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_  (     _A				):






    '''simple docstring'''






    def __init__(			self				,				__lowercase) ->			List[Any]:
        super().__init__()
        __UpperCamelCase  :Union[str, Any]    						=	nn.ModuleList(__lowercase)







    def     UpperCamelCase__     (			self				,				__lowercase				,				__lowercase				,				__lowercase				,				__lowercase				,				__lowercase				,				__lowercase = None				,				__lowercase = None				,				__lowercase = None				,				__lowercase = None				,				__lowercase = False				,				__lowercase = True				,				) ->			Union[ControlNetOutput, Tuple]:
        for i, (image, scale, controlnet) in enumerate(zip(__lowercase				,				__lowercase				,				self.nets)):
            __UpperCamelCase  :List[str]    						=	controlnet(
                __lowercase				,				__lowercase				,				__lowercase				,				__lowercase				,				__lowercase				,				__lowercase				,				__lowercase				,				__lowercase				,				__lowercase				,				__lowercase				,				__lowercase				,				)

            # merge samples
            if i == 0:
                __UpperCamelCase  :Optional[int]    						=	down_samples, mid_sample
            else:
                __UpperCamelCase  :Optional[int]    						=	[
                    samples_prev + samples_curr
                    for samples_prev, samples_curr in zip(__lowercase				,				__lowercase)
                ]
                mid_block_res_sample += mid_sample

        return down_block_res_samples, mid_block_res_sample







    def     UpperCamelCase__     (			self				,				__lowercase				,				__lowercase = True				,				__lowercase = None				,				__lowercase = False				,				__lowercase = None				,				) ->			Union[str, Any]:
        __UpperCamelCase  :List[str]    						=	0
        __UpperCamelCase  :Optional[int]    						=	save_directory
        for controlnet in self.nets:
            controlnet.save_pretrained(
                __lowercase				,				is_main_process=__lowercase				,				save_function=__lowercase				,				safe_serialization=__lowercase				,				variant=__lowercase				,				)

            idx += 1
            __UpperCamelCase  :List[Any]    						=	model_path_to_save + f"""_{idx}"""







    @classmethod
    def     UpperCamelCase__     (			cls				,				__lowercase				,				**__lowercase) ->			Dict:
        __UpperCamelCase  :List[Any]    						=	0
        __UpperCamelCase  :int    						=	[]

        # 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`, ...
        __UpperCamelCase  :Any    						=	pretrained_model_path
        while os.path.isdir(__lowercase):
            __UpperCamelCase  :List[str]    						=	ControlNetModel.from_pretrained(__lowercase				,				**__lowercase)
            controlnets.append(__lowercase)

            idx += 1
            __UpperCamelCase  :Optional[Any]    						=	pretrained_model_path + f"""_{idx}"""

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

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

        return cls(__lowercase)







import os
import unittest

from transformers.models.cpmant.tokenization_cpmant import VOCAB_FILES_NAMES, CpmAntTokenizer
from transformers.testing_utils import require_jieba, tooslow

from ...test_tokenization_common import TokenizerTesterMixin


@require_jieba
class 			lowerCamelCase_  (     UpperCAmelCase_		,			unittest.TestCase				):






    '''simple docstring'''






    a__			:		Any      			=   CpmAntTokenizer
    a__			:		Optional[Any]      			=   False







    def     UpperCamelCase__     (			self) ->			Any:
        super().setUp()

        __UpperCamelCase  :Optional[int]    						=	[
            '''<d>''',
            '''</d>''',
            '''<s>''',
            '''</s>''',
            '''</_>''',
            '''<unk>''',
            '''<pad>''',
            '''</n>''',
            '''我''',
            '''是''',
            '''C''',
            '''P''',
            '''M''',
            '''A''',
            '''n''',
            '''t''',
        ]
        __UpperCamelCase  :Optional[int]    						=	os.path.join(self.tmpdirname				,				VOCAB_FILES_NAMES['''vocab_file'''])
        with open(self.vocab_file				,				'''w'''				,				encoding='''utf-8''') as vocab_writer:
            vocab_writer.write(''''''.join([x + '''\n''' for x in vocab_tokens]))







    @tooslow
    def     UpperCamelCase__     (			self) ->			Dict:
        __UpperCamelCase  :Tuple    						=	CpmAntTokenizer.from_pretrained('''openbmb/cpm-ant-10b''')
        __UpperCamelCase  :Dict    						=	'''今天天气真好！'''
        __UpperCamelCase  :Tuple    						=	['''今天''', '''天气''', '''真''', '''好''', '''！''']
        __UpperCamelCase  :Optional[Any]    						=	tokenizer.tokenize(__lowercase)
        self.assertListEqual(__lowercase				,				__lowercase)
        __UpperCamelCase  :int    						=	'''今天天气真好！'''
        __UpperCamelCase  :List[str]    						=	[tokenizer.bos_token] + tokens

        __UpperCamelCase  :List[str]    						=	[6, 9_802, 14_962, 2_082, 831, 244]
        self.assertListEqual(tokenizer.convert_tokens_to_ids(__lowercase)				,				__lowercase)

        __UpperCamelCase  :Dict    						=	tokenizer.decode(__lowercase)
        self.assertEqual(__lowercase				,				__lowercase)





