






'''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      :       Any      			=      get_tests_dir("""fixtures/test_sentencepiece.model""")


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

__UpperCamelCase      :       Tuple      			=      50003
__UpperCamelCase      :       List[str]      			=      50002
@require_sentencepiece
@require_tokenizers
class 							__SCREAMING_SNAKE_CASE      (							_lowerCAmelCase      ,      unittest.TestCase     ):
      __a  					=PLBartTokenizer
      __a  					=None
      __a  					=False




      def  __UpperCamelCase							(  self      )							->List[Any]:



         '''simple docstring'''
         super().setUp()

         # We have a SentencePiece fixture for testing
         __a				     =    PLBartTokenizer(_UpperCAmelCase ,   language_codes='base' ,   keep_accents=_UpperCAmelCase      )
         tokenizer.save_pretrained(self.tmpdirname      )




      def  __UpperCamelCase							(  self      )							->Optional[Any]:



         '''simple docstring'''
         __a				     =    PLBartTokenizer(_UpperCAmelCase ,   language_codes='base' ,   keep_accents=_UpperCAmelCase      )

         __a				     =    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				     =    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				     =    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				     =    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>',
                 '.',
             ] ,   )

         __a				     =    tokenizer.vocab_size
         __a				     =    [tokenizer.convert_ids_to_tokens(_UpperCAmelCase      ) for x in range(end - 4 ,   _UpperCAmelCase      )]

         self.assertListEqual(_UpperCAmelCase ,   ['__java__', '__python__', '__en_XX__', '<mask>']      )

         __a				     =    'java.lang.Exception, python.lang.Exception, javascript, php, ruby, go'
         __a				     =    tokenizer(_UpperCAmelCase      ).input_ids
         self.assertEqual(
             tokenizer.decode(_UpperCAmelCase ,   skip_special_tokens=_UpperCAmelCase ,   clean_up_tokenization_spaces=_UpperCAmelCase      ) ,   _UpperCAmelCase ,   )






      def  __UpperCamelCase							(  self      )							->int:



         '''simple docstring'''
         __a				     =    PLBartTokenizer(_UpperCAmelCase ,   language_codes='multi' ,   keep_accents=_UpperCAmelCase      )

         __a				     =    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				     =    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				     =    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				     =    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>',
                 '.',
             ] ,   )
         __a				     =    tokenizer.vocab_size
         __a				     =    [tokenizer.convert_ids_to_tokens(_UpperCAmelCase      ) for x in range(end - 7 ,   _UpperCAmelCase      )]

         self.assertListEqual(
             _UpperCAmelCase ,   ['__java__', '__python__', '__en_XX__', '__javascript__', '__php__', '__ruby__', '__go__']      )
         __a				     =    'java.lang.Exception, python.lang.Exception, javascript, php, ruby, go'
         __a				     =    tokenizer(_UpperCAmelCase      ).input_ids
         self.assertEqual(
             tokenizer.decode(_UpperCAmelCase ,   skip_special_tokens=_UpperCAmelCase ,   clean_up_tokenization_spaces=_UpperCAmelCase      ) ,   _UpperCAmelCase ,   )







@require_torch
@require_sentencepiece
@require_tokenizers
class 							__SCREAMING_SNAKE_CASE      (							unittest.TestCase     ):
      __a  					="uclanlp/plbart-python-en_XX"
      __a  					=[
          "def maximum(a,b,c):NEW_LINE_INDENTreturn max([a,b,c])",
          "def sum(a,b,c):NEW_LINE_INDENTreturn sum([a,b,c])",
      ]
      __a  					=[
          "Returns the maximum value of a b c.",
          "Sums the values of a b c.",
      ]
      __a  					=[
          134,
          5_452,
          33_460,
          33_441,
          33_463,
          33_465,
          33_463,
          33_449,
          988,
          20,
          33_456,
          19,
          33_456,
          771,
          39,
          4_258,
          889,
          3_318,
          33_441,
          33_463,
          33_465,
          33_463,
          33_449,
          2_471,
          2,
          PYTHON_CODE,
      ]




      @classmethod
      def  __UpperCamelCase							(  cls      )							->Dict:



         '''simple docstring'''
         __a				     =    PLBartTokenizer.from_pretrained(
             cls.checkpoint_name ,   language_codes='base' ,   src_lang='python' ,   tgt_lang='en_XX'      )
         __a				     =    1
         return cls




      def  __UpperCamelCase							(  self      )							->Optional[Any]:



         '''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      )							->Union[str, Any]:



         '''simple docstring'''
         __a				     =    self.tokenizer.batch_encode_plus(self.src_text      ).input_ids[0]
         self.assertListEqual(self.expected_src_tokens ,   _UpperCAmelCase      )




      def  __UpperCamelCase							(  self      )							->Union[str, Any]:



         '''simple docstring'''
         self.assertIn(_UpperCAmelCase ,   self.tokenizer.all_special_ids      )
         __a				     =    [EN_CODE, 9037, 3_3442, 57, 752, 153, 14, 56, 18, 9, 2]
         __a				     =    self.tokenizer.decode(_UpperCAmelCase ,   skip_special_tokens=_UpperCAmelCase      )
         __a				     =    self.tokenizer.decode(generated_ids[1:] ,   skip_special_tokens=_UpperCAmelCase      )
         self.assertEqual(_UpperCAmelCase ,   _UpperCAmelCase      )
         self.assertNotIn(self.tokenizer.eos_token ,   _UpperCAmelCase      )




      def  __UpperCamelCase							(  self      )							->int:



