




'''simple docstring'''



class 				_a							:





       '''simple docstring'''






       def __init__(	self   ):







             '''simple docstring'''







             SCREAMING_SNAKE_CASE					:	List[Any]   =		''''''
             SCREAMING_SNAKE_CASE					:	Dict   =		''''''
             SCREAMING_SNAKE_CASE					:	Union[str, Any]   =		[]







       def     UpperCamelCase_				(	self,				A,				A   ):







             '''simple docstring'''







             if m == -1:
                   return n + 1
             elif n == -1:
                   return m + 1
             elif self.dp[m][n] > -1:
                   return self.dp[m][n]
             else:
                   if self.worda[m] == self.worda[n]:
                         SCREAMING_SNAKE_CASE					:	int   =		self.__min_dist_top_down_dp(m - 1,				n - 1   )
                   else:
                         SCREAMING_SNAKE_CASE					:	int   =		self.__min_dist_top_down_dp(__lowercase,				n - 1   )
                         SCREAMING_SNAKE_CASE					:	Dict   =		self.__min_dist_top_down_dp(m - 1,				__lowercase   )
                         SCREAMING_SNAKE_CASE					:	int   =		self.__min_dist_top_down_dp(m - 1,				n - 1   )
                         SCREAMING_SNAKE_CASE					:	List[Any]   =		1 + min(__lowercase,				__lowercase,				__lowercase   )

                   return self.dp[m][n]







       def     UpperCamelCase_				(	self,				A,				A   ):







             '''simple docstring'''







             SCREAMING_SNAKE_CASE					:	Optional[int]   =		worda
             SCREAMING_SNAKE_CASE					:	Optional[int]   =		worda
             SCREAMING_SNAKE_CASE					:	Any   =		[[-1 for _ in range(len(__lowercase   )   )] for _ in range(len(__lowercase   )   )]

             return self.__min_dist_top_down_dp(len(__lowercase   ) - 1,				len(__lowercase   ) - 1   )







       def     UpperCamelCase_				(	self,				A,				A   ):







             '''simple docstring'''







             SCREAMING_SNAKE_CASE					:	Optional[int]   =		worda
             SCREAMING_SNAKE_CASE					:	Tuple   =		worda
             SCREAMING_SNAKE_CASE					:	str   =		len(__lowercase   )
             SCREAMING_SNAKE_CASE					:	Union[str, Any]   =		len(__lowercase   )
             SCREAMING_SNAKE_CASE					:	Union[str, Any]   =		[[0 for _ in range(n + 1   )] for _ in range(m + 1   )]

             for i in range(m + 1   ):
                   for j in range(n + 1   ):
                         if i == 0:  # first string is empty
                               SCREAMING_SNAKE_CASE					:	Dict   =		j
                         elif j == 0:  # second string is empty
                               SCREAMING_SNAKE_CASE					:	Union[str, Any]   =		i
                         elif worda[i - 1] == worda[j - 1]:  # last characters are equal
                               SCREAMING_SNAKE_CASE					:	List[str]   =		self.dp[i - 1][j - 1]
                         else:
                               SCREAMING_SNAKE_CASE					:	str   =		self.dp[i][j - 1]
                               SCREAMING_SNAKE_CASE					:	List[str]   =		self.dp[i - 1][j]
                               SCREAMING_SNAKE_CASE					:	Union[str, Any]   =		self.dp[i - 1][j - 1]
                               SCREAMING_SNAKE_CASE					:	str   =		1 + min(__lowercase,				__lowercase,				__lowercase   )
             return self.dp[m][n]


if __name__ == "__main__":
      UpperCamelCase_       =							EditDistance()

      print("****************** Testing Edit Distance DP Algorithm ******************")
      print()

      UpperCamelCase_       =							input("Enter the first string: ").strip()
      UpperCamelCase_       =							input("Enter the second string: ").strip()

      print()
      print(F"""The minimum edit distance is: {solver.min_dist_top_down(Sa, Sa)}""")
      print(F"""The minimum edit distance is: {solver.min_dist_bottom_up(Sa, Sa)}""")
      print()
      print("*************** End of Testing Edit Distance DP Algorithm ***************")



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


__lowercase							 =					logging.get_logger(__name__)



def lowerCamelCase  (   SCREAMING_SNAKE_CASE	):
    '''simple docstring'''







    __UpperCamelCase     :Tuple			  =		R'''\w+[.]\d+'''
    __UpperCamelCase     :List[str]			  =		re.findall(SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE	)
    for pat in pats:
        __UpperCamelCase     :int			  =		key.replace(SCREAMING_SNAKE_CASE  ,			'''_'''.join(pat.split('''.'''	)	)	)
    return key



def lowerCamelCase  (   SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE	):
    '''simple docstring'''







    __UpperCamelCase     :Tuple			  =		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)
    ):
        __UpperCamelCase     :str			  =		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:
        __UpperCamelCase     :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:
        __UpperCamelCase     :str			  =		pt_tuple_key[:-1] + ('''embedding''',)
        return renamed_pt_tuple_key, pt_tensor

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

    # linear layer
    __UpperCamelCase     :List[str]			  =		pt_tuple_key[:-1] + ('''kernel''',)
    if pt_tuple_key[-1] == "weight":
        __UpperCamelCase     :Any			  =		pt_tensor.T
        return renamed_pt_tuple_key, pt_tensor

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

    # old PyTorch layer norm bias
    __UpperCamelCase     :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  (   SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE=42	):
    '''simple docstring'''







    __UpperCamelCase     :Union[str, Any]			  =		{k: v.numpy() for k, v in pt_state_dict.items()}

    # Step 2: Since the model is stateless, get random Flax params
    __UpperCamelCase     :str			  =		flax_model.init_weights(PRNGKey(SCREAMING_SNAKE_CASE	)	)

    __UpperCamelCase     :int			  =		flatten_dict(SCREAMING_SNAKE_CASE	)
    __UpperCamelCase     :List[Any]			  =		{}

    # Need to change some parameters name to match Flax names
    for pt_key, pt_tensor in pt_state_dict.items():
        __UpperCamelCase     :List[Any]			  =		rename_key(SCREAMING_SNAKE_CASE	)
        __UpperCamelCase     :List[Any]			  =		tuple(renamed_pt_key.split('''.'''	)	)

        # Correctly rename weight parameters
        __UpperCamelCase  ,       __UpperCamelCase     :Any			  =		rename_key_and_reshape_tensor(SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE	)

        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
        __UpperCamelCase     :str			  =		jnp.asarray(SCREAMING_SNAKE_CASE	)

    return unflatten_dict(SCREAMING_SNAKE_CASE	)





