

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


_UpperCAmelCase						:  str									=			logging.get_logger(__name__)





def    __lowerCamelCase      (					UpperCamelCase__ ):







							'''simple docstring'''






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





def    __lowerCamelCase      (					UpperCamelCase__  ,				UpperCamelCase__  ,				UpperCamelCase__ ):







							'''simple docstring'''






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

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

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

							# old PyTorch layer norm weight
							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
							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__  ,				UpperCamelCase__  ,				UpperCamelCase__=42 ):







							'''simple docstring'''






							snake_case_     							=       {k: v.numpy() for k, v in pt_state_dict.items()}

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

							snake_case_     							=       flatten_dict(UpperCamelCase__ )
							snake_case_     							=       {}

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

														# Correctly rename weight parameters
														snake_case_							,       snake_case_     							=       rename_key_and_reshape_tensor(UpperCamelCase__  ,				UpperCamelCase__  ,				UpperCamelCase__ )

														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_     							=       jnp.asarray(UpperCamelCase__ )

							return unflatten_dict(UpperCamelCase__ )







from collections.abc import Callable







class 					lowercase							:




				def __init__(   self ,  snake_case = None			):
											# Stores actual heap items.
											snake_case_     							=       []
											# Stores indexes of each item for supporting updates and deletion.
											snake_case_     							=       {}
											# Stores current size of heap.
											snake_case_     							=       0
											# Stores function used to evaluate the score of an item on which basis ordering
											# will be done.
											snake_case_     							=       key or (lambda snake_case			: x)




				def        a				(   self ,  snake_case			):
											return int((i - 1) / 2			) if i > 0 else None




				def        a				(   self ,  snake_case			):
											snake_case_     							=       int(2 * i + 1			)
											return left if 0 < left < self.size else None




				def        a				(   self ,  snake_case			):
											snake_case_     							=       int(2 * i + 2			)
											return right if 0 < right < self.size else None




				def        a				(   self ,  snake_case ,  snake_case			):
											snake_case_							,       snake_case_     							=       (
											    self.pos_map[self.arr[j][0]],
											    self.pos_map[self.arr[i][0]],
											)
											# Then swap the items in the list.
											snake_case_							,       snake_case_     							=       self.arr[j], self.arr[i]




				def        a				(   self ,  snake_case ,  snake_case			):
											return self.arr[i][1] < self.arr[j][1]




				def        a				(   self ,  snake_case			):
											snake_case_     							=       self._left(snake_case			)
											snake_case_     							=       self._right(snake_case			)
											snake_case_     							=       i

											if left is not None and not self._cmp(snake_case ,  snake_case			):
																		snake_case_     							=       left
											if right is not None and not self._cmp(snake_case ,  snake_case			):
																		snake_case_     							=       right

											return valid_parent




				def        a				(   self ,  snake_case			):
											snake_case_     							=       self._parent(snake_case			)
											while parent is not None and not self._cmp(snake_case ,  snake_case			):
																		self._swap(snake_case ,  snake_case			)
																		snake_case_							,       snake_case_     							=       parent, self._parent(snake_case			)




				def        a				(   self ,  snake_case			):
											snake_case_     							=       self._get_valid_parent(snake_case			)
											while valid_parent != index:
																		self._swap(snake_case ,  snake_case			)
																		snake_case_							,       snake_case_     							=       valid_parent, self._get_valid_parent(snake_case			)




				def        a				(   self ,  snake_case ,  snake_case			):
											if item not in self.pos_map:
																		return
											snake_case_     							=       self.pos_map[item]
											snake_case_     							=       [item, self.key(snake_case			)]
											# Make sure heap is right in both up and down direction.
											# Ideally only one of them will make any change.
											self._heapify_up(snake_case			)
											self._heapify_down(snake_case			)




				def        a				(   self ,  snake_case			):
											if item not in self.pos_map:
																		return
											snake_case_     							=       self.pos_map[item]
											del self.pos_map[item]
											snake_case_     							=       self.arr[self.size - 1]
											snake_case_     							=       index
											self.size -= 1
											# Make sure heap is right in both up and down direction. Ideally only one
											# of them will make any change- so no performance loss in calling both.
											if self.size > index:
																		self._heapify_up(snake_case			)
																		self._heapify_down(snake_case			)




				def        a				(   self ,  snake_case ,  snake_case			):
											snake_case_     							=       len(self.arr			)
											if arr_len == self.size:
																		self.arr.append([item, self.key(snake_case			)]			)
											else:
																		snake_case_     							=       [item, self.key(snake_case			)]
											snake_case_     							=       self.size
											self.size += 1
											self._heapify_up(self.size - 1			)




				def        a				(   self			):
											return self.arr[0] if self.size else None




				def        a				(   self			):
											snake_case_     							=       self.get_top()
											if top_item_tuple:
																		self.delete_item(top_item_tuple[0]			)
											return top_item_tuple





def    __lowerCamelCase      (					):







							'''simple docstring'''








if __name__ == "__main__":
					import doctest

					doctest.testmod()




