





import re

import jax.numpy as jnp
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.random import PRNGKey

from ..utils import logging


__A									=				logging.get_logger(__name__)





def      lowerCAmelCase_ (       __a		)     ->		int:







  """simple docstring"""





  lowerCamelCase__:      Union[str, Any]			  =R"\w+[.]\d+"
  lowerCamelCase__:      int			  =re.findall(__a	,    __a		)
  for pat in pats:
    lowerCamelCase__:      Optional[int]			  =key.replace(__a	,    "_".join(pat.split("."		)		)		)
  return key





def      lowerCAmelCase_ (       __a	,    __a	,    __a		)     ->		Any:







  """simple docstring"""





  lowerCamelCase__:      int			  =pt_tuple_key[:-1] + ("scale",)
  if (
      any("norm" in str_ for str_ in pt_tuple_key		)
      and (pt_tuple_key[-1] == "bias")
      and (pt_tuple_key[:-1] + ("bias",) not in random_flax_state_dict)
      and (pt_tuple_key[:-1] + ("scale",) in random_flax_state_dict)
  ):
    lowerCamelCase__:      Optional[Any]			  =pt_tuple_key[:-1] + ("scale",)
    return renamed_pt_tuple_key, pt_tensor
  elif pt_tuple_key[-1] in ["weight", "gamma"] and pt_tuple_key[:-1] + ("scale",) in random_flax_state_dict:
    lowerCamelCase__:      int			  =pt_tuple_key[:-1] + ("scale",)
    return renamed_pt_tuple_key, pt_tensor

  # embedding
  if pt_tuple_key[-1] == "weight" and pt_tuple_key[:-1] + ("embedding",) in random_flax_state_dict:
    lowerCamelCase__:      int			  =pt_tuple_key[:-1] + ("embedding",)
    return renamed_pt_tuple_key, pt_tensor

  # conv layer
  lowerCamelCase__:      Optional[Any]			  =pt_tuple_key[:-1] + ("kernel",)
  if pt_tuple_key[-1] == "weight" and pt_tensor.ndim == 4:
    lowerCamelCase__:      List[Any]			  =pt_tensor.transpose(2	,    3	,    1	,    0		)
    return renamed_pt_tuple_key, pt_tensor

  # linear layer
  lowerCamelCase__:      Union[str, Any]			  =pt_tuple_key[:-1] + ("kernel",)
  if pt_tuple_key[-1] == "weight":
    lowerCamelCase__:      int			  =pt_tensor.T
    return renamed_pt_tuple_key, pt_tensor

  # old PyTorch layer norm weight
  lowerCamelCase__:      str			  =pt_tuple_key[:-1] + ("weight",)
  if pt_tuple_key[-1] == "gamma":
    return renamed_pt_tuple_key, pt_tensor

  # old PyTorch layer norm bias
  lowerCamelCase__:      int			  =pt_tuple_key[:-1] + ("bias",)
  if pt_tuple_key[-1] == "beta":
    return renamed_pt_tuple_key, pt_tensor

  return pt_tuple_key, pt_tensor






def      lowerCAmelCase_ (       __a	,    __a	,    __a=42		)     ->		Tuple:







  """simple docstring"""





  lowerCamelCase__:      int			  ={k: v.numpy() for k, v in pt_state_dict.items()}

  # Step 2: Since the model is stateless, get random Flax params
  lowerCamelCase__:      int			  =flax_model.init_weights(PRNGKey(__a		)		)

  lowerCamelCase__:      Optional[int]			  =flatten_dict(__a		)
  lowerCamelCase__:      int			  ={}

  # Need to change some parameters name to match Flax names
  for pt_key, pt_tensor in pt_state_dict.items():
    lowerCamelCase__:      List[str]			  =rename_key(__a		)
    lowerCamelCase__:      str			  =tuple(renamed_pt_key.split("."		)		)

    # Correctly rename weight parameters
    lowerCamelCase__  ,					lowerCamelCase__:      List[str]			  =rename_key_and_reshape_tensor(__a	,    __a	,    __a		)

    if flax_key in random_flax_state_dict:
      if flax_tensor.shape != random_flax_state_dict[flax_key].shape:
        raise ValueError(
            F"""PyTorch checkpoint seems to be incorrect. Weight {pt_key} was expected to be of shape """
            F"""{random_flax_state_dict[flax_key].shape}, but is {flax_tensor.shape}."""		)

        # also add unexpected weight so that warning is thrown
    lowerCamelCase__:      Union[str, Any]			  =jnp.asarray(__a		)

  return unflatten_dict(__a		)








# 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.

import argparse
import os

from accelerate.test_utils import execute_subprocess_async


def        SCREAMING_SNAKE_CASE      (       _UpperCAmelCase=None )			->     Tuple:
    if subparsers is not None:
        lowerCamelCase__    :      Any					 =		subparsers.add_parser('test' )
    else:
        lowerCamelCase__    :      int					 =		argparse.ArgumentParser('Accelerate test command' )

    parser.add_argument(
        '--config_file'						,	default=_UpperCAmelCase						,	help=(
            'The path to use to store the config file. Will default to a file named default_config.yaml in the cache '
            'location, which is the content of the environment `HF_HOME` suffixed with \'accelerate\', or if you don\'t have '
            'such an environment variable, your cache directory (\'~/.cache\' or the content of `XDG_CACHE_HOME`) suffixed '
            'with \'huggingface\'.'
        )						,	)

    if subparsers is not None:
        parser.set_defaults(func=_UpperCAmelCase )
    return parser


def        SCREAMING_SNAKE_CASE      (       _UpperCAmelCase )			->     Union[str, Any]:
    lowerCamelCase__    :      Tuple					 =		os.path.sep.join(__file__.split(os.path.sep )[:-2] + ['test_utils', 'scripts', 'test_script.py'] )

    if args.config_file is None:
        lowerCamelCase__    :      List[str]					 =		script_name
    else:
        lowerCamelCase__    :      List[Any]					 =		F"""--config_file={args.config_file} {script_name}"""

    lowerCamelCase__    :      str					 =		['accelerate-launch'] + test_args.split()
    lowerCamelCase__    :      Dict					 =		execute_subprocess_async(_UpperCAmelCase						,	env=os.environ.copy() )
    if result.returncode == 0:
        print('Test is a success! You are ready for your distributed training!' )


def        SCREAMING_SNAKE_CASE      (       )			->     Any:
    lowerCamelCase__    :      Any					 =		test_command_parser()
    lowerCamelCase__    :      List[Any]					 =		parser.parse_args()
    test_command(_UpperCAmelCase )


if __name__ == "__main__":
    main()





