

import os
import re
from shutil import copyfile
from typing import List, Optional, Tuple

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


a		=logging.get_logger(__name__)

a		={
    """vocab_file""": """vocab.txt""",
    """merges_file""": """bpe.codes""",
}

a		={
    """vocab_file""": {
        """vinai/phobert-base""": """https://huggingface.co/vinai/phobert-base/resolve/main/vocab.txt""",
        """vinai/phobert-large""": """https://huggingface.co/vinai/phobert-large/resolve/main/vocab.txt""",
    },
    """merges_file""": {
        """vinai/phobert-base""": """https://huggingface.co/vinai/phobert-base/resolve/main/bpe.codes""",
        """vinai/phobert-large""": """https://huggingface.co/vinai/phobert-large/resolve/main/bpe.codes""",
    },
}

a		={
    """vinai/phobert-base""": 256,
    """vinai/phobert-large""": 256,
}






def        SCREAMING_SNAKE_CASE__	(  lowerCamelCase__      )  ->					Any:
	__lowerCamelCase    :    List[str] 	=			set()
	__lowerCamelCase    :    List[str] 	=			word[0]
	for char in word[1:]:
		pairs.add((prev_char, char)      )
		__lowerCamelCase    :    Tuple 	=			char

	__lowerCamelCase    :    Optional[Any] 	=			set(_lowerCamelCase      )
	return pairs






class 	A_		(	__lowercase    ):
							_UpperCAmelCase   :  Any										=				VOCAB_FILES_NAMES
							_UpperCAmelCase   :  Tuple										=				PRETRAINED_VOCAB_FILES_MAP
							_UpperCAmelCase   :  Tuple										=				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							def __init__(		self		:      Union[str, Any]       ,SCREAMING_SNAKE_CASE__		:      Dict       ,SCREAMING_SNAKE_CASE__		:      Tuple       ,SCREAMING_SNAKE_CASE__		:      Optional[Any]="<s>"       ,SCREAMING_SNAKE_CASE__		:      Dict="</s>"       ,SCREAMING_SNAKE_CASE__		:      Any="</s>"       ,SCREAMING_SNAKE_CASE__		:      Dict="<s>"       ,SCREAMING_SNAKE_CASE__		:      Union[str, Any]="<unk>"       ,SCREAMING_SNAKE_CASE__		:      Union[str, Any]="<pad>"       ,SCREAMING_SNAKE_CASE__		:      List[str]="<mask>"       ,**SCREAMING_SNAKE_CASE__		:      Optional[Any]       ,):
								super().__init__(
								    bos_token=SCREAMING_SNAKE_CASE__       ,eos_token=SCREAMING_SNAKE_CASE__       ,unk_token=SCREAMING_SNAKE_CASE__       ,sep_token=SCREAMING_SNAKE_CASE__       ,cls_token=SCREAMING_SNAKE_CASE__       ,pad_token=SCREAMING_SNAKE_CASE__       ,mask_token=SCREAMING_SNAKE_CASE__       ,**SCREAMING_SNAKE_CASE__       ,)

								__lowerCamelCase    :    List[str] 	=			vocab_file
								__lowerCamelCase    :    Any 	=			merges_file

								__lowerCamelCase    :    List[Any] 	=			{}
								__lowerCamelCase    :    int 	=			0
								__lowerCamelCase    :    Optional[int] 	=			1
								__lowerCamelCase    :    int 	=			2
								__lowerCamelCase    :    Any 	=			3

								self.add_from_file(SCREAMING_SNAKE_CASE__)

								__lowerCamelCase    :    Optional[int] 	=			{v: k for k, v in self.encoder.items()}

								with open(SCREAMING_SNAKE_CASE__       ,encoding='utf-8') as merges_handle:
									__lowerCamelCase    :    Any 	=			merges_handle.read().split('\n')[:-1]
								__lowerCamelCase    :    Tuple 	=			[tuple(merge.split()[:-1]) for merge in merges]
								__lowerCamelCase    :    Optional[int] 	=			dict(zip(SCREAMING_SNAKE_CASE__       ,range(len(SCREAMING_SNAKE_CASE__))))
								__lowerCamelCase    :    str 	=			{}
							def    lowerCAmelCase					(		self		:      str       ,SCREAMING_SNAKE_CASE__		:      List[int]       ,SCREAMING_SNAKE_CASE__		:      Optional[List[int]] = None):

								if token_ids_a is None:
									return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
								__lowerCamelCase    :    Any 	=			[self.cls_token_id]
								__lowerCamelCase    :    Optional[Any] 	=			[self.sep_token_id]
								return cls + token_ids_a + sep + sep + token_ids_a + sep
							def    lowerCAmelCase					(		self		:      List[str]       ,SCREAMING_SNAKE_CASE__		:      List[int]       ,SCREAMING_SNAKE_CASE__		:      Optional[List[int]] = None       ,SCREAMING_SNAKE_CASE__		:      bool = False):

