


'''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    lowercase	(							A__	,		unittest.TestCase					):

		"""simple docstring"""

		_a     =				CLIPTokenizer
		_a     =				CLIPTokenizerFast
		_a     =				True
		_a     =				{}
		_a     =				False




		def     lowerCAmelCase__				(		self							):

							'''simple docstring'''


							super().setUp()

							# fmt: off
							UpperCamelCase__   :Any												= ['''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
							UpperCamelCase__   :Optional[int]												= dict(zip(UpperCamelCase_    ,   range(len(UpperCamelCase_							)							)							)							)
							UpperCamelCase__   :str												= ['''#version: 0.2''', '''l o''', '''lo w</w>''', '''e r</w>''']
							UpperCamelCase__   :Optional[Any]												= {'''unk_token''': '''<unk>'''}

							UpperCamelCase__   :List[Any]												= os.path.join(self.tmpdirname    ,   VOCAB_FILES_NAMES['''vocab_file''']							)
							UpperCamelCase__   :Optional[int]												= 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(UpperCamelCase_							) + '''\n'''							)
							with open(self.merges_file    ,   '''w'''    ,   encoding='''utf-8'''							) as fp:
												fp.write('''\n'''.join(UpperCamelCase_							)							)




		def     lowerCAmelCase__				(		self    ,   **UpperCamelCase_							):

							'''simple docstring'''


							kwargs.update(self.special_tokens_map							)
							return CLIPTokenizer.from_pretrained(self.tmpdirname    ,   **UpperCamelCase_							)




		def     lowerCAmelCase__				(		self    ,   **UpperCamelCase_							):

							'''simple docstring'''


							kwargs.update(self.special_tokens_map							)
							return CLIPTokenizerFast.from_pretrained(self.tmpdirname    ,   **UpperCamelCase_							)




		def     lowerCAmelCase__				(		self    ,   UpperCamelCase_							):

							'''simple docstring'''


							UpperCamelCase__   :List[Any]												= '''lower newer'''
							UpperCamelCase__   :Union[str, Any]												= '''lower newer'''
							return input_text, output_text




		def     lowerCAmelCase__				(		self							):

							'''simple docstring'''


							UpperCamelCase__   :int												= CLIPTokenizer(self.vocab_file    ,   self.merges_file    ,   **self.special_tokens_map							)
							UpperCamelCase__   :Union[str, Any]												= '''lower newer'''
							UpperCamelCase__   :str												= ['''lo''', '''w''', '''er</w>''', '''n''', '''e''', '''w''', '''er</w>''']
							UpperCamelCase__   :str												= tokenizer.tokenize(UpperCamelCase_							)
							self.assertListEqual(UpperCamelCase_    ,   UpperCamelCase_							)

							UpperCamelCase__   :Dict												= tokens + [tokenizer.unk_token]
							UpperCamelCase__   :Tuple												= [10, 2, 16, 9, 3, 2, 16, 20]
							self.assertListEqual(tokenizer.convert_tokens_to_ids(UpperCamelCase_							)    ,   UpperCamelCase_							)




		@require_ftfy
		def     lowerCAmelCase__				(		self							):

							'''simple docstring'''


							for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
												with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})'''							):
																	UpperCamelCase__   :int												= self.tokenizer_class.from_pretrained(UpperCamelCase_    ,   **UpperCamelCase_							)
																	UpperCamelCase__   :List[str]												= self.rust_tokenizer_class.from_pretrained(UpperCamelCase_    ,   **UpperCamelCase_							)

																	UpperCamelCase__   :Any												= '''A\n\'ll 11p223RF☆ho!!to?\'d\'d\'\'d of a cat to-$\'\'d.'''
																	UpperCamelCase__   :Union[str, Any]												= tokenizer_s.tokenize(UpperCamelCase_							)
																	UpperCamelCase__   :List[Any]												= tokenizer_r.tokenize(UpperCamelCase_							)

																	self.assertListEqual(UpperCamelCase_    ,   UpperCamelCase_							)

																	# Test that the tokenization is identical on an example containing a character (Latin Small Letter A
																	# with Tilde) encoded in 2 different ways
																	UpperCamelCase__   :Tuple												= '''xa\u0303y''' + ''' ''' + '''x\xe3y'''
																	UpperCamelCase__   :Union[str, Any]												= tokenizer_s.tokenize(UpperCamelCase_							)
																	UpperCamelCase__   :Any												= tokenizer_r.tokenize(UpperCamelCase_							)

																	self.assertListEqual(UpperCamelCase_    ,   UpperCamelCase_							)

																	# Test that the tokenization is identical on unicode of space type
																	UpperCamelCase__   :List[str]												= [
																	    '''\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:
																						UpperCamelCase__   :Tuple												= tokenizer_s.tokenize(UpperCamelCase_							)
																						UpperCamelCase__   :List[str]												= tokenizer_r.tokenize(UpperCamelCase_							)

																						self.assertListEqual(UpperCamelCase_    ,   UpperCamelCase_							)

