




import json
import os
import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils import FEATURE_EXTRACTOR_NAME, is_vision_available


if is_vision_available():
   from PIL import Image

   from transformers import ChineseCLIPImageProcessor, ChineseCLIPProcessor





@require_vision
class 	lowerCamelCase_							(				unittest.TestCase ):


 '''simple docstring'''







 def 				lowerCAmelCase_  (							self  :		Union[str, Any]						):
       SCREAMING_SNAKE_CASE_     						=      tempfile.mkdtemp()

       SCREAMING_SNAKE_CASE_     						=      [
           '[UNK]',
           '[CLS]',
           '[SEP]',
           '[PAD]',
           '[MASK]',
           '的',
           '价',
           '格',
           '是',
           '15',
           '便',
           'alex',
           '##andra',
           '，',
           '。',
           '-',
           't',
           'shirt',
       ]
       SCREAMING_SNAKE_CASE_     						=      os.path.join(self.tmpdirname    ,    VOCAB_FILES_NAMES['vocab_file']						)
       with open(self.vocab_file    ,    'w'    ,    encoding='utf-8'						) as vocab_writer:
             vocab_writer.write(''.join([x + '\n' for x in vocab_tokens]						)						)

       SCREAMING_SNAKE_CASE_     						=      {
           'do_resize': True,
           'size': {'height': 224, 'width': 224},
           'do_center_crop': True,
           'crop_size': {'height': 18, 'width': 18},
           'do_normalize': True,
           'image_mean': [0.4814_5466, 0.457_8275, 0.4082_1073],
           'image_std': [0.2686_2954, 0.2613_0258, 0.2757_7711],
           'do_convert_rgb': True,
       }
       SCREAMING_SNAKE_CASE_     						=      os.path.join(self.tmpdirname    ,    _lowerCAmelCase						)
       with open(self.image_processor_file    ,    'w'    ,    encoding='utf-8'						) as fp:
             json.dump(_lowerCAmelCase    ,    _lowerCAmelCase						)



 def 				lowerCAmelCase_  (							self  :		Optional[Any]    ,    **_lowerCAmelCase  :		str						):
       return BertTokenizer.from_pretrained(self.tmpdirname    ,    **_lowerCAmelCase						)



 def 				lowerCAmelCase_  (							self  :		Dict    ,    **_lowerCAmelCase  :		Optional[int]						):
       return BertTokenizerFast.from_pretrained(self.tmpdirname    ,    **_lowerCAmelCase						)



 def 				lowerCAmelCase_  (							self  :		Optional[int]    ,    **_lowerCAmelCase  :		List[Any]						):
       return ChineseCLIPImageProcessor.from_pretrained(self.tmpdirname    ,    **_lowerCAmelCase						)



 def 				lowerCAmelCase_  (							self  :		Optional[Any]						):
       shutil.rmtree(self.tmpdirname						)



 def 				lowerCAmelCase_  (							self  :		str						):
       SCREAMING_SNAKE_CASE_     						=      [np.random.randint(255    ,    size=(3, 30, 400)    ,    dtype=np.uinta						)]

       SCREAMING_SNAKE_CASE_     						=      [Image.fromarray(np.moveaxis(_lowerCAmelCase    ,    0    ,    -1						)						) for x in image_inputs]

       return image_inputs



 def 				lowerCAmelCase_  (							self  :		Any						):
       SCREAMING_SNAKE_CASE_     						=      self.get_tokenizer()
       SCREAMING_SNAKE_CASE_     						=      self.get_rust_tokenizer()
       SCREAMING_SNAKE_CASE_     						=      self.get_image_processor()

       SCREAMING_SNAKE_CASE_     						=      ChineseCLIPProcessor(tokenizer=_lowerCAmelCase    ,    image_processor=_lowerCAmelCase						)
       processor_slow.save_pretrained(self.tmpdirname						)
       SCREAMING_SNAKE_CASE_     						=      ChineseCLIPProcessor.from_pretrained(self.tmpdirname    ,    use_fast=_lowerCAmelCase						)

       SCREAMING_SNAKE_CASE_     						=      ChineseCLIPProcessor(tokenizer=_lowerCAmelCase    ,    image_processor=_lowerCAmelCase						)
       processor_fast.save_pretrained(self.tmpdirname						)
       SCREAMING_SNAKE_CASE_     						=      ChineseCLIPProcessor.from_pretrained(self.tmpdirname						)

       self.assertEqual(processor_slow.tokenizer.get_vocab()    ,    tokenizer_slow.get_vocab()						)
       self.assertEqual(processor_fast.tokenizer.get_vocab()    ,    tokenizer_fast.get_vocab()						)
       self.assertEqual(tokenizer_slow.get_vocab()    ,    tokenizer_fast.get_vocab()						)
       self.assertIsInstance(processor_slow.tokenizer    ,    _lowerCAmelCase						)
       self.assertIsInstance(processor_fast.tokenizer    ,    _lowerCAmelCase						)

