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


SCREAMING_SNAKE_CASE__		:					Union[str, Any]						=					logging.get_logger(__name__)







def     _a				(      lowercase__  :			List[Any] ):







     '''simple docstring'''


     SCREAMING_SNAKE_CASE__				:				Dict			=		r'\w+[.]\d+'
     SCREAMING_SNAKE_CASE__				:				Dict			=		re.findall(lowercase__     ,  lowercase__ )
     for pat in pats:
          SCREAMING_SNAKE_CASE__				:				int			=		key.replace(lowercase__     ,  '_'.join(pat.split('.' ) ) )
     return key







def     _a				(      lowercase__  :			List[str]     ,  lowercase__  :			int     ,  lowercase__  :			List[Any] ):







     '''simple docstring'''


     SCREAMING_SNAKE_CASE__				:				Union[str, Any]			=		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)
     ):
          SCREAMING_SNAKE_CASE__				:				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:
          SCREAMING_SNAKE_CASE__				:				List[Any]			=		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:
          SCREAMING_SNAKE_CASE__				:				Optional[int]			=		pt_tuple_key[:-1] + ('embedding',)
          return renamed_pt_tuple_key, pt_tensor

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

     # linear layer
     SCREAMING_SNAKE_CASE__				:				int			=		pt_tuple_key[:-1] + ('kernel',)
     if pt_tuple_key[-1] == "weight":
          SCREAMING_SNAKE_CASE__				:				Dict			=		pt_tensor.T
          return renamed_pt_tuple_key, pt_tensor

     # old PyTorch layer norm weight
     SCREAMING_SNAKE_CASE__				:				Optional[int]			=		pt_tuple_key[:-1] + ('weight',)
     if pt_tuple_key[-1] == "gamma":
          return renamed_pt_tuple_key, pt_tensor

     # old PyTorch layer norm bias
     SCREAMING_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     _a				(      lowercase__  :			Tuple     ,  lowercase__  :			Tuple     ,  lowercase__  :			List[str]=42 ):







     '''simple docstring'''


     SCREAMING_SNAKE_CASE__				:				Optional[int]			=		{k: v.numpy() for k, v in pt_state_dict.items()}

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

     SCREAMING_SNAKE_CASE__				:				Any			=		flatten_dict(lowercase__ )
     SCREAMING_SNAKE_CASE__				:				List[Any]			=		{}

     # Need to change some parameters name to match Flax names
     for pt_key, pt_tensor in pt_state_dict.items():
          SCREAMING_SNAKE_CASE__				:				Any			=		rename_key(lowercase__ )
          SCREAMING_SNAKE_CASE__				:				Dict			=		tuple(renamed_pt_key.split('.' ) )

          # Correctly rename weight parameters
          SCREAMING_SNAKE_CASE__			,							SCREAMING_SNAKE_CASE__				:				Dict			=		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
          SCREAMING_SNAKE_CASE__				:				Dict			=		jnp.asarray(lowercase__ )

     return unflatten_dict(lowercase__ )




def     _a				(      lowercase__  :			int     ,  lowercase__  :			int ):







     '''simple docstring'''


     return int((input_a, input_a).count(0 ) != 0 )







def     _a				(      ):







     '''simple docstring'''


     assert nand_gate(0     ,  0 ) == 1
     assert nand_gate(0     ,  1 ) == 1
     assert nand_gate(1     ,  0 ) == 1
     assert nand_gate(1     ,  1 ) == 0


if __name__ == "__main__":
      print(nand_gate(0, 0))
      print(nand_gate(0, 1))
      print(nand_gate(1, 0))
      print(nand_gate(1, 1))



