

"""simple docstring"""




# Copyright 2022 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.

import argparse
import os
import subprocess

from packaging.version import Version, parse

from accelerate.commands.config.config_args import default_config_file, load_config_from_file


__UpperCAmelCase =				'Run commands across TPU VMs for initial setup before running `accelerate launch`.'
def   lowerCAmelCase						(					__UpperCamelCase=None      ):
 '''simple docstring'''





 if subparsers is not None:
  UpperCAmelCase__					:  Union[str, Any]					   =					subparsers.add_parser("""tpu-config"""							,    description=_description      )
 else:
  UpperCAmelCase__					:  Optional[int]					   =					argparse.ArgumentParser("""Accelerate tpu-config command"""							,    description=_description      )
 # Core arguments
 UpperCAmelCase__					:  Optional[Any]					   =					parser.add_argument_group(
     """Config Arguments"""							,    """Arguments that can be configured through `accelerate config`."""      )
 config_args.add_argument(
     """--config_file"""							,    type=__UpperCamelCase							,    default=__UpperCamelCase							,    help="""Path to the config file to use for accelerate."""							,    )
 config_args.add_argument(
     """--tpu_name"""							,    default=__UpperCamelCase							,    help="""The name of the TPU to use. If not specified, will use the TPU specified in the config file."""							,    )
 config_args.add_argument(
     """--tpu_zone"""							,    default=__UpperCamelCase							,    help="""The zone of the TPU to use. If not specified, will use the zone specified in the config file."""							,    )
 UpperCAmelCase__					:  str					   =					parser.add_argument_group("""TPU Arguments"""							,    """Arguments for options ran inside the TPU."""      )
 pod_args.add_argument(
     """--use_alpha"""							,    action="""store_true"""							,    help="""Whether to use `gcloud alpha` when running the TPU training script instead of `gcloud`."""							,    )
 pod_args.add_argument(
     """--command_file"""							,    default=__UpperCamelCase							,    help="""The path to the file containing the commands to run on the pod on startup."""							,    )
 pod_args.add_argument(
     """--command"""							,    action="""append"""							,    nargs="""+"""							,    help="""A command to run on the pod. Can be passed multiple times."""							,    )
 pod_args.add_argument(
     """--install_accelerate"""							,    action="""store_true"""							,    help="""Whether to install accelerate on the pod. Defaults to False."""							,    )
 pod_args.add_argument(
     """--accelerate_version"""							,    default="""latest"""							,    help="""The version of accelerate to install on the pod. If not specified, will use the latest pypi version. Specify 'dev' to install from GitHub."""							,    )
 pod_args.add_argument(
     """--debug"""							,    action="""store_true"""							,    help="""If set, will print the command that would be run instead of running it."""      )

 if subparsers is not None:
  parser.set_defaults(func=__UpperCamelCase      )
 return parser
def   lowerCAmelCase						(					__UpperCamelCase      ):
 '''simple docstring'''





 UpperCAmelCase__					:  List[str]					   =					None

 # Get the default from the config file if it exists.
 if args.config_file is not None or os.path.isfile(__UpperCamelCase      ):
  UpperCAmelCase__					:  Any					   =					load_config_from_file(args.config_file      )
  if not args.command_file and defaults.command_file is not None and not args.command:
   UpperCAmelCase__					:  Any					   =					defaults.command_file
  if not args.command and defaults.commands is not None:
   UpperCAmelCase__					:  Tuple					   =					defaults.commands
  if not args.tpu_name:
   UpperCAmelCase__					:  int					   =					defaults.tpu_name
  if not args.tpu_zone:
   UpperCAmelCase__					:  Union[str, Any]					   =					defaults.tpu_zone
 if args.accelerate_version == "dev":
  UpperCAmelCase__					:  Union[str, Any]					   =					"""git+https://github.com/huggingface/accelerate.git"""
 elif args.accelerate_version == "latest":
  UpperCAmelCase__					:  Tuple					   =					"""accelerate -U"""
 elif isinstance(parse(args.accelerate_version      )							,    __UpperCamelCase      ):
  UpperCAmelCase__					:  str					   =					F"accelerate=={args.accelerate_version}"

 if not args.command_file and not args.command:
  raise ValueError("""You must specify either a command file or a command to run on the pod."""      )

 if args.command_file:
  with open(args.command_file							,    """r"""      ) as f:
   UpperCAmelCase__					:  int					   =					[f.read().splitlines()]

    # To turn list of lists into list of strings
 if isinstance(args.command[0]							,    __UpperCamelCase      ):
  UpperCAmelCase__					:  List[Any]					   =					[line for cmd in args.command for line in cmd]
 # Default to the shared folder and install accelerate
 UpperCAmelCase__					:  Any					   =					["""cd /usr/share"""]
 if args.install_accelerate:
  new_cmd += [F"pip install {args.accelerate_version}"]
 new_cmd += args.command
 UpperCAmelCase__					:  Optional[Any]					   =					"""; """.join(__UpperCamelCase      )

 # Then send it to gcloud
 # Eventually try to use google-api-core to do this instead of subprocess
 UpperCAmelCase__					:  Dict					   =					["""gcloud"""]
 if args.use_alpha:
  cmd += ["alpha"]
 cmd += [
     "compute",
     "tpus",
     "tpu-vm",
     "ssh",
     args.tpu_name,
     "--zone",
     args.tpu_zone,
     "--command",
     args.command,
     "--worker",
     "all",
 ]
 if args.debug:
  print(F"Running {' '.join(__UpperCamelCase      )}"      )
  return
 subprocess.run(__UpperCamelCase      )
 print("""Successfully setup pod."""      )




def   lowerCAmelCase						(					):
 '''simple docstring'''





