






'''simple docstring'''
import unittest

from transformers import SpeechaTextaConfig
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.speech_to_text_a.modeling_speech_to_text_a import (
     SpeechaTextaDecoder,
     SpeechaTextaForCausalLM,
 )


@require_torch
class     _UpperCAmelCase  :




    def __init__(     self					:    Union[str, Any]					,       a					:    str					,       a					:    Tuple=9_9					,       a					:    List[Any]=1_3					,       a					:    Dict=1_6					,       a					:    Dict=7					,       a					:    Tuple=True					,       a					:    Optional[Any]=True					,       a					:    List[Any]=True					,       a					:    str=False					,       a					:    Tuple=True					,       a					:    Optional[int]=2					,       a					:    Optional[Any]=3_2					,       a					:    Dict=4					,       a					:    List[str]=4					,       a					:    str=3_0					,       a					:    Optional[Any]=0					,       a					:    Dict=1					,       a					:    Optional[Any]=2					,       a					:    List[str]=None					,       ):






       '''simple docstring'''






       lowercase_		:      List[str]          =       parent
       lowercase_		:      Union[str, Any]          =       batch_size
       lowercase_		:      str          =       decoder_seq_length
       # For common tests
       lowercase_		:      Any          =       self.decoder_seq_length
       lowercase_		:      Union[str, Any]          =       is_training
       lowercase_		:      str          =       use_attention_mask
       lowercase_		:      str          =       use_labels

       lowercase_		:      int          =       vocab_size
       lowercase_		:      Union[str, Any]          =       d_model
       lowercase_		:      Optional[int]          =       d_model
       lowercase_		:      Optional[Any]          =       decoder_layers
       lowercase_		:      Optional[int]          =       decoder_layers
       lowercase_		:      Optional[int]          =       decoder_ffn_dim
       lowercase_		:      Dict          =       decoder_attention_heads
       lowercase_		:      List[str]          =       decoder_attention_heads
       lowercase_		:      Union[str, Any]          =       eos_token_id
       lowercase_		:      str          =       bos_token_id
       lowercase_		:      Tuple          =       pad_token_id
       lowercase_		:      Optional[Any]          =       decoder_start_token_id
       lowercase_		:      Dict          =       use_cache
       lowercase_		:      Optional[int]          =       max_position_embeddings

       lowercase_		:      Union[str, Any]          =       None
       lowercase_		:      List[Any]          =       decoder_seq_length
       lowercase_		:      Optional[int]          =       2
       lowercase_		:      Optional[Any]          =       1




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






       '''simple docstring'''






       lowercase_		:      int          =       ids_tensor([self.batch_size, self.decoder_seq_length]					,       self.vocab_size     )

       lowercase_		:      Optional[Any]          =       None
       if self.use_attention_mask:
          lowercase_		:      int          =       ids_tensor([self.batch_size, self.decoder_seq_length]					,       vocab_size=2     )

       lowercase_		:      str          =       None
       if self.use_labels:
          lowercase_		:      List[Any]          =       ids_tensor([self.batch_size, self.decoder_seq_length]					,       self.vocab_size     )

       lowercase_		:      str          =       SpeechaTextaConfig(
           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 			lowerCAmelCase__			(     self					:    int					,       a					:    Any					,       a					:    Any					,       a					:    Optional[int]					,       a					:    Optional[int]					,       ):






       '''simple docstring'''






       lowercase_		:      Optional[Any]          =       True
       lowercase_		:      List[str]          =       SpeechaTextaDecoder(config=a     ).to(a     ).eval()
       lowercase_		:      str          =       input_ids[:2]

       input_ids[input_ids == 0] += 1
       # first forward pass
       lowercase_		:      Any          =       model(a					,       use_cache=a     )
       lowercase_		:      int          =       model(a     )
       lowercase_		:      str          =       model(a					,       use_cache=a     )

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

       lowercase_		:      Union[str, Any]          =       outputs["past_key_values"]

