'''

from collections import OrderedDict
from typing import Mapping

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


a    :							Union[str, Any]										=    logging.get_logger(__name__)

a    :							Optional[int]										=    {
    'YituTech/conv-bert-base': 'https://huggingface.co/YituTech/conv-bert-base/resolve/main/config.json',
    'YituTech/conv-bert-medium-small': (
        'https://huggingface.co/YituTech/conv-bert-medium-small/resolve/main/config.json'
    ),
    'YituTech/conv-bert-small': 'https://huggingface.co/YituTech/conv-bert-small/resolve/main/config.json',
    # See all ConvBERT models at https://huggingface.co/models?filter=convbert
}






class 		a							(  _lowerCamelCase	):
				snake_case_           =						"convbert"


				def __init__(						self       :   Any			,							lowercase_       :   Tuple=3_0522			,							lowercase_       :   Any=768			,							lowercase_       :   List[str]=12			,							lowercase_       :   Optional[Any]=12			,							lowercase_       :   Tuple=3072			,							lowercase_       :   str="gelu"			,							lowercase_       :   List[str]=0.1			,							lowercase_       :   str=0.1			,							lowercase_       :   Optional[Any]=512			,							lowercase_       :   Optional[Any]=2			,							lowercase_       :   Optional[Any]=0.02			,							lowercase_       :   Any=1e-12			,							lowercase_       :   Any=1			,							lowercase_       :   Union[str, Any]=0			,							lowercase_       :   Union[str, Any]=2			,							lowercase_       :   Optional[Any]=768			,							lowercase_       :   Optional[int]=2			,							lowercase_       :   List[str]=9			,							lowercase_       :   List[str]=1			,							lowercase_       :   Dict=None			,							**lowercase_       :   int			,							):
									super().__init__(
									    pad_token_id=lowercase_			,							bos_token_id=lowercase_			,							eos_token_id=lowercase_			,							**lowercase_			,							)

									snake_case_		     =							vocab_size
									snake_case_		     =							hidden_size
									snake_case_		     =							num_hidden_layers
									snake_case_		     =							num_attention_heads
									snake_case_		     =							intermediate_size
									snake_case_		     =							hidden_act
									snake_case_		     =							hidden_dropout_prob
									snake_case_		     =							attention_probs_dropout_prob
									snake_case_		     =							max_position_embeddings
									snake_case_		     =							type_vocab_size
									snake_case_		     =							initializer_range
									snake_case_		     =							layer_norm_eps
									snake_case_		     =							embedding_size
									snake_case_		     =							head_ratio
									snake_case_		     =							conv_kernel_size
									snake_case_		     =							num_groups
									snake_case_		     =							classifier_dropout







class 		a							(  _lowerCamelCase	):


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







'''simple docstring'''

import json
import os
import unittest

from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin






@require_tokenizers
class 		a							(  _lowerCamelCase  ,	unittest.TestCase	):
				snake_case_           =						CLIPTokenizer
				snake_case_           =						CLIPTokenizerFast
				snake_case_           =						True
				snake_case_           =						{}
				snake_case_           =						False


				def     A_					(						self       :   List[Any]   ):
									super().setUp()

									# fmt: off
									snake_case_		     =							['''l''', '''o''', '''w''', '''e''', '''r''', '''s''', '''t''', '''i''', '''d''', '''n''', '''lo''', '''l</w>''', '''w</w>''', '''r</w>''', '''t</w>''', '''low</w>''', '''er</w>''', '''lowest</w>''', '''newer</w>''', '''wider''', '''<unk>''', '''<|startoftext|>''', '''<|endoftext|>''']
									# fmt: on
									snake_case_		     =							dict(zip(lowercase_			,							range(len(lowercase_   )   )   )   )
									snake_case_		     =							['''#version: 0.2''', '''l o''', '''lo w</w>''', '''e r</w>''']
									snake_case_		     =							{'''unk_token''': '''<unk>'''}

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


				def     A_					(						self       :   Tuple			,							**lowercase_       :   Tuple   ):
									kwargs.update(self.special_tokens_map   )
									return CLIPTokenizer.from_pretrained(self.tmpdirname			,							**lowercase_   )


				def     A_					(						self       :   List[str]			,							**lowercase_       :   Dict   ):
									kwargs.update(self.special_tokens_map   )
									return CLIPTokenizerFast.from_pretrained(self.tmpdirname			,							**lowercase_   )


				def     A_					(						self       :   Optional[int]			,							lowercase_       :   Optional[int]   ):
									snake_case_		     =							'''lower newer'''
									snake_case_		     =							'''lower newer'''
									return input_text, output_text


				def     A_					(						self       :   Optional[int]   ):
									snake_case_		     =							CLIPTokenizer(self.vocab_file			,							self.merges_file			,							**self.special_tokens_map   )
									snake_case_		     =							'''lower newer'''
									snake_case_		     =							['''lo''', '''w''', '''er</w>''', '''n''', '''e''', '''w''', '''er</w>''']
									snake_case_		     =							tokenizer.tokenize(lowercase_   )
									self.assertListEqual(lowercase_			,							lowercase_   )

									snake_case_		     =							tokens + [tokenizer.unk_token]
									snake_case_		     =							[10, 2, 16, 9, 3, 2, 16, 20]
									self.assertListEqual(tokenizer.convert_tokens_to_ids(lowercase_   )			,							lowercase_   )


