



"""simple docstring"""







import tempfile
import unittest

from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
from transformers.testing_utils import (
    is_torch_available,
    require_optimum,
    require_torch,
    slow,
)


if is_torch_available():
     import torch







@require_torch
@require_optimum
@slow
class       UpperCamelCase__   (	unittest.TestCase  ):




      """simple docstring"""




      def      SCREAMING_SNAKE_CASE__ (      self				:      str       ):
        lowerCAmelCase_   :				Optional[int]								= 'hf-internal-testing/tiny-random-t5'
        lowerCAmelCase_   :				int								= AutoTokenizer.from_pretrained(SCREAMING_SNAKE_CASE_       )
        lowerCAmelCase_   :				int								= AutoModelForSeqaSeqLM.from_pretrained(SCREAMING_SNAKE_CASE_       )

        lowerCAmelCase_   :				List[Any]								= tokenizer('This is me'    ,			return_tensors='pt'       )

        lowerCAmelCase_   :				Dict								= model.to_bettertransformer()

        self.assertTrue(any('BetterTransformer' in mod.__class__.__name__ for _, mod in model.named_modules()       )       )

        lowerCAmelCase_   :				List[Any]								= model.generate(**SCREAMING_SNAKE_CASE_       )

        lowerCAmelCase_   :				List[Any]								= model.reverse_bettertransformer()

        self.assertFalse(any('BetterTransformer' in mod.__class__.__name__ for _, mod in model.named_modules()       )       )

        with tempfile.TemporaryDirectory() as tmpdirname:
          model.save_pretrained(SCREAMING_SNAKE_CASE_       )

          lowerCAmelCase_   :				Any								= AutoModelForSeqaSeqLM.from_pretrained(SCREAMING_SNAKE_CASE_       )

          self.assertFalse(
              any('BetterTransformer' in mod.__class__.__name__ for _, mod in model_reloaded.named_modules()       )       )

          lowerCAmelCase_   :				Dict								= model_reloaded.generate(**SCREAMING_SNAKE_CASE_       )
          self.assertTrue(torch.allclose(SCREAMING_SNAKE_CASE_    ,			SCREAMING_SNAKE_CASE_       )       )





      def      SCREAMING_SNAKE_CASE__ (      self				:      int       ):
        lowerCAmelCase_   :				List[Any]								= 'hf-internal-testing/tiny-random-t5'
        lowerCAmelCase_   :				Optional[Any]								= AutoModelForSeqaSeqLM.from_pretrained(SCREAMING_SNAKE_CASE_       )

        lowerCAmelCase_   :				Any								= model.to_bettertransformer()

        with tempfile.TemporaryDirectory() as tmpdirname:
          with self.assertRaises(SCREAMING_SNAKE_CASE_       ):
            model.save_pretrained(SCREAMING_SNAKE_CASE_       )

          lowerCAmelCase_   :				Union[str, Any]								= model.reverse_bettertransformer()
          model.save_pretrained(SCREAMING_SNAKE_CASE_       )










"""simple docstring"""







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


lowercase__		:				Tuple          =	logging.get_logger(__name__)

lowercase__		:				Any          =	{
    """facebook/dpr-ctx_encoder-single-nq-base""": (
        """https://huggingface.co/facebook/dpr-ctx_encoder-single-nq-base/resolve/main/config.json"""
    ),
    """facebook/dpr-question_encoder-single-nq-base""": (
        """https://huggingface.co/facebook/dpr-question_encoder-single-nq-base/resolve/main/config.json"""
    ),
    """facebook/dpr-reader-single-nq-base""": (
        """https://huggingface.co/facebook/dpr-reader-single-nq-base/resolve/main/config.json"""
    ),
    """facebook/dpr-ctx_encoder-multiset-base""": (
        """https://huggingface.co/facebook/dpr-ctx_encoder-multiset-base/resolve/main/config.json"""
    ),
    """facebook/dpr-question_encoder-multiset-base""": (
        """https://huggingface.co/facebook/dpr-question_encoder-multiset-base/resolve/main/config.json"""
    ),
    """facebook/dpr-reader-multiset-base""": (
        """https://huggingface.co/facebook/dpr-reader-multiset-base/resolve/main/config.json"""
    ),
}







class       UpperCamelCase__   (	lowercase_  ):




      """simple docstring"""




      _SCREAMING_SNAKE_CASE  				=     """dpr"""



      def __init__(      self				:      List[Any]    ,			SCREAMING_SNAKE_CASE_				:      Tuple=3_0_5_2_2    ,			SCREAMING_SNAKE_CASE_				:      Any=7_6_8    ,			SCREAMING_SNAKE_CASE_				:      Dict=1_2    ,			SCREAMING_SNAKE_CASE_				:      List[str]=1_2    ,			SCREAMING_SNAKE_CASE_				:      int=3_0_7_2    ,			SCREAMING_SNAKE_CASE_				:      List[Any]="gelu"    ,			SCREAMING_SNAKE_CASE_				:      int=0.1    ,			SCREAMING_SNAKE_CASE_				:      int=0.1    ,			SCREAMING_SNAKE_CASE_				:      Union[str, Any]=5_1_2    ,			SCREAMING_SNAKE_CASE_				:      Optional[int]=2    ,			SCREAMING_SNAKE_CASE_				:      Optional[int]=0.02    ,			SCREAMING_SNAKE_CASE_				:      List[str]=1E-12    ,			SCREAMING_SNAKE_CASE_				:      List[Any]=0    ,			SCREAMING_SNAKE_CASE_				:      Optional[int]="absolute"    ,			SCREAMING_SNAKE_CASE_				:      int = 0    ,			**SCREAMING_SNAKE_CASE_				:      Optional[int]    ,			):
        super().__init__(pad_token_id=SCREAMING_SNAKE_CASE_    ,			**SCREAMING_SNAKE_CASE_       )

        lowerCAmelCase_   :				Optional[int]								= vocab_size
        lowerCAmelCase_   :				Tuple								= hidden_size
        lowerCAmelCase_   :				int								= num_hidden_layers
        lowerCAmelCase_   :				str								= num_attention_heads
        lowerCAmelCase_   :				Any								= hidden_act
        lowerCAmelCase_   :				List[str]								= intermediate_size
        lowerCAmelCase_   :				int								= hidden_dropout_prob
        lowerCAmelCase_   :				Union[str, Any]								= attention_probs_dropout_prob
        lowerCAmelCase_   :				Tuple								= max_position_embeddings
        lowerCAmelCase_   :				List[str]								= type_vocab_size
        lowerCAmelCase_   :				str								= initializer_range
        lowerCAmelCase_   :				str								= layer_norm_eps
        lowerCAmelCase_   :				List[str]								= projection_dim
        lowerCAmelCase_   :				List[str]								= position_embedding_type