       self.assertEqual(processor_slow.image_processor.to_json_string()    ,    image_processor.to_json_string()						)
       self.assertEqual(processor_fast.image_processor.to_json_string()    ,    image_processor.to_json_string()						)
       self.assertIsInstance(processor_slow.image_processor    ,    _lowerCAmelCase						)
       self.assertIsInstance(processor_fast.image_processor    ,    _lowerCAmelCase						)



 def 				lowerCAmelCase_  (							self  :		Optional[int]						):
       SCREAMING_SNAKE_CASE_     						=      ChineseCLIPProcessor(tokenizer=self.get_tokenizer()    ,    image_processor=self.get_image_processor()						)
       processor.save_pretrained(self.tmpdirname						)

       SCREAMING_SNAKE_CASE_     						=      self.get_tokenizer(cls_token='(CLS)'    ,    sep_token='(SEP)'						)
       SCREAMING_SNAKE_CASE_     						=      self.get_image_processor(do_normalize=_lowerCAmelCase						)

       SCREAMING_SNAKE_CASE_     						=      ChineseCLIPProcessor.from_pretrained(
           self.tmpdirname    ,    cls_token='(CLS)'    ,    sep_token='(SEP)'    ,    do_normalize=_lowerCAmelCase						)

       self.assertEqual(processor.tokenizer.get_vocab()    ,    tokenizer_add_kwargs.get_vocab()						)
       self.assertIsInstance(processor.tokenizer    ,    _lowerCAmelCase						)

       self.assertEqual(processor.image_processor.to_json_string()    ,    image_processor_add_kwargs.to_json_string()						)
       self.assertIsInstance(processor.image_processor    ,    _lowerCAmelCase						)



 def 				lowerCAmelCase_  (							self  :		Optional[int]						):
       SCREAMING_SNAKE_CASE_     						=      self.get_image_processor()
       SCREAMING_SNAKE_CASE_     						=      self.get_tokenizer()

       SCREAMING_SNAKE_CASE_     						=      ChineseCLIPProcessor(tokenizer=_lowerCAmelCase    ,    image_processor=_lowerCAmelCase						)

       SCREAMING_SNAKE_CASE_     						=      self.prepare_image_inputs()

       SCREAMING_SNAKE_CASE_     						=      image_processor(_lowerCAmelCase    ,    return_tensors='np'						)
       SCREAMING_SNAKE_CASE_     						=      processor(images=_lowerCAmelCase    ,    return_tensors='np'						)

       for key in input_feat_extract.keys():
             self.assertAlmostEqual(input_feat_extract[key].sum()    ,    input_processor[key].sum()    ,    delta=1E-2						)



 def 				lowerCAmelCase_  (							self  :		Union[str, Any]						):
       SCREAMING_SNAKE_CASE_     						=      self.get_image_processor()
       SCREAMING_SNAKE_CASE_     						=      self.get_tokenizer()

       SCREAMING_SNAKE_CASE_     						=      ChineseCLIPProcessor(tokenizer=_lowerCAmelCase    ,    image_processor=_lowerCAmelCase						)

       SCREAMING_SNAKE_CASE_     						=      'Alexandra，T-shirt的价格是15便士。'

       SCREAMING_SNAKE_CASE_     						=      processor(text=_lowerCAmelCase						)

       SCREAMING_SNAKE_CASE_     						=      tokenizer(_lowerCAmelCase						)

       for key in encoded_tok.keys():
             self.assertListEqual(encoded_tok[key]    ,    encoded_processor[key]						)



 def 				lowerCAmelCase_  (							self  :		Tuple						):
       SCREAMING_SNAKE_CASE_     						=      self.get_image_processor()
       SCREAMING_SNAKE_CASE_     						=      self.get_tokenizer()

       SCREAMING_SNAKE_CASE_     						=      ChineseCLIPProcessor(tokenizer=_lowerCAmelCase    ,    image_processor=_lowerCAmelCase						)

       SCREAMING_SNAKE_CASE_     						=      'Alexandra，T-shirt的价格是15便士。'
       SCREAMING_SNAKE_CASE_     						=      self.prepare_image_inputs()

       SCREAMING_SNAKE_CASE_     						=      processor(text=_lowerCAmelCase    ,    images=_lowerCAmelCase						)

       self.assertListEqual(list(inputs.keys()						)    ,    ['input_ids', 'token_type_ids', 'attention_mask', 'pixel_values']						)

       # test if it raises when no input is passed
       with pytest.raises(_lowerCAmelCase						):
             processor()



 def 				lowerCAmelCase_  (							self  :		Optional[int]						):
       SCREAMING_SNAKE_CASE_     						=      self.get_image_processor()
       SCREAMING_SNAKE_CASE_     						=      self.get_tokenizer()

