import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple

from transformers import AddedToken, BatchEncoding, ByTaTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available

from ...test_tokenization_common import TokenizerTesterMixin


if is_torch_available():
							_lowerCamelCase					:   Optional[Any]							=		'''pt'''
elif is_tf_available():
							_lowerCamelCase					:   List[str]							=		'''tf'''
else:
							_lowerCamelCase					:   List[str]							=		'''jax'''


class 						lowercase    (     a				,       unittest.TestCase     ):
							lowercase__						:       Union[str, Any]								=							ByTaTokenizer
							lowercase__						:       str								=							False




							def 	__snake_case(						self   :					Tuple      )					->				int:



												'''simple docstring'''

												super().setUp()
												SCREAMING_SNAKE_CASE    			=       ByTaTokenizer()
												tokenizer.save_pretrained(self.tmpdirname      )




							@cached_property
							def 	__snake_case(						self   :					int      )					->				Optional[int]:



												'''simple docstring'''

												return ByTaTokenizer.from_pretrained("google/byt5-small"      )




							def 	__snake_case(						self   :					List[str]	,							**_UpperCamelCase   :					str      )					->				ByTaTokenizer:



												'''simple docstring'''

												return self.tokenizer_class.from_pretrained(self.tmpdirname	,							**_UpperCamelCase      )




							def 	__snake_case(						self   :					int	,							_UpperCamelCase   :					Dict	,							_UpperCamelCase   :					Union[str, Any]=False	,							_UpperCamelCase   :					Optional[int]=20	,							_UpperCamelCase   :					Dict=5      )					->				Tuple[str, list]:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE    			=       []
												for i in range(len(_UpperCamelCase      )      ):
																	try:
																						SCREAMING_SNAKE_CASE    			=       tokenizer.decode([i]	,							clean_up_tokenization_spaces=_UpperCamelCase      )
																	except UnicodeDecodeError:
																						pass
																	toks.append((i, tok)      )

												SCREAMING_SNAKE_CASE    			=       list(filter(lambda _UpperCamelCase      : re.match(R"^[ a-zA-Z]+$"	,							t[1]      )	,							_UpperCamelCase      )      )
												SCREAMING_SNAKE_CASE    			=       list(filter(lambda _UpperCamelCase      : [t[0]] == tokenizer.encode(t[1]	,							add_special_tokens=_UpperCamelCase      )	,							_UpperCamelCase      )      )
												if max_length is not None and len(_UpperCamelCase      ) > max_length:
																	SCREAMING_SNAKE_CASE    			=       toks[:max_length]
												if min_length is not None and len(_UpperCamelCase      ) < min_length and len(_UpperCamelCase      ) > 0:
																	while len(_UpperCamelCase      ) < min_length:
																						SCREAMING_SNAKE_CASE    			=       toks + toks
        # toks_str = [t[1] for t in toks]
												SCREAMING_SNAKE_CASE    			=       [t[0] for t in toks]

												# Ensure consistency
												SCREAMING_SNAKE_CASE    			=       tokenizer.decode(_UpperCamelCase	,							clean_up_tokenization_spaces=_UpperCamelCase      )
												if " " not in output_txt and len(_UpperCamelCase      ) > 1:
																	SCREAMING_SNAKE_CASE    			=       (
																	    tokenizer.decode([toks_ids[0]]	,							clean_up_tokenization_spaces=_UpperCamelCase      )
																	    + " "
																	    + tokenizer.decode(toks_ids[1:]	,							clean_up_tokenization_spaces=_UpperCamelCase      )
																	)
												if with_prefix_space:
																	SCREAMING_SNAKE_CASE    			=       " " + output_txt
												SCREAMING_SNAKE_CASE    			=       tokenizer.encode(_UpperCamelCase	,							add_special_tokens=_UpperCamelCase      )
												return output_txt, output_ids




							def 	__snake_case(						self   :					List[str]      )					->				Optional[int]:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE    			=       self.ta_base_tokenizer
												SCREAMING_SNAKE_CASE    			=       tokenizer(["hi</s>", "I went to the gym</s>", "</s>"]      )
												SCREAMING_SNAKE_CASE    			=       tokenizer(["hi", "I went to the gym", ""]      )
												self.assertListEqual(batch_with_eos_added["input_ids"]	,							batch_without_eos_added["input_ids"]      )




							def 	__snake_case(						self   :					int      )					->				List[Any]:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE    			=       self.ta_base_tokenizer
												SCREAMING_SNAKE_CASE    			=       "Unicode €."
												SCREAMING_SNAKE_CASE    			=       tokenizer(_UpperCamelCase      )
												SCREAMING_SNAKE_CASE    			=       [88, 113, 108, 102, 114, 103, 104, 35, 229, 133, 175, 49, 1]
												self.assertEqual(encoded["input_ids"]	,							_UpperCamelCase      )

