






'''simple docstring'''
from typing import List, Optional, Union

from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType


class        _UpperCAmelCase						(		snake_case			):
    __lowerCamelCase:   str		       =    ['image_processor', 'tokenizer']
    __lowerCamelCase:   Dict		       =    'Pix2StructImageProcessor'
    __lowerCamelCase:   Union[str, Any]		       =    ('T5Tokenizer', 'T5TokenizerFast')




    def __init__(			self  :       str  ,     a  :       Dict  ,     a  :       List[str]			):






       '''simple docstring'''






       lowercase_	:    Optional[Any]           =     False
       super().__init__(a  ,     a			)




    def __call__(			self  :       Tuple  ,     a  :       int=None  ,     a  :       Union[TextInput, PreTokenizedInput, List[TextInput], List[PreTokenizedInput]] = None  ,     a  :       bool = True  ,     a  :       Union[bool, str, PaddingStrategy] = False  ,     a  :       Union[bool, str, TruncationStrategy] = None  ,     a  :       Optional[int] = None  ,     a  :       Optional[int] = 2_0_4_8  ,     a  :       int = 0  ,     a  :       Optional[int] = None  ,     a  :       Optional[bool] = None  ,     a  :       bool = False  ,     a  :       bool = False  ,     a  :       bool = False  ,     a  :       bool = False  ,     a  :       bool = False  ,     a  :       bool = True  ,     a  :       Optional[Union[str, TensorType]] = None  ,     **a  :       List[str]  ,     ):






       '''simple docstring'''






       if images is None and text is None:
          raise ValueError("You have to specify either images or text."			)

       # Get only text
       if images is None and not self.image_processor.is_vqa:
          lowercase_	:    Dict           =     self.tokenizer
          lowercase_	:    Tuple           =     self.tokenizer(
              text=a  ,     add_special_tokens=a  ,     padding=a  ,     truncation=a  ,     max_length=a  ,     stride=a  ,     pad_to_multiple_of=a  ,     return_attention_mask=a  ,     return_overflowing_tokens=a  ,     return_special_tokens_mask=a  ,     return_offsets_mapping=a  ,     return_token_type_ids=a  ,     return_length=a  ,     verbose=a  ,     return_tensors=a  ,     **a  ,     )
          return text_encoding

       if not self.image_processor.is_vqa:
          # add pixel_values
          lowercase_	:    Optional[int]           =     self.image_processor(
              a  ,     return_tensors=a  ,     max_patches=a  ,     **a			)
       else:
          # add pixel_values and bbox
          lowercase_	:    Any           =     self.image_processor(
              a  ,     return_tensors=a  ,     max_patches=a  ,     header_text=a  ,     **a			)

       if text is not None and not self.image_processor.is_vqa:
          lowercase_	:    int           =     self.tokenizer(
              text=a  ,     add_special_tokens=a  ,     padding=a  ,     truncation=a  ,     max_length=a  ,     stride=a  ,     pad_to_multiple_of=a  ,     return_attention_mask=a  ,     return_overflowing_tokens=a  ,     return_special_tokens_mask=a  ,     return_offsets_mapping=a  ,     return_token_type_ids=a  ,     return_length=a  ,     verbose=a  ,     return_tensors=a  ,     **a  ,     )

          if "attention_mask" in text_encoding:
             lowercase_	:    str           =     text_encoding.pop("attention_mask"			)
          if "input_ids" in text_encoding:
             lowercase_	:    Dict           =     text_encoding.pop("input_ids"			)
       else:
          lowercase_	:    str           =     None

       if text_encoding is not None:
          encoding_image_processor.update(a			)

       return encoding_image_processor




    def 				lowerCAmelCase__				(			self  :       Any  ,     *a  :       str  ,     **a  :       Tuple			):






       '''simple docstring'''






       return self.tokenizer.batch_decode(*a  ,     **a			)




    def 				lowerCAmelCase__				(			self  :       str  ,     *a  :       Optional[int]  ,     **a  :       Any			):






       '''simple docstring'''






       return self.tokenizer.decode(*a  ,     **a			)





    @property
    def 				lowerCAmelCase__				(			self  :       str			):






       '''simple docstring'''






       lowercase_	:    Tuple           =     self.tokenizer.model_input_names
       lowercase_	:    Dict           =     self.image_processor.model_input_names
       return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names			)			)












