



'''simple docstring'''





import unittest

import numpy as np

from transformers import AlbertConfig, is_flax_available
from transformers.testing_utils import require_flax, slow

from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask


if is_flax_available():
     import jax.numpy as jnp

     from transformers.models.albert.modeling_flax_albert import (
         FlaxAlbertForMaskedLM,
         FlaxAlbertForMultipleChoice,
         FlaxAlbertForPreTraining,
         FlaxAlbertForQuestionAnswering,
         FlaxAlbertForSequenceClassification,
         FlaxAlbertForTokenClassification,
         FlaxAlbertModel,
     )


class 				snake_case (unittest.TestCase   ):



       def __init__(				self     ,UpperCAmelCase_     ,UpperCAmelCase_=13     ,UpperCAmelCase_=7     ,UpperCAmelCase_=True     ,UpperCAmelCase_=True     ,UpperCAmelCase_=True     ,UpperCAmelCase_=True     ,UpperCAmelCase_=99     ,UpperCAmelCase_=32     ,UpperCAmelCase_=5     ,UpperCAmelCase_=4     ,UpperCAmelCase_=37     ,UpperCAmelCase_="gelu"     ,UpperCAmelCase_=0.1     ,UpperCAmelCase_=0.1     ,UpperCAmelCase_=512     ,UpperCAmelCase_=16     ,UpperCAmelCase_=2     ,UpperCAmelCase_=0.02     ,UpperCAmelCase_=4     ,)  ->							Dict:
           lowercase__		       =						parent
           lowercase__		       =						batch_size
           lowercase__		       =						seq_length
           lowercase__		       =						is_training
           lowercase__		       =						use_attention_mask
           lowercase__		       =						use_token_type_ids
           lowercase__		       =						use_labels
           lowercase__		       =						vocab_size
           lowercase__		       =						hidden_size
           lowercase__		       =						num_hidden_layers
           lowercase__		       =						num_attention_heads
           lowercase__		       =						intermediate_size
           lowercase__		       =						hidden_act
           lowercase__		       =						hidden_dropout_prob
           lowercase__		       =						attention_probs_dropout_prob
           lowercase__		       =						max_position_embeddings
           lowercase__		       =						type_vocab_size
           lowercase__		       =						type_sequence_label_size
           lowercase__		       =						initializer_range
           lowercase__		       =						num_choices



       def 							_a      (				self      )  ->							List[str]:
           lowercase__		       =						ids_tensor([self.batch_size, self.seq_length]     ,self.vocab_size      )

           lowercase__		       =						None
           if self.use_attention_mask:
               lowercase__		       =						random_attention_mask([self.batch_size, self.seq_length]      )

           lowercase__		       =						None
           if self.use_token_type_ids:
               lowercase__		       =						ids_tensor([self.batch_size, self.seq_length]     ,self.type_vocab_size      )

           lowercase__		       =						AlbertConfig(
               vocab_size=self.vocab_size     ,hidden_size=self.hidden_size     ,num_hidden_layers=self.num_hidden_layers     ,num_attention_heads=self.num_attention_heads     ,intermediate_size=self.intermediate_size     ,hidden_act=self.hidden_act     ,hidden_dropout_prob=self.hidden_dropout_prob     ,attention_probs_dropout_prob=self.attention_probs_dropout_prob     ,max_position_embeddings=self.max_position_embeddings     ,type_vocab_size=self.type_vocab_size     ,is_decoder=UpperCamelCase__     ,initializer_range=self.initializer_range     ,)

           return config, input_ids, token_type_ids, attention_mask







       def 							_a      (				self      )  ->							List[Any]:
           lowercase__		       =						self.prepare_config_and_inputs()
           lowercase__       ,       lowercase__       ,       lowercase__       ,       lowercase__		       =						config_and_inputs
           lowercase__		       =						{"input_ids": input_ids, "token_type_ids": token_type_ids, "attention_mask": attention_mask}
           return config, inputs_dict





@require_flax
class 				snake_case (_A		,      unittest.TestCase   ):
       lowerCAmelCase__  :Dict						   =					(
           (
               FlaxAlbertModel,
               FlaxAlbertForPreTraining,
               FlaxAlbertForMaskedLM,
               FlaxAlbertForMultipleChoice,
               FlaxAlbertForQuestionAnswering,
               FlaxAlbertForSequenceClassification,
               FlaxAlbertForTokenClassification,
               FlaxAlbertForQuestionAnswering,
           )
           if is_flax_available()
           else ()
       )



       def 							_a      (				self      )  ->							List[Any]:
           lowercase__		       =						FlaxAlbertModelTester(self      )







