"""simple docstring"""






import json
import os
import unittest

from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES, XLMTokenizer
from transformers.testing_utils import slow

from ...test_tokenization_common import TokenizerTesterMixin





class 					_A		(			lowerCAmelCase    ,       unittest.TestCase      ):
      snake_case__     :  Tuple				    =      XLMTokenizer
      snake_case__     :  str				    =      False

      def 							A__			(		self		):







            """simple docstring"""



            super().setUp()

            # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
            lowercase								=      [
                """l""",
                """o""",
                """w""",
                """e""",
                """r""",
                """s""",
                """t""",
                """i""",
                """d""",
                """n""",
                """w</w>""",
                """r</w>""",
                """t</w>""",
                """lo""",
                """low""",
                """er</w>""",
                """low</w>""",
                """lowest</w>""",
                """newer</w>""",
                """wider</w>""",
                """<unk>""",
            ]
            lowercase								=      dict(zip(__lowerCAmelCase						,			range(len(__lowerCAmelCase		)		)		)		)
            lowercase								=      ["""l o 123""", """lo w 1456""", """e r</w> 1789""", """"""]

            lowercase								=      os.path.join(self.tmpdirname						,			VOCAB_FILES_NAMES["""vocab_file"""]		)
            lowercase								=      os.path.join(self.tmpdirname						,			VOCAB_FILES_NAMES["""merges_file"""]		)
            with open(self.vocab_file						,			"""w"""		) as fp:
                  fp.write(json.dumps(__lowerCAmelCase		)		)
            with open(self.merges_file						,			"""w"""		) as fp:
                  fp.write("""\n""".join(__lowerCAmelCase		)		)

      def 							A__			(		self						,			__lowerCAmelCase		):







            """simple docstring"""



            lowercase								=      """lower newer"""
            lowercase								=      """lower newer"""
            return input_text, output_text

      def 							A__			(		self		):







            """simple docstring"""



            lowercase								=      XLMTokenizer(self.vocab_file						,			self.merges_file		)

            lowercase								=      """lower"""
            lowercase								=      ["""low""", """er</w>"""]
            lowercase								=      tokenizer.tokenize(__lowerCAmelCase		)
            self.assertListEqual(__lowerCAmelCase						,			__lowerCAmelCase		)

            lowercase								=      tokens + ["""<unk>"""]
            lowercase								=      [14, 15, 20]
            self.assertListEqual(tokenizer.convert_tokens_to_ids(__lowerCAmelCase		)						,			__lowerCAmelCase		)







      @slow
      def 							A__			(		self		):







            """simple docstring"""



            lowercase								=      XLMTokenizer.from_pretrained("""xlm-mlm-en-2048"""		)

            lowercase								=      tokenizer.encode("""sequence builders"""						,			add_special_tokens=__lowerCAmelCase		)
            lowercase								=      tokenizer.encode("""multi-sequence build"""						,			add_special_tokens=__lowerCAmelCase		)

            lowercase								=      tokenizer.build_inputs_with_special_tokens(__lowerCAmelCase		)
            lowercase								=      tokenizer.build_inputs_with_special_tokens(__lowerCAmelCase						,			__lowerCAmelCase		)

            assert encoded_sentence == [0] + text + [1]
            assert encoded_pair == [0] + text + [1] + text_a + [1]




"""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.
from ..models.auto import AutoModelForSeqaSeqLM, AutoTokenizer
from .base import PipelineTool





class 					_A		(			lowerCAmelCase      ):
      snake_case__     :  List[Any]				    =      'philschmid/bart-large-cnn-samsum'
      snake_case__     :  int				    =      (
          'This is a tool that summarizes an English text. It takes an input `text` containing the text to summarize, '
          'and returns a summary of the text.'
      )
      snake_case__     :  Tuple				    =      'summarizer'
      snake_case__     :  int				    =      AutoTokenizer
      snake_case__     :  Any				    =      AutoModelForSeqaSeqLM

      snake_case__     :  Optional[int]				    =      ['text']
      snake_case__     :  Optional[int]				    =      ['text']

      def 							A__			(		self						,			__lowerCAmelCase		):







            """simple docstring"""



            return self.pre_processor(__lowerCAmelCase						,			return_tensors="""pt"""						,			truncation=__lowerCAmelCase		)

      def 							A__			(		self						,			__lowerCAmelCase		):







            """simple docstring"""



            return self.model.generate(**__lowerCAmelCase		)[0]







      def 							A__			(		self						,			__lowerCAmelCase		):







            """simple docstring"""



            return self.pre_processor.decode(__lowerCAmelCase						,			skip_special_tokens=__lowerCAmelCase						,			clean_up_tokenization_spaces=__lowerCAmelCase		)



