


"""simple docstring"""







import pickle
import shutil
import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, XGLMTokenizer, XGLMTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


__lowercase    					=      get_tests_dir("""fixtures/test_sentencepiece.model""")






@require_sentencepiece
@require_tokenizers
class 						_A  (  _a    ,unittest.TestCase  ):







    """simple docstring"""




    UpperCAmelCase       :							str	=       XGLMTokenizer
    UpperCAmelCase       :							Dict	=       XGLMTokenizerFast
    UpperCAmelCase       :							Optional[Any]	=       True
    UpperCAmelCase       :							Any	=       True






    def 	__snake_case							(					self				:    int):
      super().setUp()

      # We have a SentencePiece fixture for testing
      a						:		Optional[int]      							=			XGLMTokenizer(__UpperCAmelCase				, keep_accents=__UpperCAmelCase)
      tokenizer.save_pretrained(self.tmpdirname)






    def 	__snake_case							(					self				:    str):
      a						:		str      							=			"<pad>"
      a						:		str      							=			1

      self.assertEqual(self.get_tokenizer()._convert_token_to_id(__UpperCAmelCase)				, __UpperCAmelCase)
      self.assertEqual(self.get_tokenizer()._convert_id_to_token(__UpperCAmelCase)				, __UpperCAmelCase)






    def 	__snake_case							(					self				:    List[str]):
      a						:		int      							=			list(self.get_tokenizer().get_vocab().keys())

      self.assertEqual(vocab_keys[0]				, "<s>")
      self.assertEqual(vocab_keys[1]				, "<pad>")
      self.assertEqual(len(__UpperCAmelCase)				, 1008)






    def 	__snake_case							(					self				:    int):
      self.assertEqual(self.get_tokenizer().vocab_size				, 1008)






    def 	__snake_case							(					self				:    Union[str, Any]):
      a						:		Optional[int]      							=			XGLMTokenizer(__UpperCAmelCase				, keep_accents=__UpperCAmelCase)

      a						:		Optional[int]      							=			tokenizer.tokenize("This is a test")
      self.assertListEqual(__UpperCAmelCase				, ["▁This", "▁is", "▁a", "▁t", "est"])

      self.assertListEqual(
          tokenizer.convert_tokens_to_ids(__UpperCAmelCase)				, [value + tokenizer.fairseq_offset for value in [285, 46, 10, 170, 382]]				, )

      a						:		str      							=			tokenizer.tokenize("I was born in 92000, and this is falsé.")
      self.assertListEqual(
          __UpperCAmelCase				, [
              SPIECE_UNDERLINE + "I",
              SPIECE_UNDERLINE + "was",
              SPIECE_UNDERLINE + "b",
              "or",
              "n",
              SPIECE_UNDERLINE + "in",
              SPIECE_UNDERLINE + "",
              "9",
              "2",
              "0",
              "0",
              "0",
              ",",
              SPIECE_UNDERLINE + "and",
              SPIECE_UNDERLINE + "this",
              SPIECE_UNDERLINE + "is",
              SPIECE_UNDERLINE + "f",
              "al",
              "s",
              "é",
              ".",
          ]				, )
      a						:		int      							=			tokenizer.convert_tokens_to_ids(__UpperCAmelCase)
      self.assertListEqual(
          __UpperCAmelCase				, [
              value + tokenizer.fairseq_offset
              for value in [8, 21, 84, 55, 24, 19, 7, 2, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 2, 4]
          ]				, )

      a						:		int      							=			tokenizer.convert_ids_to_tokens(__UpperCAmelCase)
      self.assertListEqual(
          __UpperCAmelCase				, [
              SPIECE_UNDERLINE + "I",
              SPIECE_UNDERLINE + "was",
              SPIECE_UNDERLINE + "b",
              "or",
              "n",
              SPIECE_UNDERLINE + "in",
              SPIECE_UNDERLINE + "",
              "<unk>",
              "2",
              "0",
              "0",
              "0",
              ",",
              SPIECE_UNDERLINE + "and",
              SPIECE_UNDERLINE + "this",
              SPIECE_UNDERLINE + "is",
              SPIECE_UNDERLINE + "f",
              "al",
              "s",
              "<unk>",
              ".",
          ]				, )






