




import json
import os
import subprocess
import sys
import warnings
from argparse import ArgumentParser
from contextlib import AbstractContextManager
from typing import Dict, List, Optional

import requests

from ..utils import logging
from . import BaseTransformersCLICommand


lowerCamelCase__				:     Dict			       =							logging.get_logger(__name__)  # pylint: disable=invalid-name


lowerCamelCase__				:     List[Any]			       =							'lfs-multipart-upload'





class  lowerCamelCase_							(   lowerCAmelCase__      ):


 '''simple docstring'''







 @staticmethod
 def    lowerCAmelCase_						(							_lowerCAmelCase						:	List[Any]		):
       SCREAMING_SNAKE_CASE_					=    parser.add_parser(
           'lfs-enable-largefiles'       ,       help=(
               'Deprecated: use `huggingface-cli` instead. Configure your repository to enable upload of files > 5GB.'
           )       ,       )
       enable_parser.add_argument('path'       ,       type=_lowerCamelCase       ,       help='Local path to repository you want to configure.'		)
       enable_parser.set_defaults(func=lambda _lowerCAmelCase		: LfsEnableCommand(_lowerCamelCase		)		)

       SCREAMING_SNAKE_CASE_					=    parser.add_parser(
           _lowerCamelCase       ,       help=(
               'Deprecated: use `huggingface-cli` instead. '
               'Command will get called by git-lfs, do not call it directly.'
           )       ,       )
       upload_parser.set_defaults(func=lambda _lowerCAmelCase		: LfsUploadCommand(_lowerCamelCase		)		)





class  lowerCamelCase_							:


 '''simple docstring'''







 def __init__(							self						:	Tuple       ,       _lowerCAmelCase						:	Dict		):
       SCREAMING_SNAKE_CASE_					=    args




 def    lowerCAmelCase_						(							self						:	Tuple		):
       warnings.warn(
           'Managing repositories through transformers-cli is deprecated. Please use `huggingface-cli` instead.'		)
       SCREAMING_SNAKE_CASE_					=    os.path.abspath(self.args.path		)
       if not os.path.isdir(_lowerCamelCase		):
             print('This does not look like a valid git repo.'		)
             exit(1		)
       subprocess.run(
           'git config lfs.customtransfer.multipart.path transformers-cli'.split()       ,       check=_lowerCamelCase       ,       cwd=_lowerCamelCase		)
       subprocess.run(
           F"git config lfs.customtransfer.multipart.args {LFS_MULTIPART_UPLOAD_COMMAND}".split()       ,       check=_lowerCamelCase       ,       cwd=_lowerCamelCase       ,       )
       print('Local repo set up for largefiles'		)


def       UpperCAmelCase_							(   __UpperCAmelCase		:			Optional[int]							)      ->				Dict:
      SCREAMING_SNAKE_CASE_					=    json.dumps(__UpperCAmelCase							) + """\n"""
      sys.stdout.write(__UpperCAmelCase							)
      sys.stdout.flush()

def       UpperCAmelCase_							(   )      ->				Optional[Dict]:
      SCREAMING_SNAKE_CASE_					=    json.loads(sys.stdin.readline().strip()							)

      if "terminate" in (msg.get('type'							), msg.get('event'							)):
            # terminate message received
            return None

      if msg.get('event'							) not in ("download", "upload"):
            logger.critical('Received unexpected message'							)
            sys.exit(1							)

      return msg





class  lowerCamelCase_							(   lowerCAmelCase__      ):


 '''simple docstring'''







 def __init__(							self						:	Union[str, Any]       ,       _lowerCAmelCase						:	int       ,       _lowerCAmelCase						:	List[Any]       ,       _lowerCAmelCase						:	Tuple		):
       SCREAMING_SNAKE_CASE_					=    filepath
       SCREAMING_SNAKE_CASE_					=    seek_from
       SCREAMING_SNAKE_CASE_					=    read_limit
       SCREAMING_SNAKE_CASE_					=    0



 def __enter__(							self						:	Dict		):
       SCREAMING_SNAKE_CASE_					=    open(self.filepath       ,       'rb'		)
       self.f.seek(self.seek_from		)
       return self



 def __len__(							self						:	Optional[Any]		):
       SCREAMING_SNAKE_CASE_					=    os.fstat(self.f.fileno()		).st_size
       return min(self.read_limit       ,       total_length - self.seek_from		)



 def    lowerCAmelCase_						(							self						:	Dict       ,       _lowerCAmelCase						:	Dict=-1		):

       if self.n_seen >= self.read_limit:
             return b""
       SCREAMING_SNAKE_CASE_					=    self.read_limit - self.n_seen
       SCREAMING_SNAKE_CASE_					=    self.f.read(remaining_amount if n < 0 else min(_lowerCamelCase       ,       _lowerCamelCase		)		)
       self.n_seen += len(_lowerCamelCase		)
       return data



 def __iter__(							self						:	Optional[Any]		):
       yield self.read(n=4 * 1_024 * 1_024		)




 def __exit__(							self						:	str       ,       *_lowerCAmelCase						:	str		):
       self.f.close()





class  lowerCamelCase_							:


 '''simple docstring'''







 def __init__(							self						:	Any       ,       _lowerCAmelCase						:	Any		):
       SCREAMING_SNAKE_CASE_					=    args




 def    lowerCAmelCase_						(							self						:	str		):
       SCREAMING_SNAKE_CASE_					=    json.loads(sys.stdin.readline().strip()		)
       if not (init_msg.get('event'		) == "init" and init_msg.get('operation'		) == "upload"):
             write_msg({'error': {'code': 32, 'message': 'Wrong lfs init operation'}}		)
             sys.exit(1		)

