






'''simple docstring'''
import unittest

import numpy as np
import timeout_decorator  # noqa

from transformers import MarianConfig, is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_property

from ...generation.test_flax_utils import FlaxGenerationTesterMixin
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor


if is_flax_available():
   import os

   # The slow tests are often failing with OOM error on GPU
   # This makes JAX allocate exactly what is needed on demand, and deallocate memory that is no longer needed
   # but will be slower as stated here https://jax.readthedocs.io/en/latest/gpu_memory_allocation.html
   UpperCamelCase__	=     'platform'

   import jax
   import jax.numpy as jnp

   from transformers import MarianTokenizer
   from transformers.models.marian.modeling_flax_marian import FlaxMarianModel, FlaxMarianMTModel, shift_tokens_right




def 						__SCREAMING_SNAKE_CASE   (					_UpperCamelCase  ,						_UpperCamelCase  ,						_UpperCamelCase=None  ,						_UpperCamelCase=None  ,						_UpperCamelCase=None  ,						_UpperCamelCase=None  ,						_UpperCamelCase=None  ,						_UpperCamelCase=None  ,						):


   """simple docstring"""




   if attention_mask is None:
      lowercase_		:      str          =       np.where(input_ids != config.pad_token_id  ,						1  ,						0							)
   if decoder_attention_mask is None:
      lowercase_		:      int          =       np.where(decoder_input_ids != config.pad_token_id  ,						1  ,						0							)
   if head_mask is None:
      lowercase_		:      Optional[int]          =       np.ones((config.encoder_layers, config.encoder_attention_heads)							)
   if decoder_head_mask is None:
      lowercase_		:      int          =       np.ones((config.decoder_layers, config.decoder_attention_heads)							)
   if cross_attn_head_mask is None:
      lowercase_		:      Union[str, Any]          =       np.ones((config.decoder_layers, config.decoder_attention_heads)							)
   return {
       "input_ids": input_ids,
       "decoder_input_ids": decoder_input_ids,
       "attention_mask": attention_mask,
       "decoder_attention_mask": attention_mask,
   }


class     _UpperCAmelCase  :




    def __init__(     self					:    str					,       a					:    List[Any]					,       a					:    List[Any]=1_3					,       a					:    Optional[Any]=7					,       a					:    List[str]=True					,       a					:    List[str]=False					,       a					:    Dict=9_9					,       a					:    Tuple=1_6					,       a					:    Optional[int]=2					,       a					:    str=4					,       a					:    Any=4					,       a					:    List[Any]="gelu"					,       a					:    Any=0.1					,       a					:    List[str]=0.1					,       a					:    Union[str, Any]=3_2					,       a					:    Tuple=2					,       a					:    Optional[Any]=1					,       a					:    Tuple=0					,       a					:    Tuple=0.02					,       ):






       '''simple docstring'''






       lowercase_		:      List[str]          =       parent
       lowercase_		:      Optional[int]          =       batch_size
       lowercase_		:      str          =       seq_length
       lowercase_		:      str          =       is_training
       lowercase_		:      int          =       use_labels
       lowercase_		:      Optional[int]          =       vocab_size
       lowercase_		:      List[str]          =       hidden_size
       lowercase_		:      Optional[Any]          =       num_hidden_layers
       lowercase_		:      int          =       num_attention_heads
       lowercase_		:      Tuple          =       intermediate_size
       lowercase_		:      Any          =       hidden_act
       lowercase_		:      Union[str, Any]          =       hidden_dropout_prob
       lowercase_		:      Dict          =       attention_probs_dropout_prob
       lowercase_		:      Union[str, Any]          =       max_position_embeddings
       lowercase_		:      Any          =       eos_token_id
       lowercase_		:      List[str]          =       pad_token_id
       lowercase_		:      List[Any]          =       bos_token_id
       lowercase_		:      List[str]          =       initializer_range




    def 			lowerCAmelCase__			(     self					:    Any     ):






