

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					:							int      ,  _A					:							bool = False		)				->Tuple:



							"""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					:							Optional[RNGType] = None      ,  _A					:							Optional[torch.Generator] = None		)				->int:



							"""simple docstring"""
							# Get the proper rng state
							if rng_type == RNGType.TORCH:
														lowerCamelCase_								=torch.get_rng_state()
							elif rng_type == RNGType.CUDA:
														lowerCamelCase_								=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_								=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_								=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_								=torch.xpu.get_rng_state()
							elif rng_type == RNGType.GENERATOR:
														assert generator is not None, "Need a generator to synchronize its seed."
														lowerCamelCase_								=generator.get_state()

							# Broadcast the rng state from device 0 to other devices
							lowerCamelCase_								=AcceleratorState()
							if state.distributed_type == DistributedType.TPU:
														lowerCamelCase_								=rng_state.to(xm.xla_device()		)
														xm.collective_broadcast([rng_state]		)
														xm.mark_step()
														lowerCamelCase_								=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_								=rng_state.to(state.device		)
														torch.distributed.broadcast(_A      ,  0		)
														lowerCamelCase_								=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					:							List[Union[str, RNGType]]      ,  _A					:							Optional[torch.Generator] = None		)				->str:



							"""simple docstring"""
							for rng_type in rng_types:
														synchronize_rng_state(RNGType(_A		)      ,  generator=_A		)



def        __UpperCamelCase     (      _A					:							str		)				->int:



							"""simple docstring"""
							lowerCamelCase_								=lowerCamelCase_								=0
							for letter in data:
														lowerCamelCase_								=(hash_ << 4) + ord(_A		)
														lowerCamelCase_								=hash_ & 0XF0000000
														if x != 0:
																					hash_ ^= x >> 24
														hash_ &= ~x
							return hash_


if __name__ == "__main__":
	import doctest

	doctest.testmod()
