



class        lowerCamelCase__			:




		'''simple docstring'''



		def __init__(self		,__lowerCamelCase		,__lowerCamelCase		,__lowerCamelCase )     ->			Any:

						"""simple docstring"""






						lowerCAmelCase__     :				List[Any]												=     name
						lowerCAmelCase__     :				Tuple												=     value
						lowerCAmelCase__     :				Optional[Any]												=     weight



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

						"""simple docstring"""






						return f"""{self.__class__.__name__}({self.name}, {self.value}, {self.weight})"""



		def 		lowerCAmelCase__      (self )     ->			Optional[int]:

						"""simple docstring"""






						return self.value



		def 		lowerCAmelCase__      (self )     ->			str:

						"""simple docstring"""






						return self.name



		def 		lowerCAmelCase__      (self )     ->			List[str]:

						"""simple docstring"""






						return self.weight



		def 		lowerCAmelCase__      (self )     ->			List[str]:

						"""simple docstring"""






						return self.value / self.weight






def 	lowerCAmelCase__		(    lowerCamelCase_		:		int       ,lowerCamelCase_		:		Tuple       ,lowerCamelCase_		:		Tuple):





				'''simple docstring'''

				lowerCAmelCase__     :				Optional[Any]												=     []
				for i in range(len(lowerCamelCase_)):
								menu.append(Things(name[i]       ,value[i]       ,weight[i]))
				return menu






def 	lowerCAmelCase__		(    lowerCamelCase_		:		List[Any]       ,lowerCamelCase_		:		List[str]       ,lowerCamelCase_		:		Optional[int]):





				'''simple docstring'''

				lowerCAmelCase__     :				List[str]												=     sorted(lowerCamelCase_       ,key=lowerCamelCase_       ,reverse=lowerCamelCase_)
				lowerCAmelCase__     :				Union[str, Any]												=     []
				lowerCAmelCase__						,		lowerCAmelCase__     :				int												=     0.0, 0.0
				for i in range(len(lowerCamelCase_)):
								if (total_cost + items_copy[i].get_weight()) <= max_cost:
												result.append(items_copy[i])
												total_cost += items_copy[i].get_weight()
												total_value += items_copy[i].get_value()
				return (result, total_value)






def 	lowerCAmelCase__		(    ):





				'''simple docstring'''










if __name__ == "__main__":
							import doctest

							doctest.testmod()





'''simple docstring'''

import unittest

from transformers import TrOCRConfig
from transformers.testing_utils import is_torch_available, require_torch, torch_device

from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor
from ...test_pipeline_mixin import PipelineTesterMixin


if is_torch_available():
 import torch

 from transformers.models.trocr.modeling_trocr import TrOCRDecoder, TrOCRForCausalLM
@require_torch
class   __lowerCAmelCase						:





      '''simple docstring'''






      def __init__(self    :    str   ,						UpperCamelCase    :    Tuple   ,						UpperCamelCase    :    Optional[int]=99   ,						UpperCamelCase    :    Optional[int]=13   ,						UpperCamelCase    :    Tuple=16   ,						UpperCamelCase    :    Union[str, Any]=7   ,						UpperCamelCase    :    List[Any]=True   ,						UpperCamelCase    :    List[str]=True   ,						UpperCamelCase    :    str=True   ,						UpperCamelCase    :    Tuple=False   ,						UpperCamelCase    :    str=True   ,						UpperCamelCase    :    Tuple=2   ,						UpperCamelCase    :    Optional[int]=32   ,						UpperCamelCase    :    Any=4   ,						UpperCamelCase    :    Optional[int]=4   ,						UpperCamelCase    :    Tuple=30   ,						UpperCamelCase    :    str=0   ,						UpperCamelCase    :    Tuple=1   ,						UpperCamelCase    :    List[Any]=2   ,						UpperCamelCase    :    str=None   ,						):

             '''simple docstring'''







             lowercase__      			= parent
             lowercase__      			= batch_size
             lowercase__      			= decoder_seq_length
             # For common tests
             lowercase__      			= self.decoder_seq_length
             lowercase__      			= is_training
             lowercase__      			= use_attention_mask
             lowercase__      			= use_labels

             lowercase__      			= vocab_size
             lowercase__      			= d_model
             lowercase__      			= d_model
             lowercase__      			= decoder_layers
             lowercase__      			= decoder_layers
             lowercase__      			= decoder_ffn_dim
             lowercase__      			= decoder_attention_heads
             lowercase__      			= decoder_attention_heads
             lowercase__      			= eos_token_id
             lowercase__      			= bos_token_id
             lowercase__      			= pad_token_id
             lowercase__      			= decoder_start_token_id
             lowercase__      			= use_cache
             lowercase__      			= max_position_embeddings

             lowercase__      			= None
             lowercase__      			= decoder_seq_length
             lowercase__      			= 2
             lowercase__      			= 1



      def       UpperCamelCase__		(self    :    str ):

