
'''simple docstring'''



from typing import Mapping

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


UpperCamelCase__					:						Dict											=     logging.get_logger(__name__)

UpperCamelCase__					:						List[Any]											=     {
    "google/long-t5-local-base": "https://huggingface.co/google/long-t5-local-base/blob/main/config.json",
    "google/long-t5-local-large": "https://huggingface.co/google/long-t5-local-large/blob/main/config.json",
    "google/long-t5-tglobal-base": "https://huggingface.co/google/long-t5-tglobal-base/blob/main/config.json",
    "google/long-t5-tglobal-large": "https://huggingface.co/google/long-t5-tglobal-large/blob/main/config.json",
}

class       _a (_lowerCamelCase):





       """simple docstring"""




       SCREAMING_SNAKE_CASE					=     'longt5'
       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				,							A__=3_21_28				,							A__=5_12				,							A__=64				,							A__=20_48				,							A__=6				,							A__=None				,							A__=8				,							A__=1_27				,							A__=16				,							A__=32				,							A__=1_28				,							A__=0.1				,							A__=1E-6				,							A__=1.0				,							A__="relu"				,							A__=True				,							A__="local"				,							A__=True				,							A__=0				,							A__=1				,							**A__				,							)			->	Dict:
          _SCREAMING_SNAKE_CASE          = vocab_size
          _SCREAMING_SNAKE_CASE          = d_model
          _SCREAMING_SNAKE_CASE          = d_kv
          _SCREAMING_SNAKE_CASE          = d_ff
          _SCREAMING_SNAKE_CASE          = num_layers
          # default = symmetry
          _SCREAMING_SNAKE_CASE          = num_decoder_layers if num_decoder_layers is not None else self.num_layers
          _SCREAMING_SNAKE_CASE          = num_heads
          _SCREAMING_SNAKE_CASE          = local_radius
          _SCREAMING_SNAKE_CASE          = global_block_size
          _SCREAMING_SNAKE_CASE          = relative_attention_num_buckets
          _SCREAMING_SNAKE_CASE          = relative_attention_max_distance
          _SCREAMING_SNAKE_CASE          = dropout_rate
          _SCREAMING_SNAKE_CASE          = layer_norm_epsilon
          _SCREAMING_SNAKE_CASE          = initializer_factor
          _SCREAMING_SNAKE_CASE          = feed_forward_proj
          _SCREAMING_SNAKE_CASE          = encoder_attention_type
          _SCREAMING_SNAKE_CASE          = use_cache

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

          if len(A__					) > 1 and act_info[0] != "gated" or len(A__					) > 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":
             _SCREAMING_SNAKE_CASE          = """gelu_new"""

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






class       _a (_lowerCamelCase):





       """simple docstring"""




       @property
       def 				UpperCamelCase (							self					)			->	Mapping[str, Mapping[int, str]]:
          _SCREAMING_SNAKE_CASE          = {
              """input_ids""": {0: """batch""", 1: """encoder_sequence"""},
              """attention_mask""": {0: """batch""", 1: """encoder_sequence"""},
          }
          if self.use_past:
             _SCREAMING_SNAKE_CASE          = """past_encoder_sequence + sequence"""
             _SCREAMING_SNAKE_CASE          = {0: """batch"""}
             _SCREAMING_SNAKE_CASE          = {0: """batch""", 1: """past_decoder_sequence + sequence"""}
          else:
             _SCREAMING_SNAKE_CASE          = {0: """batch""", 1: """decoder_sequence"""}
             _SCREAMING_SNAKE_CASE          = {0: """batch""", 1: """decoder_sequence"""}

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

          return common_inputs






       @property
       def 				UpperCamelCase (							self					)			->	int:
          return 13








'''simple docstring'''



from ..utils import deprecate
from .attention_processor import (  # noqa: F401
    Attention,
    AttentionProcessor,
    AttnAddedKVProcessor,
    AttnProcessor2_0,
    LoRAAttnProcessor,
    LoRALinearLayer,
    LoRAXFormersAttnProcessor,
    SlicedAttnAddedKVProcessor,
    SlicedAttnProcessor,
    XFormersAttnProcessor,
)
from .attention_processor import AttnProcessor as AttnProcessorRename  # noqa: F401


deprecate(
    "cross_attention",
    "0.20.0",
    "Importing from cross_attention is deprecated. Please import from diffusers.models.attention_processor instead.",
    standard_warn=False,
)


