
"""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 		SCREAMING_SNAKE_CASE_					(		__UpperCAmelCase	,							unittest.TestCase					):




		"""simple docstring"""





		__lowercase				:    Optional[Any]		  =						GPTaTokenizer
		__lowercase				:    List[str]		  =						GPTaTokenizerFast
		__lowercase				:    Optional[Any]		  =						True
		__lowercase				:    str		  =						{'add_prefix_space': True}
		__lowercase				:    List[Any]		  =						False




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

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

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




		def       snake_case_	(	self				,    **lowerCAmelCase__):
				kwargs.update(self.special_tokens_map)
				return GPTaTokenizer.from_pretrained(self.tmpdirname				,    **lowerCAmelCase_)




		def       snake_case_	(	self				,    **lowerCAmelCase__):
				kwargs.update(self.special_tokens_map)
				return GPTaTokenizerFast.from_pretrained(self.tmpdirname				,    **lowerCAmelCase_)




		def       snake_case_	(	self				,    lowerCAmelCase__):
				__SCREAMING_SNAKE_CASE				=					'lower newer'
				__SCREAMING_SNAKE_CASE				=					'lower newer'
				return input_text, output_text




		def       snake_case_	(	self):
				__SCREAMING_SNAKE_CASE				=					GPTaTokenizer(self.vocab_file				,    self.merges_file				,    **self.special_tokens_map)
				__SCREAMING_SNAKE_CASE				=					'lower newer'
				__SCREAMING_SNAKE_CASE				=					['\u0120low', 'er', '\u0120', 'n', 'e', 'w', 'er']
				__SCREAMING_SNAKE_CASE				=					tokenizer.tokenize(lowerCAmelCase_				,    add_prefix_space=lowerCAmelCase_)
				self.assertListEqual(lowerCAmelCase_				,    lowerCAmelCase_)

				__SCREAMING_SNAKE_CASE				=					tokens + [tokenizer.unk_token]
				__SCREAMING_SNAKE_CASE				=					[1_4, 1_5, 1_0, 9, 3, 2, 1_5, 1_9]
				self.assertListEqual(tokenizer.convert_tokens_to_ids(lowerCAmelCase_)				,    lowerCAmelCase_)




		def       snake_case_	(	self):
				if not self.test_rust_tokenizer:
						return

				__SCREAMING_SNAKE_CASE				=					self.get_tokenizer()
				__SCREAMING_SNAKE_CASE				=					self.get_rust_tokenizer(add_prefix_space=lowerCAmelCase_)

				__SCREAMING_SNAKE_CASE				=					'lower newer'

				# Testing tokenization
				__SCREAMING_SNAKE_CASE				=					tokenizer.tokenize(lowerCAmelCase_				,    add_prefix_space=lowerCAmelCase_)
				__SCREAMING_SNAKE_CASE				=					rust_tokenizer.tokenize(lowerCAmelCase_)
				self.assertListEqual(lowerCAmelCase_				,    lowerCAmelCase_)

				# Testing conversion to ids without special tokens
				__SCREAMING_SNAKE_CASE				=					tokenizer.encode(lowerCAmelCase_				,    add_special_tokens=lowerCAmelCase_				,    add_prefix_space=lowerCAmelCase_)
				__SCREAMING_SNAKE_CASE				=					rust_tokenizer.encode(lowerCAmelCase_				,    add_special_tokens=lowerCAmelCase_)
				self.assertListEqual(lowerCAmelCase_				,    lowerCAmelCase_)

				# Testing conversion to ids with special tokens
				__SCREAMING_SNAKE_CASE				=					self.get_rust_tokenizer(add_prefix_space=lowerCAmelCase_)
				__SCREAMING_SNAKE_CASE				=					tokenizer.encode(lowerCAmelCase_				,    add_prefix_space=lowerCAmelCase_)
				__SCREAMING_SNAKE_CASE				=					rust_tokenizer.encode(lowerCAmelCase_)
				self.assertListEqual(lowerCAmelCase_				,    lowerCAmelCase_)