    @cached_property
    def 	__snake_case							(					self				:    str):
      return XGLMTokenizer.from_pretrained("facebook/xglm-564M")






    def 	__snake_case							(					self				:    Optional[Any]):
      with tempfile.NamedTemporaryFile() as f:
        shutil.copyfile(__UpperCAmelCase				, f.name)
        a						:		List[str]      							=			XGLMTokenizer(f.name				, keep_accents=__UpperCAmelCase)
        a						:		str      							=			pickle.dumps(__UpperCAmelCase)
      pickle.loads(__UpperCAmelCase)






    def 	__snake_case							(					self				:    List[str]):
      if not self.test_rust_tokenizer:
        return

      a						:		Dict      							=			self.get_tokenizer()
      a						:		Any      							=			self.get_rust_tokenizer()

      a						:		Optional[Any]      							=			"I was born in 92000, and this is falsé."

      a						:		Any      							=			tokenizer.tokenize(__UpperCAmelCase)
      a						:		Optional[Any]      							=			rust_tokenizer.tokenize(__UpperCAmelCase)
      self.assertListEqual(__UpperCAmelCase				, __UpperCAmelCase)

      a						:		Optional[int]      							=			tokenizer.encode(__UpperCAmelCase				, add_special_tokens=__UpperCAmelCase)
      a						:		Optional[Any]      							=			rust_tokenizer.encode(__UpperCAmelCase				, add_special_tokens=__UpperCAmelCase)
      self.assertListEqual(__UpperCAmelCase				, __UpperCAmelCase)

      a						:		str      							=			self.get_rust_tokenizer()
      a						:		int      							=			tokenizer.encode(__UpperCAmelCase)
      a						:		str      							=			rust_tokenizer.encode(__UpperCAmelCase)
      self.assertListEqual(__UpperCAmelCase				, __UpperCAmelCase)






    @slow
    def 	__snake_case							(					self				:    Optional[int]):
      a						:		Tuple      							=			"Hello World!"
      a						:		Union[str, Any]      							=			[2, 31227, 4447, 35]

      self.assertListEqual(__UpperCAmelCase				, self.big_tokenizer.encode(__UpperCAmelCase))






    @slow
    def 	__snake_case							(					self				:    Any):
      a						:		Optional[Any]      							=			(
          "This is a very long text with a lot of weird characters, such as: . , ~ ? ( ) \" [ ] ! : - . Also we will"
          " add words that should not exsist and be tokenized to unk, such as saoneuhaoesuth"
      )
      # fmt: off
      a						:		str      							=			[2, 1018, 67, 11, 1988, 2617, 5631, 278, 11, 3407, 48, 71630, 28085, 4, 3234, 157, 13, 6, 5, 6, 4, 3526, 768, 15, 659, 57, 298, 3983, 864, 129, 21, 6, 5, 13675, 377, 652, 7580, 10341, 155, 2817, 422, 1666, 7, 1674, 53, 113, 202277, 17892, 33, 60, 87, 4, 3234, 157, 61, 2667, 52376, 19, 88, 23, 735]
      # fmt: on

      self.assertListEqual(__UpperCAmelCase				, self.big_tokenizer.encode(__UpperCAmelCase))






    @slow
    def 	__snake_case							(					self				:    Optional[Any]):
      # fmt: off
      a						:		List[Any]      							=			{
          "input_ids": [[2, 108825, 1163, 15, 88010, 473, 15898, 157, 13672, 1857, 312, 8, 238021, 1163, 53, 13672, 1857, 312, 8, 53283, 182396, 8, 18566, 16, 36733, 4101, 8, 230, 244017, 122553, 7, 15, 132597, 4, 293, 12511, 7610, 4, 3414, 132597, 9, 4, 32361, 362, 4, 734, 28512, 32569, 18, 4, 32361, 26096, 14982, 73, 18715, 21433, 235261, 15, 492, 12427, 16, 53, 18715, 21433, 65454, 15, 23659, 563, 16, 278, 597, 2843, 595, 7931, 182396, 64186, 22, 886, 595, 132981, 53, 25540, 3449, 43982, 39901, 5951, 878, 330, 4, 27694, 80269, 312, 53, 6517, 11780, 611, 20408, 5], [2, 6, 132597, 67, 42897, 33, 592, 8, 163729, 25540, 361, 136997, 109514, 173230, 7, 501, 60, 102913, 196, 5631, 235, 63243, 473, 6, 231757, 74, 5277, 7905, 53, 3095, 37317, 22, 454, 183874, 5], [2, 268, 31298, 46530, 6, 132935, 43831, 7, 597, 32, 24, 3688, 9865, 5]],
          "attention_mask": [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]
      }  # noqa: E501
      # fmt: on

