


'''simple docstring'''

import json
import os
import unittest

from transformers import AutoTokenizer, GPTaTokenizer, GPTaTokenizerFast
from transformers.models.gpta.tokenization_gpta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class 					_lowerCamelCase	(						lowercase_		,					unittest.TestCase							):



		'''simple docstring'''







		A_     :      str				   =    GPTaTokenizer
		A_     :      Union[str, Any]				   =    GPTaTokenizerFast
		A_     :      Optional[Any]				   =    True
		A_     :      Union[str, Any]				   =    {"add_prefix_space": True}
		A_     :      int				   =    False







		def        __lowerCAmelCase		( self		:						Optional[int]      )  ->			int:
			super().setUp()

			# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
			__magic_name__	:   Optional[Any]					     =					[
			    'l',
			    'o',
			    'w',
			    'e',
			    'r',
			    's',
			    't',
			    'i',
			    'd',
			    'n',
			    '\u0120',
			    '\u0120l',
			    '\u0120n',
			    '\u0120lo',
			    '\u0120low',
			    'er',
			    '\u0120lowest',
			    '\u0120newer',
			    '\u0120wider',
			    '<unk>',
			    '<|endoftext|>',
			]
			__magic_name__	:   Union[str, Any]					     =					dict(zip(a__  ,					range(len(a__      )      )      )      )
			__magic_name__	:   List[str]					     =					['#version: 0.2', '\u0120 l', '\u0120l o', '\u0120lo w', 'e r', '']
			__magic_name__	:   int					     =					{'unk_token': '<unk>'}

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







		def        __lowerCAmelCase		( self		:						Union[str, Any]  ,					**_A		:						Optional[int]      )  ->			Union[str, Any]:
			kwargs.update(self.special_tokens_map      )
			return GPTaTokenizer.from_pretrained(self.tmpdirname  ,					**a__      )







		def        __lowerCAmelCase		( self		:						Tuple  ,					**_A		:						str      )  ->			List[str]:
			kwargs.update(self.special_tokens_map      )
			return GPTaTokenizerFast.from_pretrained(self.tmpdirname  ,					**a__      )







		def        __lowerCAmelCase		( self		:						List[str]  ,					_A		:						Tuple      )  ->			Union[str, Any]:
			__magic_name__	:   Tuple					     =					'lower newer'
			__magic_name__	:   List[Any]					     =					'lower newer'
			return input_text, output_text







		def        __lowerCAmelCase		( self		:						Any      )  ->			Union[str, Any]:
			__magic_name__	:   Union[str, Any]					     =					GPTaTokenizer(self.vocab_file  ,					self.merges_file  ,					**self.special_tokens_map      )
			__magic_name__	:   List[Any]					     =					'lower newer'
			__magic_name__	:   List[str]					     =					['\u0120low', 'er', '\u0120', 'n', 'e', 'w', 'er']
			__magic_name__	:   Optional[Any]					     =					tokenizer.tokenize(a__  ,					add_prefix_space=a__      )
			self.assertListEqual(a__  ,					a__      )

			__magic_name__	:   Tuple					     =					tokens + [tokenizer.unk_token]
			__magic_name__	:   Tuple					     =					[14, 15, 10, 9, 3, 2, 15, 19]
			self.assertListEqual(tokenizer.convert_tokens_to_ids(a__      )  ,					a__      )







		def        __lowerCAmelCase		( self		:						Optional[Any]      )  ->			int:




			if not self.test_rust_tokenizer:
				return

			__magic_name__	:   Any					     =					self.get_tokenizer()
			__magic_name__	:   Union[str, Any]					     =					self.get_rust_tokenizer(add_prefix_space=a__      )

			__magic_name__	:   int					     =					'lower newer'

			# Testing tokenization
			__magic_name__	:   Tuple					     =					tokenizer.tokenize(a__  ,					add_prefix_space=a__      )
			__magic_name__	:   List[Any]					     =					rust_tokenizer.tokenize(a__      )
			self.assertListEqual(a__  ,					a__      )

