




# 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      lowerCamelCase_						(			)	->			Union[str, Any]:





				"""simple docstring"""


				__lowerCamelCase									=       ArgumentParser('Accelerate CLI tool'					,	usage='accelerate <command> [<args>]'					,	allow_abbrev=UpperCamelCase__ )
				__lowerCamelCase									=       parser.add_subparsers(help='accelerate command helpers' )

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

				# Let's go
				__lowerCamelCase									=       parser.parse_args()

				if not hasattr(UpperCamelCase__					,	'func' ):
								parser.print_help()
								exit(1 )

				# Run
				args.func(UpperCamelCase__ )


if __name__ == "__main__":
					main()








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


__A								=       logging.get_logger(__name__)

__A								=       {
    "unc-nlp/lxmert-base-uncased": "https://huggingface.co/unc-nlp/lxmert-base-uncased/resolve/main/config.json",
}







class        __lowerCAmelCase					(			__magic_name__					):

			"""simple docstring"""







			snake_case_  						=			'''lxmert'''
			snake_case_  						=			{}


			def __init__( self     ,		lowerCamelCase__=30_522     ,		lowerCamelCase__=768     ,		lowerCamelCase__=12     ,		lowerCamelCase__=9_500     ,		lowerCamelCase__=1_600     ,		lowerCamelCase__=400     ,		lowerCamelCase__=3_072     ,		lowerCamelCase__="gelu"     ,		lowerCamelCase__=0.1     ,		lowerCamelCase__=0.1     ,		lowerCamelCase__=512     ,		lowerCamelCase__=2     ,		lowerCamelCase__=0.02     ,		lowerCamelCase__=1e-12     ,		lowerCamelCase__=9     ,		lowerCamelCase__=5     ,		lowerCamelCase__=5     ,		lowerCamelCase__=2_048     ,		lowerCamelCase__=4     ,		lowerCamelCase__=6.67     ,		lowerCamelCase__=True     ,		lowerCamelCase__=True     ,		lowerCamelCase__=True     ,		lowerCamelCase__=True     ,		lowerCamelCase__=True     ,		lowerCamelCase__=True     ,		lowerCamelCase__=True     ,		**lowerCamelCase__     ,		)       -> Optional[int]:



							'''simple docstring'''
							__lowerCamelCase									=       vocab_size
							__lowerCamelCase									=       hidden_size
							__lowerCamelCase									=       num_attention_heads
							__lowerCamelCase									=       hidden_act
							__lowerCamelCase									=       intermediate_size
							__lowerCamelCase									=       hidden_dropout_prob
							__lowerCamelCase									=       attention_probs_dropout_prob
							__lowerCamelCase									=       max_position_embeddings
							__lowerCamelCase									=       type_vocab_size
							__lowerCamelCase									=       initializer_range
							__lowerCamelCase									=       layer_norm_eps
							__lowerCamelCase									=       num_qa_labels
							__lowerCamelCase									=       num_object_labels
							__lowerCamelCase									=       num_attr_labels
							__lowerCamelCase									=       l_layers
							__lowerCamelCase									=       x_layers
							__lowerCamelCase									=       r_layers
							__lowerCamelCase									=       visual_feat_dim
							__lowerCamelCase									=       visual_pos_dim
							__lowerCamelCase									=       visual_loss_normalizer
							__lowerCamelCase									=       task_matched
							__lowerCamelCase									=       task_mask_lm
							__lowerCamelCase									=       task_obj_predict
							__lowerCamelCase									=       task_qa
							__lowerCamelCase									=       visual_obj_loss
							__lowerCamelCase									=       visual_attr_loss
							__lowerCamelCase									=       visual_feat_loss
							__lowerCamelCase									=       {'vision': r_layers, 'cross_encoder': x_layers, 'language': l_layers}
							super().__init__(**lowerCamelCase__				)


