import itertools
import json
import os
import unittest

from transformers import AddedToken, RobertaTokenizer, RobertaTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class SCREAMING_SNAKE_CASE_		(      __SCREAMING_SNAKE_CASE  ,     unittest.TestCase		):
   __lowerCAmelCase           =				RobertaTokenizer
   __lowerCAmelCase           =				RobertaTokenizerFast
   __lowerCAmelCase           =				True
   __lowerCAmelCase           =				{"""cls_token""": """<s>"""}







   def 						lowerCamelCase_	(     self						:						Optional[int]				):





    """simple docstring"""


    super().setUp()

    # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
    UpperCamelCase			  =      [
        'l',
        'o',
        'w',
        'e',
        'r',
        's',
        't',
        'i',
        'd',
        'n',
        '\u0120',
        '\u0120l',
        '\u0120n',
        '\u0120lo',
        '\u0120low',
        'er',
        '\u0120lowest',
        '\u0120newer',
        '\u0120wider',
        '<unk>',
    ]
    UpperCamelCase			  =      dict(zip(lowerCAmelCase__   ,   range(len(lowerCAmelCase__				)				)				)				)
    UpperCamelCase			  =      ['#version: 0.2', '\u0120 l', '\u0120l o', '\u0120lo w', 'e r', '']
    UpperCamelCase			  =      {'unk_token': '<unk>'}

    UpperCamelCase			  =      os.path.join(self.tmpdirname   ,   VOCAB_FILES_NAMES["""vocab_file"""]				)
    UpperCamelCase			  =      os.path.join(self.tmpdirname   ,   VOCAB_FILES_NAMES["""merges_file"""]				)
    with open(self.vocab_file   ,   """w"""   ,   encoding="""utf-8"""				) as fp:
     fp.write(json.dumps(lowerCAmelCase__				) + """\n"""				)
    with open(self.merges_file   ,   """w"""   ,   encoding="""utf-8"""				) as fp:
     fp.write("""\n""".join(lowerCAmelCase__				)				)







   def 						lowerCamelCase_	(     self						:						Dict   ,   **lowerCamelCase_						:						Optional[Any]				):





    """simple docstring"""


    kwargs.update(self.special_tokens_map				)
    return self.tokenizer_class.from_pretrained(self.tmpdirname   ,   **lowerCAmelCase__				)







   def 						lowerCamelCase_	(     self						:						Tuple   ,   **lowerCamelCase_						:						int				):





    """simple docstring"""


    kwargs.update(self.special_tokens_map				)
    return RobertaTokenizerFast.from_pretrained(self.tmpdirname   ,   **lowerCAmelCase__				)







   def 						lowerCamelCase_	(     self						:						Any   ,   lowerCamelCase_						:						Any				):





    """simple docstring"""


    UpperCamelCase			  =      'lower newer'
    UpperCamelCase			  =      'lower newer'
    return input_text, output_text







   def 						lowerCamelCase_	(     self						:						List[str]				):





    """simple docstring"""


    UpperCamelCase			  =      self.tokenizer_class(self.vocab_file   ,   self.merges_file   ,   **self.special_tokens_map				)
    UpperCamelCase			  =      'lower newer'
    UpperCamelCase			  =      ['l', 'o', 'w', 'er', '\u0120', 'n', 'e', 'w', 'er']
    UpperCamelCase			  =      tokenizer.tokenize(lowerCAmelCase__				)  # , add_prefix_space=True)
    self.assertListEqual(lowerCAmelCase__   ,   lowerCAmelCase__				)

    UpperCamelCase			  =      tokens + [tokenizer.unk_token]
    UpperCamelCase			  =      [0, 1, 2, 15, 10, 9, 3, 2, 15, 19]
    self.assertListEqual(tokenizer.convert_tokens_to_ids(lowerCAmelCase__				)   ,   lowerCAmelCase__				)







   def 						lowerCamelCase_	(     self						:						str				):





    """simple docstring"""


    UpperCamelCase			  =      self.get_tokenizer()

    self.assertListEqual(tokenizer.encode("""Hello world!"""   ,   add_special_tokens=lowerCAmelCase__				)   ,   [0, 3_1414, 232, 328, 2]				)
    self.assertListEqual(
        tokenizer.encode("""Hello world! cécé herlolip 418"""   ,   add_special_tokens=lowerCAmelCase__				)   ,   [0, 3_1414, 232, 328, 740, 1140, 1_2695, 69, 4_6078, 1588, 2]   ,   )