'''simple docstring'''
import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, BatchEncoding, PLBartTokenizer, is_torch_available
from transformers.testing_utils import (
    get_tests_dir,
    nested_simplify,
    require_sentencepiece,
    require_tokenizers,
    require_torch,
)

from ...test_tokenization_common import TokenizerTesterMixin


UpperCamelCase__ =			get_tests_dir('fixtures/test_sentencepiece.model')


if is_torch_available():
 from transformers.models.plbart.modeling_plbart import shift_tokens_right

UpperCamelCase__ =			50003
UpperCamelCase__ =			50002


@require_sentencepiece
@require_tokenizers
class        _UpperCAmelCase						(		snake_case				,					unittest.TestCase			):
    __lowerCamelCase:   Optional[int]		       =    PLBartTokenizer
    __lowerCamelCase:   Any		       =    None
    __lowerCamelCase:   Dict		       =    False




    def 				lowerCAmelCase__				(			self  :       int			):






       '''simple docstring'''






       super().setUp()

       # We have a SentencePiece fixture for testing
       lowercase_	:    Any           =     PLBartTokenizer(a  ,     language_codes="base"  ,     keep_accents=a			)
       tokenizer.save_pretrained(self.tmpdirname			)




    def 				lowerCAmelCase__				(			self  :       Optional[Any]			):






       '''simple docstring'''






       lowercase_	:    List[str]           =     PLBartTokenizer(a  ,     language_codes="base"  ,     keep_accents=a			)

       lowercase_	:    List[str]           =     tokenizer.tokenize("This is a test"			)
       self.assertListEqual(a  ,     ["▁This", "▁is", "▁a", "▁t", "est"]			)

       self.assertListEqual(
           tokenizer.convert_tokens_to_ids(a			)  ,     [value + tokenizer.fairseq_offset for value in [2_8_5, 4_6, 1_0, 1_7_0, 3_8_2]]  ,     )

       lowercase_	:    List[str]           =     tokenizer.tokenize("I was born in 92000, and this is falsé."			)
       self.assertListEqual(
           a  ,     [
               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",
               ".",
           ]  ,     )
       lowercase_	:    Union[str, Any]           =     tokenizer.convert_tokens_to_ids(a			)
       self.assertListEqual(
           a  ,     [
               value + tokenizer.fairseq_offset
               for value in [8, 2_1, 8_4, 5_5, 2_4, 1_9, 7, 2, 6_0_2, 3_4_7, 3_4_7, 3_4_7, 3, 1_2, 6_6, 4_6, 7_2, 8_0, 6, 2, 4]
           ]  ,     )

       lowercase_	:    Optional[int]           =     tokenizer.convert_ids_to_tokens(a			)
       self.assertListEqual(
           a  ,     [
               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>",
               ".",
           ]  ,     )

       lowercase_	:    Dict           =     tokenizer.vocab_size
       lowercase_	:    str           =     [tokenizer.convert_ids_to_tokens(a			) for x in range(end - 4  ,     a			)]

       self.assertListEqual(a  ,     ["__java__", "__python__", "__en_XX__", "<mask>"]			)

       lowercase_	:    int           =     "java.lang.Exception, python.lang.Exception, javascript, php, ruby, go"
       lowercase_	:    str           =     tokenizer(a			).input_ids
       self.assertEqual(
           tokenizer.decode(a  ,     skip_special_tokens=a  ,     clean_up_tokenization_spaces=a			)  ,     a  ,     )





    def 				lowerCAmelCase__				(			self  :       int			):






       '''simple docstring'''






       lowercase_	:    str           =     PLBartTokenizer(a  ,     language_codes="multi"  ,     keep_accents=a			)

       lowercase_	:    List[str]           =     tokenizer.tokenize("This is a test"			)
       self.assertListEqual(a  ,     ["▁This", "▁is", "▁a", "▁t", "est"]			)

       self.assertListEqual(
           tokenizer.convert_tokens_to_ids(a			)  ,     [value + tokenizer.fairseq_offset for value in [2_8_5, 4_6, 1_0, 1_7_0, 3_8_2]]  ,     )

       lowercase_	:    Optional[Any]           =     tokenizer.tokenize("I was born in 92000, and this is falsé."			)
       self.assertListEqual(
           a  ,     [
               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",
               ".",
           ]  ,     )
       lowercase_	:    Optional[Any]           =     tokenizer.convert_tokens_to_ids(a			)
       self.assertListEqual(
           a  ,     [
               value + tokenizer.fairseq_offset
               for value in [8, 2_1, 8_4, 5_5, 2_4, 1_9, 7, 2, 6_0_2, 3_4_7, 3_4_7, 3_4_7, 3, 1_2, 6_6, 4_6, 7_2, 8_0, 6, 2, 4]
           ]  ,     )

