
"""simple docstring"""





import shutil
import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartaaTokenizer, MBartaaTokenizerFast, is_torch_available
from transformers.testing_utils import (
    get_tests_dir,
    nested_simplify,
    require_sentencepiece,
    require_tokenizers,
    require_torch,
    slow,
)

from ...test_tokenization_common import TokenizerTesterMixin


__magic_name__       =			get_tests_dir("fixtures/test_sentencepiece.model")

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

__magic_name__       =			250004
__magic_name__       =			250020
@require_sentencepiece
@require_tokenizers
class 						SCREAMING_SNAKE_CASE_ (						__a     ,				unittest.TestCase ):




		"""simple docstring"""





		__lowercase							:  int						   =		MBartaaTokenizer
		__lowercase							:  str						   =		MBartaaTokenizerFast
		__lowercase							:  List[str]						   =		True
		__lowercase							:  Union[str, Any]						   =		True




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

				# We have a SentencePiece fixture for testing
				__SCREAMING_SNAKE_CASE            = MBartaaTokenizer(lowerCAmelCase__							,  src_lang="""en_XX"""							,  tgt_lang="""ro_RO"""							,  keep_accents=lowerCAmelCase__)
				tokenizer.save_pretrained(self.tmpdirname)




		def 	snake_case_     (     self):
				__SCREAMING_SNAKE_CASE            = """<s>"""
				__SCREAMING_SNAKE_CASE            = 0

				self.assertEqual(self.get_tokenizer()._convert_token_to_id(lowerCAmelCase__)							,  lowerCAmelCase__)
				self.assertEqual(self.get_tokenizer()._convert_id_to_token(lowerCAmelCase__)							,  lowerCAmelCase__)




		def 	snake_case_     (     self):
				__SCREAMING_SNAKE_CASE            = list(self.get_tokenizer().get_vocab().keys())

				self.assertEqual(vocab_keys[0]							,  """<s>""")
				self.assertEqual(vocab_keys[1]							,  """<pad>""")
				self.assertEqual(vocab_keys[-1]							,  """<mask>""")
				self.assertEqual(len(lowerCAmelCase__)							,  1_0_5_4)




		def 	snake_case_     (     self):
				self.assertEqual(self.get_tokenizer().vocab_size							,  1_0_5_4)




		def 	snake_case_     (     self):
				__SCREAMING_SNAKE_CASE            = MBartaaTokenizer(lowerCAmelCase__							,  src_lang="""en_XX"""							,  tgt_lang="""ro_RO"""							,  keep_accents=lowerCAmelCase__)

				__SCREAMING_SNAKE_CASE            = 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 [2_8_5, 4_6, 1_0, 1_7_0, 3_8_2]]							,  )

				__SCREAMING_SNAKE_CASE            = 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""", """."""]							,  )
				__SCREAMING_SNAKE_CASE            = tokenizer.convert_tokens_to_ids(lowerCAmelCase__)
				self.assertListEqual(
				    lowerCAmelCase__							,  [
				        value + tokenizer.fairseq_offset
				        for value in [8, 2_1, 8_4, 5_5, 2_4, 1_9, 7, 2, 6_0_2, 3_4_7, 3_4_7, 3_4_7, 3, 1_2, 6_6, 4_6, 7_2, 8_0, 6, 2, 4]
				    ]							,  )

