






'''simple docstring'''




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


__lowerCamelCase   :					Optional[Any]   							=					get_tests_dir('''fixtures/test_sentencepiece.model''')


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

__lowerCamelCase   :					Union[str, Any]   							=					250004
__lowerCamelCase   :					Dict   							=					250020



@require_sentencepiece
@require_tokenizers
class    A_	(a_						,					unittest.TestCase							):
							"""simple docstring"""




							a__   		=	MBartTokenizer
							a__   		=	MBartTokenizerFast
							a__   		=	True
							a__   		=	True

							def 							_A	(		self			:Dict				)				->  Any:


										'''simple docstring'''




										super().setUp()

										# We have a SentencePiece fixture for testing
										snake_case_				:					int   =       MBartTokenizer(lowerCAmelCase__       ,							keep_accents=lowerCAmelCase__				)
										tokenizer.save_pretrained(self.tmpdirname				)

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


										'''simple docstring'''




										snake_case_				:					Tuple   =       MBartTokenizer(lowerCAmelCase__       ,							keep_accents=lowerCAmelCase__				)

										snake_case_				:					List[Any]   =       tokenizer.tokenize("This is a test"				)
										self.assertListEqual(lowerCAmelCase__       ,							["▁This", "▁is", "▁a", "▁t", "est"]				)

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

										snake_case_				:					Dict   =       tokenizer.tokenize("I was born in 92000, and this is falsé."				)
										self.assertListEqual(
										    lowerCAmelCase__       ,							[
										        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",
										        ".",
										    ]       ,							)
										snake_case_				:					List[Any]   =       tokenizer.convert_tokens_to_ids(lowerCAmelCase__				)
										self.assertListEqual(
										    lowerCAmelCase__       ,							[
										        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 ^
										    ]       ,							)

										snake_case_				:					Optional[int]   =       tokenizer.convert_ids_to_tokens(lowerCAmelCase__				)
										self.assertListEqual(
										    lowerCAmelCase__       ,							[
										        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 							_A	(		self			:List[Any]				)				->  List[Any]:


										'''simple docstring'''




										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

										snake_case_				:					Optional[int]   =       (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})'''				):
																snake_case_				:					Optional[Any]   =       self.rust_tokenizer_class.from_pretrained(lowerCAmelCase__       ,							**lowerCAmelCase__				)
																snake_case_				:					List[Any]   =       self.tokenizer_class.from_pretrained(lowerCAmelCase__       ,							**lowerCAmelCase__				)

																snake_case_				:					List[str]   =       tempfile.mkdtemp()

																snake_case_				:					Optional[Any]   =       tokenizer_r.save_pretrained(lowerCAmelCase__				)
																snake_case_				:					Optional[Any]   =       tokenizer_p.save_pretrained(lowerCAmelCase__				)

																# 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				)				)
																snake_case_				:					List[Any]   =       tuple(f for f in tokenizer_r_files if "tokenizer.json" not in f				)
																self.assertSequenceEqual(lowerCAmelCase__       ,							lowerCAmelCase__				)

																# Checks everything loads correctly in the same way
																snake_case_				:					Optional[int]   =       tokenizer_r.from_pretrained(lowerCAmelCase__				)
																snake_case_				:					int   =       tokenizer_p.from_pretrained(lowerCAmelCase__				)

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

																shutil.rmtree(lowerCAmelCase__				)

																# Save tokenizer rust, legacy_format=True
																snake_case_				:					Optional[Any]   =       tempfile.mkdtemp()

																snake_case_				:					Any   =       tokenizer_r.save_pretrained(lowerCAmelCase__       ,							legacy_format=lowerCAmelCase__				)
																snake_case_				:					Optional[Any]   =       tokenizer_p.save_pretrained(lowerCAmelCase__				)

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

																# Checks everything loads correctly in the same way
																snake_case_				:					Optional[int]   =       tokenizer_r.from_pretrained(lowerCAmelCase__				)
																snake_case_				:					str   =       tokenizer_p.from_pretrained(lowerCAmelCase__				)

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

																shutil.rmtree(lowerCAmelCase__				)

																# Save tokenizer rust, legacy_format=False
																snake_case_				:					Union[str, Any]   =       tempfile.mkdtemp()

																snake_case_				:					Tuple   =       tokenizer_r.save_pretrained(lowerCAmelCase__       ,							legacy_format=lowerCAmelCase__				)
																snake_case_				:					Any   =       tokenizer_p.save_pretrained(lowerCAmelCase__				)

