
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxSeqaSeqConfigWithPast
from ...utils import logging


lowercase   =	logging.get_logger(__name__)

lowercase   =	{
    """t5-small""": """https://huggingface.co/t5-small/resolve/main/config.json""",
    """t5-base""": """https://huggingface.co/t5-base/resolve/main/config.json""",
    """t5-large""": """https://huggingface.co/t5-large/resolve/main/config.json""",
    """t5-3b""": """https://huggingface.co/t5-3b/resolve/main/config.json""",
    """t5-11b""": """https://huggingface.co/t5-11b/resolve/main/config.json""",
}





class    __A(					UpperCAmelCase							):
					SCREAMING_SNAKE_CASE           =     """t5"""
					SCREAMING_SNAKE_CASE           =     ["""past_key_values"""]
					SCREAMING_SNAKE_CASE           =     {"""hidden_size""": """d_model""", """num_attention_heads""": """num_heads""", """num_hidden_layers""": """num_layers"""}

					def __init__(						self       :  Dict ,       __UpperCamelCase       :  str=3_2_1_2_8 ,       __UpperCamelCase       :  str=5_1_2 ,       __UpperCamelCase       :  List[Any]=6_4 ,       __UpperCamelCase       :  int=2_0_4_8 ,       __UpperCamelCase       :  str=6 ,       __UpperCamelCase       :  List[str]=None ,       __UpperCamelCase       :  List[str]=8 ,       __UpperCamelCase       :  List[str]=3_2 ,       __UpperCamelCase       :  Optional[int]=1_2_8 ,       __UpperCamelCase       :  List[Any]=0.1 ,       __UpperCamelCase       :  Union[str, Any]=1E-6 ,       __UpperCamelCase       :  List[Any]=1.0 ,       __UpperCamelCase       :  Union[str, Any]="relu" ,       __UpperCamelCase       :  Union[str, Any]=True ,       __UpperCamelCase       :  int=True ,       __UpperCamelCase       :  List[str]=0 ,       __UpperCamelCase       :  str=1 ,       **__UpperCamelCase       :  List[Any] ,       ):
												lowerCamelCase_					=       vocab_size
												lowerCamelCase_					=       d_model
												lowerCamelCase_					=       d_kv
												lowerCamelCase_					=       d_ff
												lowerCamelCase_					=       num_layers
												lowerCamelCase_					=       (
												    num_decoder_layers if num_decoder_layers is not None else self.num_layers
												)  # default = symmetry
												lowerCamelCase_					=       num_heads
												lowerCamelCase_					=       relative_attention_num_buckets
												lowerCamelCase_					=       relative_attention_max_distance
												lowerCamelCase_					=       dropout_rate
												lowerCamelCase_					=       layer_norm_epsilon
												lowerCamelCase_					=       initializer_factor
												lowerCamelCase_					=       feed_forward_proj
												lowerCamelCase_					=       use_cache

												lowerCamelCase_					=       self.feed_forward_proj.split("""-""" )
												lowerCamelCase_					=       act_info[-1]
												lowerCamelCase_					=       act_info[0] == """gated"""

												if len(_lowercase ) > 1 and act_info[0] != "gated" or len(_lowercase ) > 2:
																			raise ValueError(
																			    F'''`feed_forward_proj`: {feed_forward_proj} is not a valid activation function of the dense layer.'''
																			    """Please make sure `feed_forward_proj` is of the format `gated-{ACT_FN}` or `{ACT_FN}`, e.g. """
																			    """'gated-gelu' or 'relu'""" )

												# for backwards compatibility
												if feed_forward_proj == "gated-gelu":
																			lowerCamelCase_					=       """gelu_new"""

												super().__init__(
												    pad_token_id=_lowercase ,       eos_token_id=_lowercase ,       is_encoder_decoder=_lowercase ,       **_lowercase ,       )





class    __A(					UpperCAmelCase							):

					@property
					def  lowercase__   (						self       :  str ):
												lowerCamelCase_					=       {
												    """input_ids""": {0: """batch""", 1: """encoder_sequence"""},
												    """attention_mask""": {0: """batch""", 1: """encoder_sequence"""},
												}
												if self.use_past:
																			lowerCamelCase_					=       """past_encoder_sequence + sequence"""
																			lowerCamelCase_					=       {0: """batch"""}
																			lowerCamelCase_					=       {0: """batch""", 1: """past_decoder_sequence + sequence"""}
												else:
																			lowerCamelCase_					=       {0: """batch""", 1: """decoder_sequence"""}
																			lowerCamelCase_					=       {0: """batch""", 1: """decoder_sequence"""}

												if self.use_past:
																			self.fill_with_past_key_values_(_lowercase ,       direction="""inputs""" )

												return common_inputs



					@property
					def  lowercase__   (						self       :  List[str] ):
												return 1_3








from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available


SCREAMING_SNAKE_CASE		:List[Any]						=     {"""tokenization_herbert""": ["""HerbertTokenizer"""]}

try:
 if not is_tokenizers_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 SCREAMING_SNAKE_CASE		:Union[str, Any]						=     ["""HerbertTokenizerFast"""]


if TYPE_CHECKING:
 from .tokenization_herbert import HerbertTokenizer

 try:
  if not is_tokenizers_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .tokenization_herbert_fast import HerbertTokenizerFast

else:
 import sys

 SCREAMING_SNAKE_CASE		:List[str]						=     _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)
