




import json
import os
import shutil
import tempfile
from unittest import TestCase

from transformers import BartTokenizer, BartTokenizerFast, DPRQuestionEncoderTokenizer, DPRQuestionEncoderTokenizerFast
from transformers.models.bart.configuration_bart import BartConfig
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES as DPR_VOCAB_FILES_NAMES
from transformers.models.dpr.configuration_dpr import DPRConfig
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES as BART_VOCAB_FILES_NAMES
from transformers.testing_utils import require_faiss, require_tokenizers, require_torch, slow
from transformers.utils import is_datasets_available, is_faiss_available, is_torch_available


if is_torch_available() and is_datasets_available() and is_faiss_available():
     from transformers.models.rag.configuration_rag import RagConfig
     from transformers.models.rag.tokenization_rag import RagTokenizer




@require_faiss
@require_torch
class    __lowerCAmelCase       (							lowerCAmelCase):






       def 					SCREAMING_SNAKE_CASE    (   self:					int				):
         lowercase    :Union[str, Any]      	=						tempfile.mkdtemp()
         lowercase    :int      	=						8

         # DPR tok
         lowercase    :List[str]      	=						[
             "[UNK]",
             "[CLS]",
             "[SEP]",
             "[PAD]",
             "[MASK]",
             "want",
             "##want",
             "##ed",
             "wa",
             "un",
             "runn",
             "##ing",
             ",",
             "low",
             "lowest",
         ]
         lowercase    :Any      	=						os.path.join(self.tmpdirname       ,					"dpr_tokenizer"				)
         os.makedirs(_lowerCAmelCase       ,					exist_ok=_lowerCAmelCase				)
         lowercase    :str      	=						os.path.join(_lowerCAmelCase       ,					DPR_VOCAB_FILES_NAMES["vocab_file"]				)
         with open(self.vocab_file       ,					"w"       ,					encoding="utf-8"				) as vocab_writer:
           vocab_writer.write("".join([x + "\n" for x in vocab_tokens]				)				)

         # BART tok
         lowercase    :Optional[int]      	=						[
             "l",
             "o",
             "w",
             "e",
             "r",
             "s",
             "t",
             "i",
             "d",
             "n",
             "\u0120",
             "\u0120l",
             "\u0120n",
             "\u0120lo",
             "\u0120low",
             "er",
             "\u0120lowest",
             "\u0120newer",
             "\u0120wider",
             "<unk>",
         ]
         lowercase    :str      	=						dict(zip(_lowerCAmelCase       ,					range(len(_lowerCAmelCase				)				)				)				)
         lowercase    :List[str]      	=						["#version: 0.2", "\u0120 l", "\u0120l o", "\u0120lo w", "e r", ""]
         lowercase    :List[str]      	=						{"unk_token": "<unk>"}

         lowercase    :List[Any]      	=						os.path.join(self.tmpdirname       ,					"bart_tokenizer"				)
         os.makedirs(_lowerCAmelCase       ,					exist_ok=_lowerCAmelCase				)
         lowercase    :Tuple      	=						os.path.join(_lowerCAmelCase       ,					BART_VOCAB_FILES_NAMES["vocab_file"]				)
         lowercase    :List[str]      	=						os.path.join(_lowerCAmelCase       ,					BART_VOCAB_FILES_NAMES["merges_file"]				)
         with open(self.vocab_file       ,					"w"       ,					encoding="utf-8"				) as fp:
           fp.write(json.dumps(_lowerCAmelCase				) + "\n"				)
         with open(self.merges_file       ,					"w"       ,					encoding="utf-8"				) as fp:
           fp.write("\n".join(_lowerCAmelCase				)				)






       def 					SCREAMING_SNAKE_CASE    (   self:					Any				):
         return DPRQuestionEncoderTokenizer.from_pretrained(os.path.join(self.tmpdirname       ,					"dpr_tokenizer"				)				)






       def 					SCREAMING_SNAKE_CASE    (   self:					Optional[Any]				):
         return BartTokenizer.from_pretrained(os.path.join(self.tmpdirname       ,					"bart_tokenizer"				)				)






       def 					SCREAMING_SNAKE_CASE    (   self:					List[str]				):
         shutil.rmtree(self.tmpdirname				)






       @require_tokenizers
       def 					SCREAMING_SNAKE_CASE    (   self:					int				):
         lowercase    :str      	=						os.path.join(self.tmpdirname       ,					"rag_tokenizer"				)
         lowercase    :int      	=						RagConfig(question_encoder=DPRConfig().to_dict()       ,					generator=BartConfig().to_dict()				)
         lowercase    :Optional[Any]      	=						RagTokenizer(question_encoder=self.get_dpr_tokenizer()       ,					generator=self.get_bart_tokenizer()				)
         rag_config.save_pretrained(_lowerCAmelCase				)
         rag_tokenizer.save_pretrained(_lowerCAmelCase				)
         lowercase    :List[Any]      	=						RagTokenizer.from_pretrained(_lowerCAmelCase       ,					config=_lowerCAmelCase				)
         self.assertIsInstance(new_rag_tokenizer.question_encoder       ,					_lowerCAmelCase				)
         self.assertEqual(new_rag_tokenizer.question_encoder.get_vocab()       ,					rag_tokenizer.question_encoder.get_vocab()				)
         self.assertIsInstance(new_rag_tokenizer.generator       ,					_lowerCAmelCase				)
         self.assertEqual(new_rag_tokenizer.generator.get_vocab()       ,					rag_tokenizer.generator.get_vocab()				)