       '''simple docstring'''






       lowercase_		:      Tuple          =       np.clip(ids_tensor([self.batch_size, self.seq_length - 1]					,       self.vocab_size     )					,       3					,       self.vocab_size     )
       lowercase_		:      Tuple          =       np.concatenate((input_ids, 2 * np.ones((self.batch_size, 1)					,       dtype=np.intaa     ))					,       -1     )

       lowercase_		:      str          =       shift_tokens_right(a					,       1					,       2     )

       lowercase_		:      str          =       MarianConfig(
           vocab_size=self.vocab_size					,       d_model=self.hidden_size					,       encoder_layers=self.num_hidden_layers					,       decoder_layers=self.num_hidden_layers					,       encoder_attention_heads=self.num_attention_heads					,       decoder_attention_heads=self.num_attention_heads					,       encoder_ffn_dim=self.intermediate_size					,       decoder_ffn_dim=self.intermediate_size					,       dropout=self.hidden_dropout_prob					,       attention_dropout=self.attention_probs_dropout_prob					,       max_position_embeddings=self.max_position_embeddings					,       eos_token_id=self.eos_token_id					,       bos_token_id=self.bos_token_id					,       pad_token_id=self.pad_token_id					,       initializer_range=self.initializer_range					,       use_cache=a					,       )
       lowercase_		:      int          =       prepare_marian_inputs_dict(a					,       a					,       a     )
       return config, inputs_dict




    def 			lowerCAmelCase__			(     self					:    Optional[int]     ):






       '''simple docstring'''






       lowercase_		:      List[str]          =       self.prepare_config_and_inputs()
       return config, inputs_dict




    def 			lowerCAmelCase__			(     self					:    Tuple					,       a					:    Union[str, Any]					,       a					:    List[Any]					,       a					:    str     ):






       '''simple docstring'''






       lowercase_		:      Optional[Any]          =       2_0
       lowercase_		:      List[str]          =       model_class_name(a     )

       lowercase_		:      List[str]          =       model.encode(inputs_dict["input_ids"]     )

       lowercase_		:      List[str]          =       (
           inputs_dict["decoder_input_ids"],
           inputs_dict["decoder_attention_mask"],
       )

       lowercase_		:      Dict          =       model.init_cache(decoder_input_ids.shape[0]					,       a					,       a     )
       lowercase_		:      int          =       jnp.ones((decoder_input_ids.shape[0], max_decoder_length)					,       dtype="i4"     )

       lowercase_		:      str          =       jnp.broadcast_to(
           jnp.arange(decoder_input_ids.shape[-1] - 1     )[None, :]					,       (decoder_input_ids.shape[0], decoder_input_ids.shape[-1] - 1)					,       )
       lowercase_		:      Dict          =       model.decode(
           decoder_input_ids[:, :-1]					,       a					,       decoder_attention_mask=a					,       past_key_values=a					,       decoder_position_ids=a					,       )

       lowercase_		:      Optional[int]          =       jnp.array(decoder_input_ids.shape[0] * [[decoder_input_ids.shape[-1] - 1]]					,       dtype="i4"     )
       lowercase_		:      int          =       model.decode(
           decoder_input_ids[:, -1:]					,       a					,       decoder_attention_mask=a					,       past_key_values=outputs_cache.past_key_values					,       decoder_position_ids=a					,       )

       lowercase_		:      int          =       model.decode(a					,       a     )

       lowercase_		:      Union[str, Any]          =       np.max(np.abs((outputs_cache_next[0][:, -1, :5] - outputs[0][:, -1, :5])     )     )
       self.parent.assertTrue(diff < 1e-3					,       msg=f"""Max diff is {diff}"""     )





    def 			lowerCAmelCase__			(     self					:    List[Any]					,       a					:    Any					,       a					:    Optional[int]					,       a					:    List[str]     ):






