import hashlib
import unittest

from transformers import MODEL_FOR_DEPTH_ESTIMATION_MAPPING, is_torch_available, is_vision_available
from transformers.pipelines import DepthEstimationPipeline, pipeline
from transformers.testing_utils import (
    is_pipeline_test,
    nested_simplify,
    require_tf,
    require_timm,
    require_torch,
    require_vision,
    slow,
)

from .test_pipelines_common import ANY


if is_torch_available():
  import torch

if is_vision_available():
  from PIL import Image
else:




  class 			__magic_name__	:





     """simple docstring"""




     @staticmethod
     def 	lowerCAmelCase    (						*_lowercase       :	List[str]		,	**_lowercase       :	Dict				):



      """simple docstring"""



      pass




def    lowerCAmelCase_  (		lowercase:				Image		)     ->					str:







 '''simple docstring'''
 _UpperCamelCase:  List[Any]    						=			hashlib.mda(image.tobytes()		)
 return m.hexdigest()





@is_pipeline_test
@require_vision
@require_timm
@require_torch
class 			__magic_name__	(		unittest.TestCase     ):





   """simple docstring"""




   lowerCAmelCase   :     str	      = MODEL_FOR_DEPTH_ESTIMATION_MAPPING



   def 	lowerCAmelCase    (						self       :	int		,	_lowercase       :	List[str]		,	_lowercase       :	Optional[int]		,	_lowercase       :	Optional[Any]				):



    """simple docstring"""



    _UpperCamelCase:  List[Any]    						=			DepthEstimationPipeline(model=_lowercase		,	image_processor=_lowercase				)
    return depth_estimator, [
        "./tests/fixtures/tests_samples/COCO/000000039769.png",
        "./tests/fixtures/tests_samples/COCO/000000039769.png",
    ]



   def 	lowerCAmelCase    (						self       :	Any		,	_lowercase       :	Any		,	_lowercase       :	int				):



    """simple docstring"""



    _UpperCamelCase:  List[str]    						=			depth_estimator('''./tests/fixtures/tests_samples/COCO/000000039769.png'''				)
    self.assertEqual({'''predicted_depth''': ANY(torch.Tensor				), '''depth''': ANY(Image.Image				)}		,	_lowercase				)
    import datasets

    _UpperCamelCase:  Optional[int]    						=			datasets.load_dataset('''hf-internal-testing/fixtures_image_utils'''		,	'''image'''		,	split='''test'''				)
    _UpperCamelCase:  List[Any]    						=			depth_estimator(
        [
            Image.open('''./tests/fixtures/tests_samples/COCO/000000039769.png'''				),
            '''http://images.cocodataset.org/val2017/000000039769.jpg''',
            # RGBA
            dataset[0]['''file'''],
            # LA
            dataset[1]['''file'''],
            # L
            dataset[2]['''file'''],
        ]				)
    self.assertEqual(
        [
            {'''predicted_depth''': ANY(torch.Tensor				), '''depth''': ANY(Image.Image				)},
            {'''predicted_depth''': ANY(torch.Tensor				), '''depth''': ANY(Image.Image				)},
            {'''predicted_depth''': ANY(torch.Tensor				), '''depth''': ANY(Image.Image				)},
            {'''predicted_depth''': ANY(torch.Tensor				), '''depth''': ANY(Image.Image				)},
            {'''predicted_depth''': ANY(torch.Tensor				), '''depth''': ANY(Image.Image				)},
        ]		,	_lowercase		,	)



   @require_tf
   @unittest.skip('''Depth estimation is not implemented in TF'''				)
   def 	lowerCAmelCase    (						self       :	str				):



    """simple docstring"""



    pass



   @slow
   @require_torch
   def 	lowerCAmelCase    (						self       :	List[str]				):



    """simple docstring"""



    _UpperCamelCase:  Union[str, Any]    						=			'''Intel/dpt-large'''
    _UpperCamelCase:  Tuple    						=			pipeline('''depth-estimation'''		,	model=_lowercase				)
    _UpperCamelCase:  List[Any]    						=			depth_estimator('''http://images.cocodataset.org/val2017/000000039769.jpg'''				)
    _UpperCamelCase:  List[Any]    						=			hashimage(outputs['''depth''']				)

    # This seems flaky.
    # self.assertEqual(outputs["depth"], "1a39394e282e9f3b0741a90b9f108977")
    self.assertEqual(nested_simplify(outputs['''predicted_depth'''].max().item()				)		,	29.304				)
    self.assertEqual(nested_simplify(outputs['''predicted_depth'''].min().item()				)		,	2.662				)



   @require_torch
   def 	lowerCAmelCase    (						self       :	List[str]				):



    """simple docstring"""



    self.skipTest('''There is not hf-internal-testing tiny model for either GLPN nor DPT'''				)
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


UpperCAmelCase_           =				get_tests_dir('''fixtures/dummy-config.json''')




class 			__magic_name__	(		unittest.TestCase     ):





   """simple docstring"""




   def 	lowerCAmelCase    (						self       :	str				):



    """simple docstring"""



    _UpperCamelCase:  Dict    						=			0



   def 	lowerCAmelCase    (						self       :	Any				):



