'''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 				a__(					lowerCAmelCase__	):


			'''simple docstring'''






			def __init__(   self       ,    __lowerCAmelCase):




					"""simple docstring"""


					super().__init__()
					lowerCAmelCase   					=  nn.ModuleList(__lowerCAmelCase)



			def 							a_       (   self       ,    __lowerCAmelCase       ,    __lowerCAmelCase       ,    __lowerCAmelCase       ,    __lowerCAmelCase       ,    __lowerCAmelCase       ,    __lowerCAmelCase = None       ,    __lowerCAmelCase = None       ,    __lowerCAmelCase = None       ,    __lowerCAmelCase = None       ,    __lowerCAmelCase = False       ,    __lowerCAmelCase = True       ,    ):




					"""simple docstring"""


					for i, (image, scale, controlnet) in enumerate(zip(__lowerCAmelCase       ,    __lowerCAmelCase       ,    self.nets)):
							lowerCAmelCase					,     lowerCAmelCase   					=  controlnet(
							    __lowerCAmelCase       ,    __lowerCAmelCase       ,    __lowerCAmelCase       ,    __lowerCAmelCase       ,    __lowerCAmelCase       ,    __lowerCAmelCase       ,    __lowerCAmelCase       ,    __lowerCAmelCase       ,    __lowerCAmelCase       ,    __lowerCAmelCase       ,    __lowerCAmelCase       ,    )

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

					return down_block_res_samples, mid_block_res_sample



			def 							a_       (   self       ,    __lowerCAmelCase       ,    __lowerCAmelCase = True       ,    __lowerCAmelCase = None       ,    __lowerCAmelCase = False       ,    __lowerCAmelCase = None       ,    ):




					"""simple docstring"""


					lowerCAmelCase   					=  0
					lowerCAmelCase   					=  save_directory
					for controlnet in self.nets:
							controlnet.save_pretrained(
							    __lowerCAmelCase       ,    is_main_process=__lowerCAmelCase       ,    save_function=__lowerCAmelCase       ,    safe_serialization=__lowerCAmelCase       ,    variant=__lowerCAmelCase       ,    )

							idx += 1
							lowerCAmelCase   					=  model_path_to_save + f"_{idx}"







			@classmethod
			def 							a_       (   cls       ,    __lowerCAmelCase       ,    **__lowerCAmelCase):




					"""simple docstring"""


					lowerCAmelCase   					=  0
					lowerCAmelCase   					=  []

					# 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`, ...
					lowerCAmelCase   					=  pretrained_model_path
					while os.path.isdir(__lowerCAmelCase):
							lowerCAmelCase   					=  ControlNetModel.from_pretrained(__lowerCAmelCase       ,    **__lowerCAmelCase)
							controlnets.append(__lowerCAmelCase)

							idx += 1
							lowerCAmelCase   					=  pretrained_model_path + f"_{idx}"

					logger.info(f"{len(__lowerCAmelCase)} controlnets loaded from {pretrained_model_path}.")

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

					return cls(__lowerCAmelCase)





'''simple docstring'''




from ...utils import logging
from ..ta.modeling_tf_ta import TFTaEncoderModel, TFTaForConditionalGeneration, TFTaModel
from .configuration_mta import MTaConfig


__lowercase          =  logging.get_logger(__name__)

__lowercase          =  '''T5Config'''






class 				a__(					lowerCAmelCase__	):


			'''simple docstring'''






			UpperCAmelCase_			:     List[str]      =       '''mt5'''
			UpperCAmelCase_			:     Tuple      =       MTaConfig







class 				a__(					lowerCAmelCase__	):


			'''simple docstring'''






			UpperCAmelCase_			:     List[Any]      =       '''mt5'''
			UpperCAmelCase_			:     int      =       MTaConfig







class 				a__(					lowerCAmelCase__	):


			'''simple docstring'''






			UpperCAmelCase_			:     Tuple      =       '''mt5'''
			UpperCAmelCase_			:     Union[str, Any]      =       MTaConfig




