import unittest

import numpy as np
import timeout_decorator  # noqa

from transformers import MBartConfig, 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
    lowerCAmelCase__							= 'platform'

    import jax
    import jax.numpy as jnp

    from transformers import AutoTokenizer
    from transformers.models.mbart.modeling_flax_mbart import (
        FlaxMBartForConditionalGeneration,
        FlaxMBartForQuestionAnswering,
        FlaxMBartForSequenceClassification,
        FlaxMBartModel,
        shift_tokens_right,
    )






def       __lowerCamelCase		(						lowerCAmelCase__	,  lowerCAmelCase__	,  lowerCAmelCase__=None	,  lowerCAmelCase__=None	,  lowerCAmelCase__=None	,  lowerCAmelCase__=None	,  lowerCAmelCase__=None	,  lowerCAmelCase__=None	,  ):
       if attention_mask is None:
              lowerCAmelCase__     	=					np.where(input_ids != config.pad_token_id	,  1	,  0	)
       if decoder_attention_mask is None:
              lowerCAmelCase__     	=					np.where(decoder_input_ids != config.pad_token_id	,  1	,  0	)
       if head_mask is None:
              lowerCAmelCase__     	=					np.ones((config.encoder_layers, config.encoder_attention_heads)	)
       if decoder_head_mask is None:
              lowerCAmelCase__     	=					np.ones((config.decoder_layers, config.decoder_attention_heads)	)
       if cross_attn_head_mask is None:
              lowerCAmelCase__     	=					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": decoder_attention_mask,
       }
class 				a_ (						unittest.TestCase						):






 '''simple docstring'''






 def __init__(			self					:  List[str]			,    lowercase__					:  str			,    lowercase__					:  List[Any]=13			,    lowercase__					:  Optional[int]=7			,    lowercase__					:  Union[str, Any]=True			,    lowercase__					:  List[Any]=False			,    lowercase__					:  Dict=99			,    lowercase__					:  Optional[Any]=16			,    lowercase__					:  Tuple=2			,    lowercase__					:  Optional[int]=4			,    lowercase__					:  Dict=4			,    lowercase__					:  Optional[int]="gelu"			,    lowercase__					:  List[Any]=0.1			,    lowercase__					:  List[Any]=0.1			,    lowercase__					:  Union[str, Any]=32			,    lowercase__					:  Union[str, Any]=2			,    lowercase__					:  Any=1			,    lowercase__					:  Dict=0			,    lowercase__					:  Union[str, Any]=2			,    lowercase__					:  Any=0.02			,    ):







        '''simple docstring'''



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




 def 		__snake_case						(			self					:  Tuple):







        '''simple docstring'''



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

        lowerCAmelCase__     	=					shift_tokens_right(lowercase__			,    1)

        lowerCAmelCase__     	=					MBartConfig(
            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			,    decoder_start_token_id=self.decoder_start_token_id			,    initializer_range=self.initializer_range			,    use_cache=lowercase__			,    )
        lowerCAmelCase__     	=					prepare_mbart_inputs_dict(lowercase__			,    lowercase__			,    lowercase__)
        return config, inputs_dict




 def 		__snake_case						(			self					:  Optional[Any]):







        '''simple docstring'''



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




 def 		__snake_case						(			self					:  Union[str, Any]			,    lowercase__					:  Union[str, Any]			,    lowercase__					:  Optional[int]			,    lowercase__					:  Any):







        '''simple docstring'''



        lowerCAmelCase__     	=					20
        lowerCAmelCase__     	=					model_class_name(lowercase__)

        lowerCAmelCase__     	=					model.encode(inputs_dict['input_ids'])

        lowerCAmelCase__	,					lowerCAmelCase__     	=					(
            inputs_dict['decoder_input_ids'],
            inputs_dict['decoder_attention_mask'],
        )

        lowerCAmelCase__     	=					model.init_cache(decoder_input_ids.shape[0]			,    lowercase__			,    lowercase__)
        lowerCAmelCase__     	=					jnp.ones((decoder_input_ids.shape[0], max_decoder_length)			,    dtype='i4')

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

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

        lowerCAmelCase__     	=					model.decode(lowercase__			,    lowercase__)

        lowerCAmelCase__     	=					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 		__snake_case						(			self					:  Optional[int]			,    lowercase__					:  str			,    lowercase__					:  List[str]			,    lowercase__					:  str):







        '''simple docstring'''



        lowerCAmelCase__     	=					20
        lowerCAmelCase__     	=					model_class_name(lowercase__)

        lowerCAmelCase__     	=					model.encode(inputs_dict['input_ids'])

        lowerCAmelCase__	,					lowerCAmelCase__     	=					(
            inputs_dict['decoder_input_ids'],
            inputs_dict['decoder_attention_mask'],
        )