				@require_ftfy
				def     A_					(						self       :   Optional[Any]   ):
									for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
														with self.subTest(F"{tokenizer.__class__.__name__} ({pretrained_name})"   ):
																			snake_case_		     =							self.tokenizer_class.from_pretrained(lowercase_			,							**lowercase_   )
																			snake_case_		     =							self.rust_tokenizer_class.from_pretrained(lowercase_			,							**lowercase_   )

																			snake_case_		     =							'''A\n\'ll 11p223RF☆ho!!to?\'d\'d\'\'d of a cat to-$\'\'d.'''
																			snake_case_		     =							tokenizer_s.tokenize(lowercase_   )
																			snake_case_		     =							tokenizer_r.tokenize(lowercase_   )

																			self.assertListEqual(lowercase_			,							lowercase_   )

																			# Test that the tokenization is identical on an example containing a character (Latin Small Letter A
																			# with Tilde) encoded in 2 different ways
																			snake_case_		     =							'''xa\u0303y''' + ''' ''' + '''x\xe3y'''
																			snake_case_		     =							tokenizer_s.tokenize(lowercase_   )
																			snake_case_		     =							tokenizer_r.tokenize(lowercase_   )

																			self.assertListEqual(lowercase_			,							lowercase_   )

																			# Test that the tokenization is identical on unicode of space type
																			snake_case_		     =							[
																			    '''\u0009''',  # (horizontal tab, '\t')
																			    '''\u000B''',  # (vertical tab)
																			    '''\u000C''',  # (form feed)
																			    '''\u0020''',  # (space, ' ')
																			    '''\u200E''',  # (left-to-right mark):w
																			    '''\u200F''',  # (right-to-left mark)
																			]
																			for unicode_seq in spaces_unicodes:
																								snake_case_		     =							tokenizer_s.tokenize(lowercase_   )
																								snake_case_		     =							tokenizer_r.tokenize(lowercase_   )

																								self.assertListEqual(lowercase_			,							lowercase_   )

																			# Test that the tokenization is identical on unicode of line break type
																			snake_case_		     =							[
																			    '''\u000A''',  # (line feed, '\n')
																			    '''\r\n''',  # (carriage return and line feed, '\r\n')
																			    '''\u000D''',  # (carriage return, '\r')
																			    '''\r''',  # (carriage return, '\r')
																			    '''\u000D''',  # (carriage return, '\r')
																			    '''\u2028''',  # (line separator)
																			    '''\u2029''',  # (paragraph separator)
																			    # "\u0085", # (next line)
																			]

																			# The tokenization is not identical for the character "\u0085" (next line). The slow version using ftfy transforms
																			# it into the Horizontal Ellipsis character "…" ("\u2026") while the fast version transforms it into a
																			# space (and thus into an empty list).

																			for unicode_seq in line_break_unicodes:
																								snake_case_		     =							tokenizer_s.tokenize(lowercase_   )
																								snake_case_		     =							tokenizer_r.tokenize(lowercase_   )

																								self.assertListEqual(lowercase_			,							lowercase_   )


				def     A_					(						self       :   List[str]   ):
									# Test which aims to verify that the offsets are well adapted to the argument `add_prefix_space`
									for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
														with self.subTest(F"{tokenizer.__class__.__name__} ({pretrained_name})"   ):
																			snake_case_		     =							'''hello'''  # `hello` is a token in the vocabulary of `pretrained_name`
																			snake_case_		     =							F"{text_of_1_token} {text_of_1_token}"

																			snake_case_		     =							self.rust_tokenizer_class.from_pretrained(
																			    lowercase_			,							use_fast=lowercase_			,							)
																			snake_case_		     =							tokenizer_r(lowercase_			,							return_offsets_mapping=lowercase_			,							add_special_tokens=lowercase_   )
																			self.assertEqual(encoding.offset_mapping[0]			,							(0, len(lowercase_   ))   )
																			self.assertEqual(
																			    encoding.offset_mapping[1]			,							(len(lowercase_   ) + 1, len(lowercase_   ) + 1 + len(lowercase_   ))			,							)

																			snake_case_		     =							F" {text}"

																			snake_case_		     =							self.rust_tokenizer_class.from_pretrained(
																			    lowercase_			,							use_fast=lowercase_			,							)
																			snake_case_		     =							tokenizer_r(lowercase_			,							return_offsets_mapping=lowercase_			,							add_special_tokens=lowercase_   )
																			self.assertEqual(encoding.offset_mapping[0]			,							(1, 1 + len(lowercase_   ))   )
																			self.assertEqual(
																			    encoding.offset_mapping[1]			,							(1 + len(lowercase_   ) + 1, 1 + len(lowercase_   ) + 1 + len(lowercase_   ))			,							)


				def     A_					(						self       :   Optional[Any]   ):
									# Test related to the breaking change introduced in transformers v4.17.0
									# We need to check that an error in raised when the user try to load a previous version of the tokenizer.
									with self.assertRaises(lowercase_   ) as context:
														self.rust_tokenizer_class.from_pretrained('''robot-test/old-clip-tokenizer'''   )

									self.assertTrue(
									    context.exception.args[0].startswith(
									        '''The `backend_tokenizer` provided does not match the expected format.'''   )   )


				@require_ftfy
				def     A_					(						self       :   List[str]   ):
									super().test_tokenization_python_rust_equals()


				def     A_					(						self       :   List[Any]   ):
									# CLIP always lower cases letters
									pass