												# decoding
												SCREAMING_SNAKE_CASE    			=       tokenizer.decode(_UpperCamelCase      )
												self.assertEqual(_UpperCamelCase	,							"Unicode €.</s>"      )

												SCREAMING_SNAKE_CASE    			=       tokenizer("e è é ê ë"      )
												SCREAMING_SNAKE_CASE    			=       [104, 35, 198, 171, 35, 198, 172, 35, 198, 173, 35, 198, 174, 1]
												self.assertEqual(encoded["input_ids"]	,							_UpperCamelCase      )
												# decoding
												SCREAMING_SNAKE_CASE    			=       tokenizer.decode(_UpperCamelCase      )
												self.assertEqual(_UpperCamelCase	,							"e è é ê ë</s>"      )

												# encode/decode, but with `encode` instead of `__call__`
												self.assertEqual(tokenizer.decode(tokenizer.encode("e è é ê ë"      )      )	,							"e è é ê ë</s>"      )




							def 	__snake_case(						self   :					Optional[Any]      )					->				Any:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE    			=       self.ta_base_tokenizer
												SCREAMING_SNAKE_CASE    			=       ["A long paragraph for summarization.", "Another paragraph for summarization."]
												# fmt: off
												SCREAMING_SNAKE_CASE    			=       [68, 35, 111, 114, 113, 106, 35, 115, 100, 117, 100, 106, 117, 100, 115, 107, 35, 105, 114, 117, 35, 118, 120, 112, 112, 100, 117, 108, 125, 100, 119, 108, 114, 113, 49, 1, 0]
												# fmt: on
												SCREAMING_SNAKE_CASE    			=       tokenizer(_UpperCamelCase	,							padding=_UpperCamelCase	,							return_tensors=_UpperCamelCase      )
												self.assertIsInstance(_UpperCamelCase	,							_UpperCamelCase      )

												if FRAMEWORK != "jax":
																	SCREAMING_SNAKE_CASE    			=       list(batch.input_ids.numpy()[0]      )
												else:
																	SCREAMING_SNAKE_CASE    			=       list(batch.input_ids.tolist()[0]      )

												self.assertListEqual(_UpperCamelCase	,							_UpperCamelCase      )

												self.assertEqual((2, 37)	,							batch.input_ids.shape      )
												self.assertEqual((2, 37)	,							batch.attention_mask.shape      )




							def 	__snake_case(						self   :					str      )					->				Dict:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE    			=       self.ta_base_tokenizer
												SCREAMING_SNAKE_CASE    			=       ["A long paragraph for summarization.", "Another paragraph for summarization."]
												SCREAMING_SNAKE_CASE    			=       tokenizer(_UpperCamelCase	,							padding=_UpperCamelCase	,							return_tensors=_UpperCamelCase      )
												# check if input_ids are returned and no decoder_input_ids
												self.assertIn("input_ids"	,							_UpperCamelCase      )
												self.assertIn("attention_mask"	,							_UpperCamelCase      )
												self.assertNotIn("decoder_input_ids"	,							_UpperCamelCase      )
												self.assertNotIn("decoder_attention_mask"	,							_UpperCamelCase      )




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



												'''simple docstring'''

												SCREAMING_SNAKE_CASE    			=       self.ta_base_tokenizer
												SCREAMING_SNAKE_CASE    			=       [
												    "Summary of the text.",
												    "Another summary.",
												]
												SCREAMING_SNAKE_CASE    			=       tokenizer(
												    text_target=_UpperCamelCase	,							max_length=32	,							padding="max_length"	,							truncation=_UpperCamelCase	,							return_tensors=_UpperCamelCase      )
												self.assertEqual(32	,							targets["input_ids"].shape[1]      )




							def 	__snake_case(						self   :					List[Any]      )					->				List[Any]:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE    			=       self.ta_base_tokenizer
												SCREAMING_SNAKE_CASE    			=       ["A long paragraph for summarization. </s>"]
												SCREAMING_SNAKE_CASE    			=       ["Summary of the text. </s>"]
												# fmt: off
												SCREAMING_SNAKE_CASE    			=       [68, 35, 111, 114, 113, 106, 35, 115, 100, 117, 100, 106, 117, 100, 115, 107, 35, 105, 114, 117, 35, 118, 120, 112, 112, 100, 117, 108, 125, 100, 119, 108, 114, 113, 49, 35, 1]
												SCREAMING_SNAKE_CASE    			=       [86, 120, 112, 112, 100, 117, 124, 35, 114, 105, 35, 119, 107, 104, 35, 119, 104, 123, 119, 49, 35, 1]
												# fmt: on