       SCREAMING_SNAKE_CASE_     						=      ChineseCLIPProcessor(tokenizer=_lowerCAmelCase    ,    image_processor=_lowerCAmelCase						)

       SCREAMING_SNAKE_CASE_     						=      [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

       SCREAMING_SNAKE_CASE_     						=      processor.batch_decode(_lowerCAmelCase						)
       SCREAMING_SNAKE_CASE_     						=      tokenizer.batch_decode(_lowerCAmelCase						)

       self.assertListEqual(_lowerCAmelCase    ,    _lowerCAmelCase						)




 def 				lowerCAmelCase_  (							self  :		str						):
       SCREAMING_SNAKE_CASE_     						=      self.get_image_processor()
       SCREAMING_SNAKE_CASE_     						=      self.get_tokenizer()

       SCREAMING_SNAKE_CASE_     						=      ChineseCLIPProcessor(tokenizer=_lowerCAmelCase    ,    image_processor=_lowerCAmelCase						)

       SCREAMING_SNAKE_CASE_     						=      'Alexandra，T-shirt的价格是15便士。'
       SCREAMING_SNAKE_CASE_     						=      self.prepare_image_inputs()

       SCREAMING_SNAKE_CASE_     						=      processor(text=_lowerCAmelCase    ,    images=_lowerCAmelCase						)

       self.assertListEqual(list(inputs.keys()						)    ,    processor.model_input_names						)





import importlib
import json
import os
import sys
import tempfile
import unittest
from pathlib import Path

import transformers
import transformers.models.auto
from transformers.models.auto.configuration_auto import CONFIG_MAPPING, AutoConfig
from transformers.models.bert.configuration_bert import BertConfig
from transformers.models.roberta.configuration_roberta import RobertaConfig
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, get_tests_dir


sys.path.append(str(Path(__file__).parent.parent.parent.parent / 'utils'))

from test_module.custom_configuration import CustomConfig  # noqa E402


lowerCamelCase__			:       str         =							get_tests_dir('fixtures/dummy-config.json')





class 	lowerCamelCase_							(				unittest.TestCase ):


 '''simple docstring'''







 def 				lowerCAmelCase_  (							self  :		Dict						):
       SCREAMING_SNAKE_CASE_     						=      0



 def 				lowerCAmelCase_  (							self  :		Optional[int]						):
       self.assertIsNotNone(transformers.models.auto.__spec__						)
       self.assertIsNotNone(importlib.util.find_spec('transformers.models.auto'						)						)



 def 				lowerCAmelCase_  (							self  :		Any						):
       SCREAMING_SNAKE_CASE_     						=      AutoConfig.from_pretrained('bert-base-uncased'						)
       self.assertIsInstance(_lowerCAmelCase    ,    _lowerCAmelCase						)



 def 				lowerCAmelCase_  (							self  :		Union[str, Any]						):
       SCREAMING_SNAKE_CASE_     						=      AutoConfig.from_pretrained(_lowerCAmelCase						)
       self.assertIsInstance(_lowerCAmelCase    ,    _lowerCAmelCase						)



 def 				lowerCAmelCase_  (							self  :		Optional[Any]						):
       SCREAMING_SNAKE_CASE_     						=      AutoConfig.from_pretrained(_lowerCAmelCase						)
       self.assertIsInstance(_lowerCAmelCase    ,    _lowerCAmelCase						)



 def 				lowerCAmelCase_  (							self  :		Dict						):
       SCREAMING_SNAKE_CASE_     						=      AutoConfig.for_model('roberta'						)
       self.assertIsInstance(_lowerCAmelCase    ,    _lowerCAmelCase						)



 def 				lowerCAmelCase_  (							self  :		Dict						):
       with tempfile.TemporaryDirectory() as tmp_dir:
             # This model name contains bert and roberta, but roberta ends up being picked.
             SCREAMING_SNAKE_CASE_     						=      os.path.join(_lowerCAmelCase    ,    'fake-roberta'						)
             os.makedirs(_lowerCAmelCase    ,    exist_ok=_lowerCAmelCase						)
             with open(os.path.join(_lowerCAmelCase    ,    'config.json'						)    ,    'w'						) as f:
                   f.write(json.dumps({}						)						)
             SCREAMING_SNAKE_CASE_     						=      AutoConfig.from_pretrained(_lowerCAmelCase						)
             self.assertEqual(type(_lowerCAmelCase						)    ,    _lowerCAmelCase						)



 def 				lowerCAmelCase_  (							self  :		Optional[Any]						):
       try:
             AutoConfig.register('custom'    ,    _lowerCAmelCase						)
             # Wrong model type will raise an error
             with self.assertRaises(_lowerCAmelCase						):
                   AutoConfig.register('model'    ,    _lowerCAmelCase						)
             # Trying to register something existing in the Transformers library will raise an error
             with self.assertRaises(_lowerCAmelCase						):
                   AutoConfig.register('bert'    ,    _lowerCAmelCase						)

