def      lowerCAmelCase_				(  __A							)  ->       int:







      '''simple docstring'''


      if not isinstance(__A,						__A							) or number < 0:
            raise ValueError("Input must be a non-negative integer"							)

      UpperCAmelCase__			=						number & ~(number - 1)
      UpperCAmelCase__			=						0
      while intermediate:
            intermediate >>= 1
            index += 1
      return index - 1


if __name__ == "__main__":
      import doctest

      doctest.testmod(verbose=True)




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      lowerCAmelCase_				(  __A,						__A,						__A=None,						__A=None,						__A=None,						__A=None,						__A=None,						__A=None,						)  ->       Dict:







      '''simple docstring'''


      if attention_mask is None:
            UpperCAmelCase__			=						np.where(input_ids != config.pad_token_id,						1,						0							)
      if decoder_attention_mask is None:
            UpperCAmelCase__			=						np.where(decoder_input_ids != config.pad_token_id,						1,						0							)
      if head_mask is None:
            UpperCAmelCase__			=						np.ones((config.encoder_layers, config.encoder_attention_heads)							)
      if decoder_head_mask is None:
            UpperCAmelCase__			=						np.ones((config.decoder_layers, config.decoder_attention_heads)							)
      if cross_attn_head_mask is None:
            UpperCAmelCase__			=						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   A							:


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



         UpperCAmelCase__			=						parent
         UpperCAmelCase__			=						batch_size
         UpperCAmelCase__			=						seq_length
         UpperCAmelCase__			=						is_training
         UpperCAmelCase__			=						use_labels
         UpperCAmelCase__			=						vocab_size
         UpperCAmelCase__			=						hidden_size
         UpperCAmelCase__			=						num_hidden_layers
         UpperCAmelCase__			=						num_attention_heads
         UpperCAmelCase__			=						intermediate_size
         UpperCAmelCase__			=						hidden_act
         UpperCAmelCase__			=						hidden_dropout_prob
         UpperCAmelCase__			=						attention_probs_dropout_prob
         UpperCAmelCase__			=						max_position_embeddings
         UpperCAmelCase__			=						eos_token_id
         UpperCAmelCase__			=						pad_token_id
         UpperCAmelCase__			=						bos_token_id
         UpperCAmelCase__			=						initializer_range


   def     lowercase_   (self  :		str	)		->       Union[str, Any]:
         """simple docstring"""



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

         UpperCAmelCase__			=						shift_tokens_right(__UpperCAmelCase ,						1 ,						2	)

         UpperCAmelCase__			=						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=__UpperCAmelCase ,						)
         UpperCAmelCase__			=						prepare_marian_inputs_dict(__UpperCAmelCase ,						__UpperCAmelCase ,						__UpperCAmelCase	)
         return config, inputs_dict


   def     lowercase_   (self  :		List[Any]	)		->       Tuple:
         """simple docstring"""



         UpperCAmelCase__	,   UpperCAmelCase__			=						self.prepare_config_and_inputs()
         return config, inputs_dict


   def     lowercase_   (self  :		Union[str, Any] ,						__UpperCAmelCase  :		str ,						__UpperCAmelCase  :		Optional[Any] ,						__UpperCAmelCase  :		Any	)		->       List[Any]:
         """simple docstring"""



         UpperCAmelCase__			=						2_0
         UpperCAmelCase__			=						model_class_name(__UpperCAmelCase	)

         UpperCAmelCase__			=						model.encode(inputs_dict["input_ids"]	)

         UpperCAmelCase__	,   UpperCAmelCase__			=						(
             inputs_dict["decoder_input_ids"],
             inputs_dict["decoder_attention_mask"],
         )

         UpperCAmelCase__			=						model.init_cache(decoder_input_ids.shape[0] ,						__UpperCAmelCase ,						__UpperCAmelCase	)
         UpperCAmelCase__			=						jnp.ones((decoder_input_ids.shape[0], max_decoder_length) ,						dtype="i4"	)

         UpperCAmelCase__			=						jnp.broadcast_to(
             jnp.arange(decoder_input_ids.shape[-1] - 1	)[None, :] ,						(decoder_input_ids.shape[0], decoder_input_ids.shape[-1] - 1) ,						)
         UpperCAmelCase__			=						model.decode(
             decoder_input_ids[:, :-1] ,						__UpperCAmelCase ,						decoder_attention_mask=__UpperCAmelCase ,						past_key_values=__UpperCAmelCase ,						decoder_position_ids=__UpperCAmelCase ,						)

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

         UpperCAmelCase__			=						model.decode(__UpperCAmelCase ,						__UpperCAmelCase	)