				# Testing the unknown token
				__SCREAMING_SNAKE_CASE				=					tokens + [rust_tokenizer.unk_token]
				__SCREAMING_SNAKE_CASE				=					[1_4, 1_5, 1_0, 9, 3, 2, 1_5, 1_9]
				self.assertListEqual(rust_tokenizer.convert_tokens_to_ids(lowerCAmelCase_)				,    lowerCAmelCase_)




		def       snake_case_	(	self				,    *lowerCAmelCase__				,    **lowerCAmelCase__):
				# It's very difficult to mix/test pretokenization with byte-level
				# And get both GPT2 and Roberta to work at the same time (mostly an issue of adding a space before the string)
				pass




		def       snake_case_	(	self				,    lowerCAmelCase__=1_5):
				for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
						with self.subTest(f"{tokenizer.__class__.__name__} ({pretrained_name})"):
								__SCREAMING_SNAKE_CASE				=					self.rust_tokenizer_class.from_pretrained(lowerCAmelCase_				,    **lowerCAmelCase_)

								# Simple input
								__SCREAMING_SNAKE_CASE				=					'This is a simple input'
								__SCREAMING_SNAKE_CASE				=					['This is a simple input 1', 'This is a simple input 2']
								__SCREAMING_SNAKE_CASE				=					('This is a simple input', 'This is a pair')
								__SCREAMING_SNAKE_CASE				=					[
								    ('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(lowerCAmelCase_				,    tokenizer_r.encode				,    lowerCAmelCase_				,    max_length=lowerCAmelCase_				,    padding="""max_length""")

								# Simple input
								self.assertRaises(lowerCAmelCase_				,    tokenizer_r.encode_plus				,    lowerCAmelCase_				,    max_length=lowerCAmelCase_				,    padding="""max_length""")

								# Simple input
								self.assertRaises(
								    lowerCAmelCase_				,    tokenizer_r.batch_encode_plus				,    lowerCAmelCase_				,    max_length=lowerCAmelCase_				,    padding="""max_length"""				,    )

								# Pair input
								self.assertRaises(lowerCAmelCase_				,    tokenizer_r.encode				,    lowerCAmelCase_				,    max_length=lowerCAmelCase_				,    padding="""max_length""")

								# Pair input
								self.assertRaises(lowerCAmelCase_				,    tokenizer_r.encode_plus				,    lowerCAmelCase_				,    max_length=lowerCAmelCase_				,    padding="""max_length""")

								# Pair input
								self.assertRaises(
								    lowerCAmelCase_				,    tokenizer_r.batch_encode_plus				,    lowerCAmelCase_				,    max_length=lowerCAmelCase_				,    padding="""max_length"""				,    )




		def       snake_case_	(	self):
				__SCREAMING_SNAKE_CASE				=					GPTaTokenizer.from_pretrained(self.tmpdirname				,    pad_token="""<pad>""")

				# Simple input
				__SCREAMING_SNAKE_CASE				=					'This is a simple input'
				__SCREAMING_SNAKE_CASE				=					['This is a simple input looooooooong', 'This is a simple input']
				__SCREAMING_SNAKE_CASE				=					('This is a simple input', 'This is a pair')
				__SCREAMING_SNAKE_CASE				=					[
				    ('This is a simple input loooooong', 'This is a simple input'),
				    ('This is a simple pair loooooong', 'This is a simple pair'),
				]

				__SCREAMING_SNAKE_CASE				=					tokenizer.pad_token_id

				__SCREAMING_SNAKE_CASE				=					tokenizer(lowerCAmelCase_				,    padding="""max_length"""				,    max_length=3_0				,    return_tensors="""np""")
				__SCREAMING_SNAKE_CASE				=					tokenizer(lowerCAmelCase_				,    padding=lowerCAmelCase_				,    truncate=lowerCAmelCase_				,    return_tensors="""np""")
				__SCREAMING_SNAKE_CASE				=					tokenizer(*lowerCAmelCase_				,    padding="""max_length"""				,    max_length=6_0				,    return_tensors="""np""")
				__SCREAMING_SNAKE_CASE				=					tokenizer(lowerCAmelCase_				,    padding=lowerCAmelCase_				,    truncate=lowerCAmelCase_				,    return_tensors="""np""")

