




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


lowerCamelCase       :       Any        =    logging.get_logger(__name__)




def 						SCREAMING_SNAKE_CASE__					(    lowercase     )  ->   int:
   snake_case      :				Union[str, Any]				=       R"""\w+[.]\d+"""
   snake_case      :				List[Any]				=       re.findall(lowercase						,lowercase     )
   for pat in pats:
      snake_case      :				List[Any]				=       key.replace(lowercase						,"""_""".join(pat.split("""."""     )     )     )
   return key




def 						SCREAMING_SNAKE_CASE__					(    lowercase						,lowercase						,lowercase     )  ->   Optional[int]:
   snake_case      :				Dict				=       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)
   ):
      snake_case      :				Optional[int]				=       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:
      snake_case      :				Tuple				=       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:
      snake_case      :				Any				=       pt_tuple_key[:-1] + ("""embedding""",)
      return renamed_pt_tuple_key, pt_tensor

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

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

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

   # old PyTorch layer norm bias
   snake_case      :				Dict				=       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 						SCREAMING_SNAKE_CASE__					(    lowercase						,lowercase						,lowercase=42     )  ->   str:
   snake_case      :				List[str]				=       {k: v.numpy() for k, v in pt_state_dict.items()}

   # Step 2: Since the model is stateless, get random Flax params
   snake_case      :				Any				=       flax_model.init_weights(PRNGKey(lowercase     )     )

   snake_case      :				List[Any]				=       flatten_dict(lowercase     )
   snake_case      :				str				=       {}

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

      # Correctly rename weight parameters
      snake_case	,					snake_case      :				Optional[Any]				=       rename_key_and_reshape_tensor(lowercase						,lowercase						,lowercase     )

      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
      snake_case      :				str				=       jnp.asarray(lowercase     )

   return unflatten_dict(lowercase     )












"""simple docstring"""





from __future__ import annotations


def 			UpperCAmelCase__							(  SCREAMING_SNAKE_CASE     :						str			):







      '''simple docstring'''




      return [ord(SCREAMING_SNAKE_CASE			) - 96 for elem in plain]


def 			UpperCAmelCase__							(  SCREAMING_SNAKE_CASE     :						list[int]			):







      '''simple docstring'''




      return "".join(chr(elem + 96			) for elem in encoded			)


def 			UpperCAmelCase__							(  ):







      '''simple docstring'''




      lowerCAmelCase  						=       encode(input("""-> """			).strip().lower()			)
      print("""Encoded: """							,						SCREAMING_SNAKE_CASE			)
      print("""Decoded:"""							,						decode(SCREAMING_SNAKE_CASE			)			)


if __name__ == "__main__":
       main()






