

'''simple docstring'''
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 :      Optional[Any]					 =     logging.get_logger(__name__)


def        _lowerCAmelCase					(						_UpperCamelCase						:     List[Any]				)      ->			int:
     """simple docstring"""




     _SCREAMING_SNAKE_CASE							    =R"""\w+[.]\d+"""
     _SCREAMING_SNAKE_CASE							    =re.findall(snake_case__							, snake_case__				)
     for pat in pats:
          _SCREAMING_SNAKE_CASE							    =key.replace(snake_case__							, '_'.join(pat.split('.'				)				)				)
     return key


def        _lowerCAmelCase					(						_UpperCamelCase						:     str							, _UpperCamelCase						:     Dict							, _UpperCamelCase						:     List[Any]				)      ->			int:
     """simple docstring"""




     _SCREAMING_SNAKE_CASE							    =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							    =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							    =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							    =pt_tuple_key[:-1] + ("""embedding""",)
          return renamed_pt_tuple_key, pt_tensor

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

     # linear layer
     _SCREAMING_SNAKE_CASE							    =pt_tuple_key[:-1] + ("""kernel""",)
     if pt_tuple_key[-1] == "weight":
          _SCREAMING_SNAKE_CASE							    =pt_tensor.T
          return renamed_pt_tuple_key, pt_tensor

     # old PyTorch layer norm weight
     _SCREAMING_SNAKE_CASE							    =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							    =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					(						_UpperCamelCase						:     Union[str, Any]							, _UpperCamelCase						:     Tuple							, _UpperCamelCase						:     Union[str, Any]=42				)      ->			Union[str, Any]:
     """simple docstring"""




     _SCREAMING_SNAKE_CASE							    ={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							    =flax_model.init_weights(PRNGKey(snake_case__				)				)

     _SCREAMING_SNAKE_CASE							    =flatten_dict(snake_case__				)
     _SCREAMING_SNAKE_CASE							    ={}

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

          # Correctly rename weight parameters
          _SCREAMING_SNAKE_CASE							    =rename_key_and_reshape_tensor(snake_case__							, snake_case__							, 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
          _SCREAMING_SNAKE_CASE							    =jnp.asarray(snake_case__				)

     return unflatten_dict(snake_case__				)






"""simple docstring"""


from math import factorial

A_						=				{str(d): factorial(d) for d in range(10)}


def 					UpperCAmelCase__       (snake_case__							:					int    ):
  """simple docstring"""

  return sum(DIGIT_FACTORIAL[d] for d in str(snake_case__    )    )


def 					UpperCAmelCase__       ():
  """simple docstring"""

  _snake_case							:		List[str]								=  7 * factorial(9    ) + 1
  return sum(i for i in range(3		,   snake_case__    ) if sum_of_digit_factorial(snake_case__    ) == i    )


if __name__ == "__main__":
     print(F'''{solution() = }''')


