



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__	      =       25_00_04
A__	      =       25_00_20





@require_sentencepiece
@require_tokenizers
class 					__lowerCAmelCase (     lowerCamelCase__       ,						unittest.TestCase       ):
				__lowerCamelCase =				MBartTokenizer
				__lowerCamelCase =				MBartTokenizerFast
				__lowerCamelCase =				True
				__lowerCamelCase =				True




				def 							snake_case   (							self		):



									"""simple docstring"""





									super().setUp()

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




				def 							snake_case   (							self		):



									"""simple docstring"""





									_lowerCAmelCase						=    MBartTokenizer(_snake_case						,				keep_accents=_snake_case		)

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

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

									_lowerCAmelCase						=    tokenizer.tokenize("""I was born in 92000, and this is falsé."""		)
									self.assertListEqual(
									    _snake_case						,				[
									        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""",
									        """.""",
									    ]						,				)
									_lowerCAmelCase						=    tokenizer.convert_tokens_to_ids(_snake_case		)
									self.assertListEqual(
									    _snake_case						,				[
									        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 ^
									    ]						,				)

									_lowerCAmelCase						=    tokenizer.convert_ids_to_tokens(_snake_case		)
									self.assertListEqual(
									    _snake_case						,				[
									        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 							snake_case   (							self		):



									"""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

									_lowerCAmelCase						=    (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})'		):
																			_lowerCAmelCase						=    self.rust_tokenizer_class.from_pretrained(_snake_case						,				**_snake_case		)
																			_lowerCAmelCase						=    self.tokenizer_class.from_pretrained(_snake_case						,				**_snake_case		)

																			_lowerCAmelCase						=    tempfile.mkdtemp()

																			_lowerCAmelCase						=    tokenizer_r.save_pretrained(_snake_case		)
																			_lowerCAmelCase						=    tokenizer_p.save_pretrained(_snake_case		)

																			# 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		)		)
																			_lowerCAmelCase						=    tuple(f for f in tokenizer_r_files if """tokenizer.json""" not in f		)
																			self.assertSequenceEqual(_snake_case						,				_snake_case		)

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

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

																			shutil.rmtree(_snake_case		)

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

																			_lowerCAmelCase						=    tokenizer_r.save_pretrained(_snake_case						,				legacy_format=_snake_case		)
																			_lowerCAmelCase						=    tokenizer_p.save_pretrained(_snake_case		)

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

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

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

																			shutil.rmtree(_snake_case		)

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

																			_lowerCAmelCase						=    tokenizer_r.save_pretrained(_snake_case						,				legacy_format=_snake_case		)
																			_lowerCAmelCase						=    tokenizer_p.save_pretrained(_snake_case		)

																			# 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
																			_lowerCAmelCase						=    tokenizer_r.from_pretrained(_snake_case		)
																			_lowerCAmelCase						=    tokenizer_p.from_pretrained(_snake_case		)

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

																			shutil.rmtree(_snake_case		)





@require_torch
@require_sentencepiece
@require_tokenizers
class 					__lowerCAmelCase (     unittest.TestCase       ):
				__lowerCamelCase =				'''facebook/mbart-large-en-ro'''
				__lowerCamelCase =				[
				    ''' 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.''',
				]
				__lowerCamelCase =				[
				    '''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.''',
				]
				__lowerCamelCase =				[8_274, 127_873, 25_916, 7, 8_622, 2_071, 438, 67_485, 53, 187_895, 23, 51_712, 2, EN_CODE]




				@classmethod
				def 							snake_case   (							cls		):



									"""simple docstring"""





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




				def 							snake_case   (							self		):



									"""simple docstring"""





									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 							snake_case   (							self		):



									"""simple docstring"""





									_lowerCAmelCase						=    self.tokenizer.batch_encode_plus(self.src_text		).input_ids[0]
									self.assertListEqual(self.expected_src_tokens						,				_snake_case		)




				def 							snake_case   (							self		):



									"""simple docstring"""





									self.assertIn(_snake_case						,				self.tokenizer.all_special_ids		)
									_lowerCAmelCase						=    [RO_CODE, 884, 9019, 96, 9, 916, 86792, 36, 18743, 15596, 5, 2]
									_lowerCAmelCase						=    self.tokenizer.decode(_snake_case						,				skip_special_tokens=_snake_case		)
									_lowerCAmelCase						=    self.tokenizer.decode(generated_ids[1:]						,				skip_special_tokens=_snake_case		)
									self.assertEqual(_snake_case						,				_snake_case		)
									self.assertNotIn(self.tokenizer.eos_token						,				_snake_case		)




				def 							snake_case   (							self		):



