


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

import transformers
from transformers import (
    CONFIG_MAPPING,
    IMAGE_PROCESSOR_MAPPING,
    AutoConfig,
    AutoImageProcessor,
    CLIPConfig,
    CLIPImageProcessor,
)
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER


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

from test_module.custom_configuration import CustomConfig  # noqa E402
from test_module.custom_image_processing import CustomImageProcessor  # noqa E402

class   A__ (   unittest.TestCase     ):







    """simple docstring"""

    def 		a_      (	self      ):
         snake_case					=    0
    def 		a_      (	self      ):
         snake_case					=    AutoImageProcessor.from_pretrained('''openai/clip-vit-base-patch32'''      )
         self.assertIsInstance(lowerCamelCase_      , lowerCamelCase_      )
    def 		a_      (	self      ):

         with tempfile.TemporaryDirectory() as tmpdirname:
              snake_case					=    Path(lowerCamelCase_      ) / '''preprocessor_config.json'''
              snake_case					=    Path(lowerCamelCase_      ) / '''config.json'''
              json.dump(
                  {'''image_processor_type''': '''CLIPImageProcessor''', '''processor_class''': '''CLIPProcessor'''}      , open(lowerCamelCase_      , '''w'''      )      , )
              json.dump({'''model_type''': '''clip'''}      , open(lowerCamelCase_      , '''w'''      )      )

              snake_case					=    AutoImageProcessor.from_pretrained(lowerCamelCase_      )
              self.assertIsInstance(lowerCamelCase_      , lowerCamelCase_      )
    def 		a_      (	self      ):

         with tempfile.TemporaryDirectory() as tmpdirname:
              snake_case					=    Path(lowerCamelCase_      ) / '''preprocessor_config.json'''
              snake_case					=    Path(lowerCamelCase_      ) / '''config.json'''
              json.dump(
                  {'''feature_extractor_type''': '''CLIPFeatureExtractor''', '''processor_class''': '''CLIPProcessor'''}      , open(lowerCamelCase_      , '''w'''      )      , )
              json.dump({'''model_type''': '''clip'''}      , open(lowerCamelCase_      , '''w'''      )      )

              snake_case					=    AutoImageProcessor.from_pretrained(lowerCamelCase_      )
              self.assertIsInstance(lowerCamelCase_      , lowerCamelCase_      )
    def 		a_      (	self      ):

         with tempfile.TemporaryDirectory() as tmpdirname:
              snake_case					=    CLIPConfig()

              # Create a dummy config file with image_proceesor_type
              snake_case					=    Path(lowerCamelCase_      ) / '''preprocessor_config.json'''
              snake_case					=    Path(lowerCamelCase_      ) / '''config.json'''
              json.dump(
                  {'''image_processor_type''': '''CLIPImageProcessor''', '''processor_class''': '''CLIPProcessor'''}      , open(lowerCamelCase_      , '''w'''      )      , )
              json.dump({'''model_type''': '''clip'''}      , open(lowerCamelCase_      , '''w'''      )      )

              # remove image_processor_type to make sure config.json alone is enough to load image processor locally
              snake_case					=    AutoImageProcessor.from_pretrained(lowerCamelCase_      ).to_dict()

              config_dict.pop('''image_processor_type'''      )
              snake_case					=    CLIPImageProcessor(**lowerCamelCase_      )

              # save in new folder
              model_config.save_pretrained(lowerCamelCase_      )
              config.save_pretrained(lowerCamelCase_      )

              snake_case					=    AutoImageProcessor.from_pretrained(lowerCamelCase_      )

              # make sure private variable is not incorrectly saved
              snake_case					=    json.loads(config.to_json_string()      )
              self.assertTrue('''_processor_class''' not in dict_as_saved      )

         self.assertIsInstance(lowerCamelCase_      , lowerCamelCase_      )
    def 		a_      (	self      ):

         with tempfile.TemporaryDirectory() as tmpdirname:
              snake_case					=    Path(lowerCamelCase_      ) / '''preprocessor_config.json'''
              json.dump(
                  {'''image_processor_type''': '''CLIPImageProcessor''', '''processor_class''': '''CLIPProcessor'''}      , open(lowerCamelCase_      , '''w'''      )      , )

              snake_case					=    AutoImageProcessor.from_pretrained(lowerCamelCase_      )
              self.assertIsInstance(lowerCamelCase_      , lowerCamelCase_      )
    def 		a_      (	self      ):

         with self.assertRaisesRegex(
             lowerCamelCase_      , '''clip-base is not a local folder and is not a valid model identifier'''      ):
              snake_case					=    AutoImageProcessor.from_pretrained('''clip-base'''      )
    def 		a_      (	self      ):

         with self.assertRaisesRegex(
             lowerCamelCase_      , R'''aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)'''      ):
              snake_case					=    AutoImageProcessor.from_pretrained(lowerCamelCase_      , revision='''aaaaaa'''      )
    def 		a_      (	self      ):

