



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 			a		( _UpperCAmelCase				:   int					,  _UpperCAmelCase				:   bool = False		):







		'''simple docstring'''





		if device_specific:
				seed += AcceleratorState().process_index
		random.seed(_UpperCAmelCase		)
		np.random.seed(_UpperCAmelCase		)
		torch.manual_seed(_UpperCAmelCase		)
		if is_xpu_available():
				torch.xpu.manual_seed_all(_UpperCAmelCase		)
		elif is_npu_available():
				torch.npu.manual_seed_all(_UpperCAmelCase		)
		else:
				torch.cuda.manual_seed_all(_UpperCAmelCase		)
		# ^^ safe to call this function even if cuda is not available
		if is_tpu_available():
				xm.set_rng_state(_UpperCAmelCase		)

def 			a		( _UpperCAmelCase				:   Optional[RNGType] = None					,  _UpperCAmelCase				:   Optional[torch.Generator] = None		):







		'''simple docstring'''





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

		# Broadcast the rng state from device 0 to other devices
		__UpperCAmelCase       :	List[str]						=      AcceleratorState()
		if state.distributed_type == DistributedType.TPU:
				__UpperCAmelCase       :	Optional[int]						=      rng_state.to(xm.xla_device()		)
				xm.collective_broadcast([rng_state]		)
				xm.mark_step()
				__UpperCAmelCase       :	Tuple						=      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
		):
				__UpperCAmelCase       :	List[Any]						=      rng_state.to(state.device		)
				torch.distributed.broadcast(_UpperCAmelCase					,  0		)
				__UpperCAmelCase       :	Any						=      rng_state.cpu()
		elif state.distributed_type == DistributedType.MULTI_CPU:
				torch.distributed.broadcast(_UpperCAmelCase					,  0		)

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

def 			a		( _UpperCAmelCase				:   List[Union[str, RNGType]]					,  _UpperCAmelCase				:   Optional[torch.Generator] = None		):







		'''simple docstring'''





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










import json
import os
import unittest

from transformers import HerbertTokenizer, HerbertTokenizerFast
from transformers.models.herbert.tokenization_herbert import VOCAB_FILES_NAMES
from transformers.testing_utils import get_tests_dir, require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin

@require_tokenizers
class 						UpperCAmelCase__     (     __UpperCamelCase		,unittest.TestCase  ):




			'''simple docstring'''






			UpperCamelCase     		=			HerbertTokenizer
			UpperCamelCase     		=			HerbertTokenizerFast
			UpperCamelCase     		=			True




			def 					snake_case__	(  self				:					Tuple					):
					'''simple docstring'''





					super().setUp()

					# Use a simpler test file without japanese/chinese characters
					with open(F'{get_tests_dir()}/fixtures/sample_text_no_unicode.txt'			,			encoding='''utf-8'''					) as f_data:
							__UpperCAmelCase       :	List[str]						=      f_data.read().replace('''\n\n'''			,			'''\n'''					).strip()

					__UpperCAmelCase       :	Dict						=      [
					    '''<s>''',
					    '''</s>''',
					    '''l''',
					    '''o''',
					    '''w''',
					    '''e''',
					    '''r''',
					    '''s''',
					    '''t''',
					    '''i''',
					    '''d''',
					    '''n''',
					    '''w</w>''',
					    '''r</w>''',
					    '''t</w>''',
					    '''lo''',
					    '''low''',
					    '''er</w>''',
					    '''low</w>''',
					    '''lowest</w>''',
					    '''newer</w>''',
					    '''wider</w>''',
					    ''',</w>''',
					    '''<unk>''',
					]
					__UpperCAmelCase       :	Tuple						=      dict(zip(a_			,			range(len(a_					)					)					)					)
					__UpperCAmelCase       :	Optional[int]						=      ['''l o 123''', '''lo w 1456''', '''e r</w> 1789''', '''''']

					__UpperCAmelCase       :	str						=      os.path.join(self.tmpdirname			,			VOCAB_FILES_NAMES['''vocab_file''']					)
					__UpperCAmelCase       :	List[str]						=      os.path.join(self.tmpdirname			,			VOCAB_FILES_NAMES['''merges_file''']					)
					with open(self.vocab_file			,			'''w'''					) as fp:
							fp.write(json.dumps(a_					)					)
					with open(self.merges_file			,			'''w'''					) as fp:
							fp.write('''\n'''.join(a_					)					)




			def 					snake_case__	(  self				:					Union[str, Any]			,			a_				:					Optional[Any]					):
					'''simple docstring'''





					__UpperCAmelCase       :	List[str]						=      '''lower newer'''
					__UpperCAmelCase       :	List[Any]						=      '''lower newer'''
					return input_text, output_text




			def 					snake_case__	(  self				:					int					):
					'''simple docstring'''





					__UpperCAmelCase       :	Any						=      self.tokenizer_class(vocab_file=self.vocab_file			,			merges_file=self.merges_file					)

					__UpperCAmelCase       :	Optional[int]						=      '''lower'''
					__UpperCAmelCase       :	Any						=      ['''low''', '''er</w>''']
					__UpperCAmelCase       :	Any						=      tokenizer.tokenize(a_					)
					self.assertListEqual(a_			,			a_					)

					__UpperCAmelCase       :	int						=      tokens + ['''<unk>''']
					__UpperCAmelCase       :	Optional[Any]						=      [16, 17, 23]
					self.assertListEqual(tokenizer.convert_tokens_to_ids(a_					)			,			a_					)




			def 					snake_case__	(  self				:					List[Any]					):
					'''simple docstring'''





					if not self.test_rust_tokenizer:
							return

					__UpperCAmelCase       :	str						=      self.get_tokenizer()
					__UpperCAmelCase       :	Optional[int]						=      self.get_rust_tokenizer()

					__UpperCAmelCase       :	Tuple						=      '''lower,newer'''

					__UpperCAmelCase       :	Optional[int]						=      tokenizer.tokenize(a_					)
					__UpperCAmelCase       :	Tuple						=      rust_tokenizer.tokenize(a_					)
					self.assertListEqual(a_			,			a_					)

					__UpperCAmelCase       :	Optional[Any]						=      tokenizer.encode(a_			,			add_special_tokens=a_					)
					__UpperCAmelCase       :	Union[str, Any]						=      rust_tokenizer.encode(a_			,			add_special_tokens=a_					)
					self.assertListEqual(a_			,			a_					)

					__UpperCAmelCase       :	Tuple						=      self.get_rust_tokenizer()
					__UpperCAmelCase       :	Union[str, Any]						=      tokenizer.encode(a_					)
					__UpperCAmelCase       :	str						=      rust_tokenizer.encode(a_					)
					self.assertListEqual(a_			,			a_					)




			@slow
			def 					snake_case__	(  self				:					Tuple					):
					'''simple docstring'''





					__UpperCAmelCase       :	List[Any]						=      self.tokenizer_class.from_pretrained('''allegro/herbert-base-cased'''					)

					__UpperCAmelCase       :	Tuple						=      tokenizer.encode('''konstruowanie sekwencji'''			,			add_special_tokens=a_					)
					__UpperCAmelCase       :	int						=      tokenizer.encode('''konstruowanie wielu sekwencji'''			,			add_special_tokens=a_					)

					__UpperCAmelCase       :	Union[str, Any]						=      tokenizer.build_inputs_with_special_tokens(a_					)
					__UpperCAmelCase       :	Any						=      tokenizer.build_inputs_with_special_tokens(a_			,			a_					)

					assert encoded_sentence == [0] + text + [2]
					assert encoded_pair == [0] + text + [2] + text_a + [2]