				__SCREAMING_SNAKE_CASE            = 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>""", """."""]							,  )




		@slow
		def 	snake_case_     (     self):
				# fmt: off
				__SCREAMING_SNAKE_CASE            = {"""input_ids""": [[2_5_0_0_0_4, 1_1_0_6_2, 8_2_7_7_2, 7, 1_5, 8_2_7_7_2, 5_3_8, 5_1_5_2_9, 2_3_7, 1_7_1_9_8, 1_2_9_0, 2_0_6, 9, 2_1_5_1_7_5, 1_3_1_4, 1_3_6, 1_7_1_9_8, 1_2_9_0, 2_0_6, 9, 5_6_3_5_9, 4_2, 1_2_2_0_0_9, 9, 1_6_4_6_6, 1_6, 8_7_3_4_4, 4_5_3_7, 9, 4_7_1_7, 7_8_3_8_1, 6, 1_5_9_9_5_8, 7, 1_5, 2_4_4_8_0, 6_1_8, 4, 5_2_7, 2_2_6_9_3, 5_4_2_8, 4, 2_7_7_7, 2_4_4_8_0, 9_8_7_4, 4, 4_3_5_2_3, 5_9_4, 4, 8_0_3, 1_8_3_9_2, 3_3_1_8_9, 1_8, 4, 4_3_5_2_3, 2_4_4_4_7, 1_2_3_9_9, 1_0_0, 2_4_9_5_5, 8_3_6_5_8, 9_6_2_6, 1_4_4_0_5_7, 1_5, 8_3_9, 2_2_3_3_5, 1_6, 1_3_6, 2_4_9_5_5, 8_3_6_5_8, 8_3_4_7_9, 1_5, 3_9_1_0_2, 7_2_4, 1_6, 6_7_8, 6_4_5, 2_7_8_9, 1_3_2_8, 4_5_8_9, 4_2, 1_2_2_0_0_9, 1_1_5_7_7_4, 2_3, 8_0_5, 1_3_2_8, 4_6_8_7_6, 7, 1_3_6, 5_3_8_9_4, 1_9_4_0, 4_2_2_2_7, 4_1_1_5_9, 1_7_7_2_1, 8_2_3, 4_2_5, 4, 2_7_5_1_2, 9_8_7_2_2, 2_0_6, 1_3_6, 5_5_3_1, 4_9_7_0, 9_1_9, 1_7_3_3_6, 5, 2], [2_5_0_0_0_4, 2_0_0_8_0, 6_1_8, 8_3, 8_2_7_7_5, 4_7, 4_7_9, 9, 1_5_1_7, 7_3, 5_3_8_9_4, 3_3_3, 8_0_5_8_1, 1_1_0_1_1_7, 1_8_8_1_1, 5_2_5_6, 1_2_9_5, 5_1, 1_5_2_5_2_6, 2_9_7, 7_9_8_6, 3_9_0, 1_2_4_4_1_6, 5_3_8, 3_5_4_3_1, 2_1_4, 9_8, 1_5_0_4_4, 2_5_7_3_7, 1_3_6, 7_1_0_8, 4_3_7_0_1, 2_3, 7_5_6, 1_3_5_3_5_5, 7, 5, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [2_5_0_0_0_4, 5_8_1, 6_3_7_7_3, 1_1_9_4_5_5, 6, 1_4_7_7_9_7, 8_8_2_0_3, 7, 6_4_5, 7_0, 2_1, 3_2_8_5, 1_0_2_6_9, 5, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]], """attention_mask""": [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
				# fmt: on

				self.tokenizer_integration_test_util(
				    expected_encoding=lowerCAmelCase__							,  model_name="""facebook/mbart-large-50"""							,  revision="""d3913889c59cd5c9e456b269c376325eabad57e2"""							,  )




		def 	snake_case_     (     self):
				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-mbart50""", {})
				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__)
								__SCREAMING_SNAKE_CASE            = self.tokenizer_class.from_pretrained(lowerCAmelCase__							,  **lowerCAmelCase__)

								__SCREAMING_SNAKE_CASE            = tempfile.mkdtemp()

								__SCREAMING_SNAKE_CASE            = tokenizer_r.save_pretrained(lowerCAmelCase__)
								__SCREAMING_SNAKE_CASE            = 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))
								__SCREAMING_SNAKE_CASE            = 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
								__SCREAMING_SNAKE_CASE            = tokenizer_r.from_pretrained(lowerCAmelCase__)
								__SCREAMING_SNAKE_CASE            = 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
								__SCREAMING_SNAKE_CASE            = tempfile.mkdtemp()