         with self.assertRaisesRegex(
             lowerCamelCase_      , '''hf-internal-testing/config-no-model does not appear to have a file named preprocessor_config.json.'''      , ):
              snake_case					=    AutoImageProcessor.from_pretrained('''hf-internal-testing/config-no-model'''      )
    def 		a_      (	self      ):

         with self.assertRaises(lowerCamelCase_      ):
              snake_case					=    AutoImageProcessor.from_pretrained('''hf-internal-testing/test_dynamic_image_processor'''      )
         # If remote code is disabled, we can't load this config.
         with self.assertRaises(lowerCamelCase_      ):
              snake_case					=    AutoImageProcessor.from_pretrained(
                  '''hf-internal-testing/test_dynamic_image_processor'''      , trust_remote_code=lowerCamelCase_      )

         snake_case					=    AutoImageProcessor.from_pretrained(
             '''hf-internal-testing/test_dynamic_image_processor'''      , trust_remote_code=lowerCamelCase_      )
         self.assertEqual(image_processor.__class__.__name__      , '''NewImageProcessor'''      )

         # Test image processor can be reloaded.
         with tempfile.TemporaryDirectory() as tmp_dir:
              image_processor.save_pretrained(lowerCamelCase_      )
              snake_case					=    AutoImageProcessor.from_pretrained(lowerCamelCase_      , trust_remote_code=lowerCamelCase_      )
         self.assertEqual(reloaded_image_processor.__class__.__name__      , '''NewImageProcessor'''      )
    def 		a_      (	self      ):

         try:
              AutoConfig.register('''custom'''      , lowerCamelCase_      )
              AutoImageProcessor.register(lowerCamelCase_      , lowerCamelCase_      )
              # Trying to register something existing in the Transformers library will raise an error
              with self.assertRaises(lowerCamelCase_      ):
                   AutoImageProcessor.register(lowerCamelCase_      , lowerCamelCase_      )

              with tempfile.TemporaryDirectory() as tmpdirname:
                   snake_case					=    Path(lowerCamelCase_      ) / '''preprocessor_config.json'''
                   snake_case					=    Path(lowerCamelCase_      ) / '''config.json'''
                   json.dump(
                       {'''feature_extractor_type''': '''CLIPFeatureExtractor''', '''processor_class''': '''CLIPProcessor'''}      , open(lowerCamelCase_      , '''w'''      )      , )
                   json.dump({'''model_type''': '''clip'''}      , open(lowerCamelCase_      , '''w'''      )      )

                   snake_case					=    CustomImageProcessor.from_pretrained(lowerCamelCase_      )

              # Now that the config is registered, it can be used as any other config with the auto-API
              with tempfile.TemporaryDirectory() as tmp_dir:
                   image_processor.save_pretrained(lowerCamelCase_      )
                   snake_case					=    AutoImageProcessor.from_pretrained(lowerCamelCase_      )
                   self.assertIsInstance(lowerCamelCase_      , lowerCamelCase_      )

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




    def 		a_      (	self      ):

         class   A__ (   snake_case__     ):







             """simple docstring"""

             __magic_name__        =		True

         try:
              AutoConfig.register('''custom'''      , lowerCamelCase_      )
              AutoImageProcessor.register(lowerCamelCase_      , lowerCamelCase_      )
              # If remote code is not set, the default is to use local
              snake_case					=    AutoImageProcessor.from_pretrained('''hf-internal-testing/test_dynamic_image_processor'''      )
              self.assertEqual(image_processor.__class__.__name__      , '''NewImageProcessor'''      )
              self.assertTrue(image_processor.is_local      )

              # If remote code is disabled, we load the local one.
              snake_case					=    AutoImageProcessor.from_pretrained(
                  '''hf-internal-testing/test_dynamic_image_processor'''      , trust_remote_code=lowerCamelCase_      )
              self.assertEqual(image_processor.__class__.__name__      , '''NewImageProcessor'''      )
              self.assertTrue(image_processor.is_local      )

              # If remote is enabled, we load from the Hub
              snake_case					=    AutoImageProcessor.from_pretrained(
                  '''hf-internal-testing/test_dynamic_image_processor'''      , trust_remote_code=lowerCamelCase_      )
              self.assertEqual(image_processor.__class__.__name__      , '''NewImageProcessor'''      )
              self.assertTrue(not hasattr(lowerCamelCase_      , '''is_local'''      )      )

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








from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_SCREAMING_SNAKE_CASE      :			int      				=   {
    "configuration_timesformer": ["TIMESFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", "TimesformerConfig"],
}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 _SCREAMING_SNAKE_CASE      :			Dict      				=   [
     "TIMESFORMER_PRETRAINED_MODEL_ARCHIVE_LIST",
     "TimesformerModel",
     "TimesformerForVideoClassification",
     "TimesformerPreTrainedModel",
 ]

if TYPE_CHECKING:
 from .configuration_timesformer import TIMESFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, TimesformerConfig

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_timesformer import (
      TIMESFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
      TimesformerForVideoClassification,
      TimesformerModel,
      TimesformerPreTrainedModel,
  )

else:
 import sys

 _SCREAMING_SNAKE_CASE      :			int      				=   _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)




