
from collections import OrderedDict
from typing import Mapping

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


__lowerCAmelCase					:			int			      =		logging.get_logger(__name__)

__lowerCAmelCase					:			str			      =		{
    "google/bigbird-roberta-base": "https://huggingface.co/google/bigbird-roberta-base/resolve/main/config.json",
    "google/bigbird-roberta-large": "https://huggingface.co/google/bigbird-roberta-large/resolve/main/config.json",
    "google/bigbird-base-trivia-itc": "https://huggingface.co/google/bigbird-base-trivia-itc/resolve/main/config.json",
    # See all BigBird models at https://huggingface.co/models?filter=big_bird
}


class 						__lowerCAmelCase	(	lowercase__      ):



      """simple docstring"""







      A__	:			Dict        =    '''big_bird'''




      def __init__(      self		:       Union[str, Any]				,       _snake_case		:       Dict=5_0358				,       _snake_case		:       str=768				,       _snake_case		:       List[Any]=12				,       _snake_case		:       Dict=12				,       _snake_case		:       str=3072				,       _snake_case		:       Dict="gelu_new"				,       _snake_case		:       Union[str, Any]=0.1				,       _snake_case		:       Dict=0.1				,       _snake_case		:       Union[str, Any]=4096				,       _snake_case		:       Any=2				,       _snake_case		:       Union[str, Any]=0.02				,       _snake_case		:       Any=1E-1_2				,       _snake_case		:       List[str]=True				,       _snake_case		:       List[Any]=0				,       _snake_case		:       Tuple=1				,       _snake_case		:       str=2				,       _snake_case		:       Optional[Any]=66				,       _snake_case		:       str="block_sparse"				,       _snake_case		:       Optional[Any]=True				,       _snake_case		:       List[Any]=False				,       _snake_case		:       Tuple=64				,       _snake_case		:       Tuple=3				,       _snake_case		:       Tuple=None				,       **_snake_case		:       Dict				,       ):
          super().__init__(
              pad_token_id=UpperCAmelCase__				,       bos_token_id=UpperCAmelCase__				,       eos_token_id=UpperCAmelCase__				,       sep_token_id=UpperCAmelCase__				,       **UpperCAmelCase__				,       )

          __lowercase		:			str	    =       vocab_size
          __lowercase		:			Tuple	    =       max_position_embeddings
          __lowercase		:			Dict	    =       hidden_size
          __lowercase		:			Dict	    =       num_hidden_layers
          __lowercase		:			List[Any]	    =       num_attention_heads
          __lowercase		:			List[str]	    =       intermediate_size
          __lowercase		:			Optional[int]	    =       hidden_act
          __lowercase		:			Optional[int]	    =       hidden_dropout_prob
          __lowercase		:			Tuple	    =       attention_probs_dropout_prob
          __lowercase		:			List[str]	    =       initializer_range
          __lowercase		:			Optional[int]	    =       type_vocab_size
          __lowercase		:			int	    =       layer_norm_eps
          __lowercase		:			Dict	    =       use_cache

          __lowercase		:			Dict	    =       rescale_embeddings
          __lowercase		:			List[Any]	    =       attention_type
          __lowercase		:			Optional[int]	    =       use_bias
          __lowercase		:			str	    =       block_size
          __lowercase		:			Dict	    =       num_random_blocks
          __lowercase		:			List[Any]	    =       classifier_dropout






class 						__lowerCAmelCase	(	lowercase__      ):



      """simple docstring"""







      @property
      def 		snake_case_			(      self		:       str				):
          if self.task == "multiple-choice":
              __lowercase		:			str	    =       {0: '''batch''', 1: '''choice''', 2: '''sequence'''}
          else:
              __lowercase		:			List[Any]	    =       {0: '''batch''', 1: '''sequence'''}
          return OrderedDict(
              [
                  ('''input_ids''', dynamic_axis),
                  ('''attention_mask''', dynamic_axis),
              ]				)


import unittest

from transformers import is_torch_available
from transformers.testing_utils import require_torch


if is_torch_available():
 import torch

 from transformers.activations import gelu_new, gelu_python, get_activation


@require_torch
class 						__lowerCAmelCase	(	unittest.TestCase      ):



      """simple docstring"""







      def 		snake_case_			(      self		:       Optional[Any]				):
          __lowercase		:			Union[str, Any]	    =       torch.tensor([-100, -1, -0.1, 0, 0.1, 1.0, 100]				)
          __lowercase		:			Any	    =       get_activation('''gelu'''				)
          self.assertTrue(torch.allclose(gelu_python(_snake_case				)				,       torch_builtin(_snake_case				)				)				)
          self.assertFalse(torch.allclose(gelu_python(_snake_case				)				,       gelu_new(_snake_case				)				)				)




      def 		snake_case_			(      self		:       Dict				):
          __lowercase		:			Any	    =       torch.tensor([-100, -1, -0.1, 0, 0.1, 1.0, 100]				)
          __lowercase		:			List[str]	    =       get_activation('''gelu'''				)
          __lowercase		:			Optional[Any]	    =       get_activation('''gelu_10'''				)

          __lowercase		:			Tuple	    =       torch_builtin(_snake_case				)
          __lowercase		:			List[Any]	    =       geluaa(_snake_case				)

          __lowercase		:			Tuple	    =       torch.where(y_gelu_aa < 10.0				,       1				,       0				)

          self.assertTrue(torch.max(_snake_case				).item() == 10.0				)
          self.assertTrue(torch.allclose(y_gelu * clipped_mask				,       y_gelu_aa * clipped_mask				)				)




      def 		snake_case_			(      self		:       Any				):
          get_activation('''gelu'''				)
          get_activation('''gelu_10'''				)
          get_activation('''gelu_fast'''				)
          get_activation('''gelu_new'''				)
          get_activation('''gelu_python'''				)
          get_activation('''gelu_pytorch_tanh'''				)
          get_activation('''linear'''				)
          get_activation('''mish'''				)
          get_activation('''quick_gelu'''				)
          get_activation('''relu'''				)
          get_activation('''sigmoid'''				)
          get_activation('''silu'''				)
          get_activation('''swish'''				)
          get_activation('''tanh'''				)
          with self.assertRaises(_snake_case				):
              get_activation('''bogus'''				)
          with self.assertRaises(_snake_case				):
              get_activation(_snake_case				)




      def 		snake_case_			(      self		:       Dict				):
          __lowercase		:			Union[str, Any]	    =       get_activation('''gelu'''				)
          __lowercase		:			List[str]	    =       1
          __lowercase		:			Union[str, Any]	    =       get_activation('''gelu'''				)
          self.assertEqual(acta.a				,       1				)
          with self.assertRaises(_snake_case				):
              __lowercase		:			Tuple	    =       acta.a


