

from __future__ import annotations

import math



class 						_A     :





  '''simple docstring'''



  def __init__(  self   ,SCREAMING_SNAKE_CASE_    ):

      '''simple docstring'''
      snake_case							:		Dict        =		size
      # approximate the overall size of segment tree with given value
      snake_case							:		Dict        =		[0 for i in range(0   ,4 * size    )]
      # create array to store lazy update
      snake_case							:		List[Any]        =		[0 for i in range(0   ,4 * size    )]
      snake_case							:		Any        =		[0 for i in range(0   ,4 * size    )]  # flag for lazy update





  def    snake_case_       (  self   ,SCREAMING_SNAKE_CASE_    ):

      '''simple docstring'''
      return idx * 2





  def    snake_case_       (  self   ,SCREAMING_SNAKE_CASE_    ):

      '''simple docstring'''
      return idx * 2 + 1





  def    snake_case_       (  self   ,SCREAMING_SNAKE_CASE_   ,SCREAMING_SNAKE_CASE_   ,SCREAMING_SNAKE_CASE_   ,SCREAMING_SNAKE_CASE_    ):

      '''simple docstring'''
      if left_element == right_element:
          snake_case							:		int        =		a[left_element - 1]
      else:
          snake_case							:		List[str]        =		(left_element + right_element) // 2
          self.build(self.left(SCREAMING_SNAKE_CASE_    )   ,SCREAMING_SNAKE_CASE_   ,SCREAMING_SNAKE_CASE_   ,SCREAMING_SNAKE_CASE_    )
          self.build(self.right(SCREAMING_SNAKE_CASE_    )   ,mid + 1   ,SCREAMING_SNAKE_CASE_   ,SCREAMING_SNAKE_CASE_    )
          snake_case							:		str        =		max(
              self.segment_tree[self.left(SCREAMING_SNAKE_CASE_    )]   ,self.segment_tree[self.right(SCREAMING_SNAKE_CASE_    )]    )





  def    snake_case_       (  self   ,SCREAMING_SNAKE_CASE_   ,SCREAMING_SNAKE_CASE_   ,SCREAMING_SNAKE_CASE_   ,SCREAMING_SNAKE_CASE_   ,SCREAMING_SNAKE_CASE_   ,SCREAMING_SNAKE_CASE_    ):

      '''simple docstring'''
      if self.flag[idx] is True:
          snake_case							:		int        =		self.lazy[idx]
          snake_case							:		List[str]        =		False
          if left_element != right_element:
              snake_case							:		int        =		self.lazy[idx]
              snake_case							:		List[str]        =		self.lazy[idx]
              snake_case							:		List[Any]        =		True
              snake_case							:		Union[str, Any]        =		True

      if right_element < a or left_element > b:
          return True
      if left_element >= a and right_element <= b:
          snake_case							:		Optional[Any]        =		val
          if left_element != right_element:
              snake_case							:		str        =		val
              snake_case							:		Optional[Any]        =		val
              snake_case							:		Optional[Any]        =		True
              snake_case							:		List[Any]        =		True
          return True
      snake_case							:		List[str]        =		(left_element + right_element) // 2
      self.update(self.left(SCREAMING_SNAKE_CASE_    )   ,SCREAMING_SNAKE_CASE_   ,SCREAMING_SNAKE_CASE_   ,SCREAMING_SNAKE_CASE_   ,SCREAMING_SNAKE_CASE_   ,SCREAMING_SNAKE_CASE_    )
      self.update(self.right(SCREAMING_SNAKE_CASE_    )   ,mid + 1   ,SCREAMING_SNAKE_CASE_   ,SCREAMING_SNAKE_CASE_   ,SCREAMING_SNAKE_CASE_   ,SCREAMING_SNAKE_CASE_    )
      snake_case							:		Tuple        =		max(
          self.segment_tree[self.left(SCREAMING_SNAKE_CASE_    )]   ,self.segment_tree[self.right(SCREAMING_SNAKE_CASE_    )]    )
      return True





  def    snake_case_       (  self   ,SCREAMING_SNAKE_CASE_   ,SCREAMING_SNAKE_CASE_   ,SCREAMING_SNAKE_CASE_   ,SCREAMING_SNAKE_CASE_   ,SCREAMING_SNAKE_CASE_    ):

      '''simple docstring'''
      if self.flag[idx] is True:
          snake_case							:		List[Any]        =		self.lazy[idx]
          snake_case							:		List[Any]        =		False
          if left_element != right_element:
              snake_case							:		List[str]        =		self.lazy[idx]
              snake_case							:		int        =		self.lazy[idx]
              snake_case							:		int        =		True
              snake_case							:		str        =		True
      if right_element < a or left_element > b:
          return -math.inf
      if left_element >= a and right_element <= b:
          return self.segment_tree[idx]
      snake_case							:		List[Any]        =		(left_element + right_element) // 2
      snake_case							:		List[str]        =		self.query(self.left(SCREAMING_SNAKE_CASE_    )   ,SCREAMING_SNAKE_CASE_   ,SCREAMING_SNAKE_CASE_   ,SCREAMING_SNAKE_CASE_   ,SCREAMING_SNAKE_CASE_    )
      snake_case							:		Union[str, Any]        =		self.query(self.right(SCREAMING_SNAKE_CASE_    )   ,mid + 1   ,SCREAMING_SNAKE_CASE_   ,SCREAMING_SNAKE_CASE_   ,SCREAMING_SNAKE_CASE_    )
      return max(SCREAMING_SNAKE_CASE_   ,SCREAMING_SNAKE_CASE_    )





  def __str__(  self    ):

      '''simple docstring'''
      return str([self.query(1   ,1   ,self.size   ,SCREAMING_SNAKE_CASE_   ,SCREAMING_SNAKE_CASE_    ) for i in range(1   ,self.size + 1    )]    )


if __name__ == "__main__":
     __lowercase     : Union[str, Any]       =						[1, 2, -4, 7, 3, -5, 6, 11, -20, 9, 14, 15, 5, 2, -8]
     __lowercase     : Union[str, Any]       =						15
     __lowercase     : Union[str, Any]       =						SegmentTree(size)
     segt.build(1, 1, size, A)
     print(segt.query(1, 1, size, 4, 6))
     print(segt.query(1, 1, size, 7, 11))
     print(segt.query(1, 1, size, 7, 12))
     segt.update(1, 1, size, 1, 3, 111)
     print(segt.query(1, 1, size, 1, 15))
     segt.update(1, 1, size, 7, 8, 235)
     print(segt)







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__    :int       =				logging.get_logger(__name__)

def 			lowerCAmelCase__					(     a__:						Dict			)    ->						List[str]:


							'''simple docstring'''





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

def 			lowerCAmelCase__					(     a__:						Optional[int]     ,    a__:						Dict     ,    a__:						List[Any]			)    ->						str:


							'''simple docstring'''





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

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

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

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

							# old PyTorch layer norm bias
							_UpperCAmelCase											=     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__					(     a__:						Any     ,    a__:						Optional[Any]     ,    a__:						int=4_2			)    ->						List[str]:


							'''simple docstring'''





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

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

							_UpperCAmelCase											=     flatten_dict(a__			)
							_UpperCAmelCase											=     {}

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

														# Correctly rename weight parameters
														_UpperCAmelCase						,			_UpperCAmelCase											=     rename_key_and_reshape_tensor(a__     ,    a__     ,    a__			)

														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											=     jnp.asarray(a__			)

							return unflatten_dict(a__			)