								__SCREAMING_SNAKE_CASE            = tokenizer_r.save_pretrained(lowerCAmelCase__							,  legacy_format=lowerCAmelCase__)
								__SCREAMING_SNAKE_CASE            = tokenizer_p.save_pretrained(lowerCAmelCase__)

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

								# Checks everything loads correctly in the same way
								__SCREAMING_SNAKE_CASE            = tokenizer_r.from_pretrained(lowerCAmelCase__)
								__SCREAMING_SNAKE_CASE            = 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
								__SCREAMING_SNAKE_CASE            = tempfile.mkdtemp()

								__SCREAMING_SNAKE_CASE            = tokenizer_r.save_pretrained(lowerCAmelCase__							,  legacy_format=lowerCAmelCase__)
								__SCREAMING_SNAKE_CASE            = 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
								__SCREAMING_SNAKE_CASE            = tokenizer_r.from_pretrained(lowerCAmelCase__)
								__SCREAMING_SNAKE_CASE            = 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 						SCREAMING_SNAKE_CASE_ (						unittest.TestCase ):




		"""simple docstring"""





		__lowercase							:  str						   =		'''facebook/mbart-large-50-one-to-many-mmt'''
		__lowercase							:  Any						   =		[
		    ''' 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.''',
		]
		__lowercase							:  Union[str, Any]						   =		[
		    '''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.''',
		]
		__lowercase							:  int						   =		[EN_CODE, 8274, 127873, 25916, 7, 8622, 2071, 438, 67485, 53, 187895, 23, 51712, 2]




		@classmethod
		def 	snake_case_     (     cls):
				__SCREAMING_SNAKE_CASE            = MBartaaTokenizer.from_pretrained(
				    cls.checkpoint_name							,  src_lang="""en_XX"""							,  tgt_lang="""ro_RO""")
				__SCREAMING_SNAKE_CASE            = 1
				return cls




		def 	snake_case_     (     self):
				self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["""ar_AR"""]							,  2_5_0_0_0_1)
				self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["""en_EN"""]							,  2_5_0_0_0_4)
				self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["""ro_RO"""]							,  2_5_0_0_2_0)
				self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["""mr_IN"""]							,  2_5_0_0_3_8)




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




		def 	snake_case_     (     self):
				self.assertIn(lowerCAmelCase__							,  self.tokenizer.all_special_ids)
				__SCREAMING_SNAKE_CASE            = [RO_CODE, 8_8_4, 9_0_1_9, 9_6, 9, 9_1_6, 8_6_7_9_2, 3_6, 1_8_7_4_3, 1_5_5_9_6, 5, 2]
				__SCREAMING_SNAKE_CASE            = self.tokenizer.decode(lowerCAmelCase__							,  skip_special_tokens=lowerCAmelCase__)
				__SCREAMING_SNAKE_CASE            = self.tokenizer.decode(generated_ids[1:]							,  skip_special_tokens=lowerCAmelCase__)
				self.assertEqual(lowerCAmelCase__							,  lowerCAmelCase__)
				self.assertNotIn(self.tokenizer.eos_token							,  lowerCAmelCase__)




		def 	snake_case_     (     self):
				__SCREAMING_SNAKE_CASE            = ["""this is gunna be a long sentence """ * 2_0]
				assert isinstance(src_text[0]							,  lowerCAmelCase__)
				__SCREAMING_SNAKE_CASE            = 1_0
				__SCREAMING_SNAKE_CASE            = self.tokenizer(lowerCAmelCase__							,  max_length=lowerCAmelCase__							,  truncation=lowerCAmelCase__).input_ids[0]
				self.assertEqual(ids[0]							,  lowerCAmelCase__)
				self.assertEqual(ids[-1]							,  2)
				self.assertEqual(len(lowerCAmelCase__)							,  lowerCAmelCase__)




		def 	snake_case_     (     self):
				self.assertListEqual(self.tokenizer.convert_tokens_to_ids(["""<mask>""", """ar_AR"""])							,  [2_5_0_0_5_3, 2_5_0_0_0_1])




		def 	snake_case_     (     self):
				__SCREAMING_SNAKE_CASE            = tempfile.mkdtemp()
				__SCREAMING_SNAKE_CASE            = self.tokenizer.fairseq_tokens_to_ids
				self.tokenizer.save_pretrained(lowerCAmelCase__)
				__SCREAMING_SNAKE_CASE            = MBartaaTokenizer.from_pretrained(lowerCAmelCase__)
				self.assertDictEqual(new_tok.fairseq_tokens_to_ids							,  lowerCAmelCase__)




