




from typing import List, Union

from ..utils import (
    add_end_docstrings,
    is_tf_available,
    is_torch_available,
    is_vision_available,
    logging,
    requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline


if is_vision_available():
   from PIL import Image

   from ..image_utils import load_image

if is_tf_available():
   import tensorflow as tf

   from ..models.auto.modeling_tf_auto import TF_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING
   from ..tf_utils import stable_softmax

if is_torch_available():
   from ..models.auto.modeling_auto import MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING

lowerCamelCase__			:       Dict         =							logging.get_logger(__name__)





@add_end_docstrings(_SCREAMING_SNAKE_CASE )
class 	lowerCamelCase_							(				_SCREAMING_SNAKE_CASE ):


 '''simple docstring'''







 def __init__(							self  :		List[Any]    ,    *_lowerCAmelCase  :		Tuple    ,    **_lowerCAmelCase  :		Any						):
       super().__init__(*_lowerCAmelCase    ,    **_lowerCAmelCase						)
       requires_backends(self    ,    'vision'						)
       self.check_model_type(
           TF_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING
           if self.framework == 'tf'
           else MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING						)



 def 				lowerCAmelCase_  (							self  :		str    ,    _lowerCAmelCase  :		int=None						):
       SCREAMING_SNAKE_CASE_     						=      {}
       if top_k is not None:
             SCREAMING_SNAKE_CASE_     						=      top_k
       return {}, {}, postprocess_params



 def __call__(							self  :		Dict    ,    _lowerCAmelCase  :		Union[str, List[str], "Image.Image", List["Image.Image"]]    ,    **_lowerCAmelCase  :		Optional[Any]						):
       return super().__call__(_lowerCAmelCase    ,    **_lowerCAmelCase						)



 def 				lowerCAmelCase_  (							self  :		Union[str, Any]    ,    _lowerCAmelCase  :		str						):
       SCREAMING_SNAKE_CASE_     						=      load_image(_lowerCAmelCase						)
       SCREAMING_SNAKE_CASE_     						=      self.image_processor(images=_lowerCAmelCase    ,    return_tensors=self.framework						)
       return model_inputs



 def 				lowerCAmelCase_  (							self  :		Optional[int]    ,    _lowerCAmelCase  :		Dict						):
       SCREAMING_SNAKE_CASE_     						=      self.model(**_lowerCAmelCase						)
       return model_outputs




 def 				lowerCAmelCase_  (							self  :		List[str]    ,    _lowerCAmelCase  :		int    ,    _lowerCAmelCase  :		List[Any]=5						):
       if top_k > self.model.config.num_labels:
             SCREAMING_SNAKE_CASE_     						=      self.model.config.num_labels

       if self.framework == "pt":
             SCREAMING_SNAKE_CASE_     						=      model_outputs.logits.softmax(-1						)[0]
             SCREAMING_SNAKE_CASE_						,			SCREAMING_SNAKE_CASE_     						=      probs.topk(_lowerCAmelCase						)
       elif self.framework == "tf":
             SCREAMING_SNAKE_CASE_     						=      stable_softmax(model_outputs.logits    ,    axis=-1						)[0]
             SCREAMING_SNAKE_CASE_     						=      tf.math.top_k(_lowerCAmelCase    ,    k=_lowerCAmelCase						)
             SCREAMING_SNAKE_CASE_						,			SCREAMING_SNAKE_CASE_     						=      topk.values.numpy(), topk.indices.numpy()
       else:
             raise ValueError(F"Unsupported framework: {self.framework}"						)

       SCREAMING_SNAKE_CASE_     						=      scores.tolist()
       SCREAMING_SNAKE_CASE_     						=      ids.tolist()
       return [{"score": score, "label": self.model.config.idalabel[_id]} for score, _id in zip(_lowerCAmelCase    ,    _lowerCAmelCase						)]





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"]