


"""simple docstring"""

import json
import os
from functools import lru_cache
from typing import Dict, List, Optional, Tuple, Union

import regex as re

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding, EncodedInput
from ...utils import PaddingStrategy, logging


UpperCAmelCase__					=logging.get_logger(__name__)


UpperCAmelCase__					={"vocab_file": "vocab.json", "merges_file": "merges.txt"}

# See all LED models at https://huggingface.co/models?filter=LED
UpperCAmelCase__					={
    "vocab_file": {
        "allenai/led-base-16384": "https://huggingface.co/allenai/led-base-16384/resolve/main/vocab.json",
    },
    "merges_file": {
        "allenai/led-base-16384": "https://huggingface.co/allenai/led-base-16384/resolve/main/merges.txt",
    },
    "tokenizer_file": {
        "allenai/led-base-16384": "https://huggingface.co/allenai/led-base-16384/resolve/main/tokenizer.json",
    },
}

UpperCAmelCase__					={
    "allenai/led-base-16384": 1_6384,
}


@lru_cache()
# Copied from transformers.models.bart.tokenization_bart.bytes_to_unicode
def lowerCAmelCase_   (					):






 """simple docstring"""







 __lowercase						=						(
     list(range(ord("""!"""			)					, ord("""~"""			) + 1			)			) + list(range(ord("""¡"""			)					, ord("""¬"""			) + 1			)			) + list(range(ord("""®"""			)					, ord("""ÿ"""			) + 1			)			)
 )
 __lowercase						=						bs[:]
 __lowercase						=						0
 for b in range(2**8			):
  if b not in bs:
   bs.append(UpperCamelCase__			)
   cs.append(2**8 + n			)
   n += 1
 __lowercase						=						[chr(UpperCamelCase__			) for n in cs]
 return dict(zip(UpperCamelCase__					, UpperCamelCase__			)			)


def lowerCAmelCase_   (					UpperCamelCase__						:			Union[str, Any]			):






 """simple docstring"""







 __lowercase						=						set()
 __lowercase						=						word[0]
 for char in word[1:]:
  pairs.add((prev_char, char)			)
  __lowercase						=						char
 return pairs





class  lowerCamelCase__    (		_a     ):
      a			:  int           =		VOCAB_FILES_NAMES
      a			:  Optional[int]           =		PRETRAINED_VOCAB_FILES_MAP
      a			:  List[Any]           =		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      a			:  Dict           =		["""input_ids""", """attention_mask"""]
      def __init__(		self						:						Union[str, Any]   ,							A_						:						Any   ,							A_						:						Dict   ,							A_						:						str="replace"   ,							A_						:						Optional[Any]="<s>"   ,							A_						:						Optional[int]="</s>"   ,							A_						:						int="</s>"   ,							A_						:						Union[str, Any]="<s>"   ,							A_						:						Any="<unk>"   ,							A_						:						str="<pad>"   ,							A_						:						str="<mask>"   ,							A_						:						int=False   ,							**A_						:						Any   ,							):






       '''simple docstring'''


       __lowercase						=						AddedToken(A_   ,							lstrip=A_   ,							rstrip=A_				) if isinstance(A_   ,							A_				) else bos_token
       __lowercase						=						AddedToken(A_   ,							lstrip=A_   ,							rstrip=A_				) if isinstance(A_   ,							A_				) else eos_token
       __lowercase						=						AddedToken(A_   ,							lstrip=A_   ,							rstrip=A_				) if isinstance(A_   ,							A_				) else sep_token
       __lowercase						=						AddedToken(A_   ,							lstrip=A_   ,							rstrip=A_				) if isinstance(A_   ,							A_				) else cls_token
       __lowercase						=						AddedToken(A_   ,							lstrip=A_   ,							rstrip=A_				) if isinstance(A_   ,							A_				) else unk_token
       __lowercase						=						AddedToken(A_   ,							lstrip=A_   ,							rstrip=A_				) if isinstance(A_   ,							A_				) else pad_token