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

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

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

        lowerCAmelCase__     	=					model.decode(lowercase__			,    lowercase__			,    decoder_attention_mask=lowercase__)

        lowerCAmelCase__     	=					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_ (						unittest.TestCase						):






 '''simple docstring'''






 UpperCAmelCase_	 =					99




 def 		__snake_case						(			self					:  Dict):







        '''simple docstring'''



        lowerCAmelCase__     	=					np.array(
            [
                [71, 82, 18, 33, 46, 91, 2],
                [68, 34, 26, 58, 30, 82, 2],
                [5, 97, 17, 39, 94, 40, 2],
                [76, 83, 94, 25, 70, 78, 2],
                [87, 59, 41, 35, 48, 66, 2],
                [55, 13, 16, 58, 5, 2, 1],  # note padding
                [64, 27, 31, 51, 12, 75, 2],
                [52, 64, 86, 17, 83, 39, 2],
                [48, 61, 9, 24, 71, 82, 2],
                [26, 1, 60, 48, 22, 13, 2],
                [21, 5, 62, 28, 14, 76, 2],
                [45, 98, 37, 86, 59, 48, 2],
                [70, 70, 50, 9, 28, 0, 2],
            ]			,    dtype=np.intaa			,    )

        lowerCAmelCase__     	=					input_ids.shape[0]
        lowerCAmelCase__     	=					MBartConfig(
            vocab_size=self.vocab_size			,    d_model=24			,    encoder_layers=2			,    decoder_layers=2			,    encoder_attention_heads=2			,    decoder_attention_heads=2			,    encoder_ffn_dim=32			,    decoder_ffn_dim=32			,    max_position_embeddings=48			,    eos_token_id=2			,    pad_token_id=1			,    bos_token_id=0			,    )
        return config, input_ids, batch_size




 def 		__snake_case						(			self					:  str):







        '''simple docstring'''



        lowerCAmelCase__	,					lowerCAmelCase__	,					lowerCAmelCase__     	=					self._get_config_and_data()
        lowerCAmelCase__     	=					FlaxMBartForSequenceClassification(lowercase__)
        lowerCAmelCase__     	=					model(input_ids=lowercase__			,    decoder_input_ids=lowercase__)
        lowerCAmelCase__     	=					(batch_size, config.num_labels)
        self.assertEqual(outputs['logits'].shape			,    lowercase__)




 def 		__snake_case						(			self					:  int):







        '''simple docstring'''



        lowerCAmelCase__	,					lowerCAmelCase__	,					lowerCAmelCase__     	=					self._get_config_and_data()
        lowerCAmelCase__     	=					FlaxMBartForQuestionAnswering(lowercase__)
        lowerCAmelCase__     	=					model(input_ids=lowercase__)

        self.assertEqual(outputs['start_logits'].shape			,    input_ids.shape)
        self.assertEqual(outputs['end_logits'].shape			,    input_ids.shape)




 def 		__snake_case						(			self					:  Optional[Any]):







        '''simple docstring'''



        lowerCAmelCase__	,					lowerCAmelCase__	,					lowerCAmelCase__     	=					self._get_config_and_data()
        lowerCAmelCase__     	=					FlaxMBartForConditionalGeneration(lowercase__)
        lowerCAmelCase__     	=					lm_model(input_ids=lowercase__)
        lowerCAmelCase__     	=					(batch_size, input_ids.shape[1], config.vocab_size)
        self.assertEqual(outputs['logits'].shape			,    lowercase__)




 def 		__snake_case						(			self					:  Optional[int]):







        '''simple docstring'''



        lowerCAmelCase__     	=					MBartConfig(
            vocab_size=self.vocab_size			,    d_model=14			,    encoder_layers=2			,    decoder_layers=2			,    encoder_attention_heads=2			,    decoder_attention_heads=2			,    encoder_ffn_dim=8			,    decoder_ffn_dim=8			,    max_position_embeddings=48			,    )
        lowerCAmelCase__     	=					FlaxMBartForConditionalGeneration(lowercase__)
        lowerCAmelCase__     	=					np.array([[71, 82, 18, 33, 46, 91, 2], [68, 34, 26, 58, 30, 2, 1]]			,    dtype=np.intaa)
        lowerCAmelCase__     	=					np.array([[82, 71, 82, 18, 2], [58, 68, 2, 1, 1]]			,    dtype=np.intaa)
        lowerCAmelCase__     	=					lm_model(input_ids=lowercase__			,    decoder_input_ids=lowercase__)
        lowerCAmelCase__     	=					(*summary.shape, config.vocab_size)
        self.assertEqual(outputs['logits'].shape			,    lowercase__)




 def 		__snake_case						(			self					:  List[Any]):







