






import enum
import inspect
from typing import Iterable, List, Optional, Tuple, Union
class 	a_(		enum.Enum	):



     """simple docstring"""



     __snake_case		:				str  					='''timm'''
     __snake_case		:				Tuple  					='''transformers'''





def 						A_					(						lowercase_	,  lowercase_	,  lowercase_			)				->Optional[Any]:







 """simple docstring"""

 if stage_names is None:
  raise ValueError('Stage_names must be set for transformers backbones'			)

 if out_features is not None:
  if not isinstance(lowercase_	,  (list,)			):
   raise ValueError(f'''out_features must be a list {type(lowercase_			)}'''			)
  if any(feat not in stage_names for feat in out_features			):
   raise ValueError(f'''out_features must be a subset of stage_names: {stage_names} got {out_features}'''			)

 if out_indices is not None:
  if not isinstance(lowercase_	,  (list, tuple)			):
   raise ValueError(f'''out_indices must be a list or tuple, got {type(lowercase_			)}'''			)
  if any(idx >= len(lowercase_			) for idx in out_indices			):
   raise ValueError('out_indices must be valid indices for stage_names {stage_names}, got {out_indices}'			)

 if out_features is not None and out_indices is not None:
  if len(lowercase_			) != len(lowercase_			):
   raise ValueError('out_features and out_indices should have the same length if both are set'			)
  if out_features != [stage_names[idx] for idx in out_indices]:
   raise ValueError('out_features and out_indices should correspond to the same stages if both are set'			)





def 						A_					(						lowercase_	,  lowercase_	,  lowercase_	,  )				->Union[str, Any]:







 """simple docstring"""

 if out_indices is None and out_features is None:
  SCREAMING_SNAKE_CASE				    =		[len(lowercase_			) - 1]
  SCREAMING_SNAKE_CASE				    =		[stage_names[-1]]
 elif out_indices is None and out_features is not None:
  SCREAMING_SNAKE_CASE				    =		[stage_names.index(lowercase_			) for layer in out_features]
 elif out_features is None and out_indices is not None:
  SCREAMING_SNAKE_CASE				    =		[stage_names[idx] for idx in out_indices]
 return out_features, out_indices





def 						A_					(						lowercase_	,  lowercase_	,  lowercase_	,  )				->Tuple[List[str], List[int]]:







 """simple docstring"""

 verify_out_features_out_indices(out_features=lowercase_	,  out_indices=lowercase_	,  stage_names=lowercase_			)
 SCREAMING_SNAKE_CASE    ,   SCREAMING_SNAKE_CASE				    =		_align_output_features_output_indices(
     out_features=lowercase_	,  out_indices=lowercase_	,  stage_names=lowercase_			)
 # Verify that the aligned out_features and out_indices are valid
 verify_out_features_out_indices(out_features=lowercase_	,  out_indices=lowercase_	,  stage_names=lowercase_			)
 return output_features, output_indices
class 	a_:



     """simple docstring"""



     __snake_case		:				Optional[BackboneType]  					=None





     def     __UpperCamelCase						(		self					:	Optional[Any]  ,  lowerCAmelCase__					:	List[str])							->	None:

      """simple docstring"""
      if getattr(self  ,  '_backbone'  ,  lowerCAmelCase__) is None:
       raise ValueError('self._backbone must be set before calling _init_timm_backbone')

      # These will diagree with the defaults for the transformers models e.g. for resnet50
      # the transformer model has out_features = ['stem', 'stage1', 'stage2', 'stage3', 'stage4']
      # the timm model has out_features = ['act', 'layer1', 'layer2', 'layer3', 'layer4']
      SCREAMING_SNAKE_CASE				    =		[stage['module'] for stage in self._backbone.feature_info.info]
      SCREAMING_SNAKE_CASE				    =		[stage['num_chs'] for stage in self._backbone.feature_info.info]
      SCREAMING_SNAKE_CASE				    =		self._backbone.feature_info.out_indices
      SCREAMING_SNAKE_CASE				    =		self._backbone.feature_info.module_name()

      # We verify the out indices and out features are valid
      verify_out_features_out_indices(
          out_features=lowerCAmelCase__  ,  out_indices=lowerCAmelCase__  ,  stage_names=self.stage_names)
      SCREAMING_SNAKE_CASE    ,   SCREAMING_SNAKE_CASE				    =		out_features, out_indices





     def     __UpperCamelCase						(		self					:	str  ,  lowerCAmelCase__					:	Dict)							->	None:

      """simple docstring"""
      SCREAMING_SNAKE_CASE				    =		getattr(lowerCAmelCase__  ,  'stage_names')
      SCREAMING_SNAKE_CASE				    =		getattr(lowerCAmelCase__  ,  'out_features'  ,  lowerCAmelCase__)
      SCREAMING_SNAKE_CASE				    =		getattr(lowerCAmelCase__  ,  'out_indices'  ,  lowerCAmelCase__)