             # Now that the config is registered, it can be used as any other config with the auto-API
             SCREAMING_SNAKE_CASE_     						=      CustomConfig()
             with tempfile.TemporaryDirectory() as tmp_dir:
                   config.save_pretrained(_lowerCAmelCase						)
                   SCREAMING_SNAKE_CASE_     						=      AutoConfig.from_pretrained(_lowerCAmelCase						)
                   self.assertIsInstance(_lowerCAmelCase    ,    _lowerCAmelCase						)

       finally:
             if "custom" in CONFIG_MAPPING._extra_content:
                   del CONFIG_MAPPING._extra_content["custom"]



 def 				lowerCAmelCase_  (							self  :		Optional[int]						):
       with self.assertRaisesRegex(
           _lowerCAmelCase    ,    'bert-base is not a local folder and is not a valid model identifier'						):
             SCREAMING_SNAKE_CASE_     						=      AutoConfig.from_pretrained('bert-base'						)



 def 				lowerCAmelCase_  (							self  :		int						):
       with self.assertRaisesRegex(
           _lowerCAmelCase    ,    R'aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)'						):
             SCREAMING_SNAKE_CASE_     						=      AutoConfig.from_pretrained(_lowerCAmelCase    ,    revision='aaaaaa'						)



 def 				lowerCAmelCase_  (							self  :		Tuple						):
       with self.assertRaisesRegex(
           _lowerCAmelCase    ,    'hf-internal-testing/no-config-test-repo does not appear to have a file named config.json.'    ,    ):
             SCREAMING_SNAKE_CASE_     						=      AutoConfig.from_pretrained('hf-internal-testing/no-config-test-repo'						)



 def 				lowerCAmelCase_  (							self  :		Union[str, Any]						):
       # If remote code is not set, we will time out when asking whether to load the model.
       with self.assertRaises(_lowerCAmelCase						):
             SCREAMING_SNAKE_CASE_     						=      AutoConfig.from_pretrained('hf-internal-testing/test_dynamic_model'						)
       # If remote code is disabled, we can't load this config.
       with self.assertRaises(_lowerCAmelCase						):
             SCREAMING_SNAKE_CASE_     						=      AutoConfig.from_pretrained('hf-internal-testing/test_dynamic_model'    ,    trust_remote_code=_lowerCAmelCase						)

       SCREAMING_SNAKE_CASE_     						=      AutoConfig.from_pretrained('hf-internal-testing/test_dynamic_model'    ,    trust_remote_code=_lowerCAmelCase						)
       self.assertEqual(config.__class__.__name__    ,    'NewModelConfig'						)

       # Test config can be reloaded.
       with tempfile.TemporaryDirectory() as tmp_dir:
             config.save_pretrained(_lowerCAmelCase						)
             SCREAMING_SNAKE_CASE_     						=      AutoConfig.from_pretrained(_lowerCAmelCase    ,    trust_remote_code=_lowerCAmelCase						)
       self.assertEqual(reloaded_config.__class__.__name__    ,    'NewModelConfig'						)




 def 				lowerCAmelCase_  (							self  :		Any						):





       class 	lowerCamelCase_							(				_SCREAMING_SNAKE_CASE ):


        '''simple docstring'''







        lowercase_       =   "new-model"

       try:
             AutoConfig.register('new-model'    ,    _lowerCAmelCase						)
             # If remote code is not set, the default is to use local
             SCREAMING_SNAKE_CASE_     						=      AutoConfig.from_pretrained('hf-internal-testing/test_dynamic_model'						)
             self.assertEqual(config.__class__.__name__    ,    'NewModelConfigLocal'						)

             # If remote code is disabled, we load the local one.
             SCREAMING_SNAKE_CASE_     						=      AutoConfig.from_pretrained('hf-internal-testing/test_dynamic_model'    ,    trust_remote_code=_lowerCAmelCase						)
             self.assertEqual(config.__class__.__name__    ,    'NewModelConfigLocal'						)

             # If remote is enabled, we load from the Hub
             SCREAMING_SNAKE_CASE_     						=      AutoConfig.from_pretrained('hf-internal-testing/test_dynamic_model'    ,    trust_remote_code=_lowerCAmelCase						)
             self.assertEqual(config.__class__.__name__    ,    'NewModelConfig'						)

       finally:
             if "new-model" in CONFIG_MAPPING._extra_content:
                   del CONFIG_MAPPING._extra_content["new-model"]