       lowercase_	:    List[str]           =     tokenizer.convert_ids_to_tokens(a			)
       self.assertListEqual(
           a  ,     [
               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>",
               ".",
           ]  ,     )
       lowercase_	:    Dict           =     tokenizer.vocab_size
       lowercase_	:    Union[str, Any]           =     [tokenizer.convert_ids_to_tokens(a			) for x in range(end - 7  ,     a			)]

       self.assertListEqual(
           a  ,     ["__java__", "__python__", "__en_XX__", "__javascript__", "__php__", "__ruby__", "__go__"]			)
       lowercase_	:    Any           =     "java.lang.Exception, python.lang.Exception, javascript, php, ruby, go"
       lowercase_	:    List[Any]           =     tokenizer(a			).input_ids
       self.assertEqual(
           tokenizer.decode(a  ,     skip_special_tokens=a  ,     clean_up_tokenization_spaces=a			)  ,     a  ,     )


@require_torch
@require_sentencepiece
@require_tokenizers
class        _UpperCAmelCase						(		unittest.TestCase			):
    __lowerCamelCase:   int		       =    'uclanlp/plbart-python-en_XX'
    __lowerCamelCase:   Tuple		       =    [
        'def maximum(a,b,c):NEW_LINE_INDENTreturn max([a,b,c])',
        'def sum(a,b,c):NEW_LINE_INDENTreturn sum([a,b,c])',
    ]
    __lowerCamelCase:   List[str]		       =    [
        'Returns the maximum value of a b c.',
        'Sums the values of a b c.',
    ]
    __lowerCamelCase:   List[str]		       =    [
        134,
        5452,
        3_3460,
        3_3441,
        3_3463,
        3_3465,
        3_3463,
        3_3449,
        988,
        20,
        3_3456,
        19,
        3_3456,
        771,
        39,
        4258,
        889,
        3318,
        3_3441,
        3_3463,
        3_3465,
        3_3463,
        3_3449,
        2471,
        2,
        PYTHON_CODE,
    ]




    @classmethod
    def 				lowerCAmelCase__				(			cls  :       str			):






       '''simple docstring'''






       lowercase_	:    PLBartTokenizer           =     PLBartTokenizer.from_pretrained(
           cls.checkpoint_name  ,     language_codes="base"  ,     src_lang="python"  ,     tgt_lang="en_XX"			)
       lowercase_	:    List[str]           =     1
       return cls




    def 				lowerCAmelCase__				(			self  :       int			):






       '''simple docstring'''






       self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["__java__"]  ,     5_0_0_0_1			)
       self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["__python__"]  ,     5_0_0_0_2			)
       self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["__en_XX__"]  ,     5_0_0_0_3			)




    def 				lowerCAmelCase__				(			self  :       int			):






       '''simple docstring'''






       lowercase_	:    int           =     self.tokenizer.batch_encode_plus(self.src_text			).input_ids[0]
       self.assertListEqual(self.expected_src_tokens  ,     a			)




    def 				lowerCAmelCase__				(			self  :       Tuple			):






       '''simple docstring'''






       self.assertIn(a  ,     self.tokenizer.all_special_ids			)
       lowercase_	:    List[Any]           =     [EN_CODE, 9_0_3_7, 3_3_4_4_2, 5_7, 7_5_2, 1_5_3, 1_4, 5_6, 1_8, 9, 2]
       lowercase_	:    Optional[int]           =     self.tokenizer.decode(a  ,     skip_special_tokens=a			)
       lowercase_	:    Any           =     self.tokenizer.decode(generated_ids[1:]  ,     skip_special_tokens=a			)
       self.assertEqual(a  ,     a			)
       self.assertNotIn(self.tokenizer.eos_token  ,     a			)




    def 				lowerCAmelCase__				(			self  :       Dict			):






       '''simple docstring'''






       lowercase_	:    Optional[int]           =     ["def sum(a,b,c):NEW_LINE_INDENTreturn sum([a,b,c])" * 2_0]
       self.assertIsInstance(src_text[0]  ,     a			)
       lowercase_	:    Tuple           =     1_0
       lowercase_	:    int           =     self.tokenizer(a  ,     max_length=a  ,     truncation=a			).input_ids[0]
       self.assertEqual(ids[-2]  ,     2			)
       self.assertEqual(ids[-1]  ,     a			)
       self.assertEqual(len(a			)  ,     a			)




    def 				lowerCAmelCase__				(			self  :       Dict			):