       # The transfer process should use the information it needs from the
       # initiation structure, and also perform any one-off setup tasks it
       # needs to do. It should then respond on stdout with a simple empty
       # confirmation structure, as follows:
       write_msg({}		)

       # After the initiation exchange, git-lfs will send any number of
       # transfer requests to the stdin of the transfer process, in a serial sequence.
       while True:
             SCREAMING_SNAKE_CASE_					=    read_msg()
             if msg is None:
                   # When all transfers have been processed, git-lfs will send
                   # a terminate event to the stdin of the transfer process.
                   # On receiving this message the transfer process should
                   # clean up and terminate. No response is expected.
                   sys.exit(0		)

             SCREAMING_SNAKE_CASE_					=    msg["""oid"""]
             SCREAMING_SNAKE_CASE_					=    msg["""path"""]
             SCREAMING_SNAKE_CASE_					=    msg["""action"""]["""href"""]
             SCREAMING_SNAKE_CASE_					=    msg["""action"""]["""header"""]
             SCREAMING_SNAKE_CASE_					=    int(header.pop('chunk_size'		)		)
             SCREAMING_SNAKE_CASE_					=    list(header.values()		)

             SCREAMING_SNAKE_CASE_					=    []
             for i, presigned_url in enumerate(_lowerCamelCase		):
                   with FileSlice(_lowerCamelCase       ,       seek_from=i * chunk_size       ,       read_limit=_lowerCamelCase		) as data:
                         SCREAMING_SNAKE_CASE_					=    requests.put(_lowerCamelCase       ,       data=_lowerCamelCase		)
                         r.raise_for_status()
                         parts.append(
                             {
                                 'etag': r.headers.get('etag'		),
                                 'partNumber': i + 1,
                             }		)
                         # In order to support progress reporting while data is uploading / downloading,
                         # the transfer process should post messages to stdout
                         write_msg(
                             {
                                 'event': 'progress',
                                 'oid': oid,
                                 'bytesSoFar': (i + 1) * chunk_size,
                                 'bytesSinceLast': chunk_size,
                             }		)
                         # Not precise but that's ok.

             SCREAMING_SNAKE_CASE_					=    requests.post(
                 _lowerCamelCase       ,       json={
                     'oid': oid,
                     'parts': parts,
                 }       ,       )
             r.raise_for_status()

             write_msg({'event': 'complete', 'oid': oid}		)





import os
from pathlib import Path
from typing import Dict, List

import fire
import torch

from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
from transformers.utils.logging import get_logger


lowerCamelCase__				:     Optional[Any]			       =							get_logger(__name__)

def       UpperCAmelCase_							(   __UpperCAmelCase		:			str    ,    __UpperCAmelCase		:			str							)      ->				List[str]:
      if text.startswith(__UpperCAmelCase							):
            return text[len(__UpperCAmelCase							) :]
      return text  # or whatever

def       UpperCAmelCase_							(   __UpperCAmelCase		:			Union[str, Any]							)      ->				List[Any]:
      return {remove_prefix(__UpperCAmelCase    ,    'model.'							): v for k, v in sd.items()}

def       UpperCAmelCase_							(   __UpperCAmelCase		:			List[Dict[str, torch.Tensor]]							)      ->				Dict:
      SCREAMING_SNAKE_CASE_					=    {}
      for k in state_dicts[0].keys():
            SCREAMING_SNAKE_CASE_					=    [sd[k] for sd in state_dicts]
            SCREAMING_SNAKE_CASE_					=    sum(__UpperCAmelCase							) / len(__UpperCAmelCase							)
            assert isinstance(__UpperCAmelCase    ,    torch.Tensor							)
            SCREAMING_SNAKE_CASE_					=    new_t
      return new_sd

def       UpperCAmelCase_							(   __UpperCAmelCase		:			str    ,    __UpperCAmelCase		:			str    ,    __UpperCAmelCase		:			str							)      ->				None:
      SCREAMING_SNAKE_CASE_					=    AutoModelForSeqaSeqLM.from_pretrained(__UpperCAmelCase							)
      if os.path.isfile(__UpperCAmelCase							):
            SCREAMING_SNAKE_CASE_					=    [pl_ckpt_path]
      else:
            assert os.path.isdir(__UpperCAmelCase							)
            SCREAMING_SNAKE_CASE_					=    list(Path(__UpperCAmelCase							).glob('*.ckpt'							)							)
            assert ckpt_files, f"could not find any ckpt files inside the {pl_ckpt_path} directory"

      if len(__UpperCAmelCase							) > 1:
            logger.info(f"averaging the weights of {ckpt_files}"							)

      SCREAMING_SNAKE_CASE_					=    [sanitize(torch.load(__UpperCAmelCase    ,    map_location='cpu'							)['state_dict']							) for x in ckpt_files]
      SCREAMING_SNAKE_CASE_					=    average_state_dicts(__UpperCAmelCase							)

      SCREAMING_SNAKE_CASE_		,				SCREAMING_SNAKE_CASE_					=    hf_model.load_state_dict(__UpperCAmelCase    ,    strict=__UpperCAmelCase							)
      assert not missing, f"missing keys: {missing}"
      hf_model.save_pretrained(__UpperCAmelCase							)
      try:
            SCREAMING_SNAKE_CASE_					=    AutoTokenizer.from_pretrained(__UpperCAmelCase							)
            tok.save_pretrained(__UpperCAmelCase							)
      except Exception:
            pass
            # dont copy tokenizer if cant


if __name__ == "__main__":
   fire.Fire(convert_pl_to_hf)