


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


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

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

UpperCAmelCase__   	=							25_0004
UpperCAmelCase__   	=							25_0020







@require_sentencepiece
@require_tokenizers
class       lowerCamelCase__   (       lowerCAmelCase   ,							unittest.TestCase):
     SCREAMING_SNAKE_CASE__      			=			MBartaaTokenizer
     SCREAMING_SNAKE_CASE__      			=			MBartaaTokenizerFast
     SCREAMING_SNAKE_CASE__      			=			True
     SCREAMING_SNAKE_CASE__      			=			True





     def      __A					(self       )     ->   Optional[Any]:
      super().setUp()

      # We have a SentencePiece fixture for testing
      _lowercase							      =MBartaaTokenizer(UpperCAmelCase		,     src_lang='''en_XX'''		,     tgt_lang='''ro_RO'''		,     keep_accents=UpperCAmelCase       )
      tokenizer.save_pretrained(self.tmpdirname       )





     def      __A					(self       )     ->   str:
      _lowercase							      ='''<s>'''
      _lowercase							      =0

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





     def      __A					(self       )     ->   int:
      _lowercase							      =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(UpperCAmelCase       )		,     1_0_5_4       )





     def      __A					(self       )     ->   Union[str, Any]:
      self.assertEqual(self.get_tokenizer().vocab_size		,     1_0_5_4       )





     def      __A					(self       )     ->   Any:
      _lowercase							      =MBartaaTokenizer(UpperCAmelCase		,     src_lang='''en_XX'''		,     tgt_lang='''ro_RO'''		,     keep_accents=UpperCAmelCase       )

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

      _lowercase							      =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''', '''.''']		,     )
      _lowercase							      =tokenizer.convert_tokens_to_ids(UpperCAmelCase       )
      self.assertListEqual(
          UpperCAmelCase		,     [
              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]
          ]		,     )

      _lowercase							      =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>''', '''.''']		,     )





     @slow
     def      __A					(self       )     ->   int:
      # fmt: off
      _lowercase							      ={'''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=UpperCAmelCase		,     model_name='''facebook/mbart-large-50'''		,     revision='''d3913889c59cd5c9e456b269c376325eabad57e2'''		,     )





     def      __A					(self       )     ->   Dict:
      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

      _lowercase							      =(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})"       ):
        _lowercase							      =self.rust_tokenizer_class.from_pretrained(UpperCAmelCase		,     **UpperCAmelCase       )
        _lowercase							      =self.tokenizer_class.from_pretrained(UpperCAmelCase		,     **UpperCAmelCase       )

        _lowercase							      =tempfile.mkdtemp()

        _lowercase							      =tokenizer_r.save_pretrained(UpperCAmelCase       )
        _lowercase							      =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       )       )
        _lowercase							      =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
        _lowercase							      =tokenizer_r.from_pretrained(UpperCAmelCase       )
        _lowercase							      =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
        _lowercase							      =tempfile.mkdtemp()

        _lowercase							      =tokenizer_r.save_pretrained(UpperCAmelCase		,     legacy_format=UpperCAmelCase       )
        _lowercase							      =tokenizer_p.save_pretrained(UpperCAmelCase       )

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

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

        _lowercase							      =tokenizer_r.save_pretrained(UpperCAmelCase		,     legacy_format=UpperCAmelCase       )
        _lowercase							      =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
        _lowercase							      =tokenizer_r.from_pretrained(UpperCAmelCase       )
        _lowercase							      =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):
     SCREAMING_SNAKE_CASE__      			=			'''facebook/mbart-large-50-one-to-many-mmt'''
     SCREAMING_SNAKE_CASE__      			=			[
         ''' 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.''',
     ]
     SCREAMING_SNAKE_CASE__      			=			[
         '''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.''',
     ]
     SCREAMING_SNAKE_CASE__      			=			[EN_CODE, 8274, 127873, 25916, 7, 8622, 2071, 438, 67485, 53, 187895, 23, 51712, 2]





     @classmethod
     def      __A					(cls       )     ->   List[Any]:
      _lowercase							      =MBartaaTokenizer.from_pretrained(
          cls.checkpoint_name		,     src_lang='''en_XX'''		,     tgt_lang='''ro_RO'''       )
      _lowercase							      =1
      return cls





     def      __A					(self       )     ->   Union[str, Any]:
      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      __A					(self       )     ->   Tuple:
      _lowercase							      =self.tokenizer.batch_encode_plus(self.src_text       ).input_ids[0]
      self.assertListEqual(self.expected_src_tokens		,     UpperCAmelCase       )