									"""simple docstring"""





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




				def 							snake_case   (							self		):



									"""simple docstring"""





									self.assertListEqual(self.tokenizer.convert_tokens_to_ids(["""<mask>""", """ar_AR"""]		)						,				[250026, 250001]		)




				def 							snake_case   (							self		):



									"""simple docstring"""





									_lowerCAmelCase						=    tempfile.mkdtemp()
									_lowerCAmelCase						=    self.tokenizer.fairseq_tokens_to_ids
									self.tokenizer.save_pretrained(_snake_case		)
									_lowerCAmelCase						=    MBartTokenizer.from_pretrained(_snake_case		)
									self.assertDictEqual(new_tok.fairseq_tokens_to_ids						,				_snake_case		)




				@require_torch
				def 							snake_case   (							self		):



									"""simple docstring"""





									_lowerCAmelCase						=    self.tokenizer(self.src_text						,				text_target=self.tgt_text						,				padding=_snake_case						,				return_tensors="""pt"""		)
									_lowerCAmelCase						=    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 							snake_case   (							self		):



									"""simple docstring"""





									_lowerCAmelCase						=    self.tokenizer(
									    self.src_text						,				text_target=self.tgt_text						,				padding=_snake_case						,				truncation=_snake_case						,				max_length=len(self.expected_src_tokens		)						,				return_tensors="""pt"""						,				)

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

									self.assertIsInstance(_snake_case						,				_snake_case		)

									self.assertEqual((2, 14)						,				batch.input_ids.shape		)
									self.assertEqual((2, 14)						,				batch.attention_mask.shape		)
									_lowerCAmelCase						=    batch.input_ids.tolist()[0]
									self.assertListEqual(self.expected_src_tokens						,				_snake_case		)
									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 							snake_case   (							self		):



									"""simple docstring"""





									_lowerCAmelCase						=    self.tokenizer(self.src_text						,				padding=_snake_case						,				truncation=_snake_case						,				max_length=3						,				return_tensors="""pt"""		)
									_lowerCAmelCase						=    self.tokenizer(
									    text_target=self.tgt_text						,				padding=_snake_case						,				truncation=_snake_case						,				max_length=10						,				return_tensors="""pt"""		)
									_lowerCAmelCase						=    targets["""input_ids"""]
									_lowerCAmelCase						=    shift_tokens_right(_snake_case						,				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 							snake_case   (							self		):



									"""simple docstring"""





									_lowerCAmelCase						=    self.tokenizer._build_translation_inputs(
									    """A test"""						,				return_tensors="""pt"""						,				src_lang="""en_XX"""						,				tgt_lang="""ar_AR"""		)

									self.assertEqual(
									    nested_simplify(_snake_case		)						,				{
									        # 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 argparse
import os
import re


# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_dummies.py
_a		       =							'src/diffusers'

# Matches is_xxx_available()
_a		       =							re.compile(R'is\_([a-z_]*)_available\(\)')
# Matches from xxx import bla
_a		       =							re.compile(R'\s+from\s+\S*\s+import\s+([^\(\s].*)\n')


_a		       =							'\n{0} = None\n'

_a		       =							'\nclass {0}(metaclass=DummyObject):\n    _backends = {1}\n\n    def __init__(self, *args, **kwargs):\n        requires_backends(self, {1})\n\n    @classmethod\n    def from_config(cls, *args, **kwargs):\n        requires_backends(cls, {1})\n\n    @classmethod\n    def from_pretrained(cls, *args, **kwargs):\n        requires_backends(cls, {1})\n'


_a		       =							'\ndef {0}(*args, **kwargs):\n    requires_backends({0}, {1})\n'







def 	__a     (		__lowerCamelCase  ):
   UpperCAmelCase_					:					int			     =    _re_backend.findall(__lowerCamelCase  )
   if len(__lowerCamelCase  ) == 0:
      return None

   return "_and_".join(__lowerCamelCase  )







def 	__a     (		):
   with open(os.path.join(__lowerCamelCase,		"__init__.py"  ),		"r",		encoding="utf-8",		newline="\n"  ) as f:
      UpperCAmelCase_					:					Optional[int]			     =    f.readlines()