       '''simple docstring'''






       lowercase_		:      Tuple          =       2_0
       lowercase_		:      Optional[int]          =       model_class_name(a     )

       lowercase_		:      Any          =       model.encode(inputs_dict["input_ids"]     )

       lowercase_		:      Tuple          =       (
           inputs_dict["decoder_input_ids"],
           inputs_dict["decoder_attention_mask"],
       )

       lowercase_		:      Dict          =       jnp.concatenate(
           [
               decoder_attention_mask,
               jnp.zeros((decoder_attention_mask.shape[0], max_decoder_length - decoder_attention_mask.shape[1])     ),
           ]					,       axis=-1					,       )

       lowercase_		:      List[Any]          =       model.init_cache(decoder_input_ids.shape[0]					,       a					,       a     )
       lowercase_		:      List[Any]          =       jnp.broadcast_to(
           jnp.arange(decoder_input_ids.shape[-1] - 1     )[None, :]					,       (decoder_input_ids.shape[0], decoder_input_ids.shape[-1] - 1)					,       )

       lowercase_		:      str          =       model.decode(
           decoder_input_ids[:, :-1]					,       a					,       decoder_attention_mask=a					,       past_key_values=a					,       decoder_position_ids=a					,       )
       lowercase_		:      Any          =       jnp.array(decoder_input_ids.shape[0] * [[decoder_input_ids.shape[-1] - 1]]					,       dtype="i4"     )
       lowercase_		:      Optional[Any]          =       model.decode(
           decoder_input_ids[:, -1:]					,       a					,       past_key_values=outputs_cache.past_key_values					,       decoder_attention_mask=a					,       decoder_position_ids=a					,       )

       lowercase_		:      Optional[Any]          =       model.decode(a					,       a					,       decoder_attention_mask=a     )

       lowercase_		:      Dict          =       np.max(np.abs((outputs_cache_next[0][:, -1, :5] - outputs[0][:, -1, :5])     )     )
       self.parent.assertTrue(diff < 1e-3					,       msg=f"""Max diff is {diff}"""     )


@require_flax
class     _UpperCAmelCase  (						snake_case			,   unittest.TestCase			,   snake_case     ):
    __lowerCamelCase:				Optional[Any]						    =      True
    __lowerCamelCase:				int						    =      (FlaxMarianModel, FlaxMarianMTModel) if is_flax_available() else ()
    __lowerCamelCase:				str						    =      (FlaxMarianMTModel,) if is_flax_available() else ()




    def 			lowerCAmelCase__			(     self					:    Optional[int]     ):






       '''simple docstring'''






       lowercase_		:      Optional[Any]          =       FlaxMarianModelTester(self     )




    def 			lowerCAmelCase__			(     self					:    Union[str, Any]     ):






       '''simple docstring'''






       lowercase_		:      Optional[int]          =       self.model_tester.prepare_config_and_inputs()
       for model_class in self.all_model_classes:
          self.model_tester.check_use_cache_forward(a					,       a					,       a     )




    def 			lowerCAmelCase__			(     self					:    Optional[Any]     ):






       '''simple docstring'''






       lowercase_		:      Tuple          =       self.model_tester.prepare_config_and_inputs()
       for model_class in self.all_model_classes:
          self.model_tester.check_use_cache_forward_with_attn_mask(a					,       a					,       a     )




    def 			lowerCAmelCase__			(     self					:    Dict     ):






       '''simple docstring'''






       lowercase_		:      Dict          =       self.model_tester.prepare_config_and_inputs_for_common()

       for model_class in self.all_model_classes:
          with self.subTest(model_class.__name__     ):
             lowercase_		:      Dict          =       self._prepare_for_class(a					,       a     )
             lowercase_		:      Dict          =       model_class(a     )

             @jax.jit
             def encode_jitted(a					:    Union[str, Any]					,       a					:    int=None					,       **a					:    Dict     ):
                return model.encode(input_ids=a					,       attention_mask=a     )

             with self.subTest("JIT Enabled"     ):
                lowercase_		:      Dict          =       encode_jitted(**a     ).to_tuple()

             with self.subTest("JIT Disabled"     ):
                with jax.disable_jit():
                   lowercase_		:      List[str]          =       encode_jitted(**a     ).to_tuple()

             self.assertEqual(len(a     )					,       len(a     )     )
             for jitted_output, output in zip(a					,       a     ):
                self.assertEqual(jitted_output.shape					,       output.shape     )




    def 			lowerCAmelCase__			(     self					:    str     ):