 UpperCAmelCase__					:  Optional[Any]					   =					tpu_command_parser()
 UpperCAmelCase__					:  str					   =					parser.parse_args()

 tpu_command_launcher(__UpperCamelCase      )








"""simple docstring"""




import argparse

import torch

from transformers import YosoConfig, YosoForMaskedLM
def   lowerCAmelCase						(					__UpperCamelCase      ):
 '''simple docstring'''





 if "model" in orig_key:
  UpperCAmelCase__					:  List[str]					   =					orig_key.replace("""model."""							,    """"""      )
 if "norm1" in orig_key:
  UpperCAmelCase__					:  List[Any]					   =					orig_key.replace("""norm1"""							,    """attention.output.LayerNorm"""      )
 if "norm2" in orig_key:
  UpperCAmelCase__					:  Optional[Any]					   =					orig_key.replace("""norm2"""							,    """output.LayerNorm"""      )
 if "norm" in orig_key:
  UpperCAmelCase__					:  int					   =					orig_key.replace("""norm"""							,    """LayerNorm"""      )
 if "transformer" in orig_key:
  UpperCAmelCase__					:  Any					   =					orig_key.split("""."""      )[0].split("""_"""      )[-1]
  UpperCAmelCase__					:  Dict					   =					orig_key.replace(F"transformer_{layer_num}"							,    F"encoder.layer.{layer_num}"      )
 if "mha.attn" in orig_key:
  UpperCAmelCase__					:  Tuple					   =					orig_key.replace("""mha.attn"""							,    """attention.self"""      )
 if "mha" in orig_key:
  UpperCAmelCase__					:  Dict					   =					orig_key.replace("""mha"""							,    """attention"""      )
 if "W_q" in orig_key:
  UpperCAmelCase__					:  str					   =					orig_key.replace("""W_q"""							,    """self.query"""      )
 if "W_k" in orig_key:
  UpperCAmelCase__					:  List[Any]					   =					orig_key.replace("""W_k"""							,    """self.key"""      )
 if "W_v" in orig_key:
  UpperCAmelCase__					:  str					   =					orig_key.replace("""W_v"""							,    """self.value"""      )
 if "ff1" in orig_key:
  UpperCAmelCase__					:  Optional[int]					   =					orig_key.replace("""ff1"""							,    """intermediate.dense"""      )
 if "ff2" in orig_key:
  UpperCAmelCase__					:  Dict					   =					orig_key.replace("""ff2"""							,    """output.dense"""      )
 if "ff" in orig_key:
  UpperCAmelCase__					:  Any					   =					orig_key.replace("""ff"""							,    """output.dense"""      )
 if "mlm_class" in orig_key:
  UpperCAmelCase__					:  Any					   =					orig_key.replace("""mlm.mlm_class"""							,    """cls.predictions.decoder"""      )
 if "mlm" in orig_key:
  UpperCAmelCase__					:  Optional[Any]					   =					orig_key.replace("""mlm"""							,    """cls.predictions.transform"""      )
 if "cls" not in orig_key:
  UpperCAmelCase__					:  Dict					   =					"""yoso.""" + orig_key

 return orig_key
def   lowerCAmelCase						(					__UpperCamelCase							,    __UpperCamelCase      ):
 '''simple docstring'''





 for key in orig_state_dict.copy().keys():
  UpperCAmelCase__					:  Optional[Any]					   =					orig_state_dict.pop(__UpperCamelCase      )

  if ("pooler" in key) or ("sen_class" in key):
   continue
  else:
   UpperCAmelCase__					:  Dict					   =					val

 UpperCAmelCase__					:  Dict					   =					orig_state_dict["""cls.predictions.decoder.bias"""]
 UpperCAmelCase__					:  Optional[Any]					   =					torch.arange(__UpperCamelCase      ).expand((1, -1)      ) + 2

 return orig_state_dict
def   lowerCAmelCase						(					__UpperCamelCase							,    __UpperCamelCase							,    __UpperCamelCase      ):
 '''simple docstring'''





 UpperCAmelCase__					:  int					   =					torch.load(__UpperCamelCase							,    map_location="""cpu"""      )["""model_state_dict"""]
 UpperCAmelCase__					:  List[str]					   =					YosoConfig.from_json_file(__UpperCamelCase      )
 UpperCAmelCase__					:  Union[str, Any]					   =					YosoForMaskedLM(__UpperCamelCase      )

 UpperCAmelCase__					:  Optional[int]					   =					convert_checkpoint_helper(config.max_position_embeddings							,    __UpperCamelCase      )

 print(model.load_state_dict(__UpperCamelCase      )      )
 model.eval()
 model.save_pretrained(__UpperCamelCase      )

 print(F"Checkpoint successfuly converted. Model saved at {pytorch_dump_path}"      )


if __name__ == "__main__":
      __UpperCAmelCase =				argparse.ArgumentParser()
      # Required parameters
      parser.add_argument(
          '--pytorch_model_path', default=None, type=str, required=True, help='Path to YOSO pytorch checkpoint.'
      )
      parser.add_argument(
          '--config_file',
          default=None,
          type=str,
          required=True,
          help='The json file for YOSO model config.',
      )
      parser.add_argument(
          '--pytorch_dump_path', default=None, type=str, required=True, help='Path to the output PyTorch model.'
      )
      __UpperCAmelCase =				parser.parse_args()
      convert_yoso_checkpoint(args.pytorch_model_path, args.config_file, args.pytorch_dump_path)





