



"""simple docstring"""







import requests

lowerCAmelCase_  		=  ''  # <-- Put your OpenWeatherMap appid here!
lowerCAmelCase_  		=  'https://api.openweathermap.org/data/2.5/'



def 	__UpperCAmelCase (       __lowerCamelCase = "Chicago"		,	__lowerCamelCase = APPID      )				-> Optional[Any]:
		return requests.get(URL_BASE + '''weather'''		,	params=locals()      ).json()



def 	__UpperCAmelCase (       __lowerCamelCase = "Kolkata, India"		,	__lowerCamelCase = APPID      )				-> Optional[Any]:
		return requests.get(URL_BASE + '''forecast'''		,	params=locals()      ).json()



def 	__UpperCAmelCase (       __lowerCamelCase = 5_5.6_8		,	__lowerCamelCase = 1_2.5_7		,	__lowerCamelCase = APPID      )				-> int:
		return requests.get(URL_BASE + '''onecall'''		,	params=locals()      ).json()


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

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




'''simple docstring'''


import json
import os
import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils import IMAGE_PROCESSOR_NAME, is_vision_available


if is_vision_available():
      from PIL import Image

      from transformers import AlignProcessor, EfficientNetImageProcessor







@require_vision
class 							__magic_name__	(       unittest.TestCase ):

     """simple docstring"""






     def lowerCAmelCase__  (   self		):


          '''simple docstring'''





          __A	:       int      =							tempfile.mkdtemp()

          __A	:       List[Any]      =							[
              "[UNK]",
              "[CLS]",
              "[SEP]",
              "[PAD]",
              "[MASK]",
              "want",
              "##want",
              "##ed",
              "wa",
              "un",
              "runn",
              "##ing",
              ",",
              "low",
              "lowest",
          ]
          __A	:       Tuple      =							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]		)		)

          __A	:       List[str]      =							{
              "do_resize": True,
              "size": 20,
              "do_center_crop": True,
              "crop_size": 18,
              "do_normalize": True,
              "image_mean": [0.4814_5466, 0.457_8275, 0.4082_1073],
              "image_std": [0.2686_2954, 0.2613_0258, 0.2757_7711],
          }
          __A	:       Union[str, Any]      =							os.path.join(self.tmpdirname			,     lowerCamelCase		)
          with open(self.image_processor_file			,     "w"			,     encoding="utf-8"		) as fp:
               json.dump(lowerCamelCase			,     lowerCamelCase		)


     def lowerCAmelCase__  (   self			,     **lowerCamelCase		):


          '''simple docstring'''





          return BertTokenizer.from_pretrained(self.tmpdirname			,     **lowerCamelCase		)


     def lowerCAmelCase__  (   self			,     **lowerCamelCase		):


          '''simple docstring'''





          return BertTokenizerFast.from_pretrained(self.tmpdirname			,     **lowerCamelCase		)


     def lowerCAmelCase__  (   self			,     **lowerCamelCase		):


          '''simple docstring'''





          return EfficientNetImageProcessor.from_pretrained(self.tmpdirname			,     **lowerCamelCase		)


     def lowerCAmelCase__  (   self		):


          '''simple docstring'''





          shutil.rmtree(self.tmpdirname		)


     def lowerCAmelCase__  (   self		):


          '''simple docstring'''





          __A	:       int      =							[np.random.randint(255			,     size=(3, 30, 400)			,     dtype=np.uinta		)]
          __A	:       int      =							[Image.fromarray(np.moveaxis(lowerCamelCase			,     0			,     -1		)		) for x in image_inputs]
          return image_inputs


     def lowerCAmelCase__  (   self		):


          '''simple docstring'''





          __A	:       Union[str, Any]      =							self.get_tokenizer()
          __A	:       int      =							self.get_rust_tokenizer()
          __A	:       List[str]      =							self.get_image_processor()

          __A	:       List[Any]      =							AlignProcessor(tokenizer=lowerCamelCase			,     image_processor=lowerCamelCase		)
          processor_slow.save_pretrained(self.tmpdirname		)
          __A	:       List[Any]      =							AlignProcessor.from_pretrained(self.tmpdirname			,     use_fast=lowerCamelCase		)

          __A	:       int      =							AlignProcessor(tokenizer=lowerCamelCase			,     image_processor=lowerCamelCase		)
          processor_fast.save_pretrained(self.tmpdirname		)
          __A	:       List[str]      =							AlignProcessor.from_pretrained(self.tmpdirname		)

          self.assertEqual(processor_slow.tokenizer.get_vocab()			,     tokenizer_slow.get_vocab()		)
          self.assertEqual(processor_fast.tokenizer.get_vocab()			,     tokenizer_fast.get_vocab()		)
          self.assertEqual(tokenizer_slow.get_vocab()			,     tokenizer_fast.get_vocab()		)
          self.assertIsInstance(processor_slow.tokenizer			,     lowerCamelCase		)
          self.assertIsInstance(processor_fast.tokenizer			,     lowerCamelCase		)

          self.assertEqual(processor_slow.image_processor.to_json_string()			,     image_processor.to_json_string()		)
          self.assertEqual(processor_fast.image_processor.to_json_string()			,     image_processor.to_json_string()		)
          self.assertIsInstance(processor_slow.image_processor			,     lowerCamelCase		)
          self.assertIsInstance(processor_fast.image_processor			,     lowerCamelCase		)


     def lowerCAmelCase__  (   self		):


