import shutil
import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartTokenizer, MBartTokenizerFast, is_torch_available
from transformers.testing_utils import (
    get_tests_dir,
    nested_simplify,
    require_sentencepiece,
    require_tokenizers,
    require_torch,
)

from ...test_tokenization_common import TokenizerTesterMixin


_A   					=    get_tests_dir('fixtures/test_sentencepiece.model')


if is_torch_available():
						from transformers.models.mbart.modeling_mbart import shift_tokens_right

_A   					=    2_5_0_0_0_4
_A   					=    2_5_0_0_2_0

@require_sentencepiece
@require_tokenizers
class lowerCamelCase		(SCREAMING_SNAKE_CASE_    ,    unittest.TestCase      ):






					'''simple docstring'''


					a   	=		MBartTokenizer
					a   	=		MBartTokenizerFast
					a   	=		True
					a   	=		True



					def 			lowerCAmelCase_					(						self			:				List[Any]		)							->       List[str]:
									super().setUp()

									# We have a SentencePiece fixture for testing
									SCREAMING_SNAKE_CASE__		  =				MBartTokenizer(UpperCamelCase__   , keep_accents=UpperCamelCase__		)
									tokenizer.save_pretrained(self.tmpdirname		)



					def 			lowerCAmelCase_					(						self			:				Dict		)							->       Tuple:
									SCREAMING_SNAKE_CASE__		  =				MBartTokenizer(UpperCamelCase__   , keep_accents=UpperCamelCase__		)

									SCREAMING_SNAKE_CASE__		  =				tokenizer.tokenize("This is a test"		)
									self.assertListEqual(UpperCamelCase__   , ["▁This", "▁is", "▁a", "▁t", "est"]		)

									self.assertListEqual(
									    tokenizer.convert_tokens_to_ids(UpperCamelCase__		)   , [value + tokenizer.fairseq_offset for value in [285, 46, 10, 170, 382]]   , )

									SCREAMING_SNAKE_CASE__		  =				tokenizer.tokenize("I was born in 92000, and this is falsé."		)
									self.assertListEqual(
									    UpperCamelCase__   , [
									        SPIECE_UNDERLINE + "I",
									        SPIECE_UNDERLINE + "was",
									        SPIECE_UNDERLINE + "b",
									        "or",
									        "n",
									        SPIECE_UNDERLINE + "in",
									        SPIECE_UNDERLINE + "",
									        "9",
									        "2",
									        "0",
									        "0",
									        "0",
									        ",",
									        SPIECE_UNDERLINE + "and",
									        SPIECE_UNDERLINE + "this",
									        SPIECE_UNDERLINE + "is",
									        SPIECE_UNDERLINE + "f",
									        "al",
									        "s",
									        "é",
									        ".",
									    ]   , )
									SCREAMING_SNAKE_CASE__		  =				tokenizer.convert_tokens_to_ids(UpperCamelCase__		)
									self.assertListEqual(
									    UpperCamelCase__   , [
									        value + tokenizer.fairseq_offset
									        for value in [8, 21, 84, 55, 24, 19, 7, 2, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 2, 4]
									        #                                       ^ unk: 2 + 1 = 3                  unk: 2 + 1 = 3 ^
									    ]   , )

									SCREAMING_SNAKE_CASE__		  =				tokenizer.convert_ids_to_tokens(UpperCamelCase__		)
									self.assertListEqual(
									    UpperCamelCase__   , [
									        SPIECE_UNDERLINE + "I",
									        SPIECE_UNDERLINE + "was",
									        SPIECE_UNDERLINE + "b",
									        "or",
									        "n",
									        SPIECE_UNDERLINE + "in",
									        SPIECE_UNDERLINE + "",
									        "<unk>",
									        "2",
									        "0",
									        "0",
									        "0",
									        ",",
									        SPIECE_UNDERLINE + "and",
									        SPIECE_UNDERLINE + "this",
									        SPIECE_UNDERLINE + "is",
									        SPIECE_UNDERLINE + "f",
									        "al",
									        "s",
									        "<unk>",
									        ".",
									    ]   , )



					def 			lowerCAmelCase_					(						self			:				List[Any]		)							->       Tuple:
									if not self.test_slow_tokenizer:
													# as we don't have a slow version, we can't compare the outputs between slow and fast versions
													return

