


"""simple docstring"""




import os
from typing import Any, Callable, Dict, List, Optional, Tuple, Union

import torch
from torch import nn

from ...models.controlnet import ControlNetModel, ControlNetOutput
from ...models.modeling_utils import ModelMixin
from ...utils import logging


lowercase_			     =  logging.get_logger(__name__)
class 					__lowerCAmelCase					(   __SCREAMING_SNAKE_CASE       ):


		'''simple docstring'''



		def __init__(  self							, _a      ):
				super().__init__()
				__a           =			nn.ModuleList(_a      )

		def 			__UpperCAmelCase       (  self							, _a							, _a							, _a							, _a							, _a							, _a = None							, _a = None							, _a = None							, _a = None							, _a = False							, _a = True							, ):
				for i, (image, scale, controlnet) in enumerate(zip(_a							, _a							, self.nets      )      ):
						__a      ,     __a           =			controlnet(
						    _a							, _a							, _a							, _a							, _a							, _a							, _a							, _a							, _a							, _a							, _a							, )

						# merge samples
						if i == 0:
								__a      ,     __a           =			down_samples, mid_sample
						else:
								__a           =			[
								    samples_prev + samples_curr
								    for samples_prev, samples_curr in zip(_a							, _a      )
								]
								mid_block_res_sample += mid_sample

				return down_block_res_samples, mid_block_res_sample

		def 			__UpperCAmelCase       (  self							, _a							, _a = True							, _a = None							, _a = False							, _a = None							, ):
				__a           =			0
				__a           =			save_directory
				for controlnet in self.nets:
						controlnet.save_pretrained(
						    _a							, is_main_process=_a							, save_function=_a							, safe_serialization=_a							, variant=_a							, )

						idx += 1
						__a           =			model_path_to_save + f'''_{idx}'''





		@classmethod
		def 			__UpperCAmelCase       (  cls							, _a							, **_a      ):
				__a           =			0
				__a           =			[]

				# load controlnet and append to list until no controlnet directory exists anymore
				# first controlnet has to be saved under `./mydirectory/controlnet` to be compliant with `DiffusionPipeline.from_prertained`
				# second, third, ... controlnets have to be saved under `./mydirectory/controlnet_1`, `./mydirectory/controlnet_2`, ...
				__a           =			pretrained_model_path
				while os.path.isdir(_a      ):
						__a           =			ControlNetModel.from_pretrained(_a							, **_a      )
						controlnets.append(_a      )

						idx += 1
						__a           =			pretrained_model_path + f'''_{idx}'''

				logger.info(f'''{len(_a      )} controlnets loaded from {pretrained_model_path}.'''      )

				if len(_a      ) == 0:
						raise ValueError(
						    f'''No ControlNets found under {os.path.dirname(_a      )}. Expected at least {pretrained_model_path + '_0'}.'''      )

				return cls(_a      )










"""simple docstring"""






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

from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
							from .tokenization_barthez import BarthezTokenizer
else:
							UpperCAmelCase    :     Union[str, Any]   						=		None

UpperCAmelCase    :     Union[str, Any]   						=		logging.get_logger(__name__)

UpperCAmelCase    :     Union[str, Any]   						=		{'vocab_file': 'sentencepiece.bpe.model', 'tokenizer_file': 'tokenizer.json'}

UpperCAmelCase    :     List[str]   						=		{
    'vocab_file': {
        'moussaKam/mbarthez': 'https://huggingface.co/moussaKam/mbarthez/resolve/main/sentencepiece.bpe.model',
        'moussaKam/barthez': 'https://huggingface.co/moussaKam/barthez/resolve/main/sentencepiece.bpe.model',
        'moussaKam/barthez-orangesum-title': (
            'https://huggingface.co/moussaKam/barthez-orangesum-title/resolve/main/sentencepiece.bpe.model'
        ),
    },
    'tokenizer_file': {
        'moussaKam/mbarthez': 'https://huggingface.co/moussaKam/mbarthez/resolve/main/tokenizer.json',
        'moussaKam/barthez': 'https://huggingface.co/moussaKam/barthez/resolve/main/tokenizer.json',
        'moussaKam/barthez-orangesum-title': (
            'https://huggingface.co/moussaKam/barthez-orangesum-title/resolve/main/tokenizer.json'
        ),
    },
}

