


from typing import Mapping

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


__lowerCAmelCase									=				logging.get_logger(__name__)

__lowerCAmelCase									=				{
    '''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     (       __UpperCamelCase ):
 __lowercase					:				Tuple  	=					'longt5'
 __lowercase					:				Any  	=					['past_key_values']
 __lowercase					:				Optional[Any]  	=					{'hidden_size': 'd_model', 'num_attention_heads': 'num_heads', 'num_hidden_layers': 'num_layers'}
 def __init__(  self							,					lowerCAmelCase__=32_128							,					lowerCAmelCase__=512							,					lowerCAmelCase__=64							,					lowerCAmelCase__=2_048							,					lowerCAmelCase__=6							,					lowerCAmelCase__=None							,					lowerCAmelCase__=8							,					lowerCAmelCase__=127							,					lowerCAmelCase__=16							,					lowerCAmelCase__=32							,					lowerCAmelCase__=128							,					lowerCAmelCase__=0.1							,					lowerCAmelCase__=1E-6							,					lowerCAmelCase__=1.0							,					lowerCAmelCase__="relu"							,					lowerCAmelCase__=True							,					lowerCAmelCase__="local"							,					lowerCAmelCase__=True							,					lowerCAmelCase__=0							,					lowerCAmelCase__=1							,					**lowerCAmelCase__							,					)   ->							Dict:




        '''simple docstring'''
        lowercase__:  int         =  vocab_size
        lowercase__:  List[str]         =  d_model
        lowercase__:  Any         =  d_kv
        lowercase__:  Optional[int]         =  d_ff
        lowercase__:  Tuple         =  num_layers
        # default = symmetry
        lowercase__:  str         =  num_decoder_layers if num_decoder_layers is not None else self.num_layers
        lowercase__:  List[Any]         =  num_heads
        lowercase__:  Any         =  local_radius
        lowercase__:  List[str]         =  global_block_size
        lowercase__:  Optional[int]         =  relative_attention_num_buckets
        lowercase__:  str         =  relative_attention_max_distance
        lowercase__:  Any         =  dropout_rate
        lowercase__:  List[str]         =  layer_norm_epsilon
        lowercase__:  int         =  initializer_factor
        lowercase__:  str         =  feed_forward_proj
        lowercase__:  str         =  encoder_attention_type
        lowercase__:  Any         =  use_cache

        lowercase__:  str         =  self.feed_forward_proj.split('-'					)
        lowercase__:  str         =  act_info[-1]
        lowercase__:  Dict         =  act_info[0] == 'gated'

        if len(lowerCAmelCase__					) > 1 and act_info[0] != "gated" or len(lowerCAmelCase__					) > 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":
               lowercase__:  int         =  'gelu_new'

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





class     __a     (       __UpperCamelCase ):
 @property
 def 						SCREAMING_SNAKE_CASE__  (  self					)   ->							Mapping[str, Mapping[int, str]]:




        '''simple docstring'''
        lowercase__:  Optional[Any]         =  {
            'input_ids': {0: 'batch', 1: 'encoder_sequence'},
            'attention_mask': {0: 'batch', 1: 'encoder_sequence'},
        }
        if self.use_past:
               lowercase__:  int         =  'past_encoder_sequence + sequence'
               lowercase__:  int         =  {0: 'batch'}
               lowercase__:  Tuple         =  {0: 'batch', 1: 'past_decoder_sequence + sequence'}
        else:
               lowercase__:  Tuple         =  {0: 'batch', 1: 'decoder_sequence'}
               lowercase__:  List[str]         =  {0: 'batch', 1: 'decoder_sequence'}

        if self.use_past:
               self.fill_with_past_key_values_(lowerCAmelCase__							,					direction='inputs'					)

        return common_inputs
 @property
 def 						SCREAMING_SNAKE_CASE__  (  self					)   ->							int:




        '''simple docstring'''
        return 13






from typing import TYPE_CHECKING

from ...utils import _LazyModule


__lowerCAmelCase									=				{'''tokenization_phobert''': ['''PhobertTokenizer''']}


if TYPE_CHECKING:
 from .tokenization_phobert import PhobertTokenizer

else:
 import sys

 __lowerCAmelCase									=				_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)


