
"""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     ( __a					,   unittest.TestCase       ):



							'''simple docstring'''







							_lowerCamelCase					:			int          =   CLIPTokenizer
							_lowerCamelCase					:			Tuple          =   CLIPTokenizerFast
							_lowerCamelCase					:			int          =   True
							_lowerCamelCase					:			Union[str, Any]          =   {}
							_lowerCamelCase					:			Optional[Any]          =   False
							def   SCREAMING_SNAKE_CASE						(     self       )			->							Optional[int]:




										'''simple docstring'''
										super().setUp()

										# fmt: off
										__lowercase       =       ["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
										__lowercase       =       dict(zip(_lowerCamelCase  ,    range(len(_lowerCamelCase       )       )       )       )
										__lowercase       =       ["#version: 0.2", "l o", "lo w</w>", "e r</w>"]
										__lowercase       =       {"unk_token": "<unk>"}

										__lowercase       =       os.path.join(self.tmpdirname  ,    VOCAB_FILES_NAMES["vocab_file"]       )
										__lowercase       =       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(_lowerCamelCase       ) + "\n"       )
										with open(self.merges_file  ,    "w"  ,    encoding="utf-8"       ) as fp:
													fp.write("\n".join(_lowerCamelCase       )       )
							def   SCREAMING_SNAKE_CASE						(     self  ,    **_lowerCamelCase       )			->							str:




										'''simple docstring'''
										kwargs.update(self.special_tokens_map       )
										return CLIPTokenizer.from_pretrained(self.tmpdirname  ,    **_lowerCamelCase       )
							def   SCREAMING_SNAKE_CASE						(     self  ,    **_lowerCamelCase       )			->							Union[str, Any]:




										'''simple docstring'''
										kwargs.update(self.special_tokens_map       )
										return CLIPTokenizerFast.from_pretrained(self.tmpdirname  ,    **_lowerCamelCase       )
							def   SCREAMING_SNAKE_CASE						(     self  ,    _lowerCamelCase       )			->							int:




										'''simple docstring'''
										__lowercase       =       "lower newer"
										__lowercase       =       "lower newer"
										return input_text, output_text
							def   SCREAMING_SNAKE_CASE						(     self       )			->							int:




										'''simple docstring'''
										__lowercase       =       CLIPTokenizer(self.vocab_file  ,    self.merges_file  ,    **self.special_tokens_map       )
										__lowercase       =       "lower newer"
										__lowercase       =       ["lo", "w", "er</w>", "n", "e", "w", "er</w>"]
										__lowercase       =       tokenizer.tokenize(_lowerCamelCase       )
										self.assertListEqual(_lowerCamelCase  ,    _lowerCamelCase       )

										__lowercase       =       tokens + [tokenizer.unk_token]
										__lowercase       =       [10, 2, 16, 9, 3, 2, 16, 20]
										self.assertListEqual(tokenizer.convert_tokens_to_ids(_lowerCamelCase       )  ,    _lowerCamelCase       )
							@require_ftfy
							def   SCREAMING_SNAKE_CASE						(     self       )			->							int:




										'''simple docstring'''
										for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
													with self.subTest(f'''{tokenizer.__class__.__name__} ({pretrained_name})'''       ):
																__lowercase       =       self.tokenizer_class.from_pretrained(_lowerCamelCase  ,    **_lowerCamelCase       )
																__lowercase       =       self.rust_tokenizer_class.from_pretrained(_lowerCamelCase  ,    **_lowerCamelCase       )

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

																self.assertListEqual(_lowerCamelCase  ,    _lowerCamelCase       )

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

																self.assertListEqual(_lowerCamelCase  ,    _lowerCamelCase       )

																# Test that the tokenization is identical on unicode of space type
																__lowercase       =       [
																    "\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:
																			__lowercase       =       tokenizer_s.tokenize(_lowerCamelCase       )
																			__lowercase       =       tokenizer_r.tokenize(_lowerCamelCase       )

																			self.assertListEqual(_lowerCamelCase  ,    _lowerCamelCase       )

																# Test that the tokenization is identical on unicode of line break type
																__lowercase       =       [
																    "\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:
																			__lowercase       =       tokenizer_s.tokenize(_lowerCamelCase       )
																			__lowercase       =       tokenizer_r.tokenize(_lowerCamelCase       )

																			self.assertListEqual(_lowerCamelCase  ,    _lowerCamelCase       )
							def   SCREAMING_SNAKE_CASE						(     self       )			->							Tuple:




										'''simple docstring'''
										# 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})'''       ):
																__lowercase       =       "hello"  # `hello` is a token in the vocabulary of `pretrained_name`
																__lowercase       =       f'''{text_of_1_token} {text_of_1_token}'''

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

																__lowercase       =       f''' {text}'''

																__lowercase       =       self.rust_tokenizer_class.from_pretrained(
																    _lowerCamelCase  ,    use_fast=_lowerCamelCase  ,    )
																__lowercase       =       tokenizer_r(_lowerCamelCase  ,    return_offsets_mapping=_lowerCamelCase  ,    add_special_tokens=_lowerCamelCase       )
																self.assertEqual(encoding.offset_mapping[0]  ,    (1, 1 + len(_lowerCamelCase       ))       )
																self.assertEqual(
																    encoding.offset_mapping[1]  ,    (1 + len(_lowerCamelCase       ) + 1, 1 + len(_lowerCamelCase       ) + 1 + len(_lowerCamelCase       ))  ,    )
							def   SCREAMING_SNAKE_CASE						(     self       )			->							List[str]:




										'''simple docstring'''
										# 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(_lowerCamelCase       ) 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   SCREAMING_SNAKE_CASE						(     self       )			->							List[Any]:




										'''simple docstring'''
										super().test_tokenization_python_rust_equals()





							def   SCREAMING_SNAKE_CASE						(     self       )			->							str:




										'''simple docstring'''
										# CLIP always lower cases letters
										pass







"""simple docstring"""






from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_torch_available,
)


_lowercase							=				{'''configuration_vit_mae''': ['''VIT_MAE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ViTMAEConfig''']}

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					_lowercase							=				[
					    '''VIT_MAE_PRETRAINED_MODEL_ARCHIVE_LIST''',
					    '''ViTMAEForPreTraining''',
					    '''ViTMAELayer''',
					    '''ViTMAEModel''',
					    '''ViTMAEPreTrainedModel''',
					]

try:
					if not is_tf_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					_lowercase							=				[
					    '''TFViTMAEForPreTraining''',
					    '''TFViTMAEModel''',
					    '''TFViTMAEPreTrainedModel''',
					]

if TYPE_CHECKING:
					from .configuration_vit_mae import VIT_MAE_PRETRAINED_CONFIG_ARCHIVE_MAP, ViTMAEConfig

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_vit_mae import (
										    VIT_MAE_PRETRAINED_MODEL_ARCHIVE_LIST,
										    ViTMAEForPreTraining,
										    ViTMAELayer,
										    ViTMAEModel,
										    ViTMAEPreTrainedModel,
										)

					try:
										if not is_tf_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_tf_vit_mae import TFViTMAEForPreTraining, TFViTMAEModel, TFViTMAEPreTrainedModel


else:
					import sys

					_lowercase							=				_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)