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

       # append to next input_ids and
       lowercase_		:      List[str]          =       torch.cat([input_ids, next_tokens]					,       dim=-1     )

       print(a     )

       lowercase_		:      Optional[Any]          =       model(a     )["last_hidden_state"]
       lowercase_		:      int          =       model(a					,       past_key_values=a     )["last_hidden_state"]

       # select random slice
       lowercase_		:      Tuple          =       ids_tensor((1,)					,       output_from_past.shape[-1]     ).item()
       lowercase_		:      Optional[int]          =       output_from_no_past[:, next_input_ids.shape[-1] - 1, random_slice_idx].detach()
       lowercase_		:      Optional[Any]          =       output_from_past[:, 0, random_slice_idx].detach()

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





    def 			lowerCAmelCase__			(     self					:    Optional[Any]     ):






       '''simple docstring'''






       lowercase_		:      Tuple          =       self.prepare_config_and_inputs()
       (
           lowercase_						
       )		:      List[Any]          =       config_and_inputs

       lowercase_		:      Union[str, Any]          =       {
           "input_ids": input_ids,
           "attention_mask": attention_mask,
       }
       return config, inputs_dict


@require_torch
class     _UpperCAmelCase  (						snake_case			,   snake_case			,   snake_case			,   unittest.TestCase     ):
    __lowerCamelCase:				Dict						    =      (SpeechaTextaDecoder, SpeechaTextaForCausalLM) if is_torch_available() else ()
    __lowerCamelCase:				Optional[int]						    =      (SpeechaTextaForCausalLM,) if is_torch_available() else ()
    __lowerCamelCase:				Union[str, Any]						    =      {'text-generation': SpeechaTextaForCausalLM} if is_torch_available() else {}
    __lowerCamelCase:				int						    =      True
    __lowerCamelCase:				Optional[Any]						    =      False




    def 			lowerCAmelCase__			(     self					:    str					,       ):






       '''simple docstring'''






       lowercase_		:      Union[str, Any]          =       SpeechaTextaStandaloneDecoderModelTester(self					,       is_training=a     )
       lowercase_		:      Optional[int]          =       ConfigTester(self					,       config_class=a     )




    def 			lowerCAmelCase__			(     self					:    List[str]     ):






       '''simple docstring'''






       pass




    def 			lowerCAmelCase__			(     self					:    Optional[Any]     ):






       '''simple docstring'''






       pass




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






       '''simple docstring'''






       pass




    def 			lowerCAmelCase__			(     self					:    Optional[Any]     ):






       '''simple docstring'''






       self.config_tester.run_common_tests()




    def 			lowerCAmelCase__			(     self					:    Dict     ):






       '''simple docstring'''






       lowercase_		:      int          =       self.model_tester.prepare_config_and_inputs()
       self.model_tester.create_and_check_decoder_model_past(*a     )





    def 			lowerCAmelCase__			(     self					:    Optional[int]     ):






       '''simple docstring'''






       return












'''simple docstring'''
def 						__SCREAMING_SNAKE_CASE   (					_UpperCamelCase  ,						_UpperCamelCase							):


   """simple docstring"""




   sequence.append(_UpperCamelCase							)

   lowercase_		:      Union[str, Any]          =       0
   while sequence[index] != target:
      index += 1

   sequence.pop()

   if index == len(_UpperCamelCase							):
      return None

   return index


if __name__ == "__main__":
 UpperCamelCase__	=     input('Enter numbers separated by comma:\n').strip()
 UpperCamelCase__	=     [int(item) for item in user_input.split(',')]

 UpperCamelCase__	=     input('Enter a single number to be found in the list:\n')
 UpperCamelCase__	=     int(target_input)
 UpperCamelCase__	=     sentinel_linear_search(sequence, target)
 if result is not None:
  print(f"""{target} found at positions: {result}""")
 else:
  print('Not found')