       '''simple docstring'''






       lowercase_		:      Optional[Any]          =       self.model_tester.prepare_config_and_inputs_for_common()

       for model_class in self.all_model_classes:
          with self.subTest(model_class.__name__     ):
             lowercase_		:      Any          =       model_class(a     )
             lowercase_		:      Dict          =       model.encode(inputs_dict["input_ids"]					,       inputs_dict["attention_mask"]     )

             lowercase_		:      List[Any]          =       {
                 "decoder_input_ids": inputs_dict["decoder_input_ids"],
                 "decoder_attention_mask": inputs_dict["decoder_attention_mask"],
                 "encoder_outputs": encoder_outputs,
             }

             @jax.jit
             def decode_jitted(a					:    List[str]					,       a					:    Optional[int]					,       a					:    List[Any]     ):
                return model.decode(
                    decoder_input_ids=a					,       decoder_attention_mask=a					,       encoder_outputs=a					,       )

             with self.subTest("JIT Enabled"     ):
                lowercase_		:      Any          =       decode_jitted(**a     ).to_tuple()

             with self.subTest("JIT Disabled"     ):
                with jax.disable_jit():
                   lowercase_		:      Optional[Any]          =       decode_jitted(**a     ).to_tuple()

             self.assertEqual(len(a     )					,       len(a     )     )
             for jitted_output, output in zip(a					,       a     ):
                self.assertEqual(jitted_output.shape					,       output.shape     )





    @slow
    def 			lowerCAmelCase__			(     self					:    Optional[int]     ):






       '''simple docstring'''






       for model_class_name in self.all_model_classes:
          lowercase_		:      Union[str, Any]          =       model_class_name.from_pretrained("Helsinki-NLP/opus-mt-en-de"     )
          # FlaxMarianForSequenceClassification expects eos token in input_ids
          lowercase_		:      Optional[Any]          =       np.ones((1, 1)     ) * model.config.eos_token_id
          lowercase_		:      int          =       model(a     )
          self.assertIsNotNone(a     )


@require_flax
@require_sentencepiece
@require_tokenizers
class     _UpperCAmelCase  (						unittest.TestCase     ):
    __lowerCamelCase:				int						    =      None
    __lowerCamelCase:				Optional[int]						    =      None




    @classmethod
    def 			lowerCAmelCase__			(     cls					:    Any     ):






       '''simple docstring'''






       lowercase_		:      Optional[Any]          =       f"""Helsinki-NLP/opus-mt-{cls.src}-{cls.tgt}"""
       return cls




    @cached_property
    def 			lowerCAmelCase__			(     self					:    str     ):






       '''simple docstring'''






       return MarianTokenizer.from_pretrained(self.model_name     )




    @property
    def 			lowerCAmelCase__			(     self					:    Tuple     ):






       '''simple docstring'''






       return self.tokenizer.eos_token_id




    @cached_property
    def 			lowerCAmelCase__			(     self					:    Dict     ):






       '''simple docstring'''






       lowercase_		:      FlaxMarianMTModel          =       FlaxMarianMTModel.from_pretrained(self.model_name     )
       self.assertEqual(model.config.decoder_start_token_id					,       model.config.pad_token_id     )
       return model




    def 			lowerCAmelCase__			(     self					:    List[Any]					,       **a					:    Optional[Any]     ):






       '''simple docstring'''






       lowercase_		:      List[str]          =       self.translate_src_text(**a     )
       self.assertListEqual(self.expected_text					,       a     )





    def 			lowerCAmelCase__			(     self					:    int					,       **a					:    List[str]     ):






       '''simple docstring'''






       lowercase_		:      Dict          =       self.tokenizer(self.src_text					,       padding=a					,       return_tensors="np"					,       **a     )
       lowercase_		:      str          =       self.model.generate(
           model_inputs.input_ids					,       attention_mask=model_inputs.attention_mask					,       num_beams=2					,       max_length=1_2_8					,       ).sequences
       lowercase_		:      int          =       self.tokenizer.batch_decode(a					,       skip_special_tokens=a     )
       return generated_words