				# s
				# test single string max_length padding
				self.assertEqual(out_s["""input_ids"""].shape[-1]				,    3_0)
				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]				,    3_3)
				# 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]				,    6_0)
				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]				,    5_2)
				# 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       snake_case_	(	self):
				__SCREAMING_SNAKE_CASE				=					'$$$'
				__SCREAMING_SNAKE_CASE				=					GPTaTokenizer.from_pretrained(self.tmpdirname				,    bos_token=lowerCAmelCase_				,    add_bos_token=lowerCAmelCase_)

				__SCREAMING_SNAKE_CASE				=					'This is a simple input'
				__SCREAMING_SNAKE_CASE				=					['This is a simple input 1', 'This is a simple input 2']

				__SCREAMING_SNAKE_CASE				=					tokenizer.bos_token_id

				__SCREAMING_SNAKE_CASE				=					tokenizer(lowerCAmelCase_)
				__SCREAMING_SNAKE_CASE				=					tokenizer(lowerCAmelCase_)

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

				__SCREAMING_SNAKE_CASE				=					tokenizer.decode(out_s.input_ids)
				__SCREAMING_SNAKE_CASE				=					tokenizer.batch_decode(out_sa.input_ids)

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




		def       snake_case_	(	self):
				pass




		def       snake_case_	(	self):
				# TODO: change to self.get_tokenizers() when the fast version is implemented
				__SCREAMING_SNAKE_CASE				=					[self.get_tokenizer(do_lower_case=lowerCAmelCase_				,    add_bos_token=lowerCAmelCase_)]
				for tokenizer in tokenizers:
						with self.subTest(f"{tokenizer.__class__.__name__}"):
								__SCREAMING_SNAKE_CASE				=					'Encode this.'
								__SCREAMING_SNAKE_CASE				=					'This one too please.'
								__SCREAMING_SNAKE_CASE				=					tokenizer.encode(lowerCAmelCase_				,    add_special_tokens=lowerCAmelCase_)
								encoded_sequence += tokenizer.encode(lowerCAmelCase_				,    add_special_tokens=lowerCAmelCase_)
								__SCREAMING_SNAKE_CASE				=					tokenizer.encode_plus(
								    lowerCAmelCase_				,    lowerCAmelCase_				,    add_special_tokens=lowerCAmelCase_				,    return_special_tokens_mask=lowerCAmelCase_				,    )
								__SCREAMING_SNAKE_CASE				=					encoded_sequence_dict['input_ids']
								__SCREAMING_SNAKE_CASE				=					encoded_sequence_dict['special_tokens_mask']
								self.assertEqual(len(lowerCAmelCase_)				,    len(lowerCAmelCase_))

								__SCREAMING_SNAKE_CASE				=					[
								    (x if not special_tokens_mask[i] else None) for i, x in enumerate(lowerCAmelCase_)
								]
								__SCREAMING_SNAKE_CASE				=					[x for x in filtered_sequence if x is not None]
								self.assertEqual(lowerCAmelCase_				,    lowerCAmelCase_)



@require_tokenizers
class 		SCREAMING_SNAKE_CASE_					(		unittest.TestCase					):




		"""simple docstring"""





		def       snake_case_	(	self):
				# More context:
				# https://huggingface.co/wjmcat/opt-350m-paddle/discussions/1
				# https://huggingface.slack.com/archives/C01N44FJDHT/p1653511495183519
				# https://github.com/huggingface/transformers/pull/17088#discussion_r871246439

				__SCREAMING_SNAKE_CASE				=					AutoTokenizer.from_pretrained("""facebook/opt-350m"""				,    from_slow=lowerCAmelCase_)
				__SCREAMING_SNAKE_CASE				=					'A photo of a cat'

				__SCREAMING_SNAKE_CASE				=					tokenizer.encode(
				    lowerCAmelCase_				,    )
				self.assertEqual(lowerCAmelCase_				,    [2, 2_5_0, 1_3_4_5, 9, 1_0, 4_7_5_8])
				tokenizer.save_pretrained("""test_opt""")

				__SCREAMING_SNAKE_CASE				=					AutoTokenizer.from_pretrained("""./test_opt""")
				__SCREAMING_SNAKE_CASE				=					tokenizer.encode(
				    lowerCAmelCase_				,    )
				self.assertEqual(lowerCAmelCase_				,    [2, 2_5_0, 1_3_4_5, 9, 1_0, 4_7_5_8])




		def       snake_case_	(	self):
				__SCREAMING_SNAKE_CASE				=					AutoTokenizer.from_pretrained("""facebook/opt-350m"""				,    use_slow=lowerCAmelCase_)
				__SCREAMING_SNAKE_CASE				=					'A photo of a cat'

