


'''simple docstring'''







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

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


if TYPE_CHECKING:
  from ... import FeatureExtractionMixin, PreTrainedTokenizerBase, TensorType


a__  : Dict				=	logging.get_logger(__name__)

a__  : List[str]				=	{
    'microsoft/deberta-base': 'https://huggingface.co/microsoft/deberta-base/resolve/main/config.json',
    'microsoft/deberta-large': 'https://huggingface.co/microsoft/deberta-large/resolve/main/config.json',
    'microsoft/deberta-xlarge': 'https://huggingface.co/microsoft/deberta-xlarge/resolve/main/config.json',
    'microsoft/deberta-base-mnli': 'https://huggingface.co/microsoft/deberta-base-mnli/resolve/main/config.json',
    'microsoft/deberta-large-mnli': 'https://huggingface.co/microsoft/deberta-large-mnli/resolve/main/config.json',
    'microsoft/deberta-xlarge-mnli': 'https://huggingface.co/microsoft/deberta-xlarge-mnli/resolve/main/config.json',
}
class  lowercase_					(   a__       ):
    __UpperCAmelCase             =     'deberta'


    def __init__(					self  , a=5_02_65  , a=7_68  , a=12  , a=12  , a=30_72  , a="gelu"  , a=0.1  , a=0.1  , a=5_12  , a=0  , a=0.02  , a=1e-7  , a=False  , a=-1  , a=0  , a=True  , a=None  , a=0  , a="gelu"  , **a  , ):
          super().__init__(**a   )

          UpperCamelCase__  =    hidden_size
          UpperCamelCase__  =    num_hidden_layers
          UpperCamelCase__  =    num_attention_heads
          UpperCamelCase__  =    intermediate_size
          UpperCamelCase__  =    hidden_act
          UpperCamelCase__  =    hidden_dropout_prob
          UpperCamelCase__  =    attention_probs_dropout_prob
          UpperCamelCase__  =    max_position_embeddings
          UpperCamelCase__  =    type_vocab_size
          UpperCamelCase__  =    initializer_range
          UpperCamelCase__  =    relative_attention
          UpperCamelCase__  =    max_relative_positions
          UpperCamelCase__  =    pad_token_id
          UpperCamelCase__  =    position_biased_input

          # Backwards compatibility
          if type(a   ) == str:
                UpperCamelCase__  =    [x.strip() for x in pos_att_type.lower().split("|"   )]

          UpperCamelCase__  =    pos_att_type
          UpperCamelCase__  =    vocab_size
          UpperCamelCase__  =    layer_norm_eps

          UpperCamelCase__  =    kwargs.get("pooler_hidden_size"  , a   )
          UpperCamelCase__  =    pooler_dropout
          UpperCamelCase__  =    pooler_hidden_act

class  lowercase_					(   a__       ):


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


    @property
    def        __a							(					self   ):
          return 12


    def        __a							(					self  , a  , a = -1  , a = -1  , a = -1  , a = False  , a = None  , a = 3  , a = 40  , a = 40  , a = None  , ):
          UpperCamelCase__  =    super().generate_dummy_inputs(preprocessor=a  , framework=a   )
          if self._config.type_vocab_size == 0 and "token_type_ids" in dummy_inputs:
                del dummy_inputs["token_type_ids"]
          return dummy_inputs









'''simple docstring'''







# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_torch_available,
    is_vision_available,
)


a__  : Any				=	{
    'configuration_tvlt': ['TVLT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'TvltConfig'],
    'feature_extraction_tvlt': ['TvltFeatureExtractor'],
    'processing_tvlt': ['TvltProcessor'],
}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  a__  : int				=	[
      'TVLT_PRETRAINED_MODEL_ARCHIVE_LIST',
      'TvltModel',
      'TvltForPreTraining',
      'TvltForAudioVisualClassification',
      'TvltPreTrainedModel',
  ]

try:
  if not is_vision_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  a__  : List[Any]				=	['TvltImageProcessor']


if TYPE_CHECKING:
  from .configuration_tvlt import TVLT_PRETRAINED_CONFIG_ARCHIVE_MAP, TvltConfig
  from .processing_tvlt import TvltProcessor
  from .feature_extraction_tvlt import TvltFeatureExtractor

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_tvlt import (
        TVLT_PRETRAINED_MODEL_ARCHIVE_LIST,
        TvltForAudioVisualClassification,
        TvltForPreTraining,
        TvltModel,
        TvltPreTrainedModel,
    )

  try:
    if not is_vision_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .image_processing_tvlt import TvltImageProcessor


else:
  import sys

  a__  : Any				=	_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)