      SCREAMING_SNAKE_CASE				    =		stage_names
      SCREAMING_SNAKE_CASE    ,   SCREAMING_SNAKE_CASE				    =		get_aligned_output_features_output_indices(
          out_features=lowerCAmelCase__  ,  out_indices=lowerCAmelCase__  ,  stage_names=lowerCAmelCase__)
      # Number of channels for each stage. This is set in the transformer backbone model init
      SCREAMING_SNAKE_CASE				    =		None





     def     __UpperCamelCase						(		self					:	Dict  ,  lowerCAmelCase__					:	int)							->	None:

      """simple docstring"""
      SCREAMING_SNAKE_CASE				    =		config

      SCREAMING_SNAKE_CASE				    =		getattr(lowerCAmelCase__  ,  'use_timm_backbone'  ,  lowerCAmelCase__)
      SCREAMING_SNAKE_CASE				    =		BackboneType.TIMM if self.use_timm_backbone else BackboneType.TRANSFORMERS

      if self.backbone_type == BackboneType.TIMM:
       self._init_timm_backbone(lowerCAmelCase__)
      elif self.backbone_type == BackboneType.TRANSFORMERS:
       self._init_transformers_backbone(lowerCAmelCase__)
      else:
       raise ValueError(f'''backbone_type {self.backbone_type} not supported.''')





     @property
     def     __UpperCamelCase						(		self					:	int)							->	Optional[int]:

      """simple docstring"""
      return self._out_features





     @out_features.setter
     def     __UpperCamelCase						(		self					:	Union[str, Any]  ,  lowerCAmelCase__					:	List[str])							->	Dict:

      """simple docstring"""
      SCREAMING_SNAKE_CASE    ,   SCREAMING_SNAKE_CASE				    =		get_aligned_output_features_output_indices(
          out_features=lowerCAmelCase__  ,  out_indices=lowerCAmelCase__  ,  stage_names=self.stage_names)





     @property
     def     __UpperCamelCase						(		self					:	str)							->	List[str]:

      """simple docstring"""
      return self._out_indices





     @out_indices.setter
     def     __UpperCamelCase						(		self					:	Tuple  ,  lowerCAmelCase__					:	Union[Tuple[int], List[int]])							->	Optional[int]:

      """simple docstring"""
      SCREAMING_SNAKE_CASE    ,   SCREAMING_SNAKE_CASE				    =		get_aligned_output_features_output_indices(
          out_features=lowerCAmelCase__  ,  out_indices=lowerCAmelCase__  ,  stage_names=self.stage_names)





     @property
     def     __UpperCamelCase						(		self					:	List[str])							->	Optional[Any]:

      """simple docstring"""
      # the current backbones will output the number of channels for each stage
      # even if that stage is not in the out_features list.
      return {stage: self.num_features[i] for i, stage in enumerate(self.stage_names)}





     @property
     def     __UpperCamelCase						(		self					:	Optional[int])							->	List[str]:

      """simple docstring"""
      return [self.out_feature_channels[name] for name in self.out_features]





     def     __UpperCamelCase						(		self					:	List[str]  ,  *lowerCAmelCase__					:	Any  ,  **lowerCAmelCase__					:	Tuple)							->	Tuple:

      """simple docstring"""
      SCREAMING_SNAKE_CASE				    =		dict(inspect.signature(self.forward).parameters)
      SCREAMING_SNAKE_CASE				    =		{k: v for k, v in kwargs.items() if k in signature}
      return self(*lowerCAmelCase__  ,  **lowerCAmelCase__)





     def     __UpperCamelCase						(		self					:	Optional[int]  ,  lowerCAmelCase__					:	Any  ,  lowerCAmelCase__					:	Optional[bool] = None  ,  lowerCAmelCase__					:	Optional[bool] = None  ,  lowerCAmelCase__					:	Optional[bool] = None  ,  )							->	Union[str, Any]:

      """simple docstring"""
      raise NotImplementedError('This method should be implemented by the derived class.')





     def     __UpperCamelCase						(		self					:	Tuple)							->	Dict:

      """simple docstring"""
      SCREAMING_SNAKE_CASE				    =		super().to_dict()
      SCREAMING_SNAKE_CASE				    =		output.pop('_out_features')
      SCREAMING_SNAKE_CASE				    =		output.pop('_out_indices')
      return output

class 	a_:



     """simple docstring"""



     @property
     def     __UpperCamelCase						(		self					:	Any)							->	Union[str, Any]:

      """simple docstring"""
      return self._out_features





     @out_features.setter
     def     __UpperCamelCase						(		self					:	Optional[Any]  ,  lowerCAmelCase__					:	List[str])							->	List[str]:

      """simple docstring"""
      SCREAMING_SNAKE_CASE    ,   SCREAMING_SNAKE_CASE				    =		get_aligned_output_features_output_indices(
          out_features=lowerCAmelCase__  ,  out_indices=lowerCAmelCase__  ,  stage_names=self.stage_names)





