'''simple docstring'''





from typing import List, Optional, Union

import numpy as np
import PIL.Image

from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import rescale, resize, to_channel_dimension_format
from ...image_utils import (
    ChannelDimension,
    PILImageResampling,
    get_image_size,
    make_list_of_images,
    to_numpy_array,
    valid_images,
)
from ...utils import TensorType, logging


_lowerCAmelCase  :List[Any]  				=    logging.get_logger(__name__)






class 				UpperCAmelCase (       _SCREAMING_SNAKE_CASE ):




    '''simple docstring'''







    snake_case__							:   Dict							=						["pixel_values"]






    def __init__(       self    ,							lowercase__ = True    ,							lowercase__ = 32    ,							lowercase__=PILImageResampling.BILINEAR    ,							lowercase__ = True    ,							**lowercase__    ,							)							-> None:
         SCREAMING_SNAKE_CASE					:			Tuple    	=       do_resize
         SCREAMING_SNAKE_CASE					:			Optional[Any]    	=       do_rescale
         SCREAMING_SNAKE_CASE					:			Union[str, Any]    	=       size_divisor
         SCREAMING_SNAKE_CASE					:			Tuple    	=       resample
         super().__init__(**lowercase__ )






    def       _UpperCamelCase    (       self    ,							lowercase__    ,							lowercase__    ,							lowercase__    ,							lowercase__ = None    ,							**lowercase__ )							-> np.ndarray:
         SCREAMING_SNAKE_CASE	,   SCREAMING_SNAKE_CASE					:			Any    	=       get_image_size(lowercase__ )
         # Rounds the height and width down to the closest multiple of size_divisor
         SCREAMING_SNAKE_CASE					:			int    	=       height // size_divisor * size_divisor
         SCREAMING_SNAKE_CASE					:			int    	=       width // size_divisor * size_divisor
         SCREAMING_SNAKE_CASE					:			Dict    	=       resize(lowercase__    ,							(new_h, new_w)    ,							resample=lowercase__    ,							data_format=lowercase__    ,							**lowercase__ )
         return image






    def       _UpperCamelCase    (       self    ,							lowercase__    ,							lowercase__    ,							lowercase__ = None    ,							**lowercase__ )							-> np.ndarray:
         return rescale(image=lowercase__    ,							scale=lowercase__    ,							data_format=lowercase__    ,							**lowercase__ )






    def       _UpperCamelCase    (       self    ,							lowercase__    ,							lowercase__ = None    ,							lowercase__ = None    ,							lowercase__=None    ,							lowercase__ = None    ,							lowercase__ = None    ,							lowercase__ = ChannelDimension.FIRST    ,							**lowercase__    ,							)							-> BatchFeature:
         SCREAMING_SNAKE_CASE					:			List[Any]    	=       do_resize if do_resize is not None else self.do_resize
         SCREAMING_SNAKE_CASE					:			Dict    	=       do_rescale if do_rescale is not None else self.do_rescale
         SCREAMING_SNAKE_CASE					:			Optional[int]    	=       size_divisor if size_divisor is not None else self.size_divisor
         SCREAMING_SNAKE_CASE					:			List[str]    	=       resample if resample is not None else self.resample

         if do_resize and size_divisor is None:
              raise ValueError('size_divisor is required for resizing' )

         SCREAMING_SNAKE_CASE					:			Tuple    	=       make_list_of_images(lowercase__ )

         if not valid_images(lowercase__ ):
              raise ValueError('Invalid image(s)' )

         # All transformations expect numpy arrays.
         SCREAMING_SNAKE_CASE					:			List[Any]    	=       [to_numpy_array(lowercase__ ) for img in images]

         if do_resize:
              SCREAMING_SNAKE_CASE					:			Union[str, Any]    	=       [self.resize(lowercase__    ,							size_divisor=lowercase__    ,							resample=lowercase__ ) for image in images]

         if do_rescale:
              SCREAMING_SNAKE_CASE					:			Any    	=       [self.rescale(lowercase__    ,							scale=1 / 255 ) for image in images]