       # Mask token behave like a normal word, i.e. include the space before it
       __lowercase						=						AddedToken(A_   ,							lstrip=A_   ,							rstrip=A_				) if isinstance(A_   ,							A_				) else mask_token

       super().__init__(
           errors=A_   ,							bos_token=A_   ,							eos_token=A_   ,							unk_token=A_   ,							sep_token=A_   ,							cls_token=A_   ,							pad_token=A_   ,							mask_token=A_   ,							add_prefix_space=A_   ,							**A_   ,							)

       with open(A_   ,							encoding="""utf-8"""				) as vocab_handle:
        __lowercase						=						json.load(A_				)
       __lowercase						=						{v: k for k, v in self.encoder.items()}
       __lowercase						=						errors  # how to handle errors in decoding
       __lowercase						=						bytes_to_unicode()
       __lowercase						=						{v: k for k, v in self.byte_encoder.items()}
       with open(A_   ,							encoding="""utf-8"""				) as merges_handle:
        __lowercase						=						merges_handle.read().split("""\n"""				)[1:-1]
       __lowercase						=						[tuple(merge.split()				) for merge in bpe_merges]
       __lowercase						=						dict(zip(A_   ,							range(len(A_				)				)				)				)
       __lowercase						=						{}
       __lowercase						=						add_prefix_space

       # Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
       __lowercase						=						re.compile(r"""'s|'t|'re|'ve|'m|'ll|'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+"""				)
      @property
      # Copied from transformers.models.bart.tokenization_bart.BartTokenizer.vocab_size
      def SCREAMING_SNAKE_CASE_						(		self						:						List[str]				):






       '''simple docstring'''


       return len(self.encoder				)
      def SCREAMING_SNAKE_CASE_						(		self						:						List[Any]				):






       '''simple docstring'''


       return dict(self.encoder   ,							**self.added_tokens_encoder				)
      def SCREAMING_SNAKE_CASE_						(		self						:						List[str]   ,							A_						:						Optional[int]				):






       '''simple docstring'''


       if token in self.cache:
        return self.cache[token]
       __lowercase						=						tuple(A_				)
       __lowercase						=						get_pairs(A_				)

       if not pairs:
        return token

       while True:
        __lowercase						=						min(A_   ,							key=lambda A_				: self.bpe_ranks.get(A_   ,							float("""inf"""				)				)				)
        if bigram not in self.bpe_ranks:
         break
        __lowercase				,		__lowercase						=						bigram
        __lowercase						=						[]
        __lowercase						=						0
        while i < len(A_				):
         try:
          __lowercase						=						word.index(A_   ,							A_				)
         except ValueError:
          new_word.extend(word[i:]				)
          break
         else:
          new_word.extend(word[i:j]				)
          __lowercase						=						j

         if word[i] == first and i < len(A_				) - 1 and word[i + 1] == second:
          new_word.append(first + second				)
          i += 2
         else:
          new_word.append(word[i]				)
          i += 1
        __lowercase						=						tuple(A_				)
        __lowercase						=						new_word
        if len(A_				) == 1:
         break
        else:
         __lowercase						=						get_pairs(A_				)
       __lowercase						=						""" """.join(A_				)
       __lowercase						=						word
       return word
      def SCREAMING_SNAKE_CASE_						(		self						:						Any   ,							A_						:						List[str]				):






       '''simple docstring'''


       __lowercase						=						[]
       for token in re.findall(self.pat   ,							A_				):
        __lowercase						=						"""""".join(
            self.byte_encoder[b] for b in token.encode("""utf-8"""				)				)  # Maps all our bytes to unicode strings, avoiding control tokens of the BPE (spaces in our case)
        bpe_tokens.extend(bpe_token for bpe_token in self.bpe(A_				).split(""" """				)				)
       return bpe_tokens
      def SCREAMING_SNAKE_CASE_						(		self						:						Optional[int]   ,							A_						:						Union[str, Any]				):






       '''simple docstring'''


       return self.encoder.get(A_   ,							self.encoder.get(self.unk_token				)				)
      def SCREAMING_SNAKE_CASE_						(		self						:						int   ,							A_						:						Any				):






       '''simple docstring'''


       return self.decoder.get(A_				)
      def SCREAMING_SNAKE_CASE_						(		self						:						List[Any]   ,							A_						:						Tuple				):






       '''simple docstring'''


       __lowercase						=						"""""".join(A_				)
       __lowercase						=						bytearray([self.byte_decoder[c] for c in text]				).decode("""utf-8"""   ,							errors=self.errors				)
       return text
      def SCREAMING_SNAKE_CASE_						(		self						:						Optional[int]   ,							A_						:						str   ,							A_						:						Optional[str] = None				):






       '''simple docstring'''


       if not os.path.isdir(A_				):
        logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''				)
        return
       __lowercase						=						os.path.join(
           A_   ,							(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]				)
       __lowercase						=						os.path.join(
           A_   ,							(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""merges_file"""]				)

       with open(A_   ,							"""w"""   ,							encoding="""utf-8"""				) as f:
        f.write(json.dumps(self.encoder   ,							indent=2   ,							sort_keys=A_   ,							ensure_ascii=A_				) + """\n"""				)

       __lowercase						=