												SCREAMING_SNAKE_CASE    			=       tokenizer(_UpperCamelCase	,							text_target=_UpperCamelCase      )

												self.assertEqual(_UpperCamelCase	,							batch["input_ids"][0]      )
												self.assertEqual(_UpperCamelCase	,							batch["labels"][0]      )




							def 	__snake_case(						self   :					Tuple      )					->				Tuple:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE    			=       self.get_tokenizers()
												for tokenizer in tokenizers:
																	with self.subTest(F"{tokenizer.__class__.__name__}"      ):
																						self.assertNotEqual(tokenizer.model_max_length	,							42      )

        # Now let's start the test
												SCREAMING_SNAKE_CASE    			=       self.get_tokenizers()
												for tokenizer in tokenizers:
																	with self.subTest(F"{tokenizer.__class__.__name__}"      ):
																						# Isolate this from the other tests because we save additional tokens/etc
																						SCREAMING_SNAKE_CASE    			=       tempfile.mkdtemp()

																						SCREAMING_SNAKE_CASE    			=       " He is very happy, UNwant\u00E9d,running"
																						SCREAMING_SNAKE_CASE    			=       tokenizer.encode(_UpperCamelCase	,							add_special_tokens=_UpperCamelCase      )
																						tokenizer.save_pretrained(_UpperCamelCase      )

																						SCREAMING_SNAKE_CASE    			=       tokenizer.__class__.from_pretrained(_UpperCamelCase      )
																						SCREAMING_SNAKE_CASE    			=       after_tokenizer.encode(_UpperCamelCase	,							add_special_tokens=_UpperCamelCase      )
																						self.assertListEqual(_UpperCamelCase	,							_UpperCamelCase      )

																						shutil.rmtree(_UpperCamelCase      )

												SCREAMING_SNAKE_CASE    			=       self.get_tokenizers(model_max_length=42      )
												for tokenizer in tokenizers:
																	with self.subTest(F"{tokenizer.__class__.__name__}"      ):
																						# Isolate this from the other tests because we save additional tokens/etc
																						SCREAMING_SNAKE_CASE    			=       tempfile.mkdtemp()

																						SCREAMING_SNAKE_CASE    			=       " He is very happy, UNwant\u00E9d,running"
																						tokenizer.add_tokens(["bim", "bambam"]      )
																						SCREAMING_SNAKE_CASE    			=       tokenizer.additional_special_tokens
																						additional_special_tokens.append("new_additional_special_token"      )
																						tokenizer.add_special_tokens({"additional_special_tokens": additional_special_tokens}      )
																						SCREAMING_SNAKE_CASE    			=       tokenizer.encode(_UpperCamelCase	,							add_special_tokens=_UpperCamelCase      )
																						tokenizer.save_pretrained(_UpperCamelCase      )

																						SCREAMING_SNAKE_CASE    			=       tokenizer.__class__.from_pretrained(_UpperCamelCase      )
																						SCREAMING_SNAKE_CASE    			=       after_tokenizer.encode(_UpperCamelCase	,							add_special_tokens=_UpperCamelCase      )
																						self.assertListEqual(_UpperCamelCase	,							_UpperCamelCase      )
																						self.assertIn("new_additional_special_token"	,							after_tokenizer.additional_special_tokens      )
																						self.assertEqual(after_tokenizer.model_max_length	,							42      )

