






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			:					List[str]         =	logging.get_logger(__name__)





def       __lowerCAmelCase      (						__snake_case       ):
     __lowerCAmelCase								=					r"\w+[.]\d+"
     __lowerCAmelCase								=					re.findall(__snake_case					, __snake_case       )
     for pat in pats:
          __lowerCAmelCase								=					key.replace(__snake_case					, "_".join(pat.split("."       )       )       )
     return key





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

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

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

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

     # old PyTorch layer norm bias
     __lowerCAmelCase								=					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      (						__snake_case					, __snake_case					, __snake_case=42       ):
     # Step 1: Convert pytorch tensor to numpy
     __lowerCAmelCase								=					{k: v.numpy() for k, v in pt_state_dict.items()}

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

     __lowerCAmelCase								=					flatten_dict(__snake_case       )
     __lowerCAmelCase								=					{}

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

          # Correctly rename weight parameters
          __lowerCAmelCase			, __lowerCAmelCase								=					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
          __lowerCAmelCase								=					jnp.asarray(__snake_case       )

     return unflatten_dict(__snake_case       )














def       __lowerCAmelCase      (						__snake_case					, __snake_case       ):
     if not isinstance(__snake_case					, __snake_case       ):
          raise ValueError("iterations must be defined as integers"       )
     if not isinstance(__snake_case					, __snake_case       ) or not number >= 1:
          raise ValueError(
              "starting number must be\n                         and integer and be more than 0"       )
     if not iterations >= 1:
          raise ValueError("Iterations must be done more than 0 times to play FizzBuzz"       )

     __lowerCAmelCase								=					""
     while number <= iterations:
          if number % 3 == 0:
               out += "Fizz"
          if number % 5 == 0:
               out += "Buzz"
          if 0 not in (number % 3, number % 5):
               out += str(__snake_case       )

          # print(out)
          number += 1
          out += " "
     return out


if __name__ == "__main__":
 import doctest

 doctest.testmod()