																	# Test that the tokenization is identical on unicode of line break type
																	UpperCamelCase__   :Optional[Any]												= [
																	    '''\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:
																						UpperCamelCase__   :Dict												= tokenizer_s.tokenize(UpperCamelCase_							)
																						UpperCamelCase__   :List[str]												= tokenizer_r.tokenize(UpperCamelCase_							)

																						self.assertListEqual(UpperCamelCase_    ,   UpperCamelCase_							)




		def     lowerCAmelCase__				(		self							):

							'''simple docstring'''


							for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
												with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})'''							):
																	UpperCamelCase__   :str												= '''hello'''  # `hello` is a token in the vocabulary of `pretrained_name`
																	UpperCamelCase__   :Tuple												= F'''{text_of_1_token} {text_of_1_token}'''

																	UpperCamelCase__   :Tuple												= self.rust_tokenizer_class.from_pretrained(
																	    UpperCamelCase_    ,   use_fast=UpperCamelCase_    ,   )
																	UpperCamelCase__   :Tuple												= tokenizer_r(UpperCamelCase_    ,   return_offsets_mapping=UpperCamelCase_    ,   add_special_tokens=UpperCamelCase_							)
																	self.assertEqual(encoding.offset_mapping[0]    ,   (0, len(UpperCamelCase_							))							)
																	self.assertEqual(
																	    encoding.offset_mapping[1]    ,   (len(UpperCamelCase_							) + 1, len(UpperCamelCase_							) + 1 + len(UpperCamelCase_							))    ,   )

																	UpperCamelCase__   :List[Any]												= F''' {text}'''

																	UpperCamelCase__   :List[Any]												= self.rust_tokenizer_class.from_pretrained(
																	    UpperCamelCase_    ,   use_fast=UpperCamelCase_    ,   )
																	UpperCamelCase__   :List[Any]												= tokenizer_r(UpperCamelCase_    ,   return_offsets_mapping=UpperCamelCase_    ,   add_special_tokens=UpperCamelCase_							)
																	self.assertEqual(encoding.offset_mapping[0]    ,   (1, 1 + len(UpperCamelCase_							))							)
																	self.assertEqual(
																	    encoding.offset_mapping[1]    ,   (1 + len(UpperCamelCase_							) + 1, 1 + len(UpperCamelCase_							) + 1 + len(UpperCamelCase_							))    ,   )




		def     lowerCAmelCase__				(		self							):

							'''simple docstring'''


							with self.assertRaises(UpperCamelCase_							) 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     lowerCAmelCase__				(		self							):

							'''simple docstring'''


							super().test_tokenization_python_rust_equals()




		def     lowerCAmelCase__				(		self							):

							'''simple docstring'''


							pass



'''simple docstring'''
from pathlib import Path

import fire
from tqdm import tqdm


def 			a      (			__a="ro" ,					__a="en" ,					__a="wmt16" ,					__a=None   )  ->	None:



					'''simple docstring'''






					try:
										import datasets
					except (ModuleNotFoundError, ImportError):
										raise ImportError('''run pip install datasets'''   )
					UpperCamelCase__   :int												= f'''{src_lang}-{tgt_lang}'''
					print(f'''Converting {dataset}-{pair}'''   )
					UpperCamelCase__   :Tuple												= datasets.load_dataset(__a ,					__a   )
					if save_dir is None:
										UpperCamelCase__   :Any												= f'''{dataset}-{pair}'''
					UpperCamelCase__   :Dict												= Path(__a   )
					save_dir.mkdir(exist_ok=__a   )

					for split in ds.keys():
										print(f'''Splitting {split} with {ds[split].num_rows} records'''   )

										# to save to val.source, val.target like summary datasets
										UpperCamelCase__   :Dict												= '''val''' if split == '''validation''' else split
										UpperCamelCase__   :List[Any]												= save_dir.joinpath(f'''{fn}.source'''   )
										UpperCamelCase__   :int												= save_dir.joinpath(f'''{fn}.target'''   )
										UpperCamelCase__   :Union[str, Any]												= src_path.open('''w+'''   )
										UpperCamelCase__   :Tuple												= tgt_path.open('''w+'''   )

										# reader is the bottleneck so writing one record at a time doesn't slow things down
										for x in tqdm(ds[split]   ):
															UpperCamelCase__   :Union[str, Any]												= x['''translation''']
															src_fp.write(ex[src_lang] + '''\n'''   )
															tgt_fp.write(ex[tgt_lang] + '''\n'''   )

					print(f'''Saved {dataset} dataset to {save_dir}'''   )


if __name__ == "__main__":
		fire.Fire(download_wmt_dataset)