									SCREAMING_SNAKE_CASE__		  =				(self.rust_tokenizer_class, '''hf-internal-testing/tiny-random-mbart''', {})
									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(UpperCamelCase__   , **UpperCamelCase__		)
																	SCREAMING_SNAKE_CASE__		  =				self.tokenizer_class.from_pretrained(UpperCamelCase__   , **UpperCamelCase__		)

																	SCREAMING_SNAKE_CASE__		  =				tempfile.mkdtemp()

																	SCREAMING_SNAKE_CASE__		  =				tokenizer_r.save_pretrained(UpperCamelCase__		)
																	SCREAMING_SNAKE_CASE__		  =				tokenizer_p.save_pretrained(UpperCamelCase__		)

																	# Checks it save with the same files + the tokenizer.json file for the fast one
																	self.assertTrue(any("tokenizer.json" in f for f in tokenizer_r_files		)		)
																	SCREAMING_SNAKE_CASE__		  =				tuple(f for f in tokenizer_r_files if "tokenizer.json" not in f		)
																	self.assertSequenceEqual(UpperCamelCase__   , UpperCamelCase__		)

																	# Checks everything loads correctly in the same way
																	SCREAMING_SNAKE_CASE__		  =				tokenizer_r.from_pretrained(UpperCamelCase__		)
																	SCREAMING_SNAKE_CASE__		  =				tokenizer_p.from_pretrained(UpperCamelCase__		)

																	# Check special tokens are set accordingly on Rust and Python
																	for key in tokenizer_pp.special_tokens_map:
																					self.assertTrue(hasattr(UpperCamelCase__   , UpperCamelCase__		)		)
																					# self.assertEqual(getattr(tokenizer_rp, key), getattr(tokenizer_pp, key))
																					# self.assertEqual(getattr(tokenizer_rp, key + "_id"), getattr(tokenizer_pp, key + "_id"))

																	shutil.rmtree(UpperCamelCase__		)

																	# Save tokenizer rust, legacy_format=True
																	SCREAMING_SNAKE_CASE__		  =				tempfile.mkdtemp()

																	SCREAMING_SNAKE_CASE__		  =				tokenizer_r.save_pretrained(UpperCamelCase__   , legacy_format=UpperCamelCase__		)
																	SCREAMING_SNAKE_CASE__		  =				tokenizer_p.save_pretrained(UpperCamelCase__		)

																	# Checks it save with the same files
																	self.assertSequenceEqual(UpperCamelCase__   , UpperCamelCase__		)

																	# Checks everything loads correctly in the same way
																	SCREAMING_SNAKE_CASE__		  =				tokenizer_r.from_pretrained(UpperCamelCase__		)
																	SCREAMING_SNAKE_CASE__		  =				tokenizer_p.from_pretrained(UpperCamelCase__		)

																	# Check special tokens are set accordingly on Rust and Python
																	for key in tokenizer_pp.special_tokens_map:
																					self.assertTrue(hasattr(UpperCamelCase__   , UpperCamelCase__		)		)

																	shutil.rmtree(UpperCamelCase__		)

																	# Save tokenizer rust, legacy_format=False
																	SCREAMING_SNAKE_CASE__		  =				tempfile.mkdtemp()

																	SCREAMING_SNAKE_CASE__		  =				tokenizer_r.save_pretrained(UpperCamelCase__   , legacy_format=UpperCamelCase__		)
																	SCREAMING_SNAKE_CASE__		  =				tokenizer_p.save_pretrained(UpperCamelCase__		)