@require_flax
@require_sentencepiece
@require_tokenizers
class     _UpperCAmelCase  (						snake_case     ):
    __lowerCamelCase:				Tuple						    =      'en'
    __lowerCamelCase:				Optional[int]						    =      'fr'
    __lowerCamelCase:				List[str]						    =      [
        'I am a small frog.',
        'Now I can forget the 100 words of german that I know.',
    ]
    __lowerCamelCase:				Dict						    =      [
        'Je suis une petite grenouille.',
        'Maintenant, je peux oublier les 100 mots d\'allemand que je connais.',
    ]




    @slow
    def 			lowerCAmelCase__			(     self					:    Optional[Any]     ):






       '''simple docstring'''






       self._assert_generated_batch_equal_expected()


@require_flax
@require_sentencepiece
@require_tokenizers
class     _UpperCAmelCase  (						snake_case     ):
    __lowerCamelCase:				Dict						    =      'fr'
    __lowerCamelCase:				Optional[int]						    =      'en'
    __lowerCamelCase:				List[Any]						    =      [
        'Donnez moi le micro.',
        'Tom et Mary étaient assis à une table.',  # Accents
    ]
    __lowerCamelCase:				Optional[int]						    =      [
        'Give me the microphone.',
        'Tom and Mary were sitting at a table.',
    ]




    @slow
    def 			lowerCAmelCase__			(     self					:    Optional[Any]     ):






       '''simple docstring'''






       self._assert_generated_batch_equal_expected()


@require_flax
@require_sentencepiece
@require_tokenizers
class     _UpperCAmelCase  (						snake_case     ):
    __lowerCamelCase:				Optional[int]						    =      'mt'
    __lowerCamelCase:				Dict						    =      'en'
    __lowerCamelCase:				Optional[int]						    =      ['Billi messu b\'mod ġentili, Ġesù fejjaq raġel li kien milqut bil - marda kerha tal - ġdiem.']
    __lowerCamelCase:				List[Any]						    =      ['Touching gently, Jesus healed a man who was affected by the sad disease of leprosy.']




    @slow
    def 			lowerCAmelCase__			(     self					:    int     ):






       '''simple docstring'''






       self._assert_generated_batch_equal_expected()


@require_flax
@require_sentencepiece
@require_tokenizers
class     _UpperCAmelCase  (						snake_case     ):
    __lowerCamelCase:				Optional[Any]						    =      'en'
    __lowerCamelCase:				Any						    =      'de'
    __lowerCamelCase:				Dict						    =      [
        'I am a small frog.',
        'Now I can forget the 100 words of german that I know.',
        'Tom asked his teacher for advice.',
        'That\'s how I would do it.',
        'Tom really admired Mary\'s courage.',
        'Turn around and close your eyes.',
    ]
    __lowerCamelCase:				Tuple						    =      [
        'Ich bin ein kleiner Frosch.',
        'Jetzt kann ich die 100 Wörter des Deutschen vergessen, die ich kenne.',
        'Tom bat seinen Lehrer um Rat.',
        'So würde ich das machen.',
        'Tom bewunderte Marias Mut wirklich.',
        'Drehen Sie sich um und schließen Sie die Augen.',
    ]




    @slow
    def 			lowerCAmelCase__			(     self					:    str     ):






       '''simple docstring'''






       self._assert_generated_batch_equal_expected()


@require_flax
@require_sentencepiece
@require_tokenizers
class     _UpperCAmelCase  (						snake_case     ):
    __lowerCamelCase:				List[Any]						    =      'en'
    __lowerCamelCase:				List[str]						    =      'zh'
    __lowerCamelCase:				str						    =      ['My name is Wolfgang and I live in Berlin']
    __lowerCamelCase:				int						    =      ['我叫沃尔夫冈 我住在柏林']




    @slow
    def 			lowerCAmelCase__			(     self					:    Union[str, Any]     ):






       '''simple docstring'''






       self._assert_generated_batch_equal_expected()


@require_flax
@require_sentencepiece
@require_tokenizers
class     _UpperCAmelCase  (						snake_case     ):
    __lowerCamelCase:				str						    =      'ru'
    __lowerCamelCase:				Union[str, Any]						    =      'fr'
    __lowerCamelCase:				Dict						    =      ['Он показал мне рукопись своей новой пьесы.']
    __lowerCamelCase:				Union[str, Any]						    =      ['Il m\'a montré le manuscrit de sa nouvelle pièce.']