       @slow
       def 							_a      (				self      )  ->							Any:






           for model_class_name in self.all_model_classes:
               lowercase__		       =						model_class_name.from_pretrained("albert-base-v2"      )
               lowercase__		       =						model(np.ones((1, 1)      )      )
               self.assertIsNotNone(UpperCamelCase__      )





@require_flax
class 				snake_case (unittest.TestCase   ):



       @slow
       def 							_a      (				self      )  ->							Optional[Any]:
           lowercase__		       =						FlaxAlbertModel.from_pretrained("albert-base-v2"      )
           lowercase__		       =						np.array([[0, 345, 232, 328, 740, 140, 1_695, 69, 6_078, 1_588, 2]]      )
           lowercase__		       =						np.array([[0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]      )
           lowercase__		       =						model(UpperCamelCase__     ,attention_mask=UpperCamelCase__      )[0]
           lowercase__		       =						(1, 11, 768)
           self.assertEqual(output.shape     ,UpperCamelCase__      )
           lowercase__		       =						np.array(
               [[[-0.65_13, 1.50_35, -0.27_66], [-0.65_15, 1.50_46, -0.27_80], [-0.65_12, 1.50_49, -0.27_84]]]      )

           self.assertTrue(jnp.allclose(output[:, 1:4, 1:4]     ,UpperCamelCase__     ,atol=1E-4      )      )









'''simple docstring'''





from typing import List, Optional

from tokenizers import ByteLevelBPETokenizer

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_blenderbot_small import BlenderbotSmallTokenizer


SCREAMING_SNAKE_CASE__      					=     logging.get_logger(__name__)

SCREAMING_SNAKE_CASE__      					=     {
    "vocab_file": "vocab.json",
    "merges_file": "merges.txt",
    "tokenizer_config_file": "tokenizer_config.json",
}

SCREAMING_SNAKE_CASE__      					=     {
    "vocab_file": {
        "facebook/blenderbot_small-90M": "https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/vocab.json"
    },
    "merges_file": {
        "facebook/blenderbot_small-90M": "https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/merges.txt"
    },
    "tokenizer_config_file": {
        "facebook/blenderbot_small-90M": (
            "https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/tokenizer_config.json"
        )
    },
}

SCREAMING_SNAKE_CASE__      					=     {
    "facebook/blenderbot_small-90M": 512,
}


class 				snake_case (UpperCamelCase   ):
       lowerCAmelCase__  :Union[str, Any]						   =					VOCAB_FILES_NAMES
       lowerCAmelCase__  :Any						   =					PRETRAINED_VOCAB_FILES_MAP
       lowerCAmelCase__  :str						   =					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       lowerCAmelCase__  :List[Any]						   =					BlenderbotSmallTokenizer



       def __init__(				self     ,UpperCAmelCase_=None     ,UpperCAmelCase_=None     ,UpperCAmelCase_="<|endoftext|>"     ,UpperCAmelCase_="<|endoftext|>"     ,UpperCAmelCase_="<|endoftext|>"     ,UpperCAmelCase_=False     ,UpperCAmelCase_=True     ,**UpperCAmelCase_     ,)  ->							Optional[Any]:
           super().__init__(
               ByteLevelBPETokenizer(
                   vocab=UpperCAmelCase_     ,merges=UpperCAmelCase_     ,add_prefix_space=UpperCAmelCase_     ,trim_offsets=UpperCAmelCase_     ,)     ,bos_token=UpperCAmelCase_     ,eos_token=UpperCAmelCase_     ,unk_token=UpperCAmelCase_     ,**UpperCAmelCase_     ,)
           lowercase__		       =						add_prefix_space



       def 							_a      (				self     ,UpperCAmelCase_     ,UpperCAmelCase_=None      )  ->							Optional[int]:
           lowercase__		       =						[self.bos_token_id] + token_ids_a + [self.eos_token_id]
           if token_ids_a is None:
               return output

           return output + [self.eos_token_id] + token_ids_a + [self.eos_token_id]







       def 							_a      (				self     ,UpperCAmelCase_     ,UpperCAmelCase_ = None      )  ->							List[int]:
           lowercase__		       =						[self.sep_token_id]
           lowercase__		       =						[self.cls_token_id]

           if token_ids_a is None:
               return len(cls + token_ids_a + sep      ) * [0]
           return len(cls + token_ids_a + sep + sep + token_ids_a + sep      ) * [0]