         SCREAMING_SNAKE_CASE					:			Optional[Any]    	=       [to_channel_dimension_format(lowercase__    ,							lowercase__ ) for image in images]

         SCREAMING_SNAKE_CASE					:			Tuple    	=       {'pixel_values': images}
         return BatchFeature(data=lowercase__    ,							tensor_type=lowercase__ )




'''simple docstring'''





import copy
import json
import os
import tempfile

from transformers import is_torch_available

from .test_configuration_utils import config_common_kwargs






class 				UpperCAmelCase (       _SCREAMING_SNAKE_CASE ):




    '''simple docstring'''







    def __init__(       self    ,							lowercase__    ,							lowercase__=None    ,							lowercase__=True    ,							lowercase__=None    ,							**lowercase__ )							-> Optional[Any]:
         SCREAMING_SNAKE_CASE					:			int    	=       parent
         SCREAMING_SNAKE_CASE					:			str    	=       config_class
         SCREAMING_SNAKE_CASE					:			Union[str, Any]    	=       has_text_modality
         SCREAMING_SNAKE_CASE					:			Any    	=       kwargs
         SCREAMING_SNAKE_CASE					:			Union[str, Any]    	=       common_properties






    def       _UpperCamelCase    (       self )							-> Union[str, Any]:
         SCREAMING_SNAKE_CASE					:			Optional[int]    	=       self.config_class(**self.inputs_dict )
         SCREAMING_SNAKE_CASE					:			int    	=       (
             ['hidden_size', 'num_attention_heads', 'num_hidden_layers']
             if self.common_properties is None
             else self.common_properties
         )

         # Add common fields for text models
         if self.has_text_modality:
              common_properties.extend(['vocab_size'] )

         # Test that config has the common properties as getters
         for prop in common_properties:
              self.parent.assertTrue(hasattr(lowercase__    ,							lowercase__ )    ,							msg=F"""`{prop}` does not exist""" )

         # Test that config has the common properties as setter
         for idx, name in enumerate(lowercase__ ):
              try:
                   setattr(lowercase__    ,							lowercase__    ,							lowercase__ )
                   self.parent.assertEqual(
                       getattr(lowercase__    ,							lowercase__ )    ,							lowercase__    ,							msg=F"""`{name} value {idx} expected, but was {getattr(lowercase__    ,							lowercase__ )}""" )
              except NotImplementedError:
                   # Some models might not be able to implement setters for common_properties
                   # In that case, a NotImplementedError is raised
                   pass

        # Test if config class can be called with Config(prop_name=..)
         for idx, name in enumerate(lowercase__ ):
              try:
                   SCREAMING_SNAKE_CASE					:			Optional[int]    	=       self.config_class(**{name: idx} )
                   self.parent.assertEqual(
                       getattr(lowercase__    ,							lowercase__ )    ,							lowercase__    ,							msg=F"""`{name} value {idx} expected, but was {getattr(lowercase__    ,							lowercase__ )}""" )
              except NotImplementedError:
                   # Some models might not be able to implement setters for common_properties
                   # In that case, a NotImplementedError is raised
                   pass






    def       _UpperCamelCase    (       self )							-> List[str]:
         SCREAMING_SNAKE_CASE					:			Optional[Any]    	=       self.config_class(**self.inputs_dict )
         SCREAMING_SNAKE_CASE					:			Any    	=       json.loads(config.to_json_string() )
         for key, value in self.inputs_dict.items():
              self.parent.assertEqual(obj[key]    ,							lowercase__ )






    def       _UpperCamelCase    (       self )							-> Optional[int]:
         SCREAMING_SNAKE_CASE					:			Tuple    	=       self.config_class(**self.inputs_dict )

         with tempfile.TemporaryDirectory() as tmpdirname:
              SCREAMING_SNAKE_CASE					:			List[str]    	=       os.path.join(lowercase__    ,							'config.json' )
              config_first.to_json_file(lowercase__ )
              SCREAMING_SNAKE_CASE					:			Union[str, Any]    	=       self.config_class.from_json_file(lowercase__ )