UpperCamelCase__					:						str											=     AttentionProcessor

class       _a (_lowerCamelCase):





       """simple docstring"""




       def __init__(							self				,							*A__				,							**A__					)			->	int:
          _SCREAMING_SNAKE_CASE          = F"{self.__class__.__name__} is deprecated and will be removed in `0.20.0`. Please use `from diffusers.models.attention_processor import {''.join(self.__class__.__name__.split('Cross'					)					)} instead."
          deprecate("""cross_attention"""				,							"""0.20.0"""				,							A__				,							standard_warn=A__					)
          super().__init__(*A__				,							**A__					)






class       _a (_lowerCamelCase):





       """simple docstring"""




       def __init__(							self				,							*A__				,							**A__					)			->	Any:
          _SCREAMING_SNAKE_CASE          = F"{self.__class__.__name__} is deprecated and will be removed in `0.20.0`. Please use `from diffusers.models.attention_processor import {''.join(self.__class__.__name__.split('Cross'					)					)} instead."
          deprecate("""cross_attention"""				,							"""0.20.0"""				,							A__				,							standard_warn=A__					)
          super().__init__(*A__				,							**A__					)






class       _a (_lowerCamelCase):





       """simple docstring"""




       def __init__(							self				,							*A__				,							**A__					)			->	List[str]:
          _SCREAMING_SNAKE_CASE          = F"{self.__class__.__name__} is deprecated and will be removed in `0.20.0`. Please use `from diffusers.models.attention_processor import {''.join(self.__class__.__name__.split('Cross'					)					)} instead."
          deprecate("""cross_attention"""				,							"""0.20.0"""				,							A__				,							standard_warn=A__					)
          super().__init__(*A__				,							**A__					)






class       _a (_lowerCamelCase):





       """simple docstring"""




       def __init__(							self				,							*A__				,							**A__					)			->	Tuple:
          _SCREAMING_SNAKE_CASE          = F"{self.__class__.__name__} is deprecated and will be removed in `0.20.0`. Please use `from diffusers.models.attention_processor import {''.join(self.__class__.__name__.split('Cross'					)					)} instead."
          deprecate("""cross_attention"""				,							"""0.20.0"""				,							A__				,							standard_warn=A__					)
          super().__init__(*A__				,							**A__					)






class       _a (_lowerCamelCase):





       """simple docstring"""




       def __init__(							self				,							*A__				,							**A__					)			->	str:
          _SCREAMING_SNAKE_CASE          = F"{self.__class__.__name__} is deprecated and will be removed in `0.20.0`. Please use `from diffusers.models.attention_processor import {''.join(self.__class__.__name__.split('Cross'					)					)} instead."
          deprecate("""cross_attention"""				,							"""0.20.0"""				,							A__				,							standard_warn=A__					)
          super().__init__(*A__				,							**A__					)






class       _a (_lowerCamelCase):





       """simple docstring"""




       def __init__(							self				,							*A__				,							**A__					)			->	Union[str, Any]:
          _SCREAMING_SNAKE_CASE          = F"{self.__class__.__name__} is deprecated and will be removed in `0.20.0`. Please use `from diffusers.models.attention_processor import {''.join(self.__class__.__name__.split('Cross'					)					)} instead."
          deprecate("""cross_attention"""				,							"""0.20.0"""				,							A__				,							standard_warn=A__					)
          super().__init__(*A__				,							**A__					)






class       _a (_lowerCamelCase):





       """simple docstring"""




       def __init__(							self				,							*A__				,							**A__					)			->	str:
          _SCREAMING_SNAKE_CASE          = F"{self.__class__.__name__} is deprecated and will be removed in `0.20.0`. Please use `from diffusers.models.attention_processor import {''.join(self.__class__.__name__.split('Cross'					)					)} instead."
          deprecate("""cross_attention"""				,							"""0.20.0"""				,							A__				,							standard_warn=A__					)
          super().__init__(*A__				,							**A__					)






class       _a (_lowerCamelCase):





       """simple docstring"""




       def __init__(							self				,							*A__				,							**A__					)			->	Any:
          _SCREAMING_SNAKE_CASE          = F"{self.__class__.__name__} is deprecated and will be removed in `0.20.0`. Please use `from diffusers.models.attention_processor import {''.join(self.__class__.__name__.split('Cross'					)					)} instead."
          deprecate("""cross_attention"""				,							"""0.20.0"""				,							A__				,							standard_warn=A__					)
          super().__init__(*A__				,							**A__					)






