




"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging


a_				:    List[Any]										=     logging.get_logger(__name__)

a_				:    str										=     {
    '''tanreinama/GPTSAN-2.8B-spout_is_uniform''': (
        '''https://huggingface.co/tanreinama/GPTSAN-2.8B-spout_is_uniform/resolve/main/config.json'''
    ),
}

class __lowercase(      lowercase__				):




					'''simple docstring'''


					__a						:						Optional[Any]     		= 'gptsan-japanese'
					__a						:						Optional[int]     		= [
					    'past_key_values',
					]
					__a						:						int     		= {
					    'hidden_size': 'd_model',
					    'num_attention_heads': 'num_heads',
					    'num_hidden_layers': 'num_layers',
					}
					def __init__(    self						,	__a=36000						,	__a=1280						,	__a=1024						,	__a=8192						,	__a=4096						,	__a=128						,	__a=10						,	__a=0						,	__a=16						,	__a=16						,	__a=128						,	__a=0.0						,	__a=1E-5						,	__a=False						,	__a=0.0						,	__a="float32"						,	__a=False						,	__a=False						,	__a=False						,	__a=0.002						,	__a=False						,	__a=True						,	__a=35998						,	__a=35995						,	__a=35999						,	**__a						,	):
								__lowerCamelCase					:	Any	       =				vocab_size
								__lowerCamelCase					:	List[Any]	       =				max_position_embeddings
								__lowerCamelCase					:	List[str]	       =				d_model
								__lowerCamelCase					:	List[str]	       =				d_ff
								__lowerCamelCase					:	Tuple	       =				d_ext
								__lowerCamelCase					:	str	       =				d_spout
								__lowerCamelCase					:	List[Any]	       =				num_switch_layers
								__lowerCamelCase					:	List[Any]	       =				num_ext_layers
								__lowerCamelCase					:	Tuple	       =				num_switch_layers + num_ext_layers
								__lowerCamelCase					:	Tuple	       =				num_heads
								__lowerCamelCase					:	Union[str, Any]	       =				num_experts
								__lowerCamelCase					:	Optional[Any]	       =				expert_capacity
								__lowerCamelCase					:	Dict	       =				dropout_rate
								__lowerCamelCase					:	Optional[Any]	       =				layer_norm_epsilon
								__lowerCamelCase					:	Optional[int]	       =				router_bias
								__lowerCamelCase					:	str	       =				router_jitter_noise
								__lowerCamelCase					:	List[Any]	       =				router_dtype
								__lowerCamelCase					:	List[str]	       =				router_ignore_padding_tokens
								__lowerCamelCase					:	Optional[int]	       =				output_hidden_states
								__lowerCamelCase					:	List[str]	       =				output_attentions
								__lowerCamelCase					:	Tuple	       =				initializer_factor
								__lowerCamelCase					:	Optional[int]	       =				output_router_logits
								__lowerCamelCase					:	List[Any]	       =				use_cache

								super().__init__(
								    separator_token_id=__a						,	pad_token_id=__a						,	eos_token_id=__a						,	**__a						,	)









"""simple docstring"""
import requests

a_				:    Optional[Any]										=     ''''''  # <-- Put your OpenWeatherMap appid here!
a_				:    str										=     '''https://api.openweathermap.org/data/2.5/'''





def 						UpperCAmelCase				(			A__:    str = "Chicago"							,				A__:    str = APPID     )  ->     dict:
			return requests.get(URL_BASE + 'weather'							,				params=locals()     ).json()





def 						UpperCAmelCase				(			A__:    str = "Kolkata, India"							,				A__:    str = APPID     )  ->     dict:
			return requests.get(URL_BASE + 'forecast'							,				params=locals()     ).json()





def 						UpperCAmelCase				(			A__:    float = 55.68							,				A__:    float = 12.57							,				A__:    str = APPID     )  ->     dict:
			return requests.get(URL_BASE + 'onecall'							,				params=locals()     ).json()


if __name__ == "__main__":
					from pprint import pprint

					while True:
										a_				:    List[Any]										=     input('''Enter a location:''').strip()
										if location:
															pprint(current_weather(location))
										else:
															break