        '''simple docstring'''



        lowerCAmelCase__     	=					np.array([[71, 82, 18, 33, 2, 1, 1], [68, 34, 26, 58, 30, 82, 2]]			,    dtype=np.intaa)
        lowerCAmelCase__     	=					shift_tokens_right(lowercase__			,    1)
        lowerCAmelCase__     	=					np.equal(lowercase__			,    1).astype(np.floataa).sum()
        lowerCAmelCase__     	=					np.equal(lowercase__			,    1).astype(np.floataa).sum()
        self.assertEqual(shifted.shape			,    input_ids.shape)
        self.assertEqual(lowercase__			,    n_pad_before - 1)
        self.assertTrue(np.equal(shifted[:, 0]			,    2).all())






@require_flax
class 				a_ (						SCREAMING_SNAKE_CASE       ,     unittest.TestCase       ,     SCREAMING_SNAKE_CASE						):






 '''simple docstring'''






 UpperCAmelCase_	 =					True
 UpperCAmelCase_	 =					(
     (
         FlaxMBartModel,
         FlaxMBartForConditionalGeneration,
         FlaxMBartForSequenceClassification,
         FlaxMBartForQuestionAnswering,
     )
     if is_flax_available()
     else ()
 )
 UpperCAmelCase_	 =					(FlaxMBartForConditionalGeneration,) if is_flax_available() else ()




 def 		__snake_case						(			self					:  Optional[Any]):







        '''simple docstring'''



        lowerCAmelCase__     	=					FlaxMBartModelTester(self)




 def 		__snake_case						(			self					:  str):







        '''simple docstring'''



        lowerCAmelCase__	,					lowerCAmelCase__     	=					self.model_tester.prepare_config_and_inputs()
        for model_class in self.all_model_classes:
               self.model_tester.check_use_cache_forward(lowercase__			,    lowercase__			,    lowercase__)




 def 		__snake_case						(			self					:  Optional[int]):







        '''simple docstring'''



        lowerCAmelCase__	,					lowerCAmelCase__     	=					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(lowercase__			,    lowercase__			,    lowercase__)




 def 		__snake_case						(			self					:  Any):







        '''simple docstring'''



        lowerCAmelCase__	,					lowerCAmelCase__     	=					self.model_tester.prepare_config_and_inputs_for_common()

        for model_class in self.all_model_classes:
               with self.subTest(model_class.__name__):
                      lowerCAmelCase__     	=					self._prepare_for_class(lowercase__			,    lowercase__)
                      lowerCAmelCase__     	=					model_class(lowercase__)

                      @jax.jit
                      def encode_jitted(lowercase__					:  Optional[Any]			,    lowercase__					:  Optional[int]=None			,    **lowercase__					:  Any):
                             return model.encode(input_ids=lowercase__			,    attention_mask=lowercase__)

                      with self.subTest('JIT Enabled'):
                             lowerCAmelCase__     	=					encode_jitted(**lowercase__).to_tuple()

                      with self.subTest('JIT Disabled'):
                             with jax.disable_jit():
                                    lowerCAmelCase__     	=					encode_jitted(**lowercase__).to_tuple()

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




 def 		__snake_case						(			self					:  Optional[int]):







        '''simple docstring'''



        lowerCAmelCase__	,					lowerCAmelCase__     	=					self.model_tester.prepare_config_and_inputs_for_common()

        for model_class in self.all_model_classes:
               with self.subTest(model_class.__name__):
                      lowerCAmelCase__     	=					model_class(lowercase__)
                      lowerCAmelCase__     	=					model.encode(inputs_dict['input_ids']			,    inputs_dict['attention_mask'])

                      lowerCAmelCase__     	=					{
                          '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(lowercase__					:  Dict			,    lowercase__					:  Union[str, Any]			,    lowercase__					:  Dict):
                             return model.decode(
                                 decoder_input_ids=lowercase__			,    decoder_attention_mask=lowercase__			,    encoder_outputs=lowercase__			,    )

                      with self.subTest('JIT Enabled'):
                             lowerCAmelCase__     	=					decode_jitted(**lowercase__).to_tuple()

                      with self.subTest('JIT Disabled'):
                             with jax.disable_jit():
                                    lowerCAmelCase__     	=					decode_jitted(**lowercase__).to_tuple()

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




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







        '''simple docstring'''



        for model_class_name in self.all_model_classes:
               lowerCAmelCase__     	=					model_class_name.from_pretrained('facebook/mbart-large-cc25'			,    from_pt=lowercase__)
               # FlaxMBartForSequenceClassification expects eos token in input_ids
               lowerCAmelCase__     	=					np.ones((1, 1)) * model.config.eos_token_id
               lowerCAmelCase__     	=					model(lowercase__)
               self.assertIsNotNone(lowercase__)






