





'''simple docstring'''







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


_lowercase       						=			logging.get_logger(__name__)

_lowercase       						=			{
    'studio-ousia/luke-base': 'https://huggingface.co/studio-ousia/luke-base/resolve/main/config.json',
    'studio-ousia/luke-large': 'https://huggingface.co/studio-ousia/luke-large/resolve/main/config.json',
}
class 			_lowercase						(       __a					):
     _UpperCAmelCase										=					'''luke'''







     def __init__( self    ,   A__=5_02_67    ,   A__=50_00_00    ,   A__=7_68    ,   A__=2_56    ,   A__=12    ,   A__=12    ,   A__=30_72    ,   A__="gelu"    ,   A__=0.1    ,   A__=0.1    ,   A__=5_12    ,   A__=2    ,   A__=0.0_2    ,   A__=1e-12    ,   A__=True    ,   A__=None    ,   A__=1    ,   A__=0    ,   A__=2    ,   **A__    ,   ) ->	List[Any]:
      super().__init__(pad_token_id=A__    ,   bos_token_id=A__    ,   eos_token_id=A__    ,   **A__    )

      snake_case				=			vocab_size
      snake_case				=			entity_vocab_size
      snake_case				=			hidden_size
      snake_case				=			entity_emb_size
      snake_case				=			num_hidden_layers
      snake_case				=			num_attention_heads
      snake_case				=			hidden_act
      snake_case				=			intermediate_size
      snake_case				=			hidden_dropout_prob
      snake_case				=			attention_probs_dropout_prob
      snake_case				=			max_position_embeddings
      snake_case				=			type_vocab_size
      snake_case				=			initializer_range
      snake_case				=			layer_norm_eps
      snake_case				=			use_entity_aware_attention
      snake_case				=			classifier_dropout








'''simple docstring'''







from ...utils import is_note_seq_available, is_transformers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable


try:
   if not (is_transformers_available() and is_torch_available()):
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   from ...utils.dummy_torch_and_transformers_objects import *  # noqa F403
else:
   from .notes_encoder import SpectrogramNotesEncoder
   from .continous_encoder import SpectrogramContEncoder
   from .pipeline_spectrogram_diffusion import (
       SpectrogramContEncoder,
       SpectrogramDiffusionPipeline,
       TaFilmDecoder,
   )

try:
   if not (is_transformers_available() and is_torch_available() and is_note_seq_available()):
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   from ...utils.dummy_transformers_and_torch_and_note_seq_objects import *  # noqa F403
else:
   from .midi_utils import MidiProcessor

