



"""simple docstring"""


from ...configuration_utils import PretrainedConfig
from ...utils import logging


snake_case_    					=	logging.get_logger(__name__)

snake_case_    					=	{
    """google/vivit-b-16x2-kinetics400""": (
        """https://huggingface.co/google/vivit-b-16x2-kinetics400/resolve/main/config.json"""
    ),
    # See all Vivit models at https://huggingface.co/models?filter=vivit
}







class 				A_      (					SCREAMING_SNAKE_CASE_    ):



						"""simple docstring"""
						__UpperCamelCase		    =							"""vivit"""






						def __init__( self			:List[str]       ,  lowercase_			:Dict=2_24       ,  lowercase_			:List[Any]=32       ,  lowercase_			:Optional[Any]=[2, 16, 16]       ,  lowercase_			:Union[str, Any]=3       ,  lowercase_			:int=7_68       ,  lowercase_			:Tuple=12       ,  lowercase_			:Tuple=12       ,  lowercase_			:Union[str, Any]=30_72       ,  lowercase_			:Tuple="gelu_fast"       ,  lowercase_			:Dict=0.0       ,  lowercase_			:Union[str, Any]=0.0       ,  lowercase_			:str=0.02       ,  lowercase_			:Optional[Any]=1E-06       ,  lowercase_			:Tuple=True       ,  **lowercase_			:Tuple       ,  )    ->      List[Any]:
												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					=			initializer_range
												UpperCAmelCase					=			layer_norm_eps

												UpperCAmelCase					=			image_size
												UpperCAmelCase					=			num_frames
												UpperCAmelCase					=			tubelet_size
												UpperCAmelCase					=			num_channels
												UpperCAmelCase					=			qkv_bias

												super().__init__(**lowercase_ )










"""simple docstring"""


# Copyright 2022 The HuggingFace Team and The OpenBMB 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_tokenizers_available, is_torch_available


snake_case_    					=	{
    """configuration_cpmant""": ["""CPMANT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """CpmAntConfig"""],
    """tokenization_cpmant""": ["""CpmAntTokenizer"""],
}

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				snake_case_    					=	[
				    """CPMANT_PRETRAINED_MODEL_ARCHIVE_LIST""",
				    """CpmAntForCausalLM""",
				    """CpmAntModel""",
				    """CpmAntPreTrainedModel""",
				]


if TYPE_CHECKING:
				from .configuration_cpmant import CPMANT_PRETRAINED_CONFIG_ARCHIVE_MAP, CpmAntConfig
				from .tokenization_cpmant import CpmAntTokenizer

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_cpmant import (
								    CPMANT_PRETRAINED_MODEL_ARCHIVE_LIST,
								    CpmAntForCausalLM,
								    CpmAntModel,
								    CpmAntPreTrainedModel,
								)


else:
				import sys

				snake_case_    					=	_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)





