





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


__lowerCamelCase	:					Tuple			  =					get_tests_dir("""fixtures/test_sentencepiece.model""")


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

__lowerCamelCase	:					Optional[int]			  =					5_0003
__lowerCamelCase	:					str			  =					5_0002



@require_sentencepiece
@require_tokenizers
class  A__       (	__snake_case	,       unittest.TestCase      ):
      _UpperCAmelCase     :Any						   =       PLBartTokenizer
      _UpperCAmelCase     :List[Any]						   =       None
      _UpperCAmelCase     :Optional[Any]						   =       False





      def 	__UpperCamelCase(			self       ):
       '''simple docstring'''




       super().setUp()

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





      def 	__UpperCamelCase(			self       ):
       '''simple docstring'''




       UpperCamelCase     : Union[str, Any]	     =       PLBartTokenizer(A_	,							language_codes="base"	,							keep_accents=A_       )

       UpperCamelCase     : 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 [285, 46, 10, 170, 382]]	,							)

       UpperCamelCase     : Optional[int]	     =       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",
               ".",
           ]	,							)
       UpperCamelCase     : Optional[Any]	     =       tokenizer.convert_tokens_to_ids(A_       )
       self.assertListEqual(
           A_	,							[
               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]
           ]	,							)

       UpperCamelCase     : 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>",
               ".",
           ]	,							)

       UpperCamelCase     : Tuple	     =       tokenizer.vocab_size
       UpperCamelCase     : Tuple	     =       [tokenizer.convert_ids_to_tokens(A_       ) for x in range(end - 4	,							A_       )]

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

       UpperCamelCase     : Optional[Any]	     =       "java.lang.Exception, python.lang.Exception, javascript, php, ruby, go"
       UpperCamelCase     : List[str]	     =       tokenizer(A_       ).input_ids
       self.assertEqual(
           tokenizer.decode(A_	,							skip_special_tokens=A_	,							clean_up_tokenization_spaces=A_       )	,							A_	,							)





      def 	__UpperCamelCase(			self       ):
       '''simple docstring'''




       UpperCamelCase     : int	     =       PLBartTokenizer(A_	,							language_codes="multi"	,							keep_accents=A_       )

       UpperCamelCase     : int	     =       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 [285, 46, 10, 170, 382]]	,							)

       UpperCamelCase     : 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",
               ".",
           ]	,							)
       UpperCamelCase     : Dict	     =       tokenizer.convert_tokens_to_ids(A_       )
       self.assertListEqual(
           A_	,							[
               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]
           ]	,							)

       UpperCamelCase     : 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>",
               ".",
           ]	,							)
       UpperCamelCase     : Any	     =       tokenizer.vocab_size
       UpperCamelCase     : int	     =       [tokenizer.convert_ids_to_tokens(A_       ) for x in range(end - 7	,							A_       )]

       self.assertListEqual(
           A_	,							["__java__", "__python__", "__en_XX__", "__javascript__", "__php__", "__ruby__", "__go__"]       )
       UpperCamelCase     : List[Any]	     =       "java.lang.Exception, python.lang.Exception, javascript, php, ruby, go"
       UpperCamelCase     : Optional[int]	     =       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  A__       (	unittest.TestCase      ):
      _UpperCAmelCase     :int						   =       'uclanlp/plbart-python-en_XX'
      _UpperCAmelCase     :Optional[int]						   =       [
          'def maximum(a,b,c):NEW_LINE_INDENTreturn max([a,b,c])',
          'def sum(a,b,c):NEW_LINE_INDENTreturn sum([a,b,c])',
      ]
      _UpperCAmelCase     :Union[str, Any]						   =       [
          'Returns the maximum value of a b c.',
          'Sums the values of a b c.',
      ]
      _UpperCAmelCase     :Optional[int]						   =       [
          1_3_4,
          5_4_5_2,
          3_3_4_6_0,
          3_3_4_4_1,
          3_3_4_6_3,
          3_3_4_6_5,
          3_3_4_6_3,
          3_3_4_4_9,
          9_8_8,
          2_0,
          3_3_4_5_6,
          1_9,
          3_3_4_5_6,
          7_7_1,
          3_9,
          4_2_5_8,
          8_8_9,
          3_3_1_8,
          3_3_4_4_1,
          3_3_4_6_3,
          3_3_4_6_5,
          3_3_4_6_3,
          3_3_4_4_9,
          2_4_7_1,
          2,
          PYTHON_CODE,
      ]





      @classmethod
      def 	__UpperCamelCase(			cls       ):
       '''simple docstring'''




       UpperCamelCase     : PLBartTokenizer	     =       PLBartTokenizer.from_pretrained(
           cls.checkpoint_name	,							language_codes="base"	,							src_lang="python"	,							tgt_lang="en_XX"       )
       UpperCamelCase     : int	     =       1
       return cls





      def 	__UpperCamelCase(			self       ):
       '''simple docstring'''




       self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["__java__"]	,							5_0001       )
       self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["__python__"]	,							5_0002       )
       self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["__en_XX__"]	,							5_0003       )





      def 	__UpperCamelCase(			self       ):
       '''simple docstring'''