   @slow
   def 						lowerCamelCase_	(     self						:						List[Any]				):





    """simple docstring"""


    UpperCamelCase			  =      self.tokenizer_class.from_pretrained("""roberta-base"""				)

    UpperCamelCase			  =      tokenizer.encode("""sequence builders"""   ,   add_special_tokens=lowerCAmelCase__				)
    UpperCamelCase			  =      tokenizer.encode("""multi-sequence build"""   ,   add_special_tokens=lowerCAmelCase__				)

    UpperCamelCase			  =      tokenizer.encode(
        """sequence builders"""   ,   add_special_tokens=lowerCAmelCase__   ,   add_prefix_space=lowerCAmelCase__				)
    UpperCamelCase			  =      tokenizer.encode(
        """sequence builders"""   ,   """multi-sequence build"""   ,   add_special_tokens=lowerCAmelCase__   ,   add_prefix_space=lowerCAmelCase__				)

    UpperCamelCase			  =      tokenizer.build_inputs_with_special_tokens(lowerCAmelCase__				)
    UpperCamelCase			  =      tokenizer.build_inputs_with_special_tokens(lowerCAmelCase__   ,   lowerCAmelCase__				)

    assert encoded_sentence == encoded_text_from_decode
    assert encoded_pair == encoded_pair_from_decode







   def 						lowerCamelCase_	(     self						:						List[str]				):





    """simple docstring"""


    UpperCamelCase			  =      self.get_tokenizer()

    UpperCamelCase			  =      'Encode this sequence.'
    UpperCamelCase			  =      tokenizer.byte_encoder[' '.encode("""utf-8"""				)[0]]

    # Testing encoder arguments
    UpperCamelCase			  =      tokenizer.encode(lowerCAmelCase__   ,   add_special_tokens=lowerCAmelCase__   ,   add_prefix_space=lowerCAmelCase__				)
    UpperCamelCase			  =      tokenizer.convert_ids_to_tokens(encoded[0]				)[0]
    self.assertNotEqual(lowerCAmelCase__   ,   lowerCAmelCase__				)

    UpperCamelCase			  =      tokenizer.encode(lowerCAmelCase__   ,   add_special_tokens=lowerCAmelCase__   ,   add_prefix_space=lowerCAmelCase__				)
    UpperCamelCase			  =      tokenizer.convert_ids_to_tokens(encoded[0]				)[0]
    self.assertEqual(lowerCAmelCase__   ,   lowerCAmelCase__				)

    tokenizer.add_special_tokens({"""bos_token""": """<s>"""}				)
    UpperCamelCase			  =      tokenizer.encode(lowerCAmelCase__   ,   add_special_tokens=lowerCAmelCase__				)
    UpperCamelCase			  =      tokenizer.convert_ids_to_tokens(encoded[1]				)[0]
    self.assertNotEqual(lowerCAmelCase__   ,   lowerCAmelCase__				)

    # Testing spaces after special tokens
    UpperCamelCase			  =      '<mask>'
    tokenizer.add_special_tokens(
        {"""mask_token""": AddedToken(lowerCAmelCase__   ,   lstrip=lowerCAmelCase__   ,   rstrip=lowerCAmelCase__				)}				)  # mask token has a left space
    UpperCamelCase			  =      tokenizer.convert_tokens_to_ids(lowerCAmelCase__				)

    UpperCamelCase			  =      'Encode <mask> sequence'
    UpperCamelCase			  =      'Encode <mask>sequence'

    UpperCamelCase			  =      tokenizer.encode(lowerCAmelCase__				)
    UpperCamelCase			  =      encoded.index(lowerCAmelCase__				)
    UpperCamelCase			  =      tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]				)[0]
    self.assertEqual(lowerCAmelCase__   ,   lowerCAmelCase__				)

