
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional, Union

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


if TYPE_CHECKING:
    from ...onnx.config import PatchingSpec
    from ...tokenization_utils_base import PreTrainedTokenizerBase


lowerCamelCase_						     =					logging.get_logger(__name__)

lowerCamelCase_						     =					{
    '''allenai/longformer-base-4096''': '''https://huggingface.co/allenai/longformer-base-4096/resolve/main/config.json''',
    '''allenai/longformer-large-4096''': '''https://huggingface.co/allenai/longformer-large-4096/resolve/main/config.json''',
    '''allenai/longformer-large-4096-finetuned-triviaqa''': (
        '''https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/config.json'''
    ),
    '''allenai/longformer-base-4096-extra.pos.embd.only''': (
        '''https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/config.json'''
    ),
    '''allenai/longformer-large-4096-extra.pos.embd.only''': (
        '''https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/config.json'''
    ),
}




class      __A(    __lowerCamelCase			):

  """simple docstring"""
  SCREAMING_SNAKE_CASE__         =      """longformer"""







  def __init__(self	,      SCREAMING_SNAKE_CASE_ = 5_12	,      SCREAMING_SNAKE_CASE_ = 2	,      SCREAMING_SNAKE_CASE_ = 1	,      SCREAMING_SNAKE_CASE_ = 0	,      SCREAMING_SNAKE_CASE_ = 2	,      SCREAMING_SNAKE_CASE_ = 3_05_22	,      SCREAMING_SNAKE_CASE_ = 7_68	,      SCREAMING_SNAKE_CASE_ = 12	,      SCREAMING_SNAKE_CASE_ = 12	,      SCREAMING_SNAKE_CASE_ = 30_72	,      SCREAMING_SNAKE_CASE_ = "gelu"	,      SCREAMING_SNAKE_CASE_ = 0.1	,      SCREAMING_SNAKE_CASE_ = 0.1	,      SCREAMING_SNAKE_CASE_ = 5_12	,      SCREAMING_SNAKE_CASE_ = 2	,      SCREAMING_SNAKE_CASE_ = 0.02	,      SCREAMING_SNAKE_CASE_ = 1E-12	,      SCREAMING_SNAKE_CASE_ = False	,      **SCREAMING_SNAKE_CASE_	,      ):
       super().__init__(pad_token_id=SCREAMING_SNAKE_CASE_	,      **SCREAMING_SNAKE_CASE_						)

       UpperCamelCase__				=    attention_window
       UpperCamelCase__				=    sep_token_id
       UpperCamelCase__				=    bos_token_id
       UpperCamelCase__				=    eos_token_id
       UpperCamelCase__				=    vocab_size
       UpperCamelCase__				=    hidden_size
       UpperCamelCase__				=    num_hidden_layers
       UpperCamelCase__				=    num_attention_heads
       UpperCamelCase__				=    hidden_act
       UpperCamelCase__				=    intermediate_size
       UpperCamelCase__				=    hidden_dropout_prob
       UpperCamelCase__				=    attention_probs_dropout_prob
       UpperCamelCase__				=    max_position_embeddings
       UpperCamelCase__				=    type_vocab_size
       UpperCamelCase__				=    initializer_range
       UpperCamelCase__				=    layer_norm_eps
       UpperCamelCase__				=    onnx_export






class      __A(    __lowerCamelCase			):

  """simple docstring"""







  def __init__(self	,      SCREAMING_SNAKE_CASE_	,      SCREAMING_SNAKE_CASE_ = "default"	,      SCREAMING_SNAKE_CASE_ = None						):
       super().__init__(SCREAMING_SNAKE_CASE_	,      SCREAMING_SNAKE_CASE_	,      SCREAMING_SNAKE_CASE_						)
       UpperCamelCase__				=    True







  @property
  def 	UpperCAmelCase_ (self						):
       if self.task == "multiple-choice":
            UpperCamelCase__				=    {0: """batch""", 1: """choice""", 2: """sequence"""}
       else:
            UpperCamelCase__				=    {0: """batch""", 1: """sequence"""}
       return OrderedDict(
           [
               ("""input_ids""", dynamic_axis),
               ("""attention_mask""", dynamic_axis),
               ("""global_attention_mask""", dynamic_axis),
           ]						)







  @property
  def 	UpperCAmelCase_ (self						):
       UpperCamelCase__				=    super().outputs
       if self.task == "default":
            UpperCamelCase__				=    {0: """batch"""}
       return outputs







  @property
  def 	UpperCAmelCase_ (self						):
       return 1E-4







  @property
  def 	UpperCAmelCase_ (self						):
       # needs to be >= 14 to support tril operator
       return max(super().default_onnx_opset	,      14						)







  def 	UpperCAmelCase_ (self	,      SCREAMING_SNAKE_CASE_	,      SCREAMING_SNAKE_CASE_ = -1	,      SCREAMING_SNAKE_CASE_ = -1	,      SCREAMING_SNAKE_CASE_ = False	,      SCREAMING_SNAKE_CASE_ = None	,      ):
       UpperCamelCase__				=    super().generate_dummy_inputs(
           preprocessor=SCREAMING_SNAKE_CASE_	,      batch_size=SCREAMING_SNAKE_CASE_	,      seq_length=SCREAMING_SNAKE_CASE_	,      is_pair=SCREAMING_SNAKE_CASE_	,      framework=SCREAMING_SNAKE_CASE_						)
       import torch

       # for some reason, replacing this code by inputs["global_attention_mask"] = torch.randint(2, inputs["input_ids"].shape, dtype=torch.int64)
       # makes the export fail randomly
       UpperCamelCase__				=    torch.zeros_like(inputs["""input_ids"""]						)
       # make every second token global
       UpperCamelCase__				=    1

       return inputs







from typing import TYPE_CHECKING

from ...utils import _LazyModule


lowerCamelCase_						     =					{'''processing_wav2vec2_with_lm''': ['''Wav2Vec2ProcessorWithLM''']}


if TYPE_CHECKING:
    from .processing_wavaveca_with_lm import WavaVecaProcessorWithLM
else:
    import sys

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