								if already_has_special_tokens:
									return super().get_special_tokens_mask(
									    token_ids_a=SCREAMING_SNAKE_CASE__       ,token_ids_a=SCREAMING_SNAKE_CASE__       ,already_has_special_tokens=SCREAMING_SNAKE_CASE__)

								if token_ids_a is None:
									return [1] + ([0] * len(SCREAMING_SNAKE_CASE__)) + [1]
								return [1] + ([0] * len(SCREAMING_SNAKE_CASE__)) + [1, 1] + ([0] * len(SCREAMING_SNAKE_CASE__)) + [1]
							def    lowerCAmelCase					(		self		:      Any       ,SCREAMING_SNAKE_CASE__		:      List[int]       ,SCREAMING_SNAKE_CASE__		:      Optional[List[int]] = None):
								__lowerCamelCase    :    List[Any] 	=			[self.sep_token_id]
								__lowerCamelCase    :    str 	=			[self.cls_token_id]

								if token_ids_a is None:
									return len(cls + token_ids_a + sep) * [0]
								return len(cls + token_ids_a + sep + sep + token_ids_a + sep) * [0]
							@property
							def    lowerCAmelCase					(		self		:      List[Any]):
								return len(self.encoder)
							def    lowerCAmelCase					(		self		:      Tuple):
								return dict(self.encoder       ,**self.added_tokens_encoder)
							def    lowerCAmelCase					(		self		:      int       ,SCREAMING_SNAKE_CASE__		:      List[Any]):

								if token in self.cache:
									return self.cache[token]
								__lowerCamelCase    :    Optional[Any] 	=			tuple(SCREAMING_SNAKE_CASE__)
								__lowerCamelCase    :    Any 	=			tuple(list(word[:-1]) + [word[-1] + '</w>'])
								__lowerCamelCase    :    str 	=			get_pairs(SCREAMING_SNAKE_CASE__)

								if not pairs:
									return token

								while True:
									__lowerCamelCase    :    Union[str, Any] 	=			min(SCREAMING_SNAKE_CASE__       ,key=lambda SCREAMING_SNAKE_CASE__: self.bpe_ranks.get(SCREAMING_SNAKE_CASE__       ,float('inf')))
									if bigram not in self.bpe_ranks:
										break
									__lowerCamelCase    :    Tuple 	=			bigram
									__lowerCamelCase    :    Optional[int] 	=			[]
									__lowerCamelCase    :    Dict 	=			0
									while i < len(SCREAMING_SNAKE_CASE__):
										try:
											__lowerCamelCase    :    int 	=			word.index(SCREAMING_SNAKE_CASE__       ,SCREAMING_SNAKE_CASE__)
										except ValueError:
											new_word.extend(word[i:])
											break
										else:
											new_word.extend(word[i:j])
											__lowerCamelCase    :    Union[str, Any] 	=			j

										if word[i] == first and i < len(SCREAMING_SNAKE_CASE__) - 1 and word[i + 1] == second:
											new_word.append(first + second)
											i += 2
										else:
											new_word.append(word[i])
											i += 1
									__lowerCamelCase    :    Union[str, Any] 	=			tuple(SCREAMING_SNAKE_CASE__)
									__lowerCamelCase    :    Tuple 	=			new_word
									if len(SCREAMING_SNAKE_CASE__) == 1:
										break
									else:
										__lowerCamelCase    :    Tuple 	=			get_pairs(SCREAMING_SNAKE_CASE__)
								__lowerCamelCase    :    Optional[Any] 	=			"""@@ """.join(SCREAMING_SNAKE_CASE__)
								__lowerCamelCase    :    Optional[Any] 	=			word[:-4]
								__lowerCamelCase    :    int 	=			word
								return word
							def    lowerCAmelCase					(		self		:      List[str]       ,SCREAMING_SNAKE_CASE__		:      List[Any]):
								__lowerCamelCase    :    Dict 	=			[]

								__lowerCamelCase    :    int 	=			re.findall(R'\S+\n?'       ,SCREAMING_SNAKE_CASE__)

								for token in words:
									split_tokens.extend(list(self.bpe(SCREAMING_SNAKE_CASE__).split(' ')))
								return split_tokens
							def    lowerCAmelCase					(		self		:      str       ,SCREAMING_SNAKE_CASE__		:      Optional[int]):
								return self.encoder.get(SCREAMING_SNAKE_CASE__       ,self.encoder.get(self.unk_token))
							def    lowerCAmelCase					(		self		:      Any       ,SCREAMING_SNAKE_CASE__		:      List[Any]):
								return self.decoder.get(SCREAMING_SNAKE_CASE__       ,self.unk_token)
							def    lowerCAmelCase					(		self		:      int       ,SCREAMING_SNAKE_CASE__		:      Optional[Any]):
								__lowerCamelCase    :    str 	=			""" """.join(SCREAMING_SNAKE_CASE__).replace('@@ '       ,'').strip()
								return out_string
							def    lowerCAmelCase					(		self		:      Optional[Any]       ,SCREAMING_SNAKE_CASE__		:      str       ,SCREAMING_SNAKE_CASE__		:      Optional[str] = None):