    UpperCamelCase			  =      tokenizer.encode(lowerCAmelCase__				)
    UpperCamelCase			  =      encoded.index(lowerCAmelCase__				)
    UpperCamelCase			  =      tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]				)[0]
    self.assertNotEqual(lowerCAmelCase__   ,   lowerCAmelCase__				)







   def 						lowerCamelCase_	(     self						:						List[Any]				):





    """simple docstring"""


    pass







   def 						lowerCamelCase_	(     self						:						Dict				):





    """simple docstring"""


    for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
     with self.subTest(f"""{tokenizer.__class__.__name__} ({pretrained_name})"""				):
      UpperCamelCase			  =      self.rust_tokenizer_class.from_pretrained(lowerCAmelCase__   ,   **lowerCAmelCase__				)
      UpperCamelCase			  =      self.tokenizer_class.from_pretrained(lowerCAmelCase__   ,   **lowerCAmelCase__				)
      UpperCamelCase			  =      'A, <mask> AllenNLP sentence.'
      UpperCamelCase			  =      tokenizer_r.encode_plus(lowerCAmelCase__   ,   add_special_tokens=lowerCAmelCase__   ,   return_token_type_ids=lowerCAmelCase__				)
      UpperCamelCase			  =      tokenizer_p.encode_plus(lowerCAmelCase__   ,   add_special_tokens=lowerCAmelCase__   ,   return_token_type_ids=lowerCAmelCase__				)

      # token_type_ids should put 0 everywhere
      self.assertEqual(sum(tokens_r["""token_type_ids"""]				)   ,   sum(tokens_p["""token_type_ids"""]				)				)

      # attention_mask should put 1 everywhere, so sum over length should be 1
      self.assertEqual(
          sum(tokens_r["""attention_mask"""]				) / len(tokens_r["""attention_mask"""]				)   ,   sum(tokens_p["""attention_mask"""]				) / len(tokens_p["""attention_mask"""]				)   ,   )

      UpperCamelCase			  =      tokenizer_r.convert_ids_to_tokens(tokens_r["""input_ids"""]				)
      UpperCamelCase			  =      tokenizer_p.convert_ids_to_tokens(tokens_p["""input_ids"""]				)

      # Rust correctly handles the space before the mask while python doesnt
      self.assertSequenceEqual(tokens_p["""input_ids"""]   ,   [0, 250, 6, 5_0264, 3823, 487, 2_1992, 3645, 4, 2]				)
      self.assertSequenceEqual(tokens_r["""input_ids"""]   ,   [0, 250, 6, 5_0264, 3823, 487, 2_1992, 3645, 4, 2]				)

      self.assertSequenceEqual(
          lowerCAmelCase__   ,   ["""<s>""", """A""", """,""", """<mask>""", """ĠAllen""", """N""", """LP""", """Ġsentence""", """.""", """</s>"""]				)
      self.assertSequenceEqual(
          lowerCAmelCase__   ,   ["""<s>""", """A""", """,""", """<mask>""", """ĠAllen""", """N""", """LP""", """Ġsentence""", """.""", """</s>"""]				)







   def 						lowerCamelCase_	(     self						:						Optional[Any]				):





    """simple docstring"""


    for trim_offsets, add_prefix_space in itertools.product([True, False]   ,   repeat=2				):
     UpperCamelCase			  =      self.rust_tokenizer_class.from_pretrained(
         self.tmpdirname   ,   use_fast=lowerCAmelCase__   ,   add_prefix_space=lowerCAmelCase__   ,   trim_offsets=lowerCAmelCase__				)

     UpperCamelCase			  =      json.loads(tokenizer_r.backend_tokenizer.pre_tokenizer.__getstate__()				)
     UpperCamelCase			  =      json.loads(tokenizer_r.backend_tokenizer.post_processor.__getstate__()				)

     self.assertEqual(pre_tokenizer_state["""add_prefix_space"""]   ,   lowerCAmelCase__				)

     self.assertEqual(post_processor_state["""add_prefix_space"""]   ,   lowerCAmelCase__				)
     self.assertEqual(post_processor_state["""trim_offsets"""]   ,   lowerCAmelCase__				)







   def 						lowerCamelCase_	(     self						:						Optional[Any]				):





    """simple docstring"""


    for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
     with self.subTest(f"""{tokenizer.__class__.__name__} ({pretrained_name})"""				):
      UpperCamelCase			  =      'hello'  # `hello` is a token in the vocabulary of `pretrained_name`
      UpperCamelCase			  =      f"""{text_of_1_token} {text_of_1_token}"""

