
"""simple docstring"""





import unittest

from transformers import load_tool
from transformers.utils import is_torch_available


if is_torch_available():
 import torch

from transformers.testing_utils import require_torch

from .test_tools_common import ToolTesterMixin





@require_torch
class 				a ( unittest.TestCase,    _SCREAMING_SNAKE_CASE							):





       """simple docstring"""







       def 				__A						(			self			)    ->				Dict:
          _UpperCAmelCase         =      load_tool("text-to-speech"			)
          self.tool.setup()






       def 				__A						(			self			)    ->				Tuple:
          # SpeechT5 isn't deterministic
          torch.manual_seed(0			)
          _UpperCAmelCase         =      self.tool("hey"			)
          _UpperCAmelCase         =      result.to_raw()
          self.assertTrue(
              torch.allclose(
                  resulting_tensor[:3]							,	torch.tensor([-0.0_00_59_66_66_88_32_11_58_29, -0.0_00_36_57_64_01_90_79_50_64, -0.00_01_34_39_50_27_99_88_34_85]			)							,	)			)






       def 				__A						(			self			)    ->				Any:
          # SpeechT5 isn't deterministic
          torch.manual_seed(0			)
          _UpperCAmelCase         =      self.tool("hey"			)
          _UpperCAmelCase         =      result.to_raw()
          self.assertTrue(
              torch.allclose(
                  resulting_tensor[:3]							,	torch.tensor([-0.0_00_59_66_66_88_32_11_58_29, -0.0_00_36_57_64_01_90_79_50_64, -0.00_01_34_39_50_27_99_88_34_85]			)							,	)			)



from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowercase   =	logging.get_logger(__name__)

lowercase   =	{
    '''abeja/gpt-neox-japanese-2.7b''': '''https://huggingface.co/abeja/gpt-neox-japanese-2.7b/resolve/main/config.json''',
}





class    __A(					UpperCAmelCase							):
					SCREAMING_SNAKE_CASE           =     '''gpt_neox_japanese'''

					def __init__(						self       :  Union[str, Any] ,       __UpperCamelCase       :  str=3_2_0_0_0 ,       __UpperCamelCase       :  List[Any]=2_5_6_0 ,       __UpperCamelCase       :  Any=3_2 ,       __UpperCamelCase       :  List[str]=3_2 ,       __UpperCamelCase       :  List[str]=4 ,       __UpperCamelCase       :  Dict="gelu" ,       __UpperCamelCase       :  List[Any]=1.00 ,       __UpperCamelCase       :  Any=1_0_0_0_0 ,       __UpperCamelCase       :  Optional[Any]=2_0_4_8 ,       __UpperCamelCase       :  Tuple=0.02 ,       __UpperCamelCase       :  List[str]=1E-5 ,       __UpperCamelCase       :  str=True ,       __UpperCamelCase       :  str=3_1_9_9_6 ,       __UpperCamelCase       :  int=3_1_9_9_9 ,       __UpperCamelCase       :  Optional[Any]=0.1 ,       __UpperCamelCase       :  Tuple=0.0 ,       **__UpperCamelCase       :  List[str] ,       ):
												super().__init__(bos_token_id=__UpperCamelCase ,       eos_token_id=__UpperCamelCase ,       **__UpperCamelCase )
												lowerCamelCase_					=       vocab_size
												lowerCamelCase_					=       max_position_embeddings
												lowerCamelCase_					=       hidden_size
												lowerCamelCase_					=       num_hidden_layers
												lowerCamelCase_					=       num_attention_heads
												lowerCamelCase_					=       intermediate_multiple_size
												lowerCamelCase_					=       hidden_act
												lowerCamelCase_					=       rotary_pct
												lowerCamelCase_					=       rotary_emb_base
												lowerCamelCase_					=       initializer_range
												lowerCamelCase_					=       layer_norm_eps
												lowerCamelCase_					=       use_cache
												lowerCamelCase_					=       attention_dropout
												lowerCamelCase_					=       hidden_dropout