    """simple docstring"""



    self.assertIsNotNone(transformers.models.auto.__spec__				)
    self.assertIsNotNone(importlib.util.find_spec('''transformers.models.auto'''				)				)



   def 	lowerCAmelCase    (						self       :	Union[str, Any]				):



    """simple docstring"""



    _UpperCamelCase:  List[str]    						=			AutoConfig.from_pretrained('''bert-base-uncased'''				)
    self.assertIsInstance(_lowercase		,	_lowercase				)



   def 	lowerCAmelCase    (						self       :	int				):



    """simple docstring"""



    _UpperCamelCase:  int    						=			AutoConfig.from_pretrained(_lowercase				)
    self.assertIsInstance(_lowercase		,	_lowercase				)



   def 	lowerCAmelCase    (						self       :	List[Any]				):



    """simple docstring"""



    _UpperCamelCase:  List[Any]    						=			AutoConfig.from_pretrained(_lowercase				)
    self.assertIsInstance(_lowercase		,	_lowercase				)



   def 	lowerCAmelCase    (						self       :	Optional[int]				):



    """simple docstring"""



    _UpperCamelCase:  List[str]    						=			AutoConfig.for_model('''roberta'''				)
    self.assertIsInstance(_lowercase		,	_lowercase				)



   def 	lowerCAmelCase    (						self       :	List[str]				):



    """simple docstring"""



    with tempfile.TemporaryDirectory() as tmp_dir:
     # This model name contains bert and roberta, but roberta ends up being picked.
     _UpperCamelCase:  Union[str, Any]    						=			os.path.join(_lowercase		,	'''fake-roberta'''				)
     os.makedirs(_lowercase		,	exist_ok=_lowercase				)
     with open(os.path.join(_lowercase		,	'''config.json'''				)		,	'''w'''				) as f:
      f.write(json.dumps({}				)				)
     _UpperCamelCase:  Union[str, Any]    						=			AutoConfig.from_pretrained(_lowercase				)
     self.assertEqual(type(_lowercase				)		,	_lowercase				)



   def 	lowerCAmelCase    (						self       :	Dict				):



    """simple docstring"""



    try:
     AutoConfig.register('''custom'''		,	_lowercase				)
     # Wrong model type will raise an error
     with self.assertRaises(_lowercase				):
      AutoConfig.register('''model'''		,	_lowercase				)
     # Trying to register something existing in the Transformers library will raise an error
     with self.assertRaises(_lowercase				):
      AutoConfig.register('''bert'''		,	_lowercase				)

     # Now that the config is registered, it can be used as any other config with the auto-API
     _UpperCamelCase:  Union[str, Any]    						=			CustomConfig()
     with tempfile.TemporaryDirectory() as tmp_dir:
      config.save_pretrained(_lowercase				)
      _UpperCamelCase:  Any    						=			AutoConfig.from_pretrained(_lowercase				)
      self.assertIsInstance(_lowercase		,	_lowercase				)

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



   def 	lowerCAmelCase    (						self       :	Optional[int]				):



    """simple docstring"""



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



   def 	lowerCAmelCase    (						self       :	Tuple				):



    """simple docstring"""



    with self.assertRaisesRegex(
        _lowercase		,	R'''aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)'''				):
     _UpperCamelCase:  str    						=			AutoConfig.from_pretrained(_lowercase		,	revision='''aaaaaa'''				)



   def 	lowerCAmelCase    (						self       :	Union[str, Any]				):



    """simple docstring"""



    with self.assertRaisesRegex(
        _lowercase		,	'''hf-internal-testing/no-config-test-repo does not appear to have a file named config.json.'''		,	):
     _UpperCamelCase:  int    						=			AutoConfig.from_pretrained('''hf-internal-testing/no-config-test-repo'''				)



   def 	lowerCAmelCase    (						self       :	Dict				):



    """simple docstring"""



    with self.assertRaises(_lowercase				):
     _UpperCamelCase:  List[str]    						=			AutoConfig.from_pretrained('''hf-internal-testing/test_dynamic_model'''				)
    # If remote code is disabled, we can't load this config.
    with self.assertRaises(_lowercase				):
     _UpperCamelCase:  Optional[int]    						=			AutoConfig.from_pretrained('''hf-internal-testing/test_dynamic_model'''		,	trust_remote_code=_lowercase				)

    _UpperCamelCase:  Union[str, Any]    						=			AutoConfig.from_pretrained('''hf-internal-testing/test_dynamic_model'''		,	trust_remote_code=_lowercase				)
    self.assertEqual(config.__class__.__name__		,	'''NewModelConfig'''				)

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



   def 	lowerCAmelCase    (						self       :	Any				):



    """simple docstring"""



    class 			__magic_name__	(		__a     ):





       """simple docstring"""




       lowerCAmelCase   :     List[Any]	      = '''new-model'''

    try:
     AutoConfig.register('''new-model'''		,	_lowercase				)
     # If remote code is not set, the default is to use local
     _UpperCamelCase:  List[Any]    						=			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.
     _UpperCamelCase:  Union[str, Any]    						=			AutoConfig.from_pretrained('''hf-internal-testing/test_dynamic_model'''		,	trust_remote_code=_lowercase				)
     self.assertEqual(config.__class__.__name__		,	'''NewModelConfigLocal'''				)

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

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