

"""simple docstring"""





import argparse
import json
import os

import torch
from transformers.file_utils import has_file

from diffusers import UNetaDConditionModel, UNetaDModel


__UpperCamelCase  :      List[str]							      =		False
__UpperCamelCase  :      List[Any]							      =		True
__UpperCamelCase  :      Optional[Any]							      =		False


if __name__ == "__main__":
							__UpperCamelCase  :      Any							      =		argparse.ArgumentParser()

							parser.add_argument(
							    '''--repo_path''',
							    default=None,
							    type=str,
							    required=True,
							    help='''The config json file corresponding to the architecture.''',
							)

							parser.add_argument('''--dump_path''', default=None, type=str, required=True, help='''Path to the output model.''')

							__UpperCamelCase  :      List[str]							      =		parser.parse_args()

							__UpperCamelCase  :      Tuple							      =		{
							    '''image_size''': '''sample_size''',
							    '''num_res_blocks''': '''layers_per_block''',
							    '''block_channels''': '''block_out_channels''',
							    '''down_blocks''': '''down_block_types''',
							    '''up_blocks''': '''up_block_types''',
							    '''downscale_freq_shift''': '''freq_shift''',
							    '''resnet_num_groups''': '''norm_num_groups''',
							    '''resnet_act_fn''': '''act_fn''',
							    '''resnet_eps''': '''norm_eps''',
							    '''num_head_channels''': '''attention_head_dim''',
							}

							__UpperCamelCase  :      Dict							      =		{
							    '''time_steps''': '''time_proj''',
							    '''mid''': '''mid_block''',
							    '''downsample_blocks''': '''down_blocks''',
							    '''upsample_blocks''': '''up_blocks''',
							}

							__UpperCamelCase  :      int							      =		'''''' if has_file(args.repo_path, '''config.json''') else '''unet'''

							with open(os.path.join(args.repo_path, subfolder, '''config.json'''), '''r''', encoding='''utf-8''') as reader:
														__UpperCamelCase  :      int							      =		reader.read()
														__UpperCamelCase  :      Tuple							      =		json.loads(text)

							if do_only_config:
														for key in config_parameters_to_change.keys():
																					config.pop(key, None)

							if has_file(args.repo_path, '''config.json'''):
														__UpperCamelCase  :      int							      =		UNetaDModel(**config)
							else:
														__UpperCamelCase  :      List[Any]							      =		UNetaDConditionModel if '''ldm-text2im-large-256''' in args.repo_path else UNetaDModel
														__UpperCamelCase  :      Tuple							      =		class_name(**config)

							if do_only_config:
														model.save_config(os.path.join(args.repo_path, subfolder))

							__UpperCamelCase  :      List[Any]							      =		dict(model.config)

							if do_only_renaming:
														for key, value in config_parameters_to_change.items():
																					if key in config:
																												__UpperCamelCase  :      Optional[int]							      =		config[key]
																												del config[key]

														__UpperCamelCase  :      Tuple							      =		[k.replace('''UNetRes''', '''''') for k in config['''down_block_types''']]
														__UpperCamelCase  :      Tuple							      =		[k.replace('''UNetRes''', '''''') for k in config['''up_block_types''']]

							if do_only_weights:
														__UpperCamelCase  :      List[Any]							      =		torch.load(os.path.join(args.repo_path, subfolder, '''diffusion_pytorch_model.bin'''))

														__UpperCamelCase  :      int							      =		{}
														for param_key, param_value in state_dict.items():
																					if param_key.endswith('''.op.bias''') or param_key.endswith('''.op.weight'''):
																												continue
																					__UpperCamelCase  :      Optional[Any]							      =		False
																					for key, new_key in key_parameters_to_change.items():
																												if not has_changed and param_key.split('''.''')[0] == key:
																																			__UpperCamelCase  :      List[str]							      =		param_value
																																			__UpperCamelCase  :      Any							      =		True
																					if not has_changed:
																												__UpperCamelCase  :      Union[str, Any]							      =		param_value

														model.load_state_dict(new_state_dict)
														model.save_pretrained(os.path.join(args.repo_path, subfolder))







"""simple docstring"""





import webbrowser
from sys import argv
from urllib.parse import parse_qs, quote

import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent

if __name__ == "__main__":
							__UpperCamelCase  :      Tuple							      =		'''%20'''.join(argv[1:]) if len(argv) > 1 else quote(str(input('''Search: ''')))

							print('''Googling.....''')

							__UpperCamelCase  :      Optional[int]							      =		F'''https://www.google.com/search?q={query}&num=100'''

							__UpperCamelCase  :      Optional[Any]							      =		requests.get(
							    url,
							    headers={'''User-Agent''': str(UserAgent().random)},
							)

							try:
														__UpperCamelCase  :      Union[str, Any]							      =		(
														    BeautifulSoup(res.text, '''html.parser''')
														    .find('''div''', attrs={'''class''': '''yuRUbf'''})
														    .find('''a''')
														    .get('''href''')
														)

							except AttributeError:
														__UpperCamelCase  :      str							      =		parse_qs(
														    BeautifulSoup(res.text, '''html.parser''')
														    .find('''div''', attrs={'''class''': '''kCrYT'''})
														    .find('''a''')
														    .get('''href''')
														)['''url'''][0]

							webbrowser.open(link)