       @slow
       def 					SCREAMING_SNAKE_CASE    (   self:					Optional[Any]				):
         lowercase    :int      	=						RagTokenizer.from_pretrained("facebook/rag-token-nq"				)
         lowercase    :List[Any]      	=						[
             "who got the first nobel prize in physics",
             "when is the next deadpool movie being released",
             "which mode is used for short wave broadcast service",
             "who is the owner of reading football club",
             "when is the next scandal episode coming out",
             "when is the last time the philadelphia won the superbowl",
             "what is the most current adobe flash player version",
             "how many episodes are there in dragon ball z",
             "what is the first step in the evolution of the eye",
             "where is gall bladder situated in human body",
             "what is the main mineral in lithium batteries",
             "who is the president of usa right now",
             "where do the greasers live in the outsiders",
             "panda is a national animal of which country",
             "what is the name of manchester united stadium",
         ]
         lowercase    :int      	=						tokenizer(_lowerCAmelCase				)
         self.assertIsNotNone(_lowerCAmelCase				)






       @slow
       def 					SCREAMING_SNAKE_CASE    (   self:					Tuple				):
         lowercase    :str      	=						RagTokenizer.from_pretrained("facebook/rag-sequence-nq"				)
         lowercase    :List[str]      	=						[
             "who got the first nobel prize in physics",
             "when is the next deadpool movie being released",
             "which mode is used for short wave broadcast service",
             "who is the owner of reading football club",
             "when is the next scandal episode coming out",
             "when is the last time the philadelphia won the superbowl",
             "what is the most current adobe flash player version",
             "how many episodes are there in dragon ball z",
             "what is the first step in the evolution of the eye",
             "where is gall bladder situated in human body",
             "what is the main mineral in lithium batteries",
             "who is the president of usa right now",
             "where do the greasers live in the outsiders",
             "panda is a national animal of which country",
             "what is the name of manchester united stadium",
         ]
         lowercase    :Any      	=						tokenizer(_lowerCAmelCase				)
         self.assertIsNotNone(_lowerCAmelCase				)











import os
import shutil
from pathlib import Path
from typing import Optional, Union

import numpy as np
from huggingface_hub import hf_hub_download

from ..utils import ONNX_EXTERNAL_WEIGHTS_NAME, ONNX_WEIGHTS_NAME, is_onnx_available, logging


if is_onnx_available():
     import onnxruntime as ort


_UpperCAmelCase	:						Dict			=     logging.get_logger(__name__)

_UpperCAmelCase	:						List[Any]			=     {
    "tensor(bool)": np.bool_,
    "tensor(int8)": np.inta,
    "tensor(uint8)": np.uinta,
    "tensor(int16)": np.intaa,
    "tensor(uint16)": np.uintaa,
    "tensor(int32)": np.intaa,
    "tensor(uint32)": np.uintaa,
    "tensor(int64)": np.intaa,
    "tensor(uint64)": np.uintaa,
    "tensor(float16)": np.floataa,
    "tensor(float)": np.floataa,
    "tensor(double)": np.floataa,
}




class    __lowerCAmelCase       :






       def __init__(   self:					Dict       ,					_lowerCAmelCase:					Union[str, Any]=None       ,					**_lowerCAmelCase:					Any				):
         logger.info("`diffusers.OnnxRuntimeModel` is experimental and might change in the future."				)
         lowercase    :str      	=						model
         lowercase    :Any      	=						kwargs.get("model_save_dir"       ,					_lowerCAmelCase				)
         lowercase    :Dict      	=						kwargs.get("latest_model_name"       ,					_lowerCAmelCase				)






       def __call__(   self:					Optional[Any]       ,					**_lowerCAmelCase:					List[Any]				):
         lowercase    :List[str]      	=						{k: np.array(_lowerCAmelCase				) for k, v in kwargs.items()}
         return self.model.run(_lowerCAmelCase       ,					_lowerCAmelCase				)