			# Testing conversion to ids without special tokens
			__magic_name__	:   int					     =					tokenizer.encode(a__  ,					add_special_tokens=a__  ,					add_prefix_space=a__      )
			__magic_name__	:   Optional[Any]					     =					rust_tokenizer.encode(a__  ,					add_special_tokens=a__      )
			self.assertListEqual(a__  ,					a__      )

			# Testing conversion to ids with special tokens
			__magic_name__	:   str					     =					self.get_rust_tokenizer(add_prefix_space=a__      )
			__magic_name__	:   Optional[Any]					     =					tokenizer.encode(a__  ,					add_prefix_space=a__      )
			__magic_name__	:   int					     =					rust_tokenizer.encode(a__      )
			self.assertListEqual(a__  ,					a__      )

			# Testing the unknown token
			__magic_name__	:   List[Any]					     =					tokens + [rust_tokenizer.unk_token]
			__magic_name__	:   Dict					     =					[14, 15, 10, 9, 3, 2, 15, 19]
			self.assertListEqual(rust_tokenizer.convert_tokens_to_ids(a__      )  ,					a__      )







		def        __lowerCAmelCase		( self		:						Optional[Any]  ,					*_A		:						Optional[int]  ,					**_A		:						Optional[int]      )  ->			Any:
			pass







		def        __lowerCAmelCase		( self		:						Any  ,					_A		:						Union[str, Any]=15      )  ->			Any:




			for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
				with self.subTest(F'{tokenizer.__class__.__name__} ({pretrained_name})'      ):
					__magic_name__	:   int					     =					self.rust_tokenizer_class.from_pretrained(a__  ,					**a__      )

					# Simple input
					__magic_name__	:   Union[str, Any]					     =					'This is a simple input'
					__magic_name__	:   Any					     =					['This is a simple input 1', 'This is a simple input 2']
					__magic_name__	:   Dict					     =					('This is a simple input', 'This is a pair')
					__magic_name__	:   Tuple					     =					[
					    ('This is a simple input 1', 'This is a simple input 2'),
					    ('This is a simple pair 1', 'This is a simple pair 2'),
					]

					# Simple input tests
					self.assertRaises(a__  ,					tokenizer_r.encode  ,					a__  ,					max_length=a__  ,					padding='max_length'      )

					# Simple input
					self.assertRaises(a__  ,					tokenizer_r.encode_plus  ,					a__  ,					max_length=a__  ,					padding='max_length'      )

					# Simple input
					self.assertRaises(
					    a__  ,					tokenizer_r.batch_encode_plus  ,					a__  ,					max_length=a__  ,					padding='max_length'  ,					)

					# Pair input
					self.assertRaises(a__  ,					tokenizer_r.encode  ,					a__  ,					max_length=a__  ,					padding='max_length'      )

					# Pair input
					self.assertRaises(a__  ,					tokenizer_r.encode_plus  ,					a__  ,					max_length=a__  ,					padding='max_length'      )

					# Pair input
					self.assertRaises(
					    a__  ,					tokenizer_r.batch_encode_plus  ,					a__  ,					max_length=a__  ,					padding='max_length'  ,					)







		def        __lowerCAmelCase		( self		:						List[Any]      )  ->			Any:
			__magic_name__	:   Union[str, Any]					     =					GPTaTokenizer.from_pretrained(self.tmpdirname  ,					pad_token='<pad>'      )

			# Simple input
			__magic_name__	:   Any					     =					'This is a simple input'
			__magic_name__	:   List[str]					     =					['This is a simple input looooooooong', 'This is a simple input']
			__magic_name__	:   List[str]					     =					('This is a simple input', 'This is a pair')
			__magic_name__	:   List[str]					     =					[
			    ('This is a simple input loooooong', 'This is a simple input'),
			    ('This is a simple pair loooooong', 'This is a simple pair'),
			]