																# 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
																snake_case_				:					Optional[Any]   =       tokenizer_r.from_pretrained(lowerCAmelCase__				)
																snake_case_				:					Any   =       tokenizer_p.from_pretrained(lowerCAmelCase__				)

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

																shutil.rmtree(lowerCAmelCase__				)



@require_torch
@require_sentencepiece
@require_tokenizers
class    A_	(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__   		=	[8274, 127873, 25916, 7, 8622, 2071, 438, 67485, 53, 187895, 23, 51712, 2, EN_CODE]

							@classmethod
							def 							_A	(		cls			:Union[str, Any]				)				->  Union[str, Any]:


										'''simple docstring'''




										snake_case_				:					MBartTokenizer   =       MBartTokenizer.from_pretrained(
										    cls.checkpoint_name       ,							src_lang="en_XX"       ,							tgt_lang="ro_RO"				)
										snake_case_				:					int   =       1
										return cls

							def 							_A	(		self			:Dict				)				->  Optional[Any]:


										'''simple docstring'''




										self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["ar_AR"]       ,							250_001				)
										self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["en_EN"]       ,							250_004				)
										self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["ro_RO"]       ,							250_020				)

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


										'''simple docstring'''




										snake_case_				:					Dict   =       self.tokenizer.batch_encode_plus(self.src_text				).input_ids[0]
										self.assertListEqual(self.expected_src_tokens       ,							lowerCAmelCase__				)

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


										'''simple docstring'''




										self.assertIn(lowerCAmelCase__       ,							self.tokenizer.all_special_ids				)
										snake_case_				:					int   =       [RO_CODE, 884, 9_019, 96, 9, 916, 86_792, 36, 18_743, 15_596, 5, 2]
										snake_case_				:					Any   =       self.tokenizer.decode(lowerCAmelCase__       ,							skip_special_tokens=lowerCAmelCase__				)
										snake_case_				:					Any   =       self.tokenizer.decode(generated_ids[1:]       ,							skip_special_tokens=lowerCAmelCase__				)
										self.assertEqual(lowerCAmelCase__       ,							lowerCAmelCase__				)
										self.assertNotIn(self.tokenizer.eos_token       ,							lowerCAmelCase__				)

							def 							_A	(		self			:List[Any]				)				->  Tuple:


										'''simple docstring'''




										snake_case_				:					Optional[Any]   =       ["this is gunna be a long sentence " * 20]
										assert isinstance(src_text[0]       ,							lowerCAmelCase__				)
										snake_case_				:					Any   =       10
										snake_case_				:					str   =       self.tokenizer(lowerCAmelCase__       ,							max_length=lowerCAmelCase__       ,							truncation=lowerCAmelCase__				).input_ids[0]
										self.assertEqual(ids[-2]       ,							2				)
										self.assertEqual(ids[-1]       ,							lowerCAmelCase__				)
										self.assertEqual(len(lowerCAmelCase__				)       ,							lowerCAmelCase__				)

							def 							_A	(		self			:str				)				->  str:


										'''simple docstring'''




										self.assertListEqual(self.tokenizer.convert_tokens_to_ids(["<mask>", "ar_AR"]				)       ,							[250_026, 250_001]				)

							def 							_A	(		self			:Tuple				)				->  int:


										'''simple docstring'''




										snake_case_				:					List[str]   =       tempfile.mkdtemp()
										snake_case_				:					List[str]   =       self.tokenizer.fairseq_tokens_to_ids
										self.tokenizer.save_pretrained(lowerCAmelCase__				)
										snake_case_				:					Union[str, Any]   =       MBartTokenizer.from_pretrained(lowerCAmelCase__				)
										self.assertDictEqual(new_tok.fairseq_tokens_to_ids       ,							lowerCAmelCase__				)

							@require_torch
							def 							_A	(		self			:str				)				->  Tuple:


										'''simple docstring'''




										snake_case_				:					Optional[int]   =       self.tokenizer(self.src_text       ,							text_target=self.tgt_text       ,							padding=lowerCAmelCase__       ,							return_tensors="pt"				)
										snake_case_				:					Optional[Any]   =       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 							_A	(		self			:List[Any]				)				->  List[Any]:


										'''simple docstring'''




										snake_case_				:					List[str]   =       self.tokenizer(
										    self.src_text       ,							text_target=self.tgt_text       ,							padding=lowerCAmelCase__       ,							truncation=lowerCAmelCase__       ,							max_length=len(self.expected_src_tokens				)       ,							return_tensors="pt"       ,							)

										snake_case_				:					str   =       shift_tokens_right(batch["labels"]       ,							self.tokenizer.pad_token_id				)

										self.assertIsInstance(lowerCAmelCase__       ,							lowerCAmelCase__				)

										self.assertEqual((2, 14)       ,							batch.input_ids.shape				)
										self.assertEqual((2, 14)       ,							batch.attention_mask.shape				)
										snake_case_				:					Tuple   =       batch.input_ids.tolist()[0]
										self.assertListEqual(self.expected_src_tokens       ,							lowerCAmelCase__				)
										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 							_A	(		self			:List[Any]				)				->  List[Any]:


										'''simple docstring'''




										snake_case_				:					Tuple   =       self.tokenizer(self.src_text       ,							padding=lowerCAmelCase__       ,							truncation=lowerCAmelCase__       ,							max_length=3       ,							return_tensors="pt"				)
										snake_case_				:					Union[str, Any]   =       self.tokenizer(
										    text_target=self.tgt_text       ,							padding=lowerCAmelCase__       ,							truncation=lowerCAmelCase__       ,							max_length=10       ,							return_tensors="pt"				)
										snake_case_				:					Optional[Any]   =       targets["input_ids"]
										snake_case_				:					int   =       shift_tokens_right(lowerCAmelCase__       ,							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 							_A	(		self			:Tuple				)				->  Optional[Any]:


										'''simple docstring'''




										snake_case_				:					Union[str, Any]   =       self.tokenizer._build_translation_inputs(
										    "A test"       ,							return_tensors="pt"       ,							src_lang="en_XX"       ,							tgt_lang="ar_AR"				)

										self.assertEqual(
										    nested_simplify(lowerCAmelCase__				)       ,							{
										        # A, test, EOS, en_XX
										        "input_ids": [[62, 3_034, 2, 250_004]],
										        "attention_mask": [[1, 1, 1, 1]],
										        # ar_AR
										        "forced_bos_token_id": 250_001,
										    }       ,							)












'''simple docstring'''




# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import argparse
import os

from accelerate.test_utils import execute_subprocess_async

def 	__UpperCAmelCase       ( __magic_name__=None						)->    List[str]:



			"""simple docstring"""



			if subparsers is not None:
						snake_case_				:					List[str]   =       subparsers.add_parser("test"						)
			else:
						snake_case_				:					List[Any]   =       argparse.ArgumentParser("Accelerate test command"						)

			parser.add_argument(
			    "--config_file"     ,default=__magic_name__     ,help=(
			        "The path to use to store the config file. Will default to a file named default_config.yaml in the cache "
			        "location, which is the content of the environment `HF_HOME` suffixed with 'accelerate', or if you don't have "
			        "such an environment variable, your cache directory ('~/.cache' or the content of `XDG_CACHE_HOME`) suffixed "
			        "with 'huggingface'."
			    )     ,)

			if subparsers is not None:
						parser.set_defaults(func=__magic_name__						)
			return parser

def 	__UpperCAmelCase       ( __magic_name__						)->    Tuple:



			"""simple docstring"""



			snake_case_				:					Optional[Any]   =       os.path.sep.join(__file__.split(os.path.sep						)[:-2] + ["test_utils", "scripts", "test_script.py"]						)

			if args.config_file is None:
						snake_case_				:					str   =       script_name
			else:
						snake_case_				:					Any   =       F'''--config_file={args.config_file} {script_name}'''

			snake_case_				:					Union[str, Any]   =       ["accelerate-launch"] + test_args.split()
			snake_case_				:					Optional[int]   =       execute_subprocess_async(__magic_name__     ,env=os.environ.copy()						)
			if result.returncode == 0:
						print("Test is a success! You are ready for your distributed training!"						)

def 	__UpperCAmelCase       ( )->    int:



			"""simple docstring"""



			snake_case_				:					Dict   =       test_command_parser()
			snake_case_				:					Dict   =       parser.parse_args()
			test_command(__magic_name__						)


if __name__ == "__main__":
		main()