         UpperCAmelCase__			=						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     lowercase_   (self  :		Tuple ,						__UpperCAmelCase  :		Union[str, Any] ,						__UpperCAmelCase  :		List[Any] ,						__UpperCAmelCase  :		str	)		->       int:
         """simple docstring"""



         UpperCAmelCase__			=						2_0
         UpperCAmelCase__			=						model_class_name(__UpperCAmelCase	)

         UpperCAmelCase__			=						model.encode(inputs_dict["input_ids"]	)

         UpperCAmelCase__	,   UpperCAmelCase__			=						(
             inputs_dict["decoder_input_ids"],
             inputs_dict["decoder_attention_mask"],
         )

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

         UpperCAmelCase__			=						model.init_cache(decoder_input_ids.shape[0] ,						__UpperCAmelCase ,						__UpperCAmelCase	)
         UpperCAmelCase__			=						jnp.broadcast_to(
             jnp.arange(decoder_input_ids.shape[-1] - 1	)[None, :] ,						(decoder_input_ids.shape[0], decoder_input_ids.shape[-1] - 1) ,						)

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

         UpperCAmelCase__			=						model.decode(__UpperCAmelCase ,						__UpperCAmelCase ,						decoder_attention_mask=__UpperCAmelCase	)

         UpperCAmelCase__			=						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   A							(       UpperCAmelCase_	,       unittest.TestCase	,       UpperCAmelCase_  ):
   __UpperCAmelCase				:				Any          =    True
   __UpperCAmelCase				:				List[Any]          =    (FlaxMarianModel, FlaxMarianMTModel) if is_flax_available() else ()
   __UpperCAmelCase				:				Any          =    (FlaxMarianMTModel,) if is_flax_available() else ()


   def     lowercase_   (self  :		List[str]	)		->       int:
         """simple docstring"""



         UpperCAmelCase__			=						FlaxMarianModelTester(self	)


   def     lowercase_   (self  :		List[str]	)		->       Tuple:
         """simple docstring"""



         UpperCAmelCase__	,   UpperCAmelCase__			=						self.model_tester.prepare_config_and_inputs()
         for model_class in self.all_model_classes:
               self.model_tester.check_use_cache_forward(__UpperCAmelCase ,						__UpperCAmelCase ,						__UpperCAmelCase	)


   def     lowercase_   (self  :		List[str]	)		->       int:
         """simple docstring"""



         UpperCAmelCase__	,   UpperCAmelCase__			=						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(__UpperCAmelCase ,						__UpperCAmelCase ,						__UpperCAmelCase	)


   def     lowercase_   (self  :		List[Any]	)		->       Tuple:
         """simple docstring"""



         UpperCAmelCase__	,   UpperCAmelCase__			=						self.model_tester.prepare_config_and_inputs_for_common()

         for model_class in self.all_model_classes:
               with self.subTest(model_class.__name__	):
                     UpperCAmelCase__			=						self._prepare_for_class(__UpperCAmelCase ,						__UpperCAmelCase	)
                     UpperCAmelCase__			=						model_class(__UpperCAmelCase	)

                     @jax.jit
                     def encode_jitted(__UpperCAmelCase  :		str ,						__UpperCAmelCase  :		List[Any]=None ,						**__UpperCAmelCase  :		Any	):
                           return model.encode(input_ids=__UpperCAmelCase ,						attention_mask=__UpperCAmelCase	)

                     with self.subTest("JIT Enabled"	):
                           UpperCAmelCase__			=						encode_jitted(**__UpperCAmelCase	).to_tuple()

                     with self.subTest("JIT Disabled"	):
                           with jax.disable_jit():
                                 UpperCAmelCase__			=						encode_jitted(**__UpperCAmelCase	).to_tuple()

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


   def     lowercase_   (self  :		Optional[int]	)		->       List[str]:
         """simple docstring"""



         UpperCAmelCase__	,   UpperCAmelCase__			=						self.model_tester.prepare_config_and_inputs_for_common()

         for model_class in self.all_model_classes:
               with self.subTest(model_class.__name__	):
                     UpperCAmelCase__			=						model_class(__UpperCAmelCase	)
                     UpperCAmelCase__			=						model.encode(inputs_dict["input_ids"] ,						inputs_dict["attention_mask"]	)

                     UpperCAmelCase__			=						{
                         "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(__UpperCAmelCase  :		Union[str, Any] ,						__UpperCAmelCase  :		List[str] ,						__UpperCAmelCase  :		str	):
                           return model.decode(
                               decoder_input_ids=__UpperCAmelCase ,						decoder_attention_mask=__UpperCAmelCase ,						encoder_outputs=__UpperCAmelCase ,						)

                     with self.subTest("JIT Enabled"	):
                           UpperCAmelCase__			=						decode_jitted(**__UpperCAmelCase	).to_tuple()

                     with self.subTest("JIT Disabled"	):
                           with jax.disable_jit():
                                 UpperCAmelCase__			=						decode_jitted(**__UpperCAmelCase	).to_tuple()