		@require_torch
		def 	snake_case_     (     self):
				__SCREAMING_SNAKE_CASE            = self.tokenizer(self.src_text							,  text_target=self.tgt_text							,  padding=lowerCAmelCase__							,  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][0] == EN_CODE
				assert batch.input_ids[1][-1] == 2
				assert batch.labels[1][0] == RO_CODE
				assert batch.labels[1][-1] == 2
				assert batch.decoder_input_ids[1][:2].tolist() == [2, RO_CODE]




		@require_torch
		def 	snake_case_     (     self):
				__SCREAMING_SNAKE_CASE            = self.tokenizer(
				    self.src_text							,  text_target=self.tgt_text							,  padding=lowerCAmelCase__							,  truncation=lowerCAmelCase__							,  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(lowerCAmelCase__							,  lowerCAmelCase__)

				self.assertEqual((2, 1_4)							,  batch.input_ids.shape)
				self.assertEqual((2, 1_4)							,  batch.attention_mask.shape)
				__SCREAMING_SNAKE_CASE            = batch.input_ids.tolist()[0]
				self.assertListEqual(self.expected_src_tokens							,  lowerCAmelCase__)
				self.assertEqual(2							,  batch.decoder_input_ids[0, 0])  # decoder_start_token_id
				# Test that special tokens are reset
				self.assertEqual(self.tokenizer.prefix_tokens							,  [EN_CODE])
				self.assertEqual(self.tokenizer.suffix_tokens							,  [self.tokenizer.eos_token_id])




		def 	snake_case_     (     self):
				__SCREAMING_SNAKE_CASE            = self.tokenizer(self.src_text							,  padding=lowerCAmelCase__							,  truncation=lowerCAmelCase__							,  max_length=3							,  return_tensors="""pt""")
				__SCREAMING_SNAKE_CASE            = self.tokenizer(
				    text_target=self.tgt_text							,  padding=lowerCAmelCase__							,  truncation=lowerCAmelCase__							,  max_length=1_0							,  return_tensors="""pt""")
				__SCREAMING_SNAKE_CASE            = targets["""input_ids"""]
				__SCREAMING_SNAKE_CASE            = 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]							,  1_0)




		@require_torch
		def 	snake_case_     (     self):
				__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(lowerCAmelCase__)							,  {
				        # en_XX, A, test, EOS
				        """input_ids""": [[2_5_0_0_0_4, 6_2, 3_0_3_4, 2]],
				        """attention_mask""": [[1, 1, 1, 1]],
				        # ar_AR
				        """forced_bos_token_id""": 2_5_0_0_0_1,
				    }							,  )






from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_speech_available,
    is_torch_available,
)


__a  			=					{
    'configuration_trocr': ['TROCR_PRETRAINED_CONFIG_ARCHIVE_MAP', 'TrOCRConfig'],
    'processing_trocr': ['TrOCRProcessor'],
}


try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__a  			=					[
						    'TROCR_PRETRAINED_MODEL_ARCHIVE_LIST',
						    'TrOCRForCausalLM',
						    'TrOCRPreTrainedModel',
						]


if TYPE_CHECKING:
						from .configuration_trocr import TROCR_PRETRAINED_CONFIG_ARCHIVE_MAP, TrOCRConfig
						from .processing_trocr import TrOCRProcessor

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_trocr import TROCR_PRETRAINED_MODEL_ARCHIVE_LIST, TrOCRForCausalLM, TrOCRPreTrainedModel

else:
						import sys

						__a  			=					_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)