      UpperCamelCase			  =      self.rust_tokenizer_class.from_pretrained(
          lowerCAmelCase__   ,   use_fast=lowerCAmelCase__   ,   add_prefix_space=lowerCAmelCase__   ,   trim_offsets=lowerCAmelCase__				)
      UpperCamelCase			  =      tokenizer_r(lowerCAmelCase__   ,   return_offsets_mapping=lowerCAmelCase__   ,   add_special_tokens=lowerCAmelCase__				)
      self.assertEqual(encoding.offset_mapping[0]   ,   (0, len(lowerCAmelCase__				))				)
      self.assertEqual(
          encoding.offset_mapping[1]   ,   (len(lowerCAmelCase__				) + 1, len(lowerCAmelCase__				) + 1 + len(lowerCAmelCase__				))   ,   )

      UpperCamelCase			  =      self.rust_tokenizer_class.from_pretrained(
          lowerCAmelCase__   ,   use_fast=lowerCAmelCase__   ,   add_prefix_space=lowerCAmelCase__   ,   trim_offsets=lowerCAmelCase__				)
      UpperCamelCase			  =      tokenizer_r(lowerCAmelCase__   ,   return_offsets_mapping=lowerCAmelCase__   ,   add_special_tokens=lowerCAmelCase__				)
      self.assertEqual(encoding.offset_mapping[0]   ,   (0, len(lowerCAmelCase__				))				)
      self.assertEqual(
          encoding.offset_mapping[1]   ,   (len(lowerCAmelCase__				) + 1, len(lowerCAmelCase__				) + 1 + len(lowerCAmelCase__				))   ,   )

      UpperCamelCase			  =      self.rust_tokenizer_class.from_pretrained(
          lowerCAmelCase__   ,   use_fast=lowerCAmelCase__   ,   add_prefix_space=lowerCAmelCase__   ,   trim_offsets=lowerCAmelCase__				)
      UpperCamelCase			  =      tokenizer_r(lowerCAmelCase__   ,   return_offsets_mapping=lowerCAmelCase__   ,   add_special_tokens=lowerCAmelCase__				)
      self.assertEqual(encoding.offset_mapping[0]   ,   (0, len(lowerCAmelCase__				))				)
      self.assertEqual(
          encoding.offset_mapping[1]   ,   (len(lowerCAmelCase__				), len(lowerCAmelCase__				) + 1 + len(lowerCAmelCase__				))   ,   )

      UpperCamelCase			  =      self.rust_tokenizer_class.from_pretrained(
          lowerCAmelCase__   ,   use_fast=lowerCAmelCase__   ,   add_prefix_space=lowerCAmelCase__   ,   trim_offsets=lowerCAmelCase__				)
      UpperCamelCase			  =      tokenizer_r(lowerCAmelCase__   ,   return_offsets_mapping=lowerCAmelCase__   ,   add_special_tokens=lowerCAmelCase__				)
      self.assertEqual(encoding.offset_mapping[0]   ,   (0, len(lowerCAmelCase__				))				)
      self.assertEqual(
          encoding.offset_mapping[1]   ,   (len(lowerCAmelCase__				), len(lowerCAmelCase__				) + 1 + len(lowerCAmelCase__				))   ,   )

      UpperCamelCase			  =      f""" {text}"""

      # tokenizer_r = self.rust_tokenizer_class.from_pretrained(
      #     pretrained_name, use_fast=True, add_prefix_space=True, trim_offsets=True
      # )
      # encoding = tokenizer_r(text, return_offsets_mapping=True, add_special_tokens=False)
      # self.assertEqual(encoding.offset_mapping[0], (1, 1 + len(text_of_1_token)))
      # self.assertEqual(
      #     encoding.offset_mapping[1],
      #     (1 + len(text_of_1_token) + 1, 1 + len(text_of_1_token) + 1 + len(text_of_1_token)),
      # )

