



from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available


snake_case    :						Optional[Any]  =						{
    'configuration_gpt_neo': ['GPT_NEO_PRETRAINED_CONFIG_ARCHIVE_MAP', 'GPTNeoConfig', 'GPTNeoOnnxConfig'],
}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		snake_case    :						Optional[int]  =						[
		    'GPT_NEO_PRETRAINED_MODEL_ARCHIVE_LIST',
		    'GPTNeoForCausalLM',
		    'GPTNeoForQuestionAnswering',
		    'GPTNeoForSequenceClassification',
		    'GPTNeoForTokenClassification',
		    'GPTNeoModel',
		    'GPTNeoPreTrainedModel',
		    'load_tf_weights_in_gpt_neo',
		]

try:
		if not is_flax_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		snake_case    :						List[Any]  =						[
		    'FlaxGPTNeoForCausalLM',
		    'FlaxGPTNeoModel',
		    'FlaxGPTNeoPreTrainedModel',
		]


if TYPE_CHECKING:
		from .configuration_gpt_neo import GPT_NEO_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTNeoConfig, GPTNeoOnnxConfig

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_gpt_neo import (
				    GPT_NEO_PRETRAINED_MODEL_ARCHIVE_LIST,
				    GPTNeoForCausalLM,
				    GPTNeoForQuestionAnswering,
				    GPTNeoForSequenceClassification,
				    GPTNeoForTokenClassification,
				    GPTNeoModel,
				    GPTNeoPreTrainedModel,
				    load_tf_weights_in_gpt_neo,
				)

		try:
				if not is_flax_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_flax_gpt_neo import FlaxGPTNeoForCausalLM, FlaxGPTNeoModel, FlaxGPTNeoPreTrainedModel


else:
		import sys

		snake_case    :						Optional[Any]  =						_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)




import requests

snake_case    :						int  =						''  # <-- Put your OpenWeatherMap appid here!
snake_case    :						int  =						'https://api.openweathermap.org/data/2.5/'
def 	snake_case__       (					__lowercase = "Chicago"							,     __lowercase = APPID       )		->		dict:







						"""simple docstring"""

						return requests.get(URL_BASE + "weather"							,     params=locals()       ).json()
def 	snake_case__       (					__lowercase = "Kolkata, India"							,     __lowercase = APPID       )		->		dict:







						"""simple docstring"""

						return requests.get(URL_BASE + "forecast"							,     params=locals()       ).json()
def 	snake_case__       (					__lowercase = 55.68							,     __lowercase = 12.57							,     __lowercase = APPID       )		->		dict:







						"""simple docstring"""

						return requests.get(URL_BASE + "onecall"							,     params=locals()       ).json()


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

		while True:
				snake_case    :						int  =						input('Enter a location:').strip()
				if location:
						pprint(current_weather(location))
				else:
						break