			__magic_name__	:   Tuple					     =					tokenizer.pad_token_id

			__magic_name__	:   Union[str, Any]					     =					tokenizer(a__  ,					padding='max_length'  ,					max_length=30  ,					return_tensors='np'      )
			__magic_name__	:   Dict					     =					tokenizer(a__  ,					padding=a__  ,					truncate=a__  ,					return_tensors='np'      )
			__magic_name__	:   str					     =					tokenizer(*a__  ,					padding='max_length'  ,					max_length=60  ,					return_tensors='np'      )
			__magic_name__	:   List[str]					     =					tokenizer(a__  ,					padding=a__  ,					truncate=a__  ,					return_tensors='np'      )

			# s
			# test single string max_length padding
			self.assertEqual(out_s['input_ids'].shape[-1]  ,					30      )
			self.assertTrue(pad_token_id in out_s['input_ids']      )
			self.assertTrue(0 in out_s['attention_mask']      )

			# s2
			# test automatic padding
			self.assertEqual(out_sa['input_ids'].shape[-1]  ,					33      )
			# long slice doesn't have padding
			self.assertFalse(pad_token_id in out_sa['input_ids'][0]      )
			self.assertFalse(0 in out_sa['attention_mask'][0]      )
			# short slice does have padding
			self.assertTrue(pad_token_id in out_sa['input_ids'][1]      )
			self.assertTrue(0 in out_sa['attention_mask'][1]      )

			# p
			# test single pair max_length padding
			self.assertEqual(out_p['input_ids'].shape[-1]  ,					60      )
			self.assertTrue(pad_token_id in out_p['input_ids']      )
			self.assertTrue(0 in out_p['attention_mask']      )

			# p2
			# test automatic padding pair
			self.assertEqual(out_pa['input_ids'].shape[-1]  ,					52      )
			# long slice pair doesn't have padding
			self.assertFalse(pad_token_id in out_pa['input_ids'][0]      )
			self.assertFalse(0 in out_pa['attention_mask'][0]      )
			# short slice pair does have padding
			self.assertTrue(pad_token_id in out_pa['input_ids'][1]      )
			self.assertTrue(0 in out_pa['attention_mask'][1]      )







		def        __lowerCAmelCase		( self		:						Optional[Any]      )  ->			Any:
			__magic_name__	:   Optional[int]					     =					'$$$'
			__magic_name__	:   List[str]					     =					GPTaTokenizer.from_pretrained(self.tmpdirname  ,					bos_token=a__  ,					add_bos_token=a__      )

			__magic_name__	:   Dict					     =					'This is a simple input'
			__magic_name__	:   Tuple					     =					['This is a simple input 1', 'This is a simple input 2']

			__magic_name__	:   Any					     =					tokenizer.bos_token_id

			__magic_name__	:   int					     =					tokenizer(a__      )
			__magic_name__	:   Optional[int]					     =					tokenizer(a__      )

			self.assertEqual(out_s.input_ids[0]  ,					a__      )
			self.assertTrue(all(o[0] == bos_token_id for o in out_sa.input_ids      )      )

			__magic_name__	:   str					     =					tokenizer.decode(out_s.input_ids      )
			__magic_name__	:   List[str]					     =					tokenizer.batch_decode(out_sa.input_ids      )

			self.assertEqual(decode_s.split()[0]  ,					a__      )
			self.assertTrue(all(d.split()[0] == bos_token for d in decode_sa      )      )







		def        __lowerCAmelCase		( self		:						Optional[int]      )  ->			Tuple:
			pass







		def        __lowerCAmelCase		( self		:						Optional[Any]      )  ->			Union[str, Any]:
			__magic_name__	:   Any					     =					[self.get_tokenizer(do_lower_case=a__  ,					add_bos_token=a__      )]
			for tokenizer in tokenizers:
				with self.subTest(F'{tokenizer.__class__.__name__}'      ):
					__magic_name__	:   Dict					     =					'Encode this.'
					__magic_name__	:   Any					     =					'This one too please.'
					__magic_name__	:   Union[str, Any]					     =					tokenizer.encode(a__  ,					add_special_tokens=a__      )
					encoded_sequence += tokenizer.encode(a__  ,					add_special_tokens=a__      )
					__magic_name__	:   int					     =					tokenizer.encode_plus(
					    a__  ,					a__  ,					add_special_tokens=a__  ,					return_special_tokens_mask=a__  ,					)
					__magic_name__	:   int					     =					encoded_sequence_dict['input_ids']
					__magic_name__	:   Union[str, Any]					     =					encoded_sequence_dict['special_tokens_mask']
					self.assertEqual(len(a__      )  ,					len(a__      )      )

