


def    lowercase_	(	_A    :					list					,      _A    :					int = 0		):

      """simple docstring"""




      lowerCamelCase__	:       List[Any]					=						length or len(_A		)
      lowerCamelCase__	:       List[Any]					=						False
      for i in range(length - 1		):
            if list_data[i] > list_data[i + 1]:
                  lowerCamelCase__					,     lowerCamelCase__	:       Dict					=						list_data[i + 1], list_data[i]
                  lowerCamelCase__	:       str					=						True

      return list_data if not swapped else bubble_sort(_A					,      length - 1		)


if __name__ == "__main__":
    import doctest

    doctest.testmod()






import unittest

from transformers import is_torch_available
from transformers.testing_utils import require_torch, slow, 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 import (
        OPENAI_GPT_PRETRAINED_MODEL_ARCHIVE_LIST,
        OpenAIGPTConfig,
        OpenAIGPTDoubleHeadsModel,
        OpenAIGPTForSequenceClassification,
        OpenAIGPTLMHeadModel,
        OpenAIGPTModel,
    )







class     _lowercase				:


       """simple docstring"""




       def __init__(     self							:    Dict      ,   __lowerCamelCase							:    str      ,   __lowerCamelCase							:    Optional[int]=13      ,   __lowerCamelCase							:    List[str]=7      ,   __lowerCamelCase							:    Tuple=True      ,   __lowerCamelCase							:    Optional[int]=True      ,   __lowerCamelCase							:    List[str]=True      ,   __lowerCamelCase							:    Union[str, Any]=99      ,   __lowerCamelCase							:    List[Any]=32      ,   __lowerCamelCase							:    List[Any]=5      ,   __lowerCamelCase							:    Optional[Any]=4      ,   __lowerCamelCase							:    Optional[int]=37      ,   __lowerCamelCase							:    List[str]="gelu"      ,   __lowerCamelCase							:    List[str]=0.1      ,   __lowerCamelCase							:    int=0.1      ,   __lowerCamelCase							:    List[str]=512      ,   __lowerCamelCase							:    Optional[Any]=16      ,   __lowerCamelCase							:    Optional[Any]=2      ,   __lowerCamelCase							:    str=0.0_2      ,   __lowerCamelCase							:    List[str]=3      ,   __lowerCamelCase							:    Tuple=4      ,   __lowerCamelCase							:    Optional[int]=None      ,   ):


             '''simple docstring'''



             lowerCamelCase__	:       Tuple					=						parent
             lowerCamelCase__	:       int					=						batch_size
             lowerCamelCase__	:       List[Any]					=						seq_length
             lowerCamelCase__	:       Union[str, Any]					=						is_training
             lowerCamelCase__	:       Any					=						use_token_type_ids
             lowerCamelCase__	:       Union[str, Any]					=						use_labels
             lowerCamelCase__	:       List[str]					=						vocab_size
             lowerCamelCase__	:       Union[str, Any]					=						hidden_size
             lowerCamelCase__	:       List[Any]					=						num_hidden_layers
             lowerCamelCase__	:       Optional[Any]					=						num_attention_heads
             lowerCamelCase__	:       Any					=						intermediate_size
             lowerCamelCase__	:       str					=						hidden_act
             lowerCamelCase__	:       str					=						hidden_dropout_prob
             lowerCamelCase__	:       Any					=						attention_probs_dropout_prob
             lowerCamelCase__	:       List[str]					=						max_position_embeddings
             lowerCamelCase__	:       Optional[int]					=						type_vocab_size
             lowerCamelCase__	:       List[Any]					=						type_sequence_label_size
             lowerCamelCase__	:       List[str]					=						initializer_range
             lowerCamelCase__	:       List[str]					=						num_labels
             lowerCamelCase__	:       List[Any]					=						num_choices
             lowerCamelCase__	:       Optional[Any]					=						scope
             lowerCamelCase__	:       List[Any]					=						self.vocab_size - 1





       def 		lowerCAmelCase  (     self							:    List[Any] ):