      self.tokenizer_integration_test_util(
          expected_encoding=__UpperCAmelCase				, model_name="facebook/xglm-564M"				, padding=__UpperCAmelCase				, )










"""simple docstring"""







# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import re

from ..models.auto import AutoProcessor
from ..models.vision_encoder_decoder import VisionEncoderDecoderModel
from ..utils import is_vision_available
from .base import PipelineTool


if is_vision_available():
 from PIL import Image






class 						_A  (  _a  ):







    """simple docstring"""




    UpperCAmelCase       :							str	=       """naver-clova-ix/donut-base-finetuned-docvqa"""
    UpperCAmelCase       :							Tuple	=       (
        """This is a tool that answers a question about an document (pdf). It takes an input named `document` which """
        """should be the document containing the information, as well as a `question` that is the question about the """
        """document. It returns a text that contains the answer to the question."""
    )
    UpperCAmelCase       :							List[str]	=       """document_qa"""
    UpperCAmelCase       :							str	=       AutoProcessor
    UpperCAmelCase       :							Optional[int]	=       VisionEncoderDecoderModel

    UpperCAmelCase       :							int	=       ["""image""", """text"""]
    UpperCAmelCase       :							int	=       ["""text"""]






    def __init__(					self				:    Tuple				, *__UpperCAmelCase				:    Union[str, Any]				, **__UpperCAmelCase				:    Any):
      if not is_vision_available():
        raise ValueError("Pillow must be installed to use the DocumentQuestionAnsweringTool.")

      super().__init__(*__UpperCAmelCase				, **__UpperCAmelCase)






    def 	__snake_case							(					self				:    Tuple				, __UpperCAmelCase				:    "Image"				, __UpperCAmelCase				:    str):
      a						:		Any      							=			"<s_docvqa><s_question>{user_input}</s_question><s_answer>"
      a						:		Union[str, Any]      							=			task_prompt.replace("{user_input}"				, __UpperCAmelCase)
      a						:		Optional[Any]      							=			self.pre_processor.tokenizer(
          __UpperCAmelCase				, add_special_tokens=__UpperCAmelCase				, return_tensors="pt").input_ids
      a						:		Any      							=			self.pre_processor(__UpperCAmelCase				, return_tensors="pt").pixel_values

      return {"decoder_input_ids": decoder_input_ids, "pixel_values": pixel_values}






    def 	__snake_case							(					self				:    int				, __UpperCAmelCase				:    int):
      return self.model.generate(
          inputs["pixel_values"].to(self.device)				, decoder_input_ids=inputs["decoder_input_ids"].to(self.device)				, max_length=self.model.decoder.config.max_position_embeddings				, early_stopping=__UpperCAmelCase				, pad_token_id=self.pre_processor.tokenizer.pad_token_id				, eos_token_id=self.pre_processor.tokenizer.eos_token_id				, use_cache=__UpperCAmelCase				, num_beams=1				, bad_words_ids=[[self.pre_processor.tokenizer.unk_token_id]]				, return_dict_in_generate=__UpperCAmelCase				, ).sequences






    def 	__snake_case							(					self				:    str				, __UpperCAmelCase				:    List[Any]):
      a						:		Union[str, Any]      							=			self.pre_processor.batch_decode(__UpperCAmelCase)[0]
      a						:		Optional[Any]      							=			sequence.replace(self.pre_processor.tokenizer.eos_token				, "")
      a						:		Any      							=			sequence.replace(self.pre_processor.tokenizer.pad_token				, "")
      a						:		Optional[Any]      							=			re.sub(r"<.*?>"				, ""				, __UpperCAmelCase				, count=1).strip()  # remove first task start token
      a						:		List[str]      							=			self.pre_processor.tokenajson(__UpperCAmelCase)

      return sequence["answer"]