UpperCAmelCase    :     Tuple   						=		{
    'moussaKam/mbarthez': 1024,
    'moussaKam/barthez': 1024,
    'moussaKam/barthez-orangesum-title': 1024,
}

UpperCAmelCase    :     str   						=		'▁'





class      lowerCamelCase__   (     A				):







					"""simple docstring"""


					__a	       =							VOCAB_FILES_NAMES
					__a	       =							PRETRAINED_VOCAB_FILES_MAP
					__a	       =							PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
					__a	       =							["""input_ids""", """attention_mask"""]
					__a	       =							BarthezTokenizer






					def __init__(       self    : Optional[int] ,       UpperCamelCase    : List[str]=None ,       UpperCamelCase    : List[str]=None ,       UpperCamelCase    : Union[str, Any]="<s>" ,       UpperCamelCase    : Any="</s>" ,       UpperCamelCase    : Tuple="</s>" ,       UpperCamelCase    : Tuple="<s>" ,       UpperCamelCase    : int="<unk>" ,       UpperCamelCase    : List[str]="<pad>" ,       UpperCamelCase    : int="<mask>" ,       **UpperCamelCase    : Any ,       ):
												'''simple docstring'''






												__UpperCAmelCase   :						Tuple      							=					AddedToken(UpperCamelCase ,       lstrip=UpperCamelCase ,       rstrip=UpperCamelCase  ) if isinstance(UpperCamelCase ,       UpperCamelCase  ) else mask_token

												super().__init__(
												    UpperCamelCase ,       tokenizer_file=UpperCamelCase ,       bos_token=UpperCamelCase ,       eos_token=UpperCamelCase ,       unk_token=UpperCamelCase ,       sep_token=UpperCamelCase ,       cls_token=UpperCamelCase ,       pad_token=UpperCamelCase ,       mask_token=UpperCamelCase ,       **UpperCamelCase ,       )

												__UpperCAmelCase   :						List[Any]      							=					vocab_file
												__UpperCAmelCase   :						Tuple      							=					False if not self.vocab_file else True






					def lowerCamelCase__							(       self    : Any ,       UpperCamelCase    : List[int] ,       UpperCamelCase    : Optional[List[int]] = None  ):
												'''simple docstring'''






												if token_ids_a is None:
																			return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
												__UpperCAmelCase   :						List[Any]      							=					[self.cls_token_id]
												__UpperCAmelCase   :						Tuple      							=					[self.sep_token_id]
												return cls + token_ids_a + sep + sep + token_ids_a + sep






					def lowerCamelCase__							(       self    : Union[str, Any] ,       UpperCamelCase    : List[int] ,       UpperCamelCase    : Optional[List[int]] = None  ):
												'''simple docstring'''






												__UpperCAmelCase   :						List[Any]      							=					[self.sep_token_id]
												__UpperCAmelCase   :						Union[str, Any]      							=					[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]






					def lowerCamelCase__							(       self    : Tuple ,       UpperCamelCase    : str ,       UpperCamelCase    : Optional[str] = None  ):
												'''simple docstring'''






												if not self.can_save_slow_tokenizer:
																			raise ValueError(
																			    """Your fast tokenizer does not have the necessary information to save the vocabulary for a slow """
																			    """tokenizer."""  )

												if not os.path.isdir(UpperCamelCase  ):
																			logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''  )
																			return
												__UpperCAmelCase   :						List[Any]      							=					os.path.join(
												    UpperCamelCase ,       (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]  )

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

												return (out_vocab_file,)
