






'''simple docstring'''
from collections import OrderedDict
from typing import Mapping

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


_UpperCamelCase											=			logging.get_logger(__name__)

_UpperCamelCase											=			{
    'squeezebert/squeezebert-uncased': (
        'https://huggingface.co/squeezebert/squeezebert-uncased/resolve/main/config.json'
    ),
    'squeezebert/squeezebert-mnli': 'https://huggingface.co/squeezebert/squeezebert-mnli/resolve/main/config.json',
    'squeezebert/squeezebert-mnli-headless': (
        'https://huggingface.co/squeezebert/squeezebert-mnli-headless/resolve/main/config.json'
    ),
}



class _A  (    A__    ):
		_SCREAMING_SNAKE_CASE					:    List[str]						      =			SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP
		_SCREAMING_SNAKE_CASE					:    str						      =			"squeezebert"





		def __init__(     self ,       __UpperCAmelCase=30_522 ,       __UpperCAmelCase=768 ,       __UpperCAmelCase=12 ,       __UpperCAmelCase=12 ,       __UpperCAmelCase=3_072 ,       __UpperCAmelCase="gelu" ,       __UpperCAmelCase=0.1 ,       __UpperCAmelCase=0.1 ,       __UpperCAmelCase=512 ,       __UpperCAmelCase=2 ,       __UpperCAmelCase=0.02 ,       __UpperCAmelCase=1E-12 ,       __UpperCAmelCase=0 ,       __UpperCAmelCase=768 ,       __UpperCAmelCase=4 ,       __UpperCAmelCase=4 ,       __UpperCAmelCase=4 ,       __UpperCAmelCase=1 ,       __UpperCAmelCase=4 ,       __UpperCAmelCase=4 ,       **__UpperCAmelCase ,       )       ->     Union[str, Any]:

					'''simple docstring'''
					super().__init__(pad_token_id=_lowerCAmelCase ,       **_lowerCAmelCase				)

					__UpperCAmelCase   :      Optional[Any]										=     vocab_size
					__UpperCAmelCase   :      str										=     hidden_size
					__UpperCAmelCase   :      Any										=     num_hidden_layers
					__UpperCAmelCase   :      Optional[Any]										=     num_attention_heads
					__UpperCAmelCase   :      Dict										=     hidden_act
					__UpperCAmelCase   :      List[Any]										=     intermediate_size
					__UpperCAmelCase   :      Optional[Any]										=     hidden_dropout_prob
					__UpperCAmelCase   :      List[str]										=     attention_probs_dropout_prob
					__UpperCAmelCase   :      Tuple										=     max_position_embeddings
					__UpperCAmelCase   :      Tuple										=     type_vocab_size
					__UpperCAmelCase   :      str										=     initializer_range
					__UpperCAmelCase   :      Union[str, Any]										=     layer_norm_eps
					__UpperCAmelCase   :      Optional[Any]										=     embedding_size
					__UpperCAmelCase   :      Optional[int]										=     q_groups
					__UpperCAmelCase   :      Optional[int]										=     k_groups
					__UpperCAmelCase   :      Optional[int]										=     v_groups
					__UpperCAmelCase   :      int										=     post_attention_groups
					__UpperCAmelCase   :      Optional[Any]										=     intermediate_groups
					__UpperCAmelCase   :      Any										=     output_groups



class _A  (    A__    ):





		@property
		def 							__A       (     self				)       ->     Tuple:

					'''simple docstring'''
					if self.task == "multiple-choice":
								__UpperCAmelCase   :      Union[str, Any]										=     {0: """batch""", 1: """choice""", 2: """sequence"""}
					else:
								__UpperCAmelCase   :      List[str]										=     {0: """batch""", 1: """sequence"""}
					return OrderedDict(
					    [
					        ("""input_ids""", dynamic_axis),
					        ("""attention_mask""", dynamic_axis),
					        ("""token_type_ids""", dynamic_axis),
					    ]				)









'''simple docstring'''
from .chunk_utils import chunk_layer
from .data_transforms import make_atomaa_masks
from .feats import atomaa_to_atomaa, frames_and_literature_positions_to_atomaa_pos, torsion_angles_to_frames
from .loss import compute_predicted_aligned_error, compute_tm
from .protein import Protein as OFProtein
from .protein import to_pdb
from .rigid_utils import Rigid, Rotation
from .tensor_utils import dict_multimap, flatten_final_dims, permute_final_dims