					__magic_name__	:   List[str]					     =					[
					    (x if not special_tokens_mask[i] else None) for i, x in enumerate(a__      )
					]
					__magic_name__	:   Any					     =					[x for x in filtered_sequence if x is not None]
					self.assertEqual(a__  ,					a__      )







@require_tokenizers
class 					_lowerCamelCase	(						unittest.TestCase							):



		'''simple docstring'''







		def        __lowerCAmelCase		( self		:						Tuple      )  ->			str:
			__magic_name__	:   str					     =					AutoTokenizer.from_pretrained('facebook/opt-350m'  ,					from_slow=a__      )
			__magic_name__	:   Union[str, Any]					     =					'A photo of a cat'

			__magic_name__	:   Any					     =					tokenizer.encode(
			    a__  ,					)
			self.assertEqual(a__  ,					[2, 250, 1345, 9, 10, 4758]      )
			tokenizer.save_pretrained('test_opt'      )

			__magic_name__	:   List[str]					     =					AutoTokenizer.from_pretrained('./test_opt'      )
			__magic_name__	:   List[str]					     =					tokenizer.encode(
			    a__  ,					)
			self.assertEqual(a__  ,					[2, 250, 1345, 9, 10, 4758]      )







		def        __lowerCAmelCase		( self		:						Optional[int]      )  ->			List[Any]:
			__magic_name__	:   Tuple					     =					AutoTokenizer.from_pretrained('facebook/opt-350m'  ,					use_slow=a__      )
			__magic_name__	:   List[Any]					     =					'A photo of a cat'

			__magic_name__	:   Tuple					     =					tokenizer.encode(
			    a__  ,					)
			# Same as above
			self.assertEqual(a__  ,					[2, 250, 1345, 9, 10, 4758]      )







		@unittest.skip('This test is failing because of a bug in the fast tokenizer'      )
		def        __lowerCAmelCase		( self		:						Optional[Any]      )  ->			str:
			__magic_name__	:   List[Any]					     =					AutoTokenizer.from_pretrained('facebook/opt-350m'  ,					from_slow=a__      )

			__magic_name__	:   Union[str, Any]					     =					'bos'
			__magic_name__	:   str					     =					tokenizer.get_vocab()['bos']

			__magic_name__	:   Optional[int]					     =					'A photo of a cat'
			__magic_name__	:   Optional[Any]					     =					tokenizer.encode(
			    a__  ,					)
			# We changed the bos token
			self.assertEqual(a__  ,					[31957, 250, 1345, 9, 10, 4758]      )
			tokenizer.save_pretrained('./tok'      )
			__magic_name__	:   Dict					     =					AutoTokenizer.from_pretrained('./tok'      )
			self.assertTrue(tokenizer.is_fast      )
			__magic_name__	:   Dict					     =					tokenizer.encode(
			    a__  ,					)
			self.assertEqual(a__  ,					[31957, 250, 1345, 9, 10, 4758]      )



'''simple docstring'''

import warnings

from ...utils import logging
from .image_processing_beit import BeitImageProcessor


lowerCAmelCase				:Tuple        =      logging.get_logger(__name__)
class _lowerCamelCase	(						lowercase__							):



		'''simple docstring'''







		def __init__( self		:						Any  ,					*_A		:						List[Any]  ,					**_A		:						str      )  ->			None:
			warnings.warn(
			    'The class BeitFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please'
			    ' use BeitImageProcessor instead.'  ,					_A  ,					)
			super().__init__(*_A  ,					**_A      )