





from collections import OrderedDict
from typing import Mapping

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


__UpperCamelCase:	Union[str, Any] = logging.get_logger(__name__)

__UpperCamelCase:	str = {
    """camembert-base""": """https://huggingface.co/camembert-base/resolve/main/config.json""",
    """umberto-commoncrawl-cased-v1""": (
        """https://huggingface.co/Musixmatch/umberto-commoncrawl-cased-v1/resolve/main/config.json"""
    ),
    """umberto-wikipedia-uncased-v1""": (
        """https://huggingface.co/Musixmatch/umberto-wikipedia-uncased-v1/resolve/main/config.json"""
    ),
}


class       __lowerCAmelCase					(       _UpperCamelCase      ):


	'''simple docstring'''





	_A													=				"camembert"

	def __init__(						self:						Union[str, Any],					lowerCamelCase_:						List[Any]=30522,					lowerCamelCase_:						List[str]=768,					lowerCamelCase_:						List[str]=12,					lowerCamelCase_:						Tuple=12,					lowerCamelCase_:						List[Any]=3072,					lowerCamelCase_:						Union[str, Any]="gelu",					lowerCamelCase_:						Dict=0.1,					lowerCamelCase_:						Union[str, Any]=0.1,					lowerCamelCase_:						Any=512,					lowerCamelCase_:						int=2,					lowerCamelCase_:						int=0.0_2,					lowerCamelCase_:						Optional[Any]=1E-12,					lowerCamelCase_:						Optional[int]=1,					lowerCamelCase_:						Union[str, Any]=0,					lowerCamelCase_:						Optional[int]=2,					lowerCamelCase_:						Dict="absolute",					lowerCamelCase_:						Optional[Any]=True,					lowerCamelCase_:						Union[str, Any]=None,					**lowerCamelCase_:						str,					):
			super().__init__(pad_token_id=lowerCamelCase_,					bos_token_id=lowerCamelCase_,					eos_token_id=lowerCamelCase_,					**lowerCamelCase_			)

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


class       __lowerCAmelCase					(       _UpperCamelCase      ):


	'''simple docstring'''





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









# 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

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


__UpperCamelCase:	List[Any] = {
    """configuration_efficientnet""": [
        """EFFICIENTNET_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """EfficientNetConfig""",
        """EfficientNetOnnxConfig""",
    ]
}

try:
			if not is_vision_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			__UpperCamelCase:	Dict = ["""EfficientNetImageProcessor"""]

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			__UpperCamelCase:	Dict = [
			    """EFFICIENTNET_PRETRAINED_MODEL_ARCHIVE_LIST""",
			    """EfficientNetForImageClassification""",
			    """EfficientNetModel""",
			    """EfficientNetPreTrainedModel""",
			]

if TYPE_CHECKING:
			from .configuration_efficientnet import (
			    EFFICIENTNET_PRETRAINED_CONFIG_ARCHIVE_MAP,
			    EfficientNetConfig,
			    EfficientNetOnnxConfig,
			)

			try:
						if not is_vision_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .image_processing_efficientnet import EfficientNetImageProcessor

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_efficientnet import (
						    EFFICIENTNET_PRETRAINED_MODEL_ARCHIVE_LIST,
						    EfficientNetForImageClassification,
						    EfficientNetModel,
						    EfficientNetPreTrainedModel,
						)

else:
			import sys

			__UpperCamelCase:	List[str] = _LazyModule(__name__, globals()["""__file__"""], _import_structure)


