




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


_UpperCAmelCase	:						List[str]			=     logging.get_logger(__name__)

_UpperCAmelCase	:						List[str]			=     {
    "microsoft/biogpt": "https://huggingface.co/microsoft/biogpt/resolve/main/config.json",
    # See all BioGPT models at https://huggingface.co/models?filter=biogpt
}




class    __lowerCAmelCase       (							lowerCAmelCase):
       _a 					=						'''biogpt'''






       def __init__(   self:					Tuple       ,					_lowerCAmelCase:					Any=4_23_84       ,					_lowerCAmelCase:					str=10_24       ,					_lowerCAmelCase:					Dict=24       ,					_lowerCAmelCase:					int=16       ,					_lowerCAmelCase:					Any=40_96       ,					_lowerCAmelCase:					List[Any]="gelu"       ,					_lowerCAmelCase:					List[Any]=0.1       ,					_lowerCAmelCase:					Dict=0.1       ,					_lowerCAmelCase:					Dict=10_24       ,					_lowerCAmelCase:					str=0.02       ,					_lowerCAmelCase:					Any=1e-1_2       ,					_lowerCAmelCase:					Optional[Any]=True       ,					_lowerCAmelCase:					List[Any]=True       ,					_lowerCAmelCase:					Any=0.0       ,					_lowerCAmelCase:					List[Any]=0.0       ,					_lowerCAmelCase:					Tuple=1       ,					_lowerCAmelCase:					Optional[Any]=0       ,					_lowerCAmelCase:					Tuple=2       ,					**_lowerCAmelCase:					int       ,					):
         lowercase    :Any      	=						vocab_size
         lowercase    :Dict      	=						max_position_embeddings
         lowercase    :Optional[int]      	=						hidden_size
         lowercase    :Union[str, Any]      	=						num_hidden_layers
         lowercase    :Tuple      	=						num_attention_heads
         lowercase    :Union[str, Any]      	=						intermediate_size
         lowercase    :List[str]      	=						hidden_act
         lowercase    :Optional[Any]      	=						hidden_dropout_prob
         lowercase    :str      	=						attention_probs_dropout_prob
         lowercase    :Union[str, Any]      	=						initializer_range
         lowercase    :Optional[Any]      	=						layer_norm_eps
         lowercase    :Optional[Any]      	=						scale_embedding
         lowercase    :Tuple      	=						use_cache
         lowercase    :List[str]      	=						layerdrop
         lowercase    :Any      	=						activation_dropout
         super().__init__(pad_token_id=_lowerCAmelCase       ,					bos_token_id=_lowerCAmelCase       ,					eos_token_id=_lowerCAmelCase       ,					**_lowerCAmelCase				)









import argparse
import shlex

import runhouse as rh


if __name__ == "__main__":
     # Refer to https://runhouse-docs.readthedocs-hosted.com/en/latest/api/python/cluster.html#hardware-setup for cloud access
     # setup instructions, if using on-demand hardware

     # If user passes --user <user> --host <host> --key_path <key_path> <example> <args>, fill them in as BYO cluster
     # If user passes --instance <instance> --provider <provider> <example> <args>, fill them in as on-demand cluster
     # Throw an error if user passes both BYO and on-demand cluster args
     # Otherwise, use default values
     _UpperCAmelCase	:						Optional[Any]			=     argparse.ArgumentParser()
     parser.add_argument("--user", type=str, default="ubuntu")
     parser.add_argument("--host", type=str, default="localhost")
     parser.add_argument("--key_path", type=str, default=None)
     parser.add_argument("--instance", type=str, default="V100:1")
     parser.add_argument("--provider", type=str, default="cheapest")
     parser.add_argument("--use_spot", type=bool, default=False)
     parser.add_argument("--example", type=str, default="pytorch/text-generation/run_generation.py")
     _UpperCAmelCase			,			_UpperCAmelCase	:						Dict			=     parser.parse_known_args()
     if args.host != "localhost":
          if args.instance != "V100:1" or args.provider != "cheapest":
               raise ValueError("Cannot specify both BYO and on-demand cluster args")
          _UpperCAmelCase	:						List[Any]			=     rh.cluster(
              name="rh-cluster", ips=[args.host], ssh_creds={"ssh_user": args.user, "ssh_private_key": args.key_path}
          )
     else:
          _UpperCAmelCase	:						Tuple			=     rh.cluster(
              name="rh-cluster", instance_type=args.instance, provider=args.provider, use_spot=args.use_spot
          )
     _UpperCAmelCase	:						Any			=     args.example.rsplit("/", 1)[0]

     # Set up remote environment
     cluster.install_packages(["pip:./"])  # Installs transformers from local source
     # Note transformers is copied into the home directory on the remote machine, so we can install from there
     cluster.run([f'''pip install -r transformers/examples/{example_dir}/requirements.txt'''])
     cluster.run(["pip install torch --upgrade --extra-index-url https://download.pytorch.org/whl/cu117"])

     # Run example. You can bypass the CLI wrapper and paste your own code here.
     cluster.run([f'''python transformers/examples/{args.example} {" ".join(shlex.quote(arg) for arg in unknown)}'''])

     # Alternatively, we can just import and run a training function (especially if there's no wrapper CLI):
     # from my_script... import train
     # reqs = ['pip:./', 'torch', 'datasets', 'accelerate', 'evaluate', 'tqdm', 'scipy', 'scikit-learn', 'tensorboard']
     # launch_train_gpu = rh.function(fn=train,
     #                                system=gpu,
     #                                reqs=reqs,
     #                                name='train_bert_glue')
     #
     # We can pass in arguments just like we would to a function:
     # launch_train_gpu(num_epochs = 3, lr = 2e-5, seed = 42, batch_size = 16
     #                  stream_logs=True)