       UpperCamelCase     : Any	     =       self.tokenizer.batch_encode_plus(self.src_text       ).input_ids[0]
       self.assertListEqual(self.expected_src_tokens	,							A_       )





      def 	__UpperCamelCase(			self       ):
       '''simple docstring'''




       self.assertIn(A_	,							self.tokenizer.all_special_ids       )
       UpperCamelCase     : List[str]	     =       [EN_CODE, 9037, 3_3442, 57, 752, 153, 14, 56, 18, 9, 2]
       UpperCamelCase     : int	     =       self.tokenizer.decode(A_	,							skip_special_tokens=A_       )
       UpperCamelCase     : int	     =       self.tokenizer.decode(generated_ids[1:]	,							skip_special_tokens=A_       )
       self.assertEqual(A_	,							A_       )
       self.assertNotIn(self.tokenizer.eos_token	,							A_       )





      def 	__UpperCamelCase(			self       ):
       '''simple docstring'''




       UpperCamelCase     : Union[str, Any]	     =       ["def sum(a,b,c):NEW_LINE_INDENTreturn sum([a,b,c])" * 20]
       self.assertIsInstance(src_text[0]	,							A_       )
       UpperCamelCase     : Tuple	     =       10
       UpperCamelCase     : Union[str, Any]	     =       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 	__UpperCamelCase(			self       ):
       '''simple docstring'''




       self.assertListEqual(self.tokenizer.convert_tokens_to_ids(["<mask>", "__java__"]       )	,							[5_0004, 5_0001]       )





      def 	__UpperCamelCase(			self       ):
       '''simple docstring'''




       UpperCamelCase     : int	     =       tempfile.mkdtemp()
       UpperCamelCase     : Optional[Any]	     =       self.tokenizer.fairseq_tokens_to_ids
       self.tokenizer.save_pretrained(A_       )
       UpperCamelCase     : Optional[int]	     =       PLBartTokenizer.from_pretrained(A_       )
       self.assertDictEqual(new_tok.fairseq_tokens_to_ids	,							A_       )





      @require_torch
      def 	__UpperCamelCase(			self       ):
       '''simple docstring'''




       UpperCamelCase     : Tuple	     =       self.tokenizer(self.src_text	,							text_target=self.tgt_text	,							padding=A_	,							return_tensors="pt"       )
       UpperCamelCase     : 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 	__UpperCamelCase(			self       ):
       '''simple docstring'''




       UpperCamelCase     : List[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"	,							)
       UpperCamelCase     : Dict	     =       shift_tokens_right(batch["labels"]	,							self.tokenizer.pad_token_id       )

       self.assertIsInstance(A_	,							A_       )

       self.assertEqual((2, 26)	,							batch.input_ids.shape       )
       self.assertEqual((2, 26)	,							batch.attention_mask.shape       )
       UpperCamelCase     : Union[str, Any]	     =       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 	__UpperCamelCase(			self       ):
       '''simple docstring'''




       UpperCamelCase     : Any	     =       self.tokenizer(self.src_text	,							padding=A_	,							truncation=A_	,							max_length=3	,							return_tensors="pt"       )
       UpperCamelCase     : List[str]	     =       self.tokenizer(
           text_target=self.tgt_text	,							padding=A_	,							truncation=A_	,							max_length=10	,							return_tensors="pt"       )
       UpperCamelCase     : List[Any]	     =       targets["input_ids"]
       UpperCamelCase     : Optional[Any]	     =       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]	,							10       )





      @require_torch
      def 	__UpperCamelCase(			self       ):
       '''simple docstring'''




       UpperCamelCase     : Any	     =       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": [[150, 242, 2, 5_0003]],
               "attention_mask": [[1, 1, 1, 1]],
               # java
               "forced_bos_token_id": 5_0001,
           }	,							)







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


__lowerCamelCase	:					Tuple			  =					logging.get_logger(__name__)



class  A__       (	__snake_case      ):
      _UpperCAmelCase     :List[Any]						   =       'timm_backbone'





      def __init__(			self	,							A_=None	,							A_=3	,							A_=True	,							A_=True	,							A_=None	,							**A_	,							):
       '''simple docstring'''




       super().__init__(**A_       )
       UpperCamelCase     : Tuple	     =       backbone
       UpperCamelCase     : Dict	     =       num_channels
       UpperCamelCase     : Tuple	     =       features_only
       UpperCamelCase     : Optional[int]	     =       use_pretrained_backbone
       UpperCamelCase     : Dict	     =       True
       UpperCamelCase     : List[str]	     =       out_indices if out_indices is not None else (-1,)
