





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	):







  """simple docstring"""





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





def   lowerCAmelCase_				( __a			,					__a			,					__a	):







  """simple docstring"""





  lowerCamelCase__:   Optional[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__:   Optional[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__:   Dict    						=pt_tuple_key[:-1] + ("embedding",)
    return renamed_pt_tuple_key, pt_tensor

  # conv layer
  lowerCamelCase__:   Dict    						=pt_tuple_key[:-1] + ("kernel",)
  if pt_tuple_key[-1] == "weight" and pt_tensor.ndim == 4:
    lowerCamelCase__:   Union[str, 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__:   Optional[Any]    						=pt_tensor.T
    return renamed_pt_tuple_key, pt_tensor

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

  # old PyTorch layer norm bias
  lowerCamelCase__:   Any    						=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	):







  """simple docstring"""





  lowerCamelCase__:   Optional[Any]    						={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__:   Union[str, Any]    						=flatten_dict(__a	)
  lowerCamelCase__:   Optional[int]    						={}

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

    # Correctly rename weight parameters
    lowerCamelCase__:   Any    						=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__:   List[Any]    						=jnp.asarray(__a	)

  return unflatten_dict(__a	)








# Lint as: python3
import dataclasses
import re
from dataclasses import dataclass
from functools import total_ordering
from typing import Optional, Union


__A             =       re.compile(R"^(?P<major>\d+)" R"\.(?P<minor>\d+)" R"\.(?P<patch>\d+)$")



@total_ordering
@dataclass
class      _SCREAMING_SNAKE_CASE		:







 '''simple docstring'''
 lowercase_	=    42
 lowercase_	=    None
 lowercase_	=    None
 lowercase_	=    None
 lowercase_	=    None

 def 							SCREAMING_SNAKE_CASE_      (self       :     List[Any]) ->Tuple:



   '''simple docstring'''



   lowerCamelCase__						,      lowerCamelCase__						,      lowerCamelCase__:   List[str]    						=_str_to_version_tuple(self.version_str)

 def __repr__(self       :     Union[str, Any]) ->Union[str, Any]:



   '''simple docstring'''



   return F"""{self.tuple[0]}.{self.tuple[1]}.{self.tuple[2]}"""

 @property
 def 							SCREAMING_SNAKE_CASE_      (self       :     Optional[Any]) ->Optional[Any]:



   '''simple docstring'''



   return self.major, self.minor, self.patch

 def 							SCREAMING_SNAKE_CASE_      (self       :     Dict ,				UpperCAmelCase_       :     Tuple) ->Any:



   '''simple docstring'''



   if isinstance(UpperCAmelCase_ ,				UpperCAmelCase_):
     return Version(UpperCAmelCase_)
   elif isinstance(UpperCAmelCase_ ,				UpperCAmelCase_):
     return other
   raise TypeError(F"""{other} (type {type(UpperCAmelCase_)}) cannot be compared to version.""")

 def __eq__(self       :     Optional[Any] ,				UpperCAmelCase_       :     Tuple) ->List[str]:



   '''simple docstring'''



   try:
     lowerCamelCase__:   List[Any]    						=self._validate_operand(UpperCAmelCase_)
   except (TypeError, ValueError):
     return False
   else:
     return self.tuple == other.tuple

 def __lt__(self       :     Dict ,				UpperCAmelCase_       :     List[str]) ->Union[str, Any]:



   '''simple docstring'''



   lowerCamelCase__:   Tuple    						=self._validate_operand(UpperCAmelCase_)
   return self.tuple < other.tuple

 def __hash__(self       :     Any) ->Dict:



   '''simple docstring'''



   return hash(_version_tuple_to_str(self.tuple))

 @classmethod
 def 							SCREAMING_SNAKE_CASE_      (cls       :     Union[str, Any] ,				UpperCAmelCase_       :     Optional[Any]) ->Union[str, Any]:



   '''simple docstring'''



   lowerCamelCase__:   str    						={f.name for f in dataclasses.fields(cls)}
   return cls(**{k: v for k, v in dic.items() if k in field_names})







 def 							SCREAMING_SNAKE_CASE_      (self       :     Optional[int]) ->str:



   '''simple docstring'''



   return self.version_str





def   lowerCAmelCase_				( __a	)  ->	List[Any]:







  """simple docstring"""





  lowerCamelCase__:   Optional[int]    						=_VERSION_REG.match(__a	)
  if not res:
    raise ValueError(F"""Invalid version '{version_str}'. Format should be x.y.z with {{x,y,z}} being digits."""	)
  return tuple(int(__a	) for v in [res.group("major"	), res.group("minor"	), res.group("patch"	)]	)






def   lowerCAmelCase_				( __a	)  ->	Dict:







  """simple docstring"""





  return ".".join(str(__a	) for v in version_tuple	)

