





import copy
import os
from typing import Union

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


a__:      Tuple									=		logging.get_logger(__name__)

a__:      Tuple									=		{
    '''microsoft/git-base''': '''https://huggingface.co/microsoft/git-base/resolve/main/config.json''',
}




class     SCREAMING_SNAKE_CASE__ (						a__      ):
 __SCREAMING_SNAKE_CASE							       =	"""git_vision_model"""



 def __init__(							self,__lowerCamelCase=768,__lowerCamelCase=3072,__lowerCamelCase=12,__lowerCamelCase=12,__lowerCamelCase=3,__lowerCamelCase=224,__lowerCamelCase=16,__lowerCamelCase="quick_gelu",__lowerCamelCase=1E-5,__lowerCamelCase=0.0,__lowerCamelCase=0.02,**__lowerCamelCase,):
        super().__init__(**lowerCAmelCase__ )

        A__											=						hidden_size
        A__											=						intermediate_size
        A__											=						num_hidden_layers
        A__											=						num_attention_heads
        A__											=						num_channels
        A__											=						patch_size
        A__											=						image_size
        A__											=						initializer_range
        A__											=						attention_dropout
        A__											=						layer_norm_eps
        A__											=						hidden_act




 @classmethod
 def 				UpperCamelCase			(							cls,__lowerCamelCase,**__lowerCamelCase ):
        cls._set_token_in_kwargs(lowerCAmelCase__ )

        A__											=						cls.get_config_dict(lowerCAmelCase__,**lowerCAmelCase__ )

        # get the vision config dict if we are loading from GITConfig
        if config_dict.get('''model_type''' ) == "git":
               A__											=						config_dict["vision_config"]

        if "model_type" in config_dict and hasattr(cls,'''model_type''' ) and config_dict["model_type"] != cls.model_type:
               logger.warning(
                   f"You are using a model of type {config_dict['model_type']} to instantiate a model of type "
                   f"{cls.model_type}. This is not supported for all configurations of models and can yield errors." )

        return cls.from_dict(lowerCAmelCase__,**lowerCAmelCase__ )




class     SCREAMING_SNAKE_CASE__ (						a__      ):
 __SCREAMING_SNAKE_CASE							       =	"""git"""



 def __init__(							self,__lowerCamelCase=None,__lowerCamelCase=3_0522,__lowerCamelCase=768,__lowerCamelCase=6,__lowerCamelCase=12,__lowerCamelCase=3072,__lowerCamelCase="gelu",__lowerCamelCase=0.1,__lowerCamelCase=0.1,__lowerCamelCase=1024,__lowerCamelCase=0.02,__lowerCamelCase=1E-12,__lowerCamelCase=0,__lowerCamelCase="absolute",__lowerCamelCase=True,__lowerCamelCase=False,__lowerCamelCase=101,__lowerCamelCase=102,__lowerCamelCase=None,**__lowerCamelCase,):
        super().__init__(bos_token_id=lowerCAmelCase__,eos_token_id=lowerCAmelCase__,pad_token_id=lowerCAmelCase__,**lowerCAmelCase__ )

        if vision_config is None:
               A__											=						{}
               logger.info('''vision_config is None. initializing the GitVisionConfig with default values.''' )

        A__											=						GitVisionConfig(**lowerCAmelCase__ )
        A__											=						vocab_size
        A__											=						hidden_size
        A__											=						num_hidden_layers
        A__											=						num_attention_heads
        A__											=						hidden_act
        A__											=						intermediate_size
        A__											=						hidden_dropout_prob
        A__											=						attention_probs_dropout_prob
        A__											=						max_position_embeddings
        A__											=						initializer_range
        A__											=						layer_norm_eps
        A__											=						position_embedding_type
        A__											=						use_cache
        A__											=						tie_word_embeddings
        A__											=						num_image_with_embedding

        A__											=						bos_token_id
        A__											=						eos_token_id




 def 				UpperCamelCase			(							self ):
        A__											=						copy.deepcopy(self.__dict__ )
        A__											=						self.vision_config.to_dict()
        A__											=						self.__class__.model_type
        return output












"""simple docstring"""




# Copyright 2021 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 argparse import ArgumentParser

from accelerate.commands.config import get_config_parser
from accelerate.commands.env import env_command_parser
from accelerate.commands.launch import launch_command_parser
from accelerate.commands.test import test_command_parser
from accelerate.commands.tpu import tpu_command_parser






def       _SCREAMING_SNAKE_CASE		(	) ->Dict:






	'''simple docstring'''






	a      :		Any	=				ArgumentParser("Accelerate CLI tool"    ,       usage="accelerate <command> [<args>]"    ,       allow_abbrev=_lowercase					)
	a      :		List[Any]	=				parser.add_subparsers(help="accelerate command helpers"					)

	# Register commands
	get_config_parser(subparsers=_lowercase					)
	env_command_parser(subparsers=_lowercase					)
	launch_command_parser(subparsers=_lowercase					)
	tpu_command_parser(subparsers=_lowercase					)
	test_command_parser(subparsers=_lowercase					)

	# Let's go
	a      :		List[Any]	=				parser.parse_args()

	if not hasattr(_lowercase    ,       "func"					):
		parser.print_help()
		exit(1					)

	# Run
	args.func(_lowercase					)


if __name__ == "__main__":
		main()