             '''simple docstring'''



             lowerCamelCase__	:       Optional[int]					=						ids_tensor([self.batch_size, self.seq_length]      ,   self.vocab_size )

             lowerCamelCase__	:       Optional[Any]					=						None
             if self.use_token_type_ids:
                   lowerCamelCase__	:       Optional[Any]					=						ids_tensor([self.batch_size, self.seq_length]      ,   self.type_vocab_size )

             lowerCamelCase__	:       Any					=						None
             lowerCamelCase__	:       str					=						None
             lowerCamelCase__	:       str					=						None
             if self.use_labels:
                   lowerCamelCase__	:       Dict					=						ids_tensor([self.batch_size]      ,   self.type_sequence_label_size )
                   lowerCamelCase__	:       Dict					=						ids_tensor([self.batch_size, self.seq_length]      ,   self.num_labels )
                   lowerCamelCase__	:       Dict					=						ids_tensor([self.batch_size]      ,   self.num_choices )

             lowerCamelCase__	:       Union[str, Any]					=						OpenAIGPTConfig(
                 vocab_size=self.vocab_size      ,   n_embd=self.hidden_size      ,   n_layer=self.num_hidden_layers      ,   n_head=self.num_attention_heads      ,   n_positions=self.max_position_embeddings      ,   pad_token_id=self.pad_token_id      ,   )

             lowerCamelCase__	:       Optional[int]					=						ids_tensor([self.num_hidden_layers, self.num_attention_heads]      ,   2 )

             return (
                 config,
                 input_ids,
                 head_mask,
                 token_type_ids,
                 sequence_labels,
                 token_labels,
                 choice_labels,
             )





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


             '''simple docstring'''



             lowerCamelCase__	:       Optional[int]					=						OpenAIGPTModel(config=__lowerCamelCase )
             model.to(__lowerCamelCase )
             model.eval()

             lowerCamelCase__	:       Tuple					=						model(__lowerCamelCase      ,   token_type_ids=__lowerCamelCase      ,   head_mask=__lowerCamelCase )
             lowerCamelCase__	:       str					=						model(__lowerCamelCase      ,   token_type_ids=__lowerCamelCase )
             lowerCamelCase__	:       Optional[int]					=						model(__lowerCamelCase )

             self.parent.assertEqual(result.last_hidden_state.shape      ,   (self.batch_size, self.seq_length, self.hidden_size) )





       def 		lowerCAmelCase  (     self							:    str      ,   __lowerCamelCase							:    List[Any]      ,   __lowerCamelCase							:    Union[str, Any]      ,   __lowerCamelCase							:    List[str]      ,   __lowerCamelCase							:    Any      ,   *__lowerCamelCase							:    Optional[int] ):


             '''simple docstring'''



             lowerCamelCase__	:       Tuple					=						OpenAIGPTLMHeadModel(__lowerCamelCase )
             model.to(__lowerCamelCase )
             model.eval()

             lowerCamelCase__	:       List[str]					=						model(__lowerCamelCase      ,   token_type_ids=__lowerCamelCase      ,   labels=__lowerCamelCase )
             self.parent.assertEqual(result.loss.shape      ,   () )
             self.parent.assertEqual(result.logits.shape      ,   (self.batch_size, self.seq_length, self.vocab_size) )





       def 		lowerCAmelCase  (     self							:    Dict      ,   __lowerCamelCase							:    Any      ,   __lowerCamelCase							:    Union[str, Any]      ,   __lowerCamelCase							:    Optional[int]      ,   __lowerCamelCase							:    Optional[int]      ,   *__lowerCamelCase							:    Tuple ):