       '''simple docstring'''






       self.assertListEqual(self.tokenizer.convert_tokens_to_ids(["<mask>", "__java__"]			)  ,     [5_0_0_0_4, 5_0_0_0_1]			)




    def 				lowerCAmelCase__				(			self  :       str			):






       '''simple docstring'''






       lowercase_	:    Optional[int]           =     tempfile.mkdtemp()
       lowercase_	:    List[str]           =     self.tokenizer.fairseq_tokens_to_ids
       self.tokenizer.save_pretrained(a			)
       lowercase_	:    Tuple           =     PLBartTokenizer.from_pretrained(a			)
       self.assertDictEqual(new_tok.fairseq_tokens_to_ids  ,     a			)




    @require_torch
    def 				lowerCAmelCase__				(			self  :       Optional[int]			):






       '''simple docstring'''






       lowercase_	:    int           =     self.tokenizer(self.src_text  ,     text_target=self.tgt_text  ,     padding=a  ,     return_tensors="pt"			)
       lowercase_	:    List[str]           =     shift_tokens_right(batch["labels"]  ,     self.tokenizer.pad_token_id			)

       # fairseq batch: https://gist.github.com/sshleifer/cba08bc2109361a74ac3760a7e30e4f4
       self.assertEqual(batch.input_ids[1][-2:].tolist()  ,     [2, PYTHON_CODE]			)
       self.assertEqual(batch.decoder_input_ids[1][0]  ,     a			)
       self.assertEqual(batch.decoder_input_ids[1][-1]  ,     2			)
       self.assertEqual(batch.labels[1][-2:].tolist()  ,     [2, EN_CODE]			)




    @require_torch
    def 				lowerCAmelCase__				(			self  :       List[str]			):






       '''simple docstring'''






       lowercase_	:    Union[str, Any]           =     self.tokenizer(
           self.src_text  ,     text_target=self.tgt_text  ,     padding=a  ,     truncation=a  ,     max_length=len(self.expected_src_tokens			)  ,     return_tensors="pt"  ,     )
       lowercase_	:    Dict           =     shift_tokens_right(batch["labels"]  ,     self.tokenizer.pad_token_id			)

       self.assertIsInstance(a  ,     a			)

       self.assertEqual((2, 2_6)  ,     batch.input_ids.shape			)
       self.assertEqual((2, 2_6)  ,     batch.attention_mask.shape			)
       lowercase_	:    Dict           =     batch.input_ids.tolist()[0]
       self.assertListEqual(self.expected_src_tokens  ,     a			)
       self.assertEqual(2  ,     batch.decoder_input_ids[0, -1]			)  # EOS
       # Test that special tokens are reset
       self.assertEqual(self.tokenizer.prefix_tokens  ,     []			)
       self.assertEqual(self.tokenizer.suffix_tokens  ,     [self.tokenizer.eos_token_id, PYTHON_CODE]			)




    def 				lowerCAmelCase__				(			self  :       int			):






       '''simple docstring'''






       lowercase_	:    List[str]           =     self.tokenizer(self.src_text  ,     padding=a  ,     truncation=a  ,     max_length=3  ,     return_tensors="pt"			)
       lowercase_	:    List[str]           =     self.tokenizer(
           text_target=self.tgt_text  ,     padding=a  ,     truncation=a  ,     max_length=1_0  ,     return_tensors="pt"			)
       lowercase_	:    Dict           =     targets["input_ids"]
       lowercase_	:    str           =     shift_tokens_right(a  ,     self.tokenizer.pad_token_id			)

       self.assertEqual(batch.input_ids.shape[1]  ,     3			)
       self.assertEqual(batch.decoder_input_ids.shape[1]  ,     1_0			)





    @require_torch
    def 				lowerCAmelCase__				(			self  :       List[str]			):






       '''simple docstring'''






       lowercase_	:    List[str]           =     self.tokenizer._build_translation_inputs(
           "A test"  ,     return_tensors="pt"  ,     src_lang="en_XX"  ,     tgt_lang="java"			)

       self.assertEqual(
           nested_simplify(a			)  ,     {
               # A, test, EOS, en_XX
               "input_ids": [[1_5_0, 2_4_2, 2, 5_0_0_0_3]],
               "attention_mask": [[1, 1, 1, 1]],
               # java
               "forced_bos_token_id": 5_0_0_0_1,
           }  ,     )