																	# Checks it saved the tokenizer.json file
																	self.assertTrue(any("tokenizer.json" in f for f in tokenizer_r_files		)		)

																	# Checks everything loads correctly in the same way
																	SCREAMING_SNAKE_CASE__		  =				tokenizer_r.from_pretrained(UpperCamelCase__		)
																	SCREAMING_SNAKE_CASE__		  =				tokenizer_p.from_pretrained(UpperCamelCase__		)

																	# Check special tokens are set accordingly on Rust and Python
																	for key in tokenizer_pp.special_tokens_map:
																					self.assertTrue(hasattr(UpperCamelCase__   , UpperCamelCase__		)		)

																	shutil.rmtree(UpperCamelCase__		)



@require_torch
@require_sentencepiece
@require_tokenizers
class lowerCamelCase		(unittest.TestCase      ):






					'''simple docstring'''


					a   	=		"facebook/mbart-large-en-ro"
					a   	=		[
					    " UN Chief Says There Is No Military Solution in Syria",
					    " Secretary-General Ban Ki-moon says his response to Russia's stepped up military support for Syria is that \"there is no military solution\" to the nearly five-year conflict and more weapons will only worsen the violence and misery for millions of people.",
					]
					a   	=		[
					    "Şeful ONU declară că nu există o soluţie militară în Siria",
					    "Secretarul General Ban Ki-moon declară că răspunsul său la intensificarea sprijinului militar al Rusiei"
					    " pentru Siria este că \"nu există o soluţie militară\" la conflictul de aproape cinci ani şi că noi arme nu vor"
					    " face decât să înrăutăţească violenţele şi mizeria pentru milioane de oameni.",
					]
					a   	=		[8_2_7_4, 1_2_7_8_7_3, 2_5_9_1_6, 7, 8_6_2_2, 2_0_7_1, 4_3_8, 6_7_4_8_5, 5_3, 1_8_7_8_9_5, 2_3, 5_1_7_1_2, 2, EN_CODE]



					@classmethod
					def 			lowerCAmelCase_					(						cls			:				Dict		)							->       Tuple:
									SCREAMING_SNAKE_CASE__		  =				MBartTokenizer.from_pretrained(
									    cls.checkpoint_name   , src_lang="en_XX"   , tgt_lang="ro_RO"		)
									SCREAMING_SNAKE_CASE__		  =				1
									return cls



					def 			lowerCAmelCase_					(						self			:				str		)							->       str:
									self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["ar_AR"]   , 250001		)
									self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["en_EN"]   , 250004		)
									self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["ro_RO"]   , 250020		)



					def 			lowerCAmelCase_					(						self			:				Optional[int]		)							->       Tuple:
									SCREAMING_SNAKE_CASE__		  =				self.tokenizer.batch_encode_plus(self.src_text		).input_ids[0]
									self.assertListEqual(self.expected_src_tokens   , UpperCamelCase__		)



					def 			lowerCAmelCase_					(						self			:				Any		)							->       Any:
									self.assertIn(UpperCamelCase__   , self.tokenizer.all_special_ids		)
									SCREAMING_SNAKE_CASE__		  =				[RO_CODE, 884, 9019, 96, 9, 916, 86792, 36, 18743, 15596, 5, 2]
									SCREAMING_SNAKE_CASE__		  =				self.tokenizer.decode(UpperCamelCase__   , skip_special_tokens=UpperCamelCase__		)
									SCREAMING_SNAKE_CASE__		  =				self.tokenizer.decode(generated_ids[1:]   , skip_special_tokens=UpperCamelCase__		)
									self.assertEqual(UpperCamelCase__   , UpperCamelCase__		)
									self.assertNotIn(self.tokenizer.eos_token   , UpperCamelCase__		)