          '''simple docstring'''





          __A	:       List[Any]      =							AlignProcessor(tokenizer=self.get_tokenizer()			,     image_processor=self.get_image_processor()		)
          processor.save_pretrained(self.tmpdirname		)

          __A	:       List[str]      =							self.get_tokenizer(bos_token="(BOS)"			,     eos_token="(EOS)"		)
          __A	:       int      =							self.get_image_processor(do_normalize=lowerCamelCase			,     padding_value=1.0		)

          __A	:       Optional[int]      =							AlignProcessor.from_pretrained(
              self.tmpdirname			,     bos_token="(BOS)"			,     eos_token="(EOS)"			,     do_normalize=lowerCamelCase			,     padding_value=1.0		)

          self.assertEqual(processor.tokenizer.get_vocab()			,     tokenizer_add_kwargs.get_vocab()		)
          self.assertIsInstance(processor.tokenizer			,     lowerCamelCase		)

          self.assertEqual(processor.image_processor.to_json_string()			,     image_processor_add_kwargs.to_json_string()		)
          self.assertIsInstance(processor.image_processor			,     lowerCamelCase		)


     def lowerCAmelCase__  (   self		):


          '''simple docstring'''





          __A	:       Optional[Any]      =							self.get_image_processor()
          __A	:       Optional[Any]      =							self.get_tokenizer()

          __A	:       List[str]      =							AlignProcessor(tokenizer=lowerCamelCase			,     image_processor=lowerCamelCase		)

          __A	:       int      =							self.prepare_image_inputs()

          __A	:       Optional[int]      =							image_processor(lowerCamelCase			,     return_tensors="np"		)
          __A	:       Dict      =							processor(images=lowerCamelCase			,     return_tensors="np"		)

          for key in input_image_proc.keys():
               self.assertAlmostEqual(input_image_proc[key].sum()			,     input_processor[key].sum()			,     delta=1E-2		)


     def lowerCAmelCase__  (   self		):


          '''simple docstring'''





          __A	:       str      =							self.get_image_processor()
          __A	:       int      =							self.get_tokenizer()

          __A	:       Optional[int]      =							AlignProcessor(tokenizer=lowerCamelCase			,     image_processor=lowerCamelCase		)

          __A	:       Optional[Any]      =							"lower newer"

          __A	:       Union[str, Any]      =							processor(text=lowerCamelCase		)

          __A	:       int      =							tokenizer(lowerCamelCase			,     padding="max_length"			,     max_length=64		)

          for key in encoded_tok.keys():
               self.assertListEqual(encoded_tok[key]			,     encoded_processor[key]		)


     def lowerCAmelCase__  (   self		):


          '''simple docstring'''





          __A	:       Optional[int]      =							self.get_image_processor()
          __A	:       Optional[Any]      =							self.get_tokenizer()

          __A	:       int      =							AlignProcessor(tokenizer=lowerCamelCase			,     image_processor=lowerCamelCase		)

          __A	:       Tuple      =							"lower newer"
          __A	:       int      =							self.prepare_image_inputs()

          __A	:       str      =							processor(text=lowerCamelCase			,     images=lowerCamelCase		)

          self.assertListEqual(list(inputs.keys()		)			,     ["input_ids", "token_type_ids", "attention_mask", "pixel_values"]		)

          # test if it raises when no input is passed
          with pytest.raises(lowerCamelCase		):
               processor()


     def lowerCAmelCase__  (   self		):


          '''simple docstring'''





          __A	:       Dict      =							self.get_image_processor()
          __A	:       Tuple      =							self.get_tokenizer()

          __A	:       Dict      =							AlignProcessor(tokenizer=lowerCamelCase			,     image_processor=lowerCamelCase		)

          __A	:       Optional[int]      =							[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

          __A	:       Optional[int]      =							processor.batch_decode(lowerCamelCase		)
          __A	:       Optional[int]      =							tokenizer.batch_decode(lowerCamelCase		)

          self.assertListEqual(lowerCamelCase			,     lowerCamelCase		)


     def lowerCAmelCase__  (   self		):


          '''simple docstring'''





          __A	:       str      =							self.get_image_processor()
          __A	:       Union[str, Any]      =							self.get_tokenizer()

          __A	:       Union[str, Any]      =							AlignProcessor(tokenizer=lowerCamelCase			,     image_processor=lowerCamelCase		)

          __A	:       int      =							"lower newer"
          __A	:       str      =							self.prepare_image_inputs()

          __A	:       Tuple      =							processor(text=lowerCamelCase			,     images=lowerCamelCase		)

          self.assertListEqual(list(inputs.keys()		)			,     processor.model_input_names		)