      UpperCamelCase			  =      self.rust_tokenizer_class.from_pretrained(
          lowerCAmelCase__   ,   use_fast=lowerCAmelCase__   ,   add_prefix_space=lowerCAmelCase__   ,   trim_offsets=lowerCAmelCase__				)
      UpperCamelCase			  =      tokenizer_r(lowerCAmelCase__   ,   return_offsets_mapping=lowerCAmelCase__   ,   add_special_tokens=lowerCAmelCase__				)
      self.assertEqual(encoding.offset_mapping[0]   ,   (1, 1 + len(lowerCAmelCase__				))				)
      self.assertEqual(
          encoding.offset_mapping[1]   ,   (1 + len(lowerCAmelCase__				) + 1, 1 + len(lowerCAmelCase__				) + 1 + len(lowerCAmelCase__				))   ,   )

      UpperCamelCase			  =      self.rust_tokenizer_class.from_pretrained(
          lowerCAmelCase__   ,   use_fast=lowerCAmelCase__   ,   add_prefix_space=lowerCAmelCase__   ,   trim_offsets=lowerCAmelCase__				)
      UpperCamelCase			  =      tokenizer_r(lowerCAmelCase__   ,   return_offsets_mapping=lowerCAmelCase__   ,   add_special_tokens=lowerCAmelCase__				)
      self.assertEqual(encoding.offset_mapping[0]   ,   (0, 1 + len(lowerCAmelCase__				))				)
      self.assertEqual(
          encoding.offset_mapping[1]   ,   (1 + len(lowerCAmelCase__				), 1 + len(lowerCAmelCase__				) + 1 + len(lowerCAmelCase__				))   ,   )

      UpperCamelCase			  =      self.rust_tokenizer_class.from_pretrained(
          lowerCAmelCase__   ,   use_fast=lowerCAmelCase__   ,   add_prefix_space=lowerCAmelCase__   ,   trim_offsets=lowerCAmelCase__				)
      UpperCamelCase			  =      tokenizer_r(lowerCAmelCase__   ,   return_offsets_mapping=lowerCAmelCase__   ,   add_special_tokens=lowerCAmelCase__				)
      self.assertEqual(encoding.offset_mapping[0]   ,   (0, 1 + len(lowerCAmelCase__				))				)
      self.assertEqual(
          encoding.offset_mapping[1]   ,   (1 + len(lowerCAmelCase__				), 1 + len(lowerCAmelCase__				) + 1 + len(lowerCAmelCase__				))   ,   )




import numpy as np
import torch
from imwatermark import WatermarkEncoder


# Copied from https://github.com/Stability-AI/generative-models/blob/613af104c6b85184091d42d374fef420eddb356d/scripts/demo/streamlit_helpers.py#L66
lowerCAmelCase__			:      Optional[int]								=0B1011_0011_1110_1100_1001_0000_0111_1011_1011_0001_1001_1110
# bin(x)[2:] gives bits of x as str, use int to convert them to 0/1
lowerCAmelCase__			:      str								=[int(bit) for bit in bin(WATERMARK_MESSAGE)[2:]]







class 	__lowercase    :





							"""simple docstring"""







							def __init__(      self       ):





										"""simple docstring"""




										SCREAMING_SNAKE_CASE_		:     List[Any]					=					WATERMARK_BITS
										SCREAMING_SNAKE_CASE_		:     int					=					WatermarkEncoder()

										self.encoder.set_watermark('bits'			,						self.watermark       )






							def 					UpperCamelCase__     (      self			,						lowerCAmelCase__       ):





										"""simple docstring"""




										if images.shape[-1] < 2_5_6:
													return images

										SCREAMING_SNAKE_CASE_		:     Tuple					=					(2_5_5 * (images / 2 + 0.5)).cpu().permute(0			,						2			,						3			,						1       ).float().numpy()

										SCREAMING_SNAKE_CASE_		:     Optional[int]					=					[self.encoder.encode(lowerCAmelCase__			,						'dwtDct'       ) for image in images]

										SCREAMING_SNAKE_CASE_		:     List[str]					=					torch.from_numpy(np.array(lowerCAmelCase__       )       ).permute(0			,						3			,						1			,						2       )

										SCREAMING_SNAKE_CASE_		:     Union[str, Any]					=					torch.clamp(2 * (images / 2_5_5 - 0.5)			,						min=-1.0			,						max=1.0       )
										return images