					def 			lowerCAmelCase_					(						self			:				Dict		)							->       Union[str, Any]:
									SCREAMING_SNAKE_CASE__		  =				['''this is gunna be a long sentence ''' * 20]
									assert isinstance(src_text[0]   , UpperCamelCase__		)
									SCREAMING_SNAKE_CASE__		  =				10
									SCREAMING_SNAKE_CASE__		  =				self.tokenizer(UpperCamelCase__   , max_length=UpperCamelCase__   , truncation=UpperCamelCase__		).input_ids[0]
									self.assertEqual(ids[-2]   , 2		)
									self.assertEqual(ids[-1]   , UpperCamelCase__		)
									self.assertEqual(len(UpperCamelCase__		)   , UpperCamelCase__		)



					def 			lowerCAmelCase_					(						self			:				List[str]		)							->       str:
									self.assertListEqual(self.tokenizer.convert_tokens_to_ids(["<mask>", "ar_AR"]		)   , [250026, 250001]		)



					def 			lowerCAmelCase_					(						self			:				Tuple		)							->       Optional[int]:
									SCREAMING_SNAKE_CASE__		  =				tempfile.mkdtemp()
									SCREAMING_SNAKE_CASE__		  =				self.tokenizer.fairseq_tokens_to_ids
									self.tokenizer.save_pretrained(UpperCamelCase__		)
									SCREAMING_SNAKE_CASE__		  =				MBartTokenizer.from_pretrained(UpperCamelCase__		)
									self.assertDictEqual(new_tok.fairseq_tokens_to_ids   , UpperCamelCase__		)



					@require_torch
					def 			lowerCAmelCase_					(						self			:				str		)							->       Any:
									SCREAMING_SNAKE_CASE__		  =				self.tokenizer(self.src_text   , text_target=self.tgt_text   , padding=UpperCamelCase__   , return_tensors="pt"		)
									SCREAMING_SNAKE_CASE__		  =				shift_tokens_right(batch["labels"]   , self.tokenizer.pad_token_id		)

									# fairseq batch: https://gist.github.com/sshleifer/cba08bc2109361a74ac3760a7e30e4f4
									assert batch.input_ids[1][-2:].tolist() == [2, EN_CODE]
									assert batch.decoder_input_ids[1][0].tolist() == RO_CODE
									assert batch.decoder_input_ids[1][-1] == 2
									assert batch.labels[1][-2:].tolist() == [2, RO_CODE]



					@require_torch
					def 			lowerCAmelCase_					(						self			:				Union[str, Any]		)							->       List[Any]:
									SCREAMING_SNAKE_CASE__		  =				self.tokenizer(
									    self.src_text   , text_target=self.tgt_text   , padding=UpperCamelCase__   , truncation=UpperCamelCase__   , max_length=len(self.expected_src_tokens		)   , return_tensors="pt"   , )

									SCREAMING_SNAKE_CASE__		  =				shift_tokens_right(batch["labels"]   , self.tokenizer.pad_token_id		)

									self.assertIsInstance(UpperCamelCase__   , UpperCamelCase__		)

									self.assertEqual((2, 14)   , batch.input_ids.shape		)
									self.assertEqual((2, 14)   , batch.attention_mask.shape		)
									SCREAMING_SNAKE_CASE__		  =				batch.input_ids.tolist()[0]
									self.assertListEqual(self.expected_src_tokens   , UpperCamelCase__		)
									self.assertEqual(2   , batch.decoder_input_ids[0, -1]		)  # EOS
									# Test that special tokens are reset
									self.assertEqual(self.tokenizer.prefix_tokens   , []		)
									self.assertEqual(self.tokenizer.suffix_tokens   , [self.tokenizer.eos_token_id, EN_CODE]		)



					def 			lowerCAmelCase_					(						self			:				str		)							->       Dict:
									SCREAMING_SNAKE_CASE__		  =				self.tokenizer(self.src_text   , padding=UpperCamelCase__   , truncation=UpperCamelCase__   , max_length=3   , return_tensors="pt"		)
									SCREAMING_SNAKE_CASE__		  =				self.tokenizer(
									    text_target=self.tgt_text   , padding=UpperCamelCase__   , truncation=UpperCamelCase__   , max_length=10   , return_tensors="pt"		)
									SCREAMING_SNAKE_CASE__		  =				targets['''input_ids''']
									SCREAMING_SNAKE_CASE__		  =				shift_tokens_right(UpperCamelCase__   , self.tokenizer.pad_token_id		)

									self.assertEqual(batch.input_ids.shape[1]   , 3		)
									self.assertEqual(batch.decoder_input_ids.shape[1]   , 10		)