     def      __A					(self       )     ->   Optional[int]:
      self.assertIn(UpperCAmelCase		,     self.tokenizer.all_special_ids       )
      _lowercase							      =[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]
      _lowercase							      =self.tokenizer.decode(UpperCAmelCase		,     skip_special_tokens=UpperCAmelCase       )
      _lowercase							      =self.tokenizer.decode(generated_ids[1:]		,     skip_special_tokens=UpperCAmelCase       )
      self.assertEqual(UpperCAmelCase		,     UpperCAmelCase       )
      self.assertNotIn(self.tokenizer.eos_token		,     UpperCAmelCase       )





     def      __A					(self       )     ->   Any:
      _lowercase							      =['''this is gunna be a long sentence ''' * 2_0]
      assert isinstance(src_text[0]		,     UpperCAmelCase       )
      _lowercase							      =1_0
      _lowercase							      =self.tokenizer(UpperCAmelCase		,     max_length=UpperCAmelCase		,     truncation=UpperCAmelCase       ).input_ids[0]
      self.assertEqual(ids[0]		,     UpperCAmelCase       )
      self.assertEqual(ids[-1]		,     2       )
      self.assertEqual(len(UpperCAmelCase       )		,     UpperCAmelCase       )





     def      __A					(self       )     ->   str:
      self.assertListEqual(self.tokenizer.convert_tokens_to_ids(['''<mask>''', '''ar_AR''']       )		,     [2_5_0_0_5_3, 2_5_0_0_0_1]       )





     def      __A					(self       )     ->   Dict:
      _lowercase							      =tempfile.mkdtemp()
      _lowercase							      =self.tokenizer.fairseq_tokens_to_ids
      self.tokenizer.save_pretrained(UpperCAmelCase       )
      _lowercase							      =MBartaaTokenizer.from_pretrained(UpperCAmelCase       )
      self.assertDictEqual(new_tok.fairseq_tokens_to_ids		,     UpperCAmelCase       )





     @require_torch
     def      __A					(self       )     ->   int:
      _lowercase							      =self.tokenizer(self.src_text		,     text_target=self.tgt_text		,     padding=UpperCAmelCase		,     return_tensors='''pt'''       )
      _lowercase							      =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      __A					(self       )     ->   List[Any]:
      _lowercase							      =self.tokenizer(
          self.src_text		,     text_target=self.tgt_text		,     padding=UpperCAmelCase		,     truncation=UpperCAmelCase		,     max_length=len(self.expected_src_tokens       )		,     return_tensors='''pt'''		,     )
      _lowercase							      =shift_tokens_right(batch['''labels''']		,     self.tokenizer.pad_token_id       )

      self.assertIsInstance(UpperCAmelCase		,     UpperCAmelCase       )

      self.assertEqual((2, 1_4)		,     batch.input_ids.shape       )
      self.assertEqual((2, 1_4)		,     batch.attention_mask.shape       )
      _lowercase							      =batch.input_ids.tolist()[0]
      self.assertListEqual(self.expected_src_tokens		,     UpperCAmelCase       )
      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      __A					(self       )     ->   List[Any]:
      _lowercase							      =self.tokenizer(self.src_text		,     padding=UpperCAmelCase		,     truncation=UpperCAmelCase		,     max_length=3		,     return_tensors='''pt'''       )
      _lowercase							      =self.tokenizer(
          text_target=self.tgt_text		,     padding=UpperCAmelCase		,     truncation=UpperCAmelCase		,     max_length=1_0		,     return_tensors='''pt'''       )
      _lowercase							      =targets['''input_ids''']
      _lowercase							      =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]		,     1_0       )





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

      self.assertEqual(
          nested_simplify(UpperCAmelCase       )		,     {
              # 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,
          }		,     )





# Copyright 2023 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.
from typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


UpperCAmelCase__   	=							{
    '''configuration_efficientnet''': [
        '''EFFICIENTNET_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''EfficientNetConfig''',
        '''EfficientNetOnnxConfig''',
    ]
}

try:
  if not is_vision_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  UpperCAmelCase__   	=							['''EfficientNetImageProcessor''']

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  UpperCAmelCase__   	=							[
      '''EFFICIENTNET_PRETRAINED_MODEL_ARCHIVE_LIST''',
      '''EfficientNetForImageClassification''',
      '''EfficientNetModel''',
      '''EfficientNetPreTrainedModel''',
  ]

if TYPE_CHECKING:
  from .configuration_efficientnet import (
      EFFICIENTNET_PRETRAINED_CONFIG_ARCHIVE_MAP,
      EfficientNetConfig,
      EfficientNetOnnxConfig,
  )

  try:
    if not is_vision_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .image_processing_efficientnet import EfficientNetImageProcessor

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_efficientnet import (
        EFFICIENTNET_PRETRAINED_MODEL_ARCHIVE_LIST,
        EfficientNetForImageClassification,
        EfficientNetModel,
        EfficientNetPreTrainedModel,
    )

else:
  import sys

  UpperCAmelCase__   	=							_LazyModule(__name__, globals()['''__file__'''], _import_structure)