				__SCREAMING_SNAKE_CASE				=					tokenizer.encode(
				    lowerCAmelCase_				,    )
				# Same as above
				self.assertEqual(lowerCAmelCase_				,    [2, 2_5_0, 1_3_4_5, 9, 1_0, 4_7_5_8])




		@unittest.skip("""This test is failing because of a bug in the fast tokenizer""")
		def       snake_case_	(	self):
				__SCREAMING_SNAKE_CASE				=					AutoTokenizer.from_pretrained("""facebook/opt-350m"""				,    from_slow=lowerCAmelCase_)

				__SCREAMING_SNAKE_CASE				=					'bos'
				__SCREAMING_SNAKE_CASE				=					tokenizer.get_vocab()['bos']

				__SCREAMING_SNAKE_CASE				=					'A photo of a cat'
				__SCREAMING_SNAKE_CASE				=					tokenizer.encode(
				    lowerCAmelCase_				,    )
				# We changed the bos token
				self.assertEqual(lowerCAmelCase_				,    [3_1_9_5_7, 2_5_0, 1_3_4_5, 9, 1_0, 4_7_5_8])
				tokenizer.save_pretrained("""./tok""")
				__SCREAMING_SNAKE_CASE				=					AutoTokenizer.from_pretrained("""./tok""")
				self.assertTrue(tokenizer.is_fast)
				__SCREAMING_SNAKE_CASE				=					tokenizer.encode(
				    lowerCAmelCase_				,    )
				self.assertEqual(lowerCAmelCase_				,    [3_1_9_5_7, 2_5_0, 1_3_4_5, 9, 1_0, 4_7_5_8])












"""simple docstring"""
class _lowerCAmelCase						:







						def __init__(    self   ,				lowerCAmelCase_							)		->							None:
										_SCREAMING_SNAKE_CASE   :		Dict       		=    size
										_SCREAMING_SNAKE_CASE   :		str       		=    [0] * size
										_SCREAMING_SNAKE_CASE   :		Any       		=    [0] * size







						@staticmethod
						def 			A      (    lowerCAmelCase_							)		->							int:
										return index | (index + 1)







						@staticmethod
						def 			A      (    lowerCAmelCase_							)		->							int:
										return (index & (index + 1)) - 1







						def 			A      (    self   ,				lowerCAmelCase_   ,				lowerCAmelCase_							)		->							None:
										_SCREAMING_SNAKE_CASE   :		str       		=    value
										while index < self.size:
														_SCREAMING_SNAKE_CASE   :		List[str]       		=    self.get_prev(lowerCAmelCase_							) + 1
														if current_left_border == index:
																		_SCREAMING_SNAKE_CASE   :		List[str]       		=    value
														else:
																		_SCREAMING_SNAKE_CASE   :		Optional[Any]       		=    max(lowerCAmelCase_   ,				lowerCAmelCase_   ,				lowerCAmelCase_							)
														_SCREAMING_SNAKE_CASE   :		str       		=    self.get_next(lowerCAmelCase_							)







						def 			A      (    self   ,				lowerCAmelCase_   ,				lowerCAmelCase_							)		->							int:
										right -= 1  # Because of right is exclusive
										_SCREAMING_SNAKE_CASE   :		List[Any]       		=    0
										while left <= right:
														_SCREAMING_SNAKE_CASE   :		Union[str, Any]       		=    self.get_prev(lowerCAmelCase_							)
														if left <= current_left:
																		_SCREAMING_SNAKE_CASE   :		Union[str, Any]       		=    max(lowerCAmelCase_   ,				self.tree[right]							)
																		_SCREAMING_SNAKE_CASE   :		List[Any]       		=    current_left
														else:
																		_SCREAMING_SNAKE_CASE   :		List[str]       		=    max(lowerCAmelCase_   ,				self.arr[right]							)
																		right -= 1
										return result


if __name__ == "__main__":
			import doctest

			doctest.testmod()

