




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


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

a_				:    Tuple										=     {
    '''CarlCochet/trajectory-transformer-halfcheetah-medium-v2''': (
        '''https://huggingface.co/CarlCochet/trajectory-transformer-halfcheetah-medium-v2/resolve/main/config.json'''
    ),
    # See all TrajectoryTransformer models at https://huggingface.co/models?filter=trajectory_transformer
}

class __lowercase(      lowercase__				):




					'''simple docstring'''


					__a						:						Optional[int]     		= 'trajectory_transformer'
					__a						:						Tuple     		= ['past_key_values']
					__a						:						Optional[int]     		= {
					    'hidden_size': 'n_embd',
					    'num_attention_heads': 'n_head',
					    'num_hidden_layers': 'n_layer',
					}
					def __init__(    self						,	__a=100						,	__a=5						,	__a=1						,	__a=1						,	__a=249						,	__a=6						,	__a=17						,	__a=25						,	__a=4						,	__a=4						,	__a=128						,	__a=0.1						,	__a=0.1						,	__a=0.1						,	__a=0.0_006						,	__a=512						,	__a=0.02						,	__a=1E-12						,	__a=1						,	__a=True						,	__a=1						,	__a=50256						,	__a=50256						,	**__a						,	):
								__lowerCamelCase					:	int	       =				vocab_size
								__lowerCamelCase					:	Any	       =				action_weight
								__lowerCamelCase					:	int	       =				reward_weight
								__lowerCamelCase					:	Union[str, Any]	       =				value_weight
								__lowerCamelCase					:	Tuple	       =				max_position_embeddings
								__lowerCamelCase					:	Any	       =				block_size
								__lowerCamelCase					:	List[str]	       =				action_dim
								__lowerCamelCase					:	Tuple	       =				observation_dim
								__lowerCamelCase					:	int	       =				transition_dim
								__lowerCamelCase					:	List[str]	       =				learning_rate
								__lowerCamelCase					:	Union[str, Any]	       =				n_layer
								__lowerCamelCase					:	Union[str, Any]	       =				n_head
								__lowerCamelCase					:	int	       =				n_embd
								__lowerCamelCase					:	str	       =				embd_pdrop
								__lowerCamelCase					:	Any	       =				attn_pdrop
								__lowerCamelCase					:	int	       =				resid_pdrop
								__lowerCamelCase					:	Tuple	       =				initializer_range
								__lowerCamelCase					:	List[str]	       =				layer_norm_eps
								__lowerCamelCase					:	Union[str, Any]	       =				kaiming_initializer_range
								__lowerCamelCase					:	Tuple	       =				use_cache
								super().__init__(pad_token_id=__a						,	bos_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