    @slow
    def 			lowerCAmelCase__			(     self					:    Optional[Any]     ):






       '''simple docstring'''






       self._assert_generated_batch_equal_expected()


@require_flax
@require_sentencepiece
@require_tokenizers
class     _UpperCAmelCase  (						snake_case     ):
    __lowerCamelCase:				List[Any]						    =      'en'
    __lowerCamelCase:				List[Any]						    =      'ROMANCE'
    __lowerCamelCase:				Union[str, Any]						    =      [
        '>>fr<< Don\'t spend so much time watching TV.',
        '>>pt<< Your message has been sent.',
        '>>es<< He\'s two years older than me.',
    ]
    __lowerCamelCase:				Tuple						    =      [
        'Ne passez pas autant de temps à regarder la télé.',
        'A sua mensagem foi enviada.',
        'Es dos años más viejo que yo.',
    ]




    @slow
    def 			lowerCAmelCase__			(     self					:    str     ):






       '''simple docstring'''






       self._assert_generated_batch_equal_expected()












'''simple docstring'''
from urllib.error import HTTPError

from bsa import BeautifulSoup
from requests import exceptions, get

UpperCamelCase__	=     'https://www.wellrx.com/prescriptions/{0}/{1}/?freshSearch=true'




def 						__SCREAMING_SNAKE_CASE   (					_UpperCamelCase  ,						_UpperCamelCase							):


   """simple docstring"""




   try:
      # Has user provided both inputs?
      if not drug_name or not zip_code:
         return None

      lowercase_		:      List[str]          =       BASE_URL.format(_UpperCamelCase  ,						_UpperCamelCase							)
      lowercase_		:      Union[str, Any]          =       get(_UpperCamelCase							)

      # Is the response ok?
      response.raise_for_status()

      # Scrape the data using bs4
      lowercase_		:      Any          =       BeautifulSoup(response.text  ,						"html.parser"							)

      # This list will store the name and price.
      lowercase_		:      List[str]          =       []

      # Fetch all the grids that contains the items.
      lowercase_		:      Tuple          =       soup.find_all("div"  ,						{"class": "grid-x pharmCard"}							)
      if grid_list and len(_UpperCamelCase							) > 0:
         for grid in grid_list:
            # Get the pharmacy price.
            lowercase_		:      Tuple          =       grid.find("p"  ,						{"class": "list-title"}							).text

            # Get price of the drug.
            lowercase_		:      List[str]          =       grid.find("span"  ,						{"p", "price price-large"}							).text

            pharmacy_price_list.append(
                {
                    "pharmacy_name": pharmacy_name,
                    "price": price,
                }							)

      return pharmacy_price_list

   except (HTTPError, exceptions.RequestException, ValueError):
      return None


if __name__ == "__main__":
 # Enter a drug name and a zip code
 UpperCamelCase__	=     input('Enter drug name: ').strip()
 UpperCamelCase__	=     input('Enter zip code: ').strip()

 UpperCamelCase__	=     fetch_pharmacy_and_price_list(
     drug_name, zip_code
 )

 if pharmacy_price_list:
  print(f"""\nSearch results for {drug_name} at location {zip_code}:""")
  for pharmacy_price in pharmacy_price_list:
   UpperCamelCase__	=     pharmacy_price['pharmacy_name']
   UpperCamelCase__	=     pharmacy_price['price']

   print(f"""Pharmacy: {name} Price: {price}""")
 else:
  print(f"""No results found for {drug_name}""")




