"""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		:



    """simple docstring"""

    def __init__(     self					,    _UpperCAmelCase					,    _UpperCAmelCase=99					,    _UpperCAmelCase=13					,    _UpperCAmelCase=16					,    _UpperCAmelCase=7					,    _UpperCAmelCase=True					,    _UpperCAmelCase=True					,    _UpperCAmelCase=True					,    _UpperCAmelCase=False					,    _UpperCAmelCase=True					,    _UpperCAmelCase=2					,    _UpperCAmelCase=32					,    _UpperCAmelCase=4					,    _UpperCAmelCase=4					,    _UpperCAmelCase=30					,    _UpperCAmelCase=0					,    _UpperCAmelCase=1					,    _UpperCAmelCase=2					,    _UpperCAmelCase=None					,    ):
       lowercase__:     List[Any]      =   parent
       lowercase__:     List[str]      =   batch_size
       lowercase__:     Optional[Any]      =   decoder_seq_length
       # For common tests
       lowercase__:     List[Any]      =   self.decoder_seq_length
       lowercase__:     str      =   is_training
       lowercase__:     List[str]      =   use_attention_mask
       lowercase__:     List[str]      =   use_labels

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

       lowercase__:     Optional[Any]      =   None
       lowercase__:     Any      =   decoder_seq_length
       lowercase__:     Union[str, Any]      =   2
       lowercase__:     Tuple      =   1






    def _snake_case    (     self							):
       lowercase__:     List[str]      =   ids_tensor([self.batch_size, self.decoder_seq_length]					,    self.vocab_size							)

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

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

       lowercase__:     Union[str, Any]      =   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 _snake_case    (     self					,    _UpperCAmelCase					,    _UpperCAmelCase					,    _UpperCAmelCase					,    _UpperCAmelCase					,    ):
       lowercase__:     str      =   True
       lowercase__:     Optional[Any]      =   SpeechaTextaDecoder(config=UpperCAmelCase_							).to(UpperCAmelCase_							).eval()
       lowercase__:     Union[str, Any]      =   input_ids[:2]

       input_ids[input_ids == 0] += 1
       # first forward pass
       lowercase__:     List[Any]      =   model(UpperCAmelCase_					,    use_cache=UpperCAmelCase_							)
       lowercase__:     List[Any]      =   model(UpperCAmelCase_							)
       lowercase__:     str      =   model(UpperCAmelCase_					,    use_cache=UpperCAmelCase_							)

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

       lowercase__:     Tuple      =   outputs['past_key_values']

       # create hypothetical next token and extent to next_input_ids
       lowercase__:     Union[str, Any]      =   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(UpperCAmelCase_							)

       lowercase__:     Union[str, Any]      =   model(UpperCAmelCase_							)['last_hidden_state']
       lowercase__:     Optional[int]      =   model(UpperCAmelCase_					,    past_key_values=UpperCAmelCase_							)['last_hidden_state']

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

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






    def _snake_case    (     self							):
       lowercase__:     int      =   self.prepare_config_and_inputs()
       (
           lowercase__  
       ):     Any      =   config_and_inputs

       lowercase__:     Union[str, Any]      =   {
           'input_ids': input_ids,
           'attention_mask': attention_mask,
       }
       return config, inputs_dict



@require_torch
class 					_UpperCAmelCase		(_UpperCAmelCase					,_UpperCAmelCase					,_UpperCAmelCase					,unittest.TestCase						):



    """simple docstring"""

    _UpperCAmelCase			:List[Any]							=				(SpeechaTextaDecoder, SpeechaTextaForCausalLM) if is_torch_available() else ()
    _UpperCAmelCase			:int							=				(SpeechaTextaForCausalLM,) if is_torch_available() else ()
    _UpperCAmelCase			:List[Any]							=				{"text-generation": SpeechaTextaForCausalLM} if is_torch_available() else {}
    _UpperCAmelCase			:int							=				True
    _UpperCAmelCase			:Dict							=				False






    def _snake_case    (     self					,    ):
       lowercase__:     Optional[Any]      =   SpeechaTextaStandaloneDecoderModelTester(self					,    is_training=UpperCAmelCase_							)
       lowercase__:     Dict      =   ConfigTester(self					,    config_class=UpperCAmelCase_							)






    def _snake_case    (     self							):
       pass






    def _snake_case    (     self							):
       pass






    def _snake_case    (     self							):
       pass






    def _snake_case    (     self							):
       self.config_tester.run_common_tests()






    def _snake_case    (     self							):
       lowercase__:     int      =   self.model_tester.prepare_config_and_inputs()
       self.model_tester.create_and_check_decoder_model_past(*UpperCAmelCase_							)






    def _snake_case    (     self							):
       return

"""simple docstring"""






def SCREAMING_SNAKE_CASE__    (     __UpperCAmelCase				)						->						Optional[int]:
   lowercase__:     str      =   [7_0_1, 3_0_1, 1_3_2, 5_7, 2_3, 1_0, 4, 1]
   for gap in gaps:
      for i in range(__UpperCAmelCase ,					len(__UpperCAmelCase				)				):
         lowercase__:     Any      =   collection[i]
         lowercase__:     Tuple      =   i
         while j >= gap and collection[j - gap] > insert_value:
            lowercase__:     List[str]      =   collection[j - gap]
            j -= gap
         if j != i:
            lowercase__:     List[str]      =   insert_value
   return collection


if __name__ == "__main__":
       from doctest import testmod

       testmod()
       __A         =				input("Enter numbers separated by a comma:\n").strip()
       __A         =				[int(item) for item in user_input.split(",")]
       print(shell_sort(unsorted))