								if not os.path.isdir(SCREAMING_SNAKE_CASE__):
									logger.error(F"Vocabulary path ({save_directory}) should be a directory")
									return
								__lowerCamelCase    :    str 	=			os.path.join(
								    SCREAMING_SNAKE_CASE__       ,(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file'])
								__lowerCamelCase    :    List[str] 	=			os.path.join(
								    SCREAMING_SNAKE_CASE__       ,(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['merges_file'])

								if os.path.abspath(self.vocab_file) != os.path.abspath(SCREAMING_SNAKE_CASE__):
									copyfile(self.vocab_file       ,SCREAMING_SNAKE_CASE__)

								if os.path.abspath(self.merges_file) != os.path.abspath(SCREAMING_SNAKE_CASE__):
									copyfile(self.merges_file       ,SCREAMING_SNAKE_CASE__)

								return out_vocab_file, out_merge_file


							def    lowerCAmelCase					(		self		:      str       ,SCREAMING_SNAKE_CASE__		:      Optional[int]):

								if isinstance(SCREAMING_SNAKE_CASE__       ,SCREAMING_SNAKE_CASE__):
									try:
										with open(SCREAMING_SNAKE_CASE__       ,'r'       ,encoding='utf-8') as fd:
											self.add_from_file(SCREAMING_SNAKE_CASE__)
									except FileNotFoundError as fnfe:
										raise fnfe
									except UnicodeError:
										raise Exception(F"Incorrect encoding detected in {f}, please rebuild the dataset")
									return

								__lowerCamelCase    :    int 	=			f.readlines()
								for lineTmp in lines:
									__lowerCamelCase    :    Any 	=			lineTmp.strip()
									__lowerCamelCase    :    int 	=			line.rfind(' ')
									if idx == -1:
										raise ValueError('Incorrect dictionary format, expected \'<token> <cnt>\'')
									__lowerCamelCase    :    Tuple 	=			line[:idx]
									__lowerCamelCase    :    Dict 	=			len(self.encoder)







import unittest

import numpy as np

from diffusers import OnnxStableDiffusionInpaintPipelineLegacy
from diffusers.utils.testing_utils import (
    is_onnx_available,
    load_image,
    load_numpy,
    nightly,
    require_onnxruntime,
    require_torch_gpu,
)


if is_onnx_available():
					import onnxruntime as ort






@nightly
@require_onnxruntime
@require_torch_gpu
class 	A_		(	unittest.TestCase    ):
							@property
							def    lowerCAmelCase					(		self		:      Union[str, Any]):
								return (
								    "CUDAExecutionProvider",
								    {
								        "gpu_mem_limit": "15000000000",  # 15GB
								        "arena_extend_strategy": "kSameAsRequested",
								    },
								)
							@property
							def    lowerCAmelCase					(		self		:      Optional[Any]):
								__lowerCamelCase    :    Optional[int] 	=			ort.SessionOptions()
								__lowerCamelCase    :    Tuple 	=			False
								return options


							def    lowerCAmelCase					(		self		:      Any):
								__lowerCamelCase    :    Tuple 	=			load_image(
								    'https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main'
								    '/in_paint/overture-creations-5sI6fQgYIuo.png')
								__lowerCamelCase    :    List[str] 	=			load_image(
								    'https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main'
								    '/in_paint/overture-creations-5sI6fQgYIuo_mask.png')
								__lowerCamelCase    :    Optional[int] 	=			load_numpy(
								    'https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main'
								    '/in_paint/red_cat_sitting_on_a_park_bench_onnx.npy')

								# using the PNDM scheduler by default
								__lowerCamelCase    :    Dict 	=			OnnxStableDiffusionInpaintPipelineLegacy.from_pretrained(
								    'CompVis/stable-diffusion-v1-4'       ,revision='onnx'       ,safety_checker=SCREAMING_SNAKE_CASE__       ,feature_extractor=SCREAMING_SNAKE_CASE__       ,provider=self.gpu_provider       ,sess_options=self.gpu_options       ,)
								pipe.set_progress_bar_config(disable=SCREAMING_SNAKE_CASE__)

								__lowerCamelCase    :    Union[str, Any] 	=			'A red cat sitting on a park bench'

								__lowerCamelCase    :    Any 	=			np.random.RandomState(0)
								__lowerCamelCase    :    List[Any] 	=			pipe(
								    prompt=SCREAMING_SNAKE_CASE__       ,image=SCREAMING_SNAKE_CASE__       ,mask_image=SCREAMING_SNAKE_CASE__       ,strength=0.75       ,guidance_scale=7.5       ,num_inference_steps=1_5       ,generator=SCREAMING_SNAKE_CASE__       ,output_type='np'       ,)

								__lowerCamelCase    :    Union[str, Any] 	=			output.images[0]

								assert image.shape == (5_1_2, 5_1_2, 3)
								assert np.abs(expected_image - image).max() < 1E-2