   # Get to the point we do the actual imports for type checking
   UpperCAmelCase_					:					Union[str, Any]			     =    0
   UpperCAmelCase_					:					Optional[int]			     =    {}
   # Go through the end of the file
   while line_index < len(__lowerCamelCase  ):
      # If the line contains is_backend_available, we grab all objects associated with the `else` block
      UpperCAmelCase_					:					Union[str, Any]			     =    find_backend(lines[line_index]  )
      if backend is not None:
         while not lines[line_index].startswith("else:"  ):
            line_index += 1
         line_index += 1
         UpperCAmelCase_					:					List[str]			     =    []
         # Until we unindent, add backend objects to the list
         while line_index < len(__lowerCamelCase  ) and len(lines[line_index]  ) > 1:
            UpperCAmelCase_					:					Union[str, Any]			     =    lines[line_index]
            UpperCAmelCase_					:					Optional[Any]			     =    _re_single_line_import.search(__lowerCamelCase  )
            if single_line_import_search is not None:
               objects.extend(single_line_import_search.groups()[0].split(", "  )  )
            elif line.startswith(" " * 8  ):
               objects.append(line[8:-2]  )
            line_index += 1

         if len(__lowerCamelCase  ) > 0:
            UpperCAmelCase_					:					Optional[int]			     =    objects
      else:
         line_index += 1

   return backend_specific_objects







def 	__a     (		__lowerCamelCase,		__lowerCamelCase  ):
   if name.isupper():
      return DUMMY_CONSTANT.format(__lowerCamelCase  )
   elif name.islower():
      return DUMMY_FUNCTION.format(__lowerCamelCase,		__lowerCamelCase  )
   else:
      return DUMMY_CLASS.format(__lowerCamelCase,		__lowerCamelCase  )







def 	__a     (		__lowerCamelCase=None  ):
   if backend_specific_objects is None:
      UpperCAmelCase_					:					Tuple			     =    read_init()
   # For special correspondence backend to module name as used in the function requires_modulename
   UpperCAmelCase_					:					str			     =    {}

   for backend, objects in backend_specific_objects.items():
      UpperCAmelCase_					:					int			     =    "[" + ", ".join(f"""\"{b}\"""" for b in backend.split("_and_"  )  ) + "]"
      UpperCAmelCase_					:					Dict			     =    "# This file is autogenerated by the command `make fix-copies`, do not edit.\n"
      dummy_file += "from ..utils import DummyObject, requires_backends\n\n"
      dummy_file += "\n".join([create_dummy_object(__lowerCamelCase,		__lowerCamelCase  ) for o in objects]  )
      UpperCAmelCase_					:					int			     =    dummy_file

   return dummy_files







def 	__a     (		__lowerCamelCase=False  ):
   UpperCAmelCase_					:					Optional[Any]			     =    create_dummy_files()
   # For special correspondence backend to shortcut as used in utils/dummy_xxx_objects.py
   UpperCAmelCase_					:					Union[str, Any]			     =    {"torch": "pt"}

   # Locate actual dummy modules and read their content.
   UpperCAmelCase_					:					List[str]			     =    os.path.join(__lowerCamelCase,		"utils"  )
   UpperCAmelCase_					:					Optional[int]			     =    {
       backend: os.path.join(__lowerCamelCase,		f"""dummy_{short_names.get(__lowerCamelCase,		__lowerCamelCase  )}_objects.py"""  )
       for backend in dummy_files.keys()
   }

   UpperCAmelCase_					:					Any			     =    {}
   for backend, file_path in dummy_file_paths.items():
      if os.path.isfile(__lowerCamelCase  ):
         with open(__lowerCamelCase,		"r",		encoding="utf-8",		newline="\n"  ) as f:
            UpperCAmelCase_					:					Optional[int]			     =    f.read()
      else:
         UpperCAmelCase_					:					Any			     =    ""

   for backend in dummy_files.keys():
      if dummy_files[backend] != actual_dummies[backend]:
         if overwrite:
            print(
                f"""Updating diffusers.utils.dummy_{short_names.get(__lowerCamelCase,		__lowerCamelCase  )}_objects.py as the main """
                "__init__ has new objects."  )
            with open(dummy_file_paths[backend],		"w",		encoding="utf-8",		newline="\n"  ) as f:
               f.write(dummy_files[backend]  )
         else:
            raise ValueError(
                "The main __init__ has objects that are not present in "
                f"""diffusers.utils.dummy_{short_names.get(__lowerCamelCase,		__lowerCamelCase  )}_objects.py. Run `make fix-copies` """
                "to fix this."  )


if __name__ == "__main__":
    _a		       =							argparse.ArgumentParser()
    parser.add_argument('--fix_and_overwrite', action='store_true', help='Whether to fix inconsistencies.')
    _a		       =							parser.parse_args()

    check_dummies(args.fix_and_overwrite)