@require_flax
@require_sentencepiece
@require_tokenizers
class 				a_ (						unittest.TestCase						):






 '''simple docstring'''






 UpperCAmelCase_	 =					[
     ' UN Chief Says There Is No Military Solution in Syria',
 ]
 UpperCAmelCase_	 =					[
     'Şeful ONU declară că nu există o soluţie militară în Siria',
 ]
 UpperCAmelCase_	 =					'facebook/mbart-large-en-ro'




 @cached_property
 def 		__snake_case						(			self					:  str):







        '''simple docstring'''



        return AutoTokenizer.from_pretrained(self.model_name)




 @cached_property
 def 		__snake_case						(			self					:  Any):







        '''simple docstring'''



        lowerCAmelCase__     	=					FlaxMBartForConditionalGeneration.from_pretrained(self.model_name			,    from_pt=lowercase__)
        return model




 def 		__snake_case						(			self					:  str			,    **lowercase__					:  Union[str, Any]):







        '''simple docstring'''



        lowerCAmelCase__     	=					self.translate_src_text(**lowercase__)
        self.assertListEqual(self.expected_text			,    lowercase__)




 def 		__snake_case						(			self					:  Any			,    **lowercase__					:  Optional[Any]):







        '''simple docstring'''



        lowerCAmelCase__     	=					self.tokenizer(self.src_text			,    **lowercase__			,    return_tensors='np')
        lowerCAmelCase__     	=					self.model.generate(
            model_inputs.input_ids			,    attention_mask=model_inputs.attention_mask			,    decoder_start_token_id=self.tokenizer.lang_code_to_id['ro_RO']			,    early_stopping=lowercase__			,    num_beams=2			,    ).sequences
        lowerCAmelCase__     	=					self.tokenizer.batch_decode(lowercase__			,    skip_special_tokens=lowercase__)
        return generated_words




 @slow
 def 		__snake_case						(			self					:  str):







        '''simple docstring'''



        self._assert_generated_batch_equal_expected()

from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowerCAmelCase__							= logging.get_logger(__name__)

lowerCAmelCase__							= {
    'dandelin/vilt-b32-mlm': 'https://huggingface.co/dandelin/vilt-b32-mlm/blob/main/config.json'
}
class 				a_ (						SCREAMING_SNAKE_CASE						):






 '''simple docstring'''






 UpperCAmelCase_	 =					'vilt'




 def __init__(			self					:  Optional[Any]			,    lowercase__					:  Dict=30_522			,    lowercase__					:  Tuple=2			,    lowercase__					:  int=2			,    lowercase__					:  Optional[int]=40			,    lowercase__					:  Optional[int]=768			,    lowercase__					:  Tuple=12			,    lowercase__					:  Tuple=12			,    lowercase__					:  Union[str, Any]=3_072			,    lowercase__					:  int="gelu"			,    lowercase__					:  Tuple=0.0			,    lowercase__					:  Dict=0.0			,    lowercase__					:  Optional[int]=0.02			,    lowercase__					:  Tuple=1e-12			,    lowercase__					:  Dict=384			,    lowercase__					:  int=32			,    lowercase__					:  List[str]=3			,    lowercase__					:  int=True			,    lowercase__					:  List[str]=-1			,    lowercase__					:  Union[str, Any]=False			,    lowercase__					:  List[str]=-1			,    **lowercase__					:  int			,    ):







        '''simple docstring'''



        super().__init__(tie_word_embeddings=lowercase__			,    **lowercase__)

        lowerCAmelCase__     	=					vocab_size
        lowerCAmelCase__     	=					type_vocab_size
        lowerCAmelCase__     	=					modality_type_vocab_size
        lowerCAmelCase__     	=					max_position_embeddings

        lowerCAmelCase__     	=					hidden_size
        lowerCAmelCase__     	=					num_hidden_layers
        lowerCAmelCase__     	=					num_attention_heads
        lowerCAmelCase__     	=					intermediate_size
        lowerCAmelCase__     	=					hidden_act
        lowerCAmelCase__     	=					hidden_dropout_prob
        lowerCAmelCase__     	=					attention_probs_dropout_prob
        lowerCAmelCase__     	=					initializer_range
        lowerCAmelCase__     	=					layer_norm_eps

        lowerCAmelCase__     	=					image_size
        lowerCAmelCase__     	=					patch_size
        lowerCAmelCase__     	=					num_channels
        lowerCAmelCase__     	=					qkv_bias
        lowerCAmelCase__     	=					max_image_length
        lowerCAmelCase__     	=					num_images