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





   @slow
   def     lowercase_   (self  :		int	)		->       Any:
         """simple docstring"""



         for model_class_name in self.all_model_classes:
               UpperCAmelCase__			=						model_class_name.from_pretrained("Helsinki-NLP/opus-mt-en-de"	)
               # FlaxMarianForSequenceClassification expects eos token in input_ids
               UpperCAmelCase__			=						np.ones((1, 1)	) * model.config.eos_token_id
               UpperCAmelCase__			=						model(__UpperCAmelCase	)
               self.assertIsNotNone(__UpperCAmelCase	)





@require_flax
@require_sentencepiece
@require_tokenizers
class   A							(       unittest.TestCase  ):
   __UpperCAmelCase				:				Union[str, Any]          =    None
   __UpperCAmelCase				:				Dict          =    None


   @classmethod
   def     lowercase_   (cls  :		Tuple	)		->       None:
         """simple docstring"""



         UpperCAmelCase__			=						f"""Helsinki-NLP/opus-mt-{cls.src}-{cls.tgt}"""
         return cls


   @cached_property
   def     lowercase_   (self  :		Optional[Any]	)		->       List[Any]:
         """simple docstring"""



         return MarianTokenizer.from_pretrained(self.model_name	)


   @property
   def     lowercase_   (self  :		List[str]	)		->       int:
         """simple docstring"""



         return self.tokenizer.eos_token_id


   @cached_property
   def     lowercase_   (self  :		Optional[Any]	)		->       Union[str, Any]:
         """simple docstring"""



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


   def     lowercase_   (self  :		int ,						**__UpperCAmelCase  :		List[Any]	)		->       Union[str, Any]:
         """simple docstring"""



         UpperCAmelCase__			=						self.translate_src_text(**__UpperCAmelCase	)
         self.assertListEqual(self.expected_text ,						__UpperCAmelCase	)





   def     lowercase_   (self  :		Tuple ,						**__UpperCAmelCase  :		Optional[Any]	)		->       List[Any]:
         """simple docstring"""



         UpperCAmelCase__			=						self.tokenizer(self.src_text ,						padding=__UpperCAmelCase ,						return_tensors="np" ,						**__UpperCAmelCase	)
         UpperCAmelCase__			=						self.model.generate(
             model_inputs.input_ids ,						attention_mask=model_inputs.attention_mask ,						num_beams=2 ,						max_length=1_2_8 ,						).sequences
         UpperCAmelCase__			=						self.tokenizer.batch_decode(__UpperCAmelCase ,						skip_special_tokens=__UpperCAmelCase	)
         return generated_words





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


   @slow
   def     lowercase_   (self  :		Union[str, Any]	)		->       int:
         """simple docstring"""



         self._assert_generated_batch_equal_expected()





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


   @slow
   def     lowercase_   (self  :		str	)		->       Dict:
         """simple docstring"""



         self._assert_generated_batch_equal_expected()





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


   @slow
   def     lowercase_   (self  :		List[Any]	)		->       Tuple:
         """simple docstring"""



         self._assert_generated_batch_equal_expected()





@require_flax
@require_sentencepiece
@require_tokenizers
class   A							(       UpperCAmelCase_  ):
   __UpperCAmelCase				:				Any          =    'en'
   __UpperCAmelCase				:				Dict          =    'de'
   __UpperCAmelCase				:				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.',
   ]
   __UpperCAmelCase				:				List[str]          =    [
       '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     lowercase_   (self  :		Tuple	)		->       Optional[Any]:
         """simple docstring"""



         self._assert_generated_batch_equal_expected()





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


   @slow
   def     lowercase_   (self  :		Optional[Any]	)		->       Optional[int]:
         """simple docstring"""



         self._assert_generated_batch_equal_expected()





@require_flax
@require_sentencepiece
@require_tokenizers
class   A							(       UpperCAmelCase_  ):
   __UpperCAmelCase				:				Optional[int]          =    'ru'
   __UpperCAmelCase				:				List[Any]          =    'fr'
   __UpperCAmelCase				:				Dict          =    ['Он показал мне рукопись своей новой пьесы.']
   __UpperCAmelCase				:				str          =    ['Il m\'a montré le manuscrit de sa nouvelle pièce.']


   @slow
   def     lowercase_   (self  :		List[str]	)		->       Dict:
         """simple docstring"""



         self._assert_generated_batch_equal_expected()





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


   @slow
   def     lowercase_   (self  :		Dict	)		->       Optional[Any]:
         """simple docstring"""



         self._assert_generated_batch_equal_expected()