       @staticmethod
       def 					SCREAMING_SNAKE_CASE    (   _lowerCAmelCase:					Union[str, Path]       ,					_lowerCAmelCase:					List[Any]=None       ,					_lowerCAmelCase:					List[Any]=None				):
         if provider is None:
           logger.info("No onnxruntime provider specified, using CPUExecutionProvider"				)
           lowercase    :int      	=						"CPUExecutionProvider"

         return ort.InferenceSession(_lowerCAmelCase       ,					providers=[provider]       ,					sess_options=_lowerCAmelCase				)






       def 					SCREAMING_SNAKE_CASE    (   self:					List[Any]       ,					_lowerCAmelCase:					Union[str, Path]       ,					_lowerCAmelCase:					Optional[str] = None       ,					**_lowerCAmelCase:					Any				):
         lowercase    :Optional[int]      	=						file_name if file_name is not None else ONNX_WEIGHTS_NAME

         lowercase    :Tuple      	=						self.model_save_dir.joinpath(self.latest_model_name				)
         lowercase    :Optional[int]      	=						Path(_lowerCAmelCase				).joinpath(_lowerCAmelCase				)
         try:
           shutil.copyfile(_lowerCAmelCase       ,					_lowerCAmelCase				)
         except shutil.SameFileError:
           pass

         # copy external weights (for models >2GB)
         lowercase    :Tuple      	=						self.model_save_dir.joinpath(_lowerCAmelCase				)
         if src_path.exists():
           lowercase    :Dict      	=						Path(_lowerCAmelCase				).joinpath(_lowerCAmelCase				)
           try:
             shutil.copyfile(_lowerCAmelCase       ,					_lowerCAmelCase				)
           except shutil.SameFileError:
             pass






       def 					SCREAMING_SNAKE_CASE    (   self:					Optional[Any]       ,					_lowerCAmelCase:					Union[str, os.PathLike]       ,					**_lowerCAmelCase:					int       ,					):
         if os.path.isfile(_lowerCAmelCase				):
           logger.error(F"Provided path ({save_directory}) should be a directory, not a file"				)
           return

         os.makedirs(_lowerCAmelCase       ,					exist_ok=_lowerCAmelCase				)

         # saving model weights/files
         self._save_pretrained(_lowerCAmelCase       ,					**_lowerCAmelCase				)






       @classmethod
       def 					SCREAMING_SNAKE_CASE    (   cls:					Dict       ,					_lowerCAmelCase:					Union[str, Path]       ,					_lowerCAmelCase:					Optional[Union[bool, str, None]] = None       ,					_lowerCAmelCase:					Optional[Union[str, None]] = None       ,					_lowerCAmelCase:					bool = False       ,					_lowerCAmelCase:					Optional[str] = None       ,					_lowerCAmelCase:					Optional[str] = None       ,					_lowerCAmelCase:					Optional[str] = None       ,					_lowerCAmelCase:					Optional["ort.SessionOptions"] = None       ,					**_lowerCAmelCase:					Optional[int]       ,					):
         lowercase    :List[str]      	=						file_name if file_name is not None else ONNX_WEIGHTS_NAME
         # load model from local directory
         if os.path.isdir(_lowerCAmelCase				):
           lowercase    :Union[str, Any]      	=						OnnxRuntimeModel.load_model(
               os.path.join(_lowerCAmelCase       ,					_lowerCAmelCase				)       ,					provider=_lowerCAmelCase       ,					sess_options=_lowerCAmelCase				)
           lowercase    :Optional[Any]      	=						Path(_lowerCAmelCase				)
         # load model from hub
         else:
           # download model
           lowercase    :str      	=						hf_hub_download(
               repo_id=_lowerCAmelCase       ,					filename=_lowerCAmelCase       ,					use_auth_token=_lowerCAmelCase       ,					revision=_lowerCAmelCase       ,					cache_dir=_lowerCAmelCase       ,					force_download=_lowerCAmelCase       ,					)
           lowercase    :Optional[int]      	=						Path(_lowerCAmelCase				).parent
           lowercase    :Tuple      	=						Path(_lowerCAmelCase				).name
           lowercase    :Tuple      	=						OnnxRuntimeModel.load_model(_lowerCAmelCase       ,					provider=_lowerCAmelCase       ,					sess_options=_lowerCAmelCase				)
         return cls(model=_lowerCAmelCase       ,					**_lowerCAmelCase				)






       @classmethod
       def 					SCREAMING_SNAKE_CASE    (   cls:					str       ,					_lowerCAmelCase:					Union[str, Path]       ,					_lowerCAmelCase:					bool = True       ,					_lowerCAmelCase:					Optional[str] = None       ,					_lowerCAmelCase:					Optional[str] = None       ,					**_lowerCAmelCase:					Any       ,					):
         lowercase    :List[str]      	=						None
         if len(str(_lowerCAmelCase				).split("@"				)				) == 2:
           lowercase	,    lowercase    :Tuple      	=						model_id.split("@"				)

         return cls._from_pretrained(
             model_id=_lowerCAmelCase       ,					revision=_lowerCAmelCase       ,					cache_dir=_lowerCAmelCase       ,					force_download=_lowerCAmelCase       ,					use_auth_token=_lowerCAmelCase       ,					**_lowerCAmelCase       ,					)



