


'''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     :					int       , _A     :					bool = False					)     ->   Dict:




	"""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					)     ->   Union[str, Any]:




	"""simple docstring"""





	if rng_type == RNGType.TORCH:
		lowerCAmelCase       :     int   				=			torch.get_rng_state()
	elif rng_type == RNGType.CUDA:
		lowerCAmelCase       :     Dict   				=			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       :     Any   				=			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       :     Tuple   				=			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       :     Any   				=			generator.get_state()

	# Broadcast the rng state from device 0 to other devices
	lowerCAmelCase       :     int   				=			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[Any]   				=			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       :     Optional[Any]   				=			rng_state.to(state.device					)
		torch.distributed.broadcast(_A       , 0					)
		lowerCAmelCase       :     Union[str, Any]   				=			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					)     ->   int:




	"""simple docstring"""





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




'''simple docstring'''




from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available, is_tokenizers_available


_lowerCAmelCase	:		Dict		  =						{}

try:
				if not is_sentencepiece_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				_lowerCAmelCase	:		Union[str, Any]		  =						['BarthezTokenizer']

try:
				if not is_tokenizers_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				_lowerCAmelCase	:		Union[str, Any]		  =						['BarthezTokenizerFast']


if TYPE_CHECKING:
				try:
								if not is_sentencepiece_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .tokenization_barthez import BarthezTokenizer

				try:
								if not is_tokenizers_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .tokenization_barthez_fast import BarthezTokenizerFast

else:
				import sys

				_lowerCAmelCase	:		List[str]		  =						_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)