             '''simple docstring'''



             lowerCamelCase__	:       List[Any]					=						OpenAIGPTDoubleHeadsModel(__lowerCamelCase )
             model.to(__lowerCamelCase )
             model.eval()

             lowerCamelCase__	:       Optional[Any]					=						model(__lowerCamelCase      ,   token_type_ids=__lowerCamelCase      ,   labels=__lowerCamelCase )
             self.parent.assertEqual(result.loss.shape      ,   () )
             self.parent.assertEqual(result.logits.shape      ,   (self.batch_size, self.seq_length, self.vocab_size) )





       def 		lowerCAmelCase  (     self							:    Tuple      ,   __lowerCamelCase							:    Union[str, Any]      ,   __lowerCamelCase							:    Union[str, Any]      ,   __lowerCamelCase							:    Optional[Any]      ,   __lowerCamelCase							:    List[Any]      ,   *__lowerCamelCase							:    Optional[int] ):


             '''simple docstring'''



             lowerCamelCase__	:       Dict					=						self.num_labels
             lowerCamelCase__	:       Tuple					=						OpenAIGPTForSequenceClassification(__lowerCamelCase )
             model.to(__lowerCamelCase )
             model.eval()

             lowerCamelCase__	:       Dict					=						ids_tensor([self.batch_size]      ,   self.type_sequence_label_size )
             lowerCamelCase__	:       List[str]					=						model(__lowerCamelCase      ,   token_type_ids=__lowerCamelCase      ,   labels=__lowerCamelCase )
             self.parent.assertEqual(result.logits.shape      ,   (self.batch_size, self.num_labels) )





       def 		lowerCAmelCase  (     self							:    List[str] ):


             '''simple docstring'''



             lowerCamelCase__	:       str					=						self.prepare_config_and_inputs()
             (
                 (
                 lowerCamelCase__
             )					,     (
                 lowerCamelCase__
             )					,     (
                 lowerCamelCase__
             )					,     (
                 lowerCamelCase__
             )					,     (
                 lowerCamelCase__
             )					,     (
                 lowerCamelCase__
             )					,     (
                 lowerCamelCase__
             )					,     
             )	:       Any					=						config_and_inputs
             lowerCamelCase__	:       Union[str, Any]					=						{
                 "input_ids": input_ids,
                 "token_type_ids": token_type_ids,
                 "head_mask": head_mask,
             }

             return config, inputs_dict







@require_torch
class     _lowercase				(							lowercase__							,						lowercase__							,						lowercase__							,						unittest.TestCase):


       """simple docstring"""




       A__      		=    (
           (OpenAIGPTModel, OpenAIGPTLMHeadModel, OpenAIGPTDoubleHeadsModel, OpenAIGPTForSequenceClassification)
           if is_torch_available()
           else ()
       )
       A__      		=    (
           (OpenAIGPTLMHeadModel,) if is_torch_available() else ()
       )  # TODO (PVP): Add Double HeadsModel when generate() function is changed accordingly
       A__      		=    (
           {
               "feature-extraction": OpenAIGPTModel,
               "text-classification": OpenAIGPTForSequenceClassification,
               "text-generation": OpenAIGPTLMHeadModel,
               "zero-shot": OpenAIGPTForSequenceClassification,
           }
           if is_torch_available()
           else {}
       )





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


             '''simple docstring'''



             if pipeline_test_casse_name == "ZeroShotClassificationPipelineTests":
                   # Get `tokenizer does not have a padding token` error for both fast/slow tokenizers.
                   # `OpenAIGPTConfig` was never used in pipeline tests, either because of a missing checkpoint or because a
                   # tiny config could not be created.
                   return True

             return False





       def 		lowerCAmelCase  (     self							:    Union[str, Any]      ,   __lowerCamelCase							:    Optional[int]      ,   __lowerCamelCase							:    Tuple      ,   __lowerCamelCase							:    Tuple=False ):


