
"""simple docstring"""

import random
from typing import List, Optional, Union

import numpy as np
import torch

from ..state import AcceleratorState
from .constants import CUDA_DISTRIBUTED_TYPES
from .dataclasses import DistributedType, RNGType
from .imports import is_npu_available, is_tpu_available, is_xpu_available


if is_tpu_available(check_device=False):
					import torch_xla.core.xla_model as xm
def 		UpperCAmelCase					(		a_,						a_ = False			):





		'''simple docstring'''


		if device_specific:
				seed += AcceleratorState().process_index
		random.seed(a_			)
		np.random.seed(a_			)
		torch.manual_seed(a_			)
		if is_xpu_available():
				torch.xpu.manual_seed_all(a_			)
		elif is_npu_available():
				torch.npu.manual_seed_all(a_			)
		else:
				torch.cuda.manual_seed_all(a_			)
		# ^^ safe to call this function even if cuda is not available
		if is_tpu_available():
				xm.set_rng_state(a_			)
def 		UpperCAmelCase					(		a_ = None,						a_ = None			):





		'''simple docstring'''


		if rng_type == RNGType.TORCH:
				lowerCamelCase     :			Optional[Any]		=    torch.get_rng_state()
		elif rng_type == RNGType.CUDA:
				lowerCamelCase     :			List[Any]		=    torch.cuda.get_rng_state()
		elif rng_type == RNGType.XLA:
				assert is_tpu_available(), "Can't synchronize XLA seeds on an environment without TPUs."
				lowerCamelCase     :			Dict		=    torch.tensor(xm.get_rng_state()			)
		elif rng_type == RNGType.NPU:
				assert is_npu_available(), "Can't synchronize NPU seeds on an environment without NPUs."
				lowerCamelCase     :			int		=    torch.npu.get_rng_state()
		elif rng_type == RNGType.XPU:
				assert is_xpu_available(), "Can't synchronize XPU seeds on an environment without XPUs."
				lowerCamelCase     :			Tuple		=    torch.xpu.get_rng_state()
		elif rng_type == RNGType.GENERATOR:
				assert generator is not None, "Need a generator to synchronize its seed."
				lowerCamelCase     :			Union[str, Any]		=    generator.get_state()

		# Broadcast the rng state from device 0 to other devices
		lowerCamelCase     :			Union[str, Any]		=    AcceleratorState()
		if state.distributed_type == DistributedType.TPU:
				lowerCamelCase     :			Tuple		=    rng_state.to(xm.xla_device()			)
				xm.collective_broadcast([rng_state]			)
				xm.mark_step()
				lowerCamelCase     :			List[str]		=    rng_state.cpu()
		elif (
		    state.distributed_type in CUDA_DISTRIBUTED_TYPES
		    or state.distributed_type == DistributedType.MULTI_NPU
		    or state.distributed_type == DistributedType.MULTI_XPU
		):
				lowerCamelCase     :			Union[str, Any]		=    rng_state.to(state.device			)
				torch.distributed.broadcast(a_,						0			)
				lowerCamelCase     :			Tuple		=    rng_state.cpu()
		elif state.distributed_type == DistributedType.MULTI_CPU:
				torch.distributed.broadcast(a_,						0			)

		# Set the broadcast rng state
		if rng_type == RNGType.TORCH:
				torch.set_rng_state(a_			)
		elif rng_type == RNGType.CUDA:
				torch.cuda.set_rng_state(a_			)
		elif rng_type == RNGType.NPU:
				torch.npu.set_rng_state(a_			)
		elif rng_type == RNGType.XPU:
				torch.xpu.set_rng_state(a_			)
		elif rng_type == RNGType.XLA:
				xm.set_rng_state(rng_state.item()			)
		elif rng_type == RNGType.GENERATOR:
				generator.set_state(a_			)





def 		UpperCAmelCase					(		a_,						a_ = None			):





		'''simple docstring'''


		for rng_type in rng_types:
				synchronize_rng_state(RNGType(a_			),						generator=a_			)














"""simple docstring"""
class 		a_      :







      '''simple docstring'''

      class 		a_      :







            '''simple docstring'''

            lowerCamelCase__       :				List[Any] =	'_prev', '_data', '_next'




            def __init__(self,     lowerCamelCase_,     lowerCamelCase_,     lowerCamelCase_					):

             '''simple docstring'''



             lowerCamelCase__     :			Optional[int]     				=						link_p
             lowerCamelCase__     :			Optional[Any]     				=						element
             lowerCamelCase__     :			List[Any]     				=						link_n





            def 			a__							(self					):

             '''simple docstring'''



             return (
                 f''' Prev -> {self._prev is not None}, Next -> {self._next is not None}'''
             )




      def __init__(self					):

       '''simple docstring'''



       lowerCamelCase__     :			Any     				=						self._Node(lowerCamelCase_,     lowerCamelCase_,     lowerCamelCase_					)
       lowerCamelCase__     :			Dict     				=						self._Node(lowerCamelCase_,     lowerCamelCase_,     lowerCamelCase_					)
       lowerCamelCase__     :			List[str]     				=						self._trailer
       lowerCamelCase__     :			Union[str, Any]     				=						self._header
       lowerCamelCase__     :			Any     				=						0




      def __len__(self					):

       '''simple docstring'''



       return self._size




      def 			a__							(self					):

       '''simple docstring'''



       return self.__len__() == 0




      def 			a__							(self,     lowerCamelCase_,     lowerCamelCase_,     lowerCamelCase_					):

       '''simple docstring'''



       lowerCamelCase__     :			int     				=						self._Node(lowerCamelCase_,     lowerCamelCase_,     lowerCamelCase_					)
       lowerCamelCase__     :			Optional[int]     				=						new_node
       lowerCamelCase__     :			List[Any]     				=						new_node
       self._size += 1
       return self





      def 			a__							(self,     lowerCamelCase_					):

       '''simple docstring'''



       lowerCamelCase__     :			Optional[Any]     				=						node._prev
       lowerCamelCase__     :			List[str]     				=						node._next

       lowerCamelCase__     :			Tuple     				=						successor
       lowerCamelCase__     :			Tuple     				=						predecessor
       self._size -= 1
       lowerCamelCase__     :			int     				=						node._data
       lowerCamelCase__     :			Dict     				=						None
       del node
       return temp



class 		a_      (	_DoublyLinkedBase ):







      '''simple docstring'''

      def 			a__							(self					):

       '''simple docstring'''



       if self.is_empty():
        raise Exception('List is empty'					)
       return self._header._next._data




      def 			a__							(self					):

       '''simple docstring'''



       if self.is_empty():
        raise Exception('List is empty'					)
       return self._trailer._prev._data




      def 			a__							(self,     lowerCamelCase_					):

       '''simple docstring'''



       return self._insert(self._header,     lowerCamelCase_,     self._header._next					)




      def 			a__							(self,     lowerCamelCase_					):

       '''simple docstring'''



       return self._insert(self._trailer._prev,     lowerCamelCase_,     self._trailer					)




      def 			a__							(self					):

       '''simple docstring'''



       if self.is_empty():
        raise IndexError('remove_first from empty list'					)
       return self._delete(self._header._next					)





      def 			a__							(self					):

       '''simple docstring'''



       if self.is_empty():
        raise IndexError('remove_first from empty list'					)
       return self._delete(self._trailer._prev					)