					@require_torch
					def 			lowerCAmelCase_					(						self			:				Optional[Any]		)							->       Optional[Any]:
									SCREAMING_SNAKE_CASE__		  =				self.tokenizer._build_translation_inputs(
									    "A test"   , return_tensors="pt"   , src_lang="en_XX"   , tgt_lang="ar_AR"		)

									self.assertEqual(
									    nested_simplify(UpperCamelCase__		)   , {
									        # A, test, EOS, en_XX
									        "input_ids": [[62, 3034, 2, 250004]],
									        "attention_mask": [[1, 1, 1, 1]],
									        # ar_AR
									        "forced_bos_token_id": 250001,
									    }   , )





"""simple docstring"""






import sys




def 						SCREAMING_SNAKE_CASE					(  __UpperCAmelCase       )							->   Any:
				SCREAMING_SNAKE_CASE__		  =				len(__UpperCAmelCase       )
				SCREAMING_SNAKE_CASE__		  =				[[0 for x in range(__UpperCAmelCase       )] for x in range(__UpperCAmelCase       )]
				SCREAMING_SNAKE_CASE__		  =				[[0 for x in range(__UpperCAmelCase       )] for x in range(__UpperCAmelCase       )]

				for chain_length in range(2  ,					__UpperCAmelCase       ):
								for a in range(1  ,					n - chain_length + 1       ):
												SCREAMING_SNAKE_CASE__		  =				a + chain_length - 1

												SCREAMING_SNAKE_CASE__		  =				sys.maxsize
												for c in range(__UpperCAmelCase  ,					__UpperCAmelCase       ):
																SCREAMING_SNAKE_CASE__		  =				(
																    matrix[a][c] + matrix[c + 1][b] + array[a - 1] * array[c] * array[b]
																)
																if cost < matrix[a][b]:
																				SCREAMING_SNAKE_CASE__		  =				cost
																				SCREAMING_SNAKE_CASE__		  =				c
				return matrix, sol




def 						SCREAMING_SNAKE_CASE					(  __UpperCAmelCase  ,					__UpperCAmelCase  ,					__UpperCAmelCase       )							->   Union[str, Any]:
				if i == j:
								print("A" + str(__UpperCAmelCase       )  ,					end=" "       )
				else:
								print("("  ,					end=" "       )
								print_optiomal_solution(__UpperCAmelCase  ,					__UpperCAmelCase  ,					optimal_solution[i][j]       )
								print_optiomal_solution(__UpperCAmelCase  ,					optimal_solution[i][j] + 1  ,					__UpperCAmelCase       )
								print(")"  ,					end=" "       )




def 						SCREAMING_SNAKE_CASE					(  )							->   Any:
				SCREAMING_SNAKE_CASE__		  =				[30, 35, 15, 5, 10, 20, 25]
				SCREAMING_SNAKE_CASE__		  =				len(__UpperCAmelCase       )
				# Size of matrix created from above array will be
				# 30*35 35*15 15*5 5*10 10*20 20*25
				SCREAMING_SNAKE_CASE__  ,       SCREAMING_SNAKE_CASE__		  =				matrix_chain_order(__UpperCAmelCase       )

				print("No. of Operation required: " + str(matrix[1][n - 1]       )       )
				print_optiomal_solution(__UpperCAmelCase  ,					1  ,					n - 1       )


if __name__ == "__main__":
						main()