     @property
     def     __UpperCamelCase						(		self					:	Tuple)							->	List[str]:

      """simple docstring"""
      return self._out_indices





     @out_indices.setter
     def     __UpperCamelCase						(		self					:	Optional[Any]  ,  lowerCAmelCase__					:	Union[Tuple[int], List[int]])							->	Dict:

      """simple docstring"""
      SCREAMING_SNAKE_CASE    ,   SCREAMING_SNAKE_CASE				    =		get_aligned_output_features_output_indices(
          out_features=lowerCAmelCase__  ,  out_indices=lowerCAmelCase__  ,  stage_names=self.stage_names)





     def     __UpperCamelCase						(		self					:	str)							->	Tuple:

      """simple docstring"""
      SCREAMING_SNAKE_CASE				    =		super().to_dict()
      SCREAMING_SNAKE_CASE				    =		output.pop('_out_features')
      SCREAMING_SNAKE_CASE				    =		output.pop('_out_indices')
      return output












import json
import os
import tempfile
import unittest

from transformers.modelcard import ModelCard
class 	a_(		unittest.TestCase	):



     """simple docstring"""



     def     __UpperCamelCase						(		self					:	Optional[int])							->	List[str]:

      """simple docstring"""
      SCREAMING_SNAKE_CASE				    =		{
          'model_details': {
              'Organization': 'testing',
              'Model date': 'today',
              'Model version': 'v2.1, Developed by Test Corp in 2019.',
              'Architecture': 'Convolutional Neural Network.',
          },
          'metrics': 'BLEU and ROUGE-1',
          'evaluation_data': {
              'Datasets': {'BLEU': 'My-great-dataset-v1', 'ROUGE-1': 'My-short-dataset-v2.1'},
              'Preprocessing': 'See details on https://arxiv.org/pdf/1810.03993.pdf',
          },
          'training_data': {
              'Dataset': 'English Wikipedia dump dated 2018-12-01',
              'Preprocessing': (
                  'Using SentencePiece vocabulary of size 52k tokens. See details on'
                  ' https://arxiv.org/pdf/1810.03993.pdf'
              ),
          },
          'quantitative_analyses': {'BLEU': 55.1, 'ROUGE-1': 7_6},
      }





     def     __UpperCamelCase						(		self					:	Optional[Any])							->	Any:

      """simple docstring"""
      SCREAMING_SNAKE_CASE				    =		ModelCard.from_dict(self.inputs_dict)
      self.assertTrue(hasattr(lowerCAmelCase__  ,  'model_details'))
      self.assertTrue(hasattr(lowerCAmelCase__  ,  'intended_use'))
      self.assertTrue(hasattr(lowerCAmelCase__  ,  'factors'))
      self.assertTrue(hasattr(lowerCAmelCase__  ,  'metrics'))
      self.assertTrue(hasattr(lowerCAmelCase__  ,  'evaluation_data'))
      self.assertTrue(hasattr(lowerCAmelCase__  ,  'training_data'))
      self.assertTrue(hasattr(lowerCAmelCase__  ,  'quantitative_analyses'))
      self.assertTrue(hasattr(lowerCAmelCase__  ,  'ethical_considerations'))
      self.assertTrue(hasattr(lowerCAmelCase__  ,  'caveats_and_recommendations'))





     def     __UpperCamelCase						(		self					:	Any)							->	Any:

      """simple docstring"""
      SCREAMING_SNAKE_CASE				    =		ModelCard.from_dict(self.inputs_dict)
      SCREAMING_SNAKE_CASE				    =		json.loads(modelcard.to_json_string())
      for key, value in self.inputs_dict.items():
       self.assertEqual(obj[key]  ,  lowerCAmelCase__)





     def     __UpperCamelCase						(		self					:	int)							->	Optional[Any]:

      """simple docstring"""
      SCREAMING_SNAKE_CASE				    =		ModelCard.from_dict(self.inputs_dict)

      with tempfile.TemporaryDirectory() as tmpdirname:
       SCREAMING_SNAKE_CASE				    =		os.path.join(lowerCAmelCase__  ,  'modelcard.json')
       model_card_first.to_json_file(lowerCAmelCase__)
       SCREAMING_SNAKE_CASE				    =		ModelCard.from_json_file(lowerCAmelCase__)

      self.assertEqual(model_card_second.to_dict()  ,  model_card_first.to_dict())





     def     __UpperCamelCase						(		self					:	Optional[int])							->	Any:

      """simple docstring"""
      SCREAMING_SNAKE_CASE				    =		ModelCard.from_dict(self.inputs_dict)

      with tempfile.TemporaryDirectory() as tmpdirname:
       model_card_first.save_pretrained(lowerCAmelCase__)
       SCREAMING_SNAKE_CASE				    =		ModelCard.from_pretrained(lowerCAmelCase__)

      self.assertEqual(model_card_second.to_dict()  ,  model_card_first.to_dict())