         '''simple docstring'''
         __a				     =    ['def sum(a,b,c):NEW_LINE_INDENTreturn sum([a,b,c])' * 20]
         self.assertIsInstance(src_text[0] ,   _UpperCAmelCase      )
         __a				     =    10
         __a				     =    self.tokenizer(_UpperCAmelCase ,   max_length=_UpperCAmelCase ,   truncation=_UpperCAmelCase      ).input_ids[0]
         self.assertEqual(ids[-2] ,   2      )
         self.assertEqual(ids[-1] ,   _UpperCAmelCase      )
         self.assertEqual(len(_UpperCAmelCase      ) ,   _UpperCAmelCase      )




      def  __UpperCamelCase							(  self      )							->Optional[int]:



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




      def  __UpperCamelCase							(  self      )							->List[str]:



         '''simple docstring'''
         __a				     =    tempfile.mkdtemp()
         __a				     =    self.tokenizer.fairseq_tokens_to_ids
         self.tokenizer.save_pretrained(_UpperCAmelCase      )
         __a				     =    PLBartTokenizer.from_pretrained(_UpperCAmelCase      )
         self.assertDictEqual(new_tok.fairseq_tokens_to_ids ,   _UpperCAmelCase      )




      @require_torch
      def  __UpperCamelCase							(  self      )							->List[Any]:



         '''simple docstring'''
         __a				     =    self.tokenizer(self.src_text ,   text_target=self.tgt_text ,   padding=_UpperCAmelCase ,   return_tensors='pt'      )
         __a				     =    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] ,   _UpperCAmelCase      )
         self.assertEqual(batch.decoder_input_ids[1][-1] ,   2      )
         self.assertEqual(batch.labels[1][-2:].tolist() ,   [2, EN_CODE]      )




      @require_torch
      def  __UpperCamelCase							(  self      )							->str:



         '''simple docstring'''
         __a				     =    self.tokenizer(
             self.src_text ,   text_target=self.tgt_text ,   padding=_UpperCAmelCase ,   truncation=_UpperCAmelCase ,   max_length=len(self.expected_src_tokens      ) ,   return_tensors='pt' ,   )
         __a				     =    shift_tokens_right(batch['labels'] ,   self.tokenizer.pad_token_id      )

         self.assertIsInstance(_UpperCAmelCase ,   _UpperCAmelCase      )

         self.assertEqual((2, 26) ,   batch.input_ids.shape      )
         self.assertEqual((2, 26) ,   batch.attention_mask.shape      )
         __a				     =    batch.input_ids.tolist()[0]
         self.assertListEqual(self.expected_src_tokens ,   _UpperCAmelCase      )
         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      )							->List[Any]:



         '''simple docstring'''
         __a				     =    self.tokenizer(self.src_text ,   padding=_UpperCAmelCase ,   truncation=_UpperCAmelCase ,   max_length=3 ,   return_tensors='pt'      )
         __a				     =    self.tokenizer(
             text_target=self.tgt_text ,   padding=_UpperCAmelCase ,   truncation=_UpperCAmelCase ,   max_length=10 ,   return_tensors='pt'      )
         __a				     =    targets['input_ids']
         __a				     =    shift_tokens_right(_UpperCAmelCase ,   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      )							->List[str]:



         '''simple docstring'''
         __a				     =    self.tokenizer._build_translation_inputs(
             'A test' ,   return_tensors='pt' ,   src_lang='en_XX' ,   tgt_lang='java'      )

         self.assertEqual(
             nested_simplify(_UpperCAmelCase      ) ,   {
                 # 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,
             } ,   )







'''simple docstring'''



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


__UpperCamelCase      :       List[str]      			=      logging.get_logger(__name__)

__UpperCamelCase      :       Tuple      			=      {
    """sayakpaul/vit-msn-base""": """https://huggingface.co/sayakpaul/vit-msn-base/resolve/main/config.json""",
    # See all ViT MSN models at https://huggingface.co/models?filter=vit_msn
}
class 							__SCREAMING_SNAKE_CASE       (							_lowerCAmelCase     ):
      __a  					="vit_msn"




      def __init__(  self ,   lowerCamelCase=768 ,   lowerCamelCase=12 ,   lowerCamelCase=12 ,   lowerCamelCase=3072 ,   lowerCamelCase="gelu" ,   lowerCamelCase=0.0 ,   lowerCamelCase=0.0 ,   lowerCamelCase=0.02 ,   lowerCamelCase=1e-06 ,   lowerCamelCase=224 ,   lowerCamelCase=16 ,   lowerCamelCase=3 ,   lowerCamelCase=True ,   **lowerCamelCase ,   )							->Tuple:



         '''simple docstring'''
         super().__init__(**lowerCamelCase      )

         __a				     =    hidden_size
         __a				     =    num_hidden_layers
         __a				     =    num_attention_heads
         __a				     =    intermediate_size
         __a				     =    hidden_act
         __a				     =    hidden_dropout_prob
         __a				     =    attention_probs_dropout_prob
         __a				     =    initializer_range
         __a				     =    layer_norm_eps
         __a				     =    image_size
         __a				     =    patch_size
         __a				     =    num_channels
         __a				     =    qkv_bias