             '''simple docstring'''







             lowercase__      			= ids_tensor([self.batch_size, self.decoder_seq_length]   ,						self.vocab_size )

             lowercase__      			= None
             if self.use_attention_mask:
                    lowercase__      			= ids_tensor([self.batch_size, self.decoder_seq_length]   ,						vocab_size=2 )

             lowercase__      			= None
             if self.use_labels:
                    lowercase__      			= ids_tensor([self.batch_size, self.decoder_seq_length]   ,						self.vocab_size )

             lowercase__      			= TrOCRConfig(
                 vocab_size=self.vocab_size   ,						d_model=self.d_model   ,						decoder_layers=self.decoder_layers   ,						decoder_ffn_dim=self.decoder_ffn_dim   ,						decoder_attention_heads=self.decoder_attention_heads   ,						eos_token_id=self.eos_token_id   ,						bos_token_id=self.bos_token_id   ,						use_cache=self.use_cache   ,						pad_token_id=self.pad_token_id   ,						decoder_start_token_id=self.decoder_start_token_id   ,						max_position_embeddings=self.max_position_embeddings   ,						)

             return (config, input_ids, attention_mask, lm_labels)



      def       UpperCamelCase__		(self    :    Tuple   ,						UpperCamelCase    :    List[Any]   ,						UpperCamelCase    :    Optional[Any]   ,						UpperCamelCase    :    Tuple   ,						UpperCamelCase    :    List[str]   ,						):

             '''simple docstring'''







             lowercase__      			= True
             lowercase__      			= TrOCRDecoder(config=UpperCamelCase ).to(UpperCamelCase ).eval()
             lowercase__      			= input_ids[:2]

             input_ids[input_ids == 0] += 1
             # first forward pass
             lowercase__      			= model(UpperCamelCase   ,						use_cache=UpperCamelCase )
             lowercase__      			= model(UpperCamelCase )
             lowercase__      			= model(UpperCamelCase   ,						use_cache=UpperCamelCase )

             self.parent.assertTrue(len(UpperCamelCase ) == len(UpperCamelCase ) )
             self.parent.assertTrue(len(UpperCamelCase ) == len(UpperCamelCase ) + 1 )

             lowercase__      			= outputs['''past_key_values''']

             # create hypothetical next token and extent to next_input_ids
             lowercase__      			= ids_tensor((2, 1)   ,						config.vocab_size - 1 ) + 1

             # append to next input_ids and
             lowercase__      			= torch.cat([input_ids, next_tokens]   ,						dim=-1 )

             lowercase__      			= model(UpperCamelCase )['''last_hidden_state''']
             lowercase__      			= model(UpperCamelCase   ,						past_key_values=UpperCamelCase )['''last_hidden_state''']

             # select random slice
             lowercase__      			= ids_tensor((1,)   ,						output_from_past.shape[-1] ).item()
             lowercase__      			= output_from_no_past[:, next_input_ids.shape[-1] - 1, random_slice_idx].detach()
             lowercase__      			= output_from_past[:, 0, random_slice_idx].detach()

             # test that outputs are equal for slice
             assert torch.allclose(UpperCamelCase   ,						UpperCamelCase   ,						atol=1E-3 )






      def       UpperCamelCase__		(self    :    Optional[Any] ):

             '''simple docstring'''







             lowercase__      			= self.prepare_config_and_inputs()
             lowercase__			,lowercase__			,lowercase__			,lowercase__      			= config_and_inputs

             lowercase__      			= {'''input_ids''': input_ids, '''attention_mask''': attention_mask}
             return config, inputs_dict






@require_torch
class   __lowerCAmelCase						(lowercase_  ,     lowercase_  ,     lowercase_  ,     unittest.TestCase     ):





      '''simple docstring'''






      lowerCAmelCase__					:     List[str]  					=							(TrOCRDecoder, TrOCRForCausalLM) if is_torch_available() else ()
      lowerCAmelCase__					:     List[Any]  					=							(TrOCRForCausalLM,) if is_torch_available() else ()
      lowerCAmelCase__					:     Optional[Any]  					=							{"""text-generation""": TrOCRForCausalLM} if is_torch_available() else {}
      lowerCAmelCase__					:     Optional[Any]  					=							True
      lowerCAmelCase__					:     List[str]  					=							False



      def       UpperCamelCase__		(self    :    Any ):

             '''simple docstring'''







             lowercase__      			= TrOCRStandaloneDecoderModelTester(self   ,						is_training=UpperCamelCase )
             lowercase__      			= ConfigTester(self   ,						config_class=UpperCamelCase )



      def       UpperCamelCase__		(self    :    List[str] ):

             '''simple docstring'''







             pass



      def       UpperCamelCase__		(self    :    Optional[int] ):

             '''simple docstring'''







             pass



      def       UpperCamelCase__		(self    :    Any ):

             '''simple docstring'''







             pass



      def       UpperCamelCase__		(self    :    Any ):

             '''simple docstring'''







             self.config_tester.run_common_tests()



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

             '''simple docstring'''







             lowercase__      			= self.model_tester.prepare_config_and_inputs()
             self.model_tester.create_and_check_decoder_model_past(*UpperCamelCase )



      def       UpperCamelCase__		(self    :    Optional[int] ):

             '''simple docstring'''







             return






      @unittest.skip('''The model doesn\'t support left padding''' )  # and it's not used enough to be worth fixing :)
      def       UpperCamelCase__		(self    :    List[str] ):

             '''simple docstring'''







             pass