         self.parent.assertEqual(config_second.to_dict()    ,							config_first.to_dict() )






    def       _UpperCamelCase    (       self )							-> Dict:
         SCREAMING_SNAKE_CASE					:			Optional[Any]    	=       self.config_class(**self.inputs_dict )

         with tempfile.TemporaryDirectory() as tmpdirname:
              config_first.save_pretrained(lowercase__ )
              SCREAMING_SNAKE_CASE					:			Optional[int]    	=       self.config_class.from_pretrained(lowercase__ )

         self.parent.assertEqual(config_second.to_dict()    ,							config_first.to_dict() )






    def       _UpperCamelCase    (       self )							-> int:
         SCREAMING_SNAKE_CASE					:			List[Any]    	=       self.config_class(**self.inputs_dict )

         SCREAMING_SNAKE_CASE					:			Optional[int]    	=       'test'
         with tempfile.TemporaryDirectory() as tmpdirname:
              SCREAMING_SNAKE_CASE					:			Tuple    	=       os.path.join(lowercase__    ,							lowercase__ )
              config_first.save_pretrained(lowercase__ )
              SCREAMING_SNAKE_CASE					:			Dict    	=       self.config_class.from_pretrained(lowercase__    ,							subfolder=lowercase__ )

         self.parent.assertEqual(config_second.to_dict()    ,							config_first.to_dict() )






    def       _UpperCamelCase    (       self )							-> List[Any]:
         SCREAMING_SNAKE_CASE					:			Dict    	=       self.config_class(**self.inputs_dict    ,							num_labels=5 )
         self.parent.assertEqual(len(config.idalabel )    ,							5 )
         self.parent.assertEqual(len(config.labelaid )    ,							5 )

         SCREAMING_SNAKE_CASE					:			Union[str, Any]    	=       3
         self.parent.assertEqual(len(config.idalabel )    ,							3 )
         self.parent.assertEqual(len(config.labelaid )    ,							3 )






    def       _UpperCamelCase    (       self )							-> Dict:
         if self.config_class.is_composition:
              return
         SCREAMING_SNAKE_CASE					:			int    	=       self.config_class()
         self.parent.assertIsNotNone(lowercase__ )






    def       _UpperCamelCase    (       self )							-> Tuple:
         SCREAMING_SNAKE_CASE					:			Union[str, Any]    	=       copy.deepcopy(lowercase__ )
         SCREAMING_SNAKE_CASE					:			Any    	=       self.config_class(**lowercase__ )
         SCREAMING_SNAKE_CASE					:			str    	=       []
         for key, value in config_common_kwargs.items():
              if key == "torch_dtype":
                   if not is_torch_available():
                        continue
                   else:
                        import torch

                        if config.torch_dtype != torch.floataa:
                             wrong_values.append(('torch_dtype', config.torch_dtype, torch.floataa) )
              elif getattr(lowercase__    ,							lowercase__ ) != value:
                   wrong_values.append((key, getattr(lowercase__    ,							lowercase__ ), value) )

         if len(lowercase__ ) > 0:
              SCREAMING_SNAKE_CASE					:			List[Any]    	=       '\n'.join([F"""- {v[0]}: got {v[1]} instead of {v[2]}""" for v in wrong_values] )
              raise ValueError(F"""The following keys were not properly set in the config:\n{errors}""" )






    def       _UpperCamelCase    (       self )							-> Optional[int]:
         self.create_and_test_config_common_properties()
         self.create_and_test_config_to_json_string()
         self.create_and_test_config_to_json_file()
         self.create_and_test_config_from_and_save_pretrained()
         self.create_and_test_config_from_and_save_pretrained_subfolder()
         self.create_and_test_config_with_num_labels()
         self.check_config_can_be_init_without_params()
         self.check_config_arguments_init()