             '''simple docstring'''



             lowerCamelCase__	:       Tuple					=						super()._prepare_for_class(__lowerCamelCase      ,   __lowerCamelCase      ,   return_labels=__lowerCamelCase )

             if return_labels:
                   if model_class.__name__ == "OpenAIGPTDoubleHeadsModel":
                         lowerCamelCase__	:       Optional[Any]					=						torch.zeros(
                             (self.model_tester.batch_size, self.model_tester.num_choices, self.model_tester.seq_length)      ,   dtype=torch.long      ,   device=__lowerCamelCase      ,   )
                         lowerCamelCase__	:       Tuple					=						inputs_dict["labels"]
                         lowerCamelCase__	:       Any					=						inputs_dict["labels"]
                         lowerCamelCase__	:       Any					=						torch.zeros(
                             (self.model_tester.batch_size, self.model_tester.num_choices)      ,   dtype=torch.long      ,   device=__lowerCamelCase      ,   )
                         lowerCamelCase__	:       Union[str, Any]					=						torch.zeros(
                             self.model_tester.batch_size      ,   dtype=torch.long      ,   device=__lowerCamelCase )
             return inputs_dict





       def 		lowerCAmelCase  (     self							:    List[Any] ):


             '''simple docstring'''



             lowerCamelCase__	:       Tuple					=						OpenAIGPTModelTester(self )
             lowerCamelCase__	:       Union[str, Any]					=						ConfigTester(self      ,   config_class=__lowerCamelCase      ,   n_embd=37 )





       def 		lowerCAmelCase  (     self							:    int ):


             '''simple docstring'''



             self.config_tester.run_common_tests()





       def 		lowerCAmelCase  (     self							:    Dict ):


             '''simple docstring'''



             lowerCamelCase__	:       List[Any]					=						self.model_tester.prepare_config_and_inputs()
             self.model_tester.create_and_check_openai_gpt_model(*__lowerCamelCase )





       def 		lowerCAmelCase  (     self							:    str ):


             '''simple docstring'''



             lowerCamelCase__	:       Union[str, Any]					=						self.model_tester.prepare_config_and_inputs()
             self.model_tester.create_and_check_lm_head_model(*__lowerCamelCase )





       def 		lowerCAmelCase  (     self							:    Dict ):


             '''simple docstring'''



             lowerCamelCase__	:       Optional[int]					=						self.model_tester.prepare_config_and_inputs()
             self.model_tester.create_and_check_double_lm_head_model(*__lowerCamelCase )





       def 		lowerCAmelCase  (     self							:    Optional[int] ):


             '''simple docstring'''



             lowerCamelCase__	:       Optional[int]					=						self.model_tester.prepare_config_and_inputs()
             self.model_tester.create_and_check_openai_gpt_for_sequence_classification(*__lowerCamelCase )





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


             '''simple docstring'''



             for model_name in OPENAI_GPT_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
                   lowerCamelCase__	:       Any					=						OpenAIGPTModel.from_pretrained(__lowerCamelCase )
                   self.assertIsNotNone(__lowerCamelCase )







@require_torch
class     _lowercase				(							unittest.TestCase):


       """simple docstring"""




       @slow
       def 		lowerCAmelCase  (     self							:    Any ):


             '''simple docstring'''



             lowerCamelCase__	:       List[Any]					=						OpenAIGPTLMHeadModel.from_pretrained("openai-gpt" )
             model.to(__lowerCamelCase )
             lowerCamelCase__	:       int					=						torch.tensor([[481, 4735, 544]]      ,   dtype=torch.long      ,   device=__lowerCamelCase )  # the president is
             lowerCamelCase__	:       Union[str, Any]					=						[
                 481,
                 4735,
                 544,
                 246,
                 963,
                 870,
                 762,
                 239,
                 244,
                 40477,
                 244,
                 249,
                 719,
                 881,
                 487,
                 544,
                 240,
                 244,
                 603,
                 481,
             ]  # the president is a very good man. " \n " i\'m sure he is, " said the

             lowerCamelCase__	:       int					=						model.generate(__lowerCamelCase      ,   do_sample=__lowerCamelCase )
             self.assertListEqual(output_ids[0].tolist()      ,   __lowerCamelCase )