																						SCREAMING_SNAKE_CASE    			=       tokenizer.__class__.from_pretrained(_UpperCamelCase	,							model_max_length=43      )
																						self.assertEqual(tokenizer.model_max_length	,							43      )

																						shutil.rmtree(_UpperCamelCase      )




							def 	__snake_case(						self   :					str      )					->				Union[str, Any]:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE    			=       []
												if self.test_slow_tokenizer:
																	tokenizer_list.append((self.tokenizer_class, self.get_tokenizer())      )

												if self.test_rust_tokenizer:
																	tokenizer_list.append((self.rust_tokenizer_class, self.get_rust_tokenizer())      )

												for tokenizer_class, tokenizer_utils in tokenizer_list:
																	with tempfile.TemporaryDirectory() as tmp_dir:
																						tokenizer_utils.save_pretrained(_UpperCamelCase      )

																						with open(os.path.join(_UpperCamelCase	,							"special_tokens_map.json"      )	,							encoding="utf-8"      ) as json_file:
																											SCREAMING_SNAKE_CASE    			=       json.load(_UpperCamelCase      )

																						with open(os.path.join(_UpperCamelCase	,							"tokenizer_config.json"      )	,							encoding="utf-8"      ) as json_file:
																											SCREAMING_SNAKE_CASE    			=       json.load(_UpperCamelCase      )

																						SCREAMING_SNAKE_CASE    			=       [F"<extra_id_{i}>" for i in range(125      )]

																						SCREAMING_SNAKE_CASE    			=       added_tokens_extra_ids + [
																						    "an_additional_special_token"
																						]
																						SCREAMING_SNAKE_CASE    			=       added_tokens_extra_ids + [
																						    "an_additional_special_token"
																						]

																						with open(os.path.join(_UpperCamelCase	,							"special_tokens_map.json"      )	,							"w"	,							encoding="utf-8"      ) as outfile:
																											json.dump(_UpperCamelCase	,							_UpperCamelCase      )
																						with open(os.path.join(_UpperCamelCase	,							"tokenizer_config.json"      )	,							"w"	,							encoding="utf-8"      ) as outfile:
																											json.dump(_UpperCamelCase	,							_UpperCamelCase      )

																						# the following checks allow us to verify that our test works as expected, i.e. that the tokenizer takes
																						# into account the new value of additional_special_tokens given in the "tokenizer_config.json" and
																						# "special_tokens_map.json" files
																						SCREAMING_SNAKE_CASE    			=       tokenizer_class.from_pretrained(
																						    _UpperCamelCase	,							)
																						self.assertIn(
																						    "an_additional_special_token"	,							tokenizer_without_change_in_init.additional_special_tokens      )
																						# self.assertIn("an_additional_special_token",tokenizer_without_change_in_init.get_vocab()) # ByT5Tokenization no vocab
																						self.assertEqual(
																						    ["an_additional_special_token"]	,							tokenizer_without_change_in_init.convert_ids_to_tokens(
																						        tokenizer_without_change_in_init.convert_tokens_to_ids(["an_additional_special_token"]      )      )	,							)

																						# Now we test that we can change the value of additional_special_tokens in the from_pretrained
																						SCREAMING_SNAKE_CASE    			=       added_tokens_extra_ids + [AddedToken("a_new_additional_special_token"	,							lstrip=_UpperCamelCase      )]
																						SCREAMING_SNAKE_CASE    			=       tokenizer_class.from_pretrained(
																						    _UpperCamelCase	,							additional_special_tokens=_UpperCamelCase	,							)

																						self.assertIn("a_new_additional_special_token"	,							tokenizer.additional_special_tokens      )
																						self.assertEqual(
																						    ["a_new_additional_special_token"]	,							tokenizer.convert_ids_to_tokens(
																						        tokenizer.convert_tokens_to_ids(["a_new_additional_special_token"]      )      )	,							)




							def 	__snake_case(						self   :					Optional[Any]      )					->				List[str]:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE    			=       []
												if self.test_slow_tokenizer:
																	tokenizer_list.append((self.tokenizer_class, self.get_tokenizer())      )

												if self.test_rust_tokenizer:
																	tokenizer_list.append((self.rust_tokenizer_class, self.get_rust_tokenizer())      )

												for tokenizer_class, tokenizer_utils in tokenizer_list:
																	with tempfile.TemporaryDirectory() as tmp_dir:
																						tokenizer_utils.save_pretrained(_UpperCamelCase      )

																						SCREAMING_SNAKE_CASE    			=       tokenizer_class.from_pretrained(_UpperCamelCase      )

																						self.assertTrue(tokenizer.decode([255]      ) == ""      )




							def 	__snake_case(						self   :					str      )					->				Optional[int]:



												'''simple docstring'''

												pass




							def 	__snake_case(						self   :					List[Any]      )					->				str:



												'''simple docstring'''

												pass




							def 	__snake_case(						self   :					Any      )					->				int:



												'''simple docstring'''

												pass




							def 	__snake_case(						self   :					Dict      )					->				int:



												'''simple docstring'''

												pass




							def 	__snake_case(						self   :					Optional[Any]      )					->				Optional[Any]:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE    			=       self.get_tokenizers(fast=_UpperCamelCase	,							do_lower_case=_UpperCamelCase      )
												for tokenizer in tokenizers:
																	with self.subTest(F"{tokenizer.__class__.__name__}"      ):
																						SCREAMING_SNAKE_CASE    			=       ["t", "h", "i", "s", " ", "i", "s", " ", "a", " ", "t", "e", "x", "t", "</s>"]
																						SCREAMING_SNAKE_CASE    			=       tokenizer.convert_tokens_to_string(_UpperCamelCase      )

																						self.assertIsInstance(_UpperCamelCase	,							_UpperCamelCase      )





							def 	__snake_case(						self   :					int      )					->				str:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE    			=       self.get_tokenizers()
												for tokenizer in tokenizers:
																	with self.subTest(F"{tokenizer.__class__.__name__}"      ):
																						SCREAMING_SNAKE_CASE    			=       [
																						    "bos_token",
																						    "eos_token",
																						    "unk_token",
																						    "sep_token",
																						    "pad_token",
																						    "cls_token",
																						    "mask_token",
																						]

																						SCREAMING_SNAKE_CASE    			=       0
																						SCREAMING_SNAKE_CASE    			=       tokenizer.convert_ids_to_tokens(
																						    _UpperCamelCase	,							skip_special_tokens=_UpperCamelCase      )

																						for attr in attributes_list:
																											setattr(_UpperCamelCase	,							attr + "_id"	,							_UpperCamelCase      )
																											self.assertEqual(getattr(_UpperCamelCase	,							_UpperCamelCase      )	,							_UpperCamelCase      )
																											self.assertEqual(getattr(_UpperCamelCase	,							attr + "_id"      )	,							_UpperCamelCase      )

																											setattr(_UpperCamelCase	,							attr + "_id"	,							_UpperCamelCase      )
																											self.assertEqual(getattr(_UpperCamelCase	,							_UpperCamelCase      )	,							_UpperCamelCase      )
																											self.assertEqual(getattr(_UpperCamelCase	,							attr + "_id"      )	,							_UpperCamelCase      )

																						setattr(_UpperCamelCase	,							"additional_special_tokens_ids"	,							[]      )
																						self.assertListEqual(getattr(_UpperCamelCase	,							"additional_special_tokens"      )	,							[]      )
																						self.assertListEqual(getattr(_UpperCamelCase	,							"additional_special_tokens_ids"      )	,							[]      )

																						setattr(_UpperCamelCase	,							"additional_special_tokens_ids"	,							[token_id_to_test_setters]      )
																						self.assertListEqual(getattr(_UpperCamelCase	,							"additional_special_tokens"      )	,							[token_to_test_setters]      )
																						self.assertListEqual(getattr(_UpperCamelCase	,							"additional_special_tokens_ids"      )	,							[token_id_to_test_setters]      )





import functools





def 	__lowerCamelCase							(UpperCAmelCase__     :							list[int]      , UpperCAmelCase__     :							list[int]  ):

					# Validation
					if not isinstance(UpperCAmelCase__      , UpperCAmelCase__  ) or not all(isinstance(UpperCAmelCase__      , UpperCAmelCase__  ) for day in days  ):
										raise ValueError("The parameter days should be a list of integers"  )

					if len(UpperCAmelCase__  ) != 3 or not all(isinstance(UpperCAmelCase__      , UpperCAmelCase__  ) for cost in costs  ):
										raise ValueError("The parameter costs should be a list of three integers"  )

					if len(UpperCAmelCase__  ) == 0:
										return 0

					if min(UpperCAmelCase__  ) <= 0:
										raise ValueError("All days elements should be greater than 0"  )

					if max(UpperCAmelCase__  ) >= 3_6_6:
										raise ValueError("All days elements should be less than 366"  )

					SCREAMING_SNAKE_CASE    			=       set(UpperCAmelCase__  )

					@functools.cache
					def dynamic_programming(UpperCAmelCase__     :							int  ) -> int:
										if index > 3_6_5:
															return 0

										if index not in days_set:
															return dynamic_programming(index + 1  )

										return min(
										    costs[0] + dynamic_programming(index + 1  )      , costs[1] + dynamic_programming(index + 7  )      , costs[2] + dynamic_programming(index + 3_0  )      , )

					return dynamic_programming(1  )


if __name__ == "__main__":
							import doctest

							doctest.testmod()




