



"""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     (					_UpperCAmelCase					,    unittest.TestCase):







						"""simple docstring"""







						_A		:							Dict							       =		CLIPTokenizer
						_A		:							Any							       =		CLIPTokenizerFast
						_A		:							List[Any]							       =		True
						_A		:							Optional[Any]							       =		{}
						_A		:							int							       =		False







						def 						__UpperCamelCase							(self       ):
											super().setUp()

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

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







						def 						__UpperCamelCase							(self   ,		**lowercase__       ):
											kwargs.update(self.special_tokens_map       )
											return CLIPTokenizer.from_pretrained(self.tmpdirname   ,		**lowercase__       )







						def 						__UpperCamelCase							(self   ,		**lowercase__       ):
											kwargs.update(self.special_tokens_map       )
											return CLIPTokenizerFast.from_pretrained(self.tmpdirname   ,		**lowercase__       )







						def 						__UpperCamelCase							(self   ,		lowercase__       ):
											snake_case_					:		Tuple 					=					"""lower newer"""
											snake_case_					:		str 					=					"""lower newer"""
											return input_text, output_text







						def 						__UpperCamelCase							(self       ):
											snake_case_					:		Optional[int] 					=					CLIPTokenizer(self.vocab_file   ,		self.merges_file   ,		**self.special_tokens_map       )
											snake_case_					:		Optional[Any] 					=					"""lower newer"""
											snake_case_					:		Union[str, Any] 					=					["""lo""", """w""", """er</w>""", """n""", """e""", """w""", """er</w>"""]
											snake_case_					:		Any 					=					tokenizer.tokenize(lowercase__       )
											self.assertListEqual(lowercase__   ,		lowercase__       )

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







						@require_ftfy
						def 						__UpperCamelCase							(self       ):
											for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
																with self.subTest(f'{tokenizer.__class__.__name__} ({pretrained_name})'       ):
																					snake_case_					:		List[str] 					=					self.tokenizer_class.from_pretrained(lowercase__   ,		**lowercase__       )
																					snake_case_					:		Optional[Any] 					=					self.rust_tokenizer_class.from_pretrained(lowercase__   ,		**lowercase__       )

																					snake_case_					:		List[Any] 					=					"""A\n'll 11p223RF☆ho!!to?'d'd''d of a cat to-$''d."""
																					snake_case_					:		List[Any] 					=					tokenizer_s.tokenize(lowercase__       )
																					snake_case_					:		Optional[Any] 					=					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_					:		str 					=					"""xa\u0303y""" + """ """ + """x\xe3y"""
																					snake_case_					:		Dict 					=					tokenizer_s.tokenize(lowercase__       )
																					snake_case_					:		List[str] 					=					tokenizer_r.tokenize(lowercase__       )

																					self.assertListEqual(lowercase__   ,		lowercase__       )

																					# Test that the tokenization is identical on unicode of space type
																					snake_case_					:		Optional[Any] 					=					[
																					    """\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_					:		Tuple 					=					tokenizer_s.tokenize(lowercase__       )
																										snake_case_					:		List[Any] 					=					tokenizer_r.tokenize(lowercase__       )

																										self.assertListEqual(lowercase__   ,		lowercase__       )

																					# Test that the tokenization is identical on unicode of line break type
																					snake_case_					:		Dict 					=					[
																					    """\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_					:		Any 					=					tokenizer_s.tokenize(lowercase__       )
																										snake_case_					:		Optional[int] 					=					tokenizer_r.tokenize(lowercase__       )

																										self.assertListEqual(lowercase__   ,		lowercase__       )







						def 						__UpperCamelCase							(self       ):
											# 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_					:		List[str] 					=					"""hello"""  # `hello` is a token in the vocabulary of `pretrained_name`
																					snake_case_					:		Dict 					=					f'{text_of_1_token} {text_of_1_token}'

																					snake_case_					:		List[str] 					=					self.rust_tokenizer_class.from_pretrained(
																					    lowercase__   ,		use_fast=lowercase__   ,		)
																					snake_case_					:		Union[str, Any] 					=					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_					:		Optional[int] 					=					f' {text}'

																					snake_case_					:		int 					=					self.rust_tokenizer_class.from_pretrained(
																					    lowercase__   ,		use_fast=lowercase__   ,		)
																					snake_case_					:		List[Any] 					=					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 						__UpperCamelCase							(self       ):
											# 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 						__UpperCamelCase							(self       ):
											super().test_tokenization_python_rust_equals()







						def 						__UpperCamelCase							(self       ):
											# CLIP always lower cases letters
											pass









"""simple docstring"""

import argparse
import logging
import pickle
from collections import Counter


logging.basicConfig(
    format='''%(asctime)s - %(levelname)s - %(name)s - %(message)s''', datefmt='''%m/%d/%Y %H:%M:%S''', level=logging.INFO
)
a_			   =					logging.getLogger(__name__)

if __name__ == "__main__":
			a_			   =					argparse.ArgumentParser(
			    description='''Token Counts for smoothing the masking probabilities in MLM (cf XLM/word2vec)'''
			)
			parser.add_argument(
			    '''--data_file''', type=str, default='''data/dump.bert-base-uncased.pickle''', help='''The binarized dataset.'''
			)
			parser.add_argument(
			    '''--token_counts_dump''', type=str, default='''data/token_counts.bert-base-uncased.pickle''', help='''The dump file.'''
			)
			parser.add_argument('''--vocab_size''', default=30522, type=int)
			a_			   =					parser.parse_args()

			logger.info(F'''Loading data from {args.data_file}''')
			with open(args.data_file, '''rb''') as fp:
						a_			   =					pickle.load(fp)

			logger.info('''Counting occurrences for MLM.''')
			a_			   =					Counter()
			for tk_ids in data:
						counter.update(tk_ids)
			a_			   =					[0] * args.vocab_size
			for k, v in counter.items():
						a_			   =					v

			logger.info(F'''Dump to {args.token_counts_dump}''')
			with open(args.token_counts_dump, '''wb''') as handle:
						pickle.dump(counts, handle, protocol=pickle.HIGHEST_PROTOCOL)




