




from collections import OrderedDict
from typing import Mapping

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


UpperCamelCase__            =     logging.get_logger(__name__)

UpperCamelCase__            =     {
    """uclanlp/plbart-base""": """https://huggingface.co/uclanlp/plbart-base/resolve/main/config.json""",
    # See all PLBART models at https://huggingface.co/models?filter=plbart
}
class      a__       (   snake_case__ ):
						_a				:       Optional[int]   =       """plbart"""
						_a				:       Optional[int]   =       ["""past_key_values"""]
						_a				:       List[Any]   =       {"""num_attention_heads""": """encoder_attention_heads""", """hidden_size""": """d_model"""}






						def __init__(  self						,     _A=5_0_0_0_5						,     _A=1_0_2_4						,     _A=6						,     _A=3_0_7_2						,     _A=1_2						,     _A=6						,     _A=3_0_7_2						,     _A=1_2						,     _A=0.0						,     _A=0.0						,     _A=True						,     _A=True						,     _A="gelu"						,     _A=7_6_8						,     _A=0.1						,     _A=0.1						,     _A=0.0						,     _A=0.02						,     _A=0.0						,     _A=True						,     _A=1						,     _A=0						,     _A=2						,     _A=2						,     **_A						,     ):




											"""simple docstring"""



											__lowerCAmelCase							  =			vocab_size
											__lowerCAmelCase							  =			max_position_embeddings
											__lowerCAmelCase							  =			d_model
											__lowerCAmelCase							  =			encoder_ffn_dim
											__lowerCAmelCase							  =			encoder_layers
											__lowerCAmelCase							  =			encoder_attention_heads
											__lowerCAmelCase							  =			decoder_ffn_dim
											__lowerCAmelCase							  =			decoder_layers
											__lowerCAmelCase							  =			decoder_attention_heads
											__lowerCAmelCase							  =			dropout
											__lowerCAmelCase							  =			attention_dropout
											__lowerCAmelCase							  =			activation_dropout
											__lowerCAmelCase							  =			activation_function
											__lowerCAmelCase							  =			init_std
											__lowerCAmelCase							  =			encoder_layerdrop
											__lowerCAmelCase							  =			decoder_layerdrop
											__lowerCAmelCase							  =			classifier_dropout
											__lowerCAmelCase							  =			use_cache
											__lowerCAmelCase							  =			encoder_layers
											__lowerCAmelCase							  =			scale_embedding  # scale factor will be sqrt(d_model) if True
											super().__init__(
											    pad_token_id=_A						,     bos_token_id=_A						,     eos_token_id=_A						,     is_encoder_decoder=_A						,     forced_eos_token_id=_A						,     **_A						,     )






class      a__       (   snake_case__ ):






						@property
						def 							__SCREAMING_SNAKE_CASE(  self     ):




											"""simple docstring"""



											return OrderedDict(
											    [
											        ("input_ids", {0: "batch", 1: "sequence"}),
											        ("attention_mask", {0: "batch", 1: "sequence"}),
											    ]     )






						@property
						def 							__SCREAMING_SNAKE_CASE(  self     ):




											"""simple docstring"""



											if self.use_past:
																return OrderedDict(
																    [
																        ("last_hidden_state", {0: "batch", 1: "sequence"}),
																        ("past_keys", {0: "batch", 2: "sequence"}),
																        ("encoder_last_hidden_state", {0: "batch", 1: "sequence"}),
																    ]     )
											else:
																return OrderedDict(
																    [
																        ("last_hidden_state", {0: "batch", 1: "sequence"}),
																        ("encoder_last_hidden_state", {0: "batch", 1: "sequence"}),
																    ]     )










import json
import logging
import os
import subprocess
from argparse import ArgumentParser


UpperCamelCase__            =     logging.getLogger(__name__)







def       _a (		):
					__lowerCAmelCase							  =			ArgumentParser()
					__lowerCAmelCase  ,				__lowerCAmelCase							  =			parser.parse_known_args()
					for arg in unknown:
										if arg.startswith(("-", "--")	):
															parser.add_argument(arg.split("="	)[0]	)

					return parser.parse_args()







def       _a (		):
					__lowerCAmelCase							  =			parse_args()
					__lowerCAmelCase							  =			88_88
					__lowerCAmelCase							  =			int(os.environ["SM_NUM_GPUS"]	)
					__lowerCAmelCase							  =			json.loads(os.environ["SM_HOSTS"]	)
					__lowerCAmelCase							  =			len(SCREAMING_SNAKE_CASE_	)
					__lowerCAmelCase							  =			os.environ["SM_CURRENT_HOST"]
					__lowerCAmelCase							  =			hosts.index(SCREAMING_SNAKE_CASE_	)
					__lowerCAmelCase							  =			"INFO"

					if num_nodes > 1:
										__lowerCAmelCase							  =			F"""python -m torch.distributed.launch \
                --nnodes={num_nodes}  \
                --node_rank={rank}  \
                --nproc_per_node={num_gpus}  \
                --master_addr={hosts[0]}  \
                --master_port={port} \
                ./run_glue.py \
                {''.join(['nested fstring' for parameter,value in args.__dict__.items()]	)}"""
					else:
										__lowerCAmelCase							  =			F"""python -m torch.distributed.launch \
            --nproc_per_node={num_gpus}  \
            ./run_glue.py \
            {''.join(['nested fstring' for parameter,value in args.__dict__.items()]	)}"""
					try:
										subprocess.run(SCREAMING_SNAKE_CASE_ , shell=SCREAMING_SNAKE_CASE_	)
					except Exception as e:
										logger.info(SCREAMING_SNAKE_CASE_	)


if __name__ == "__main__":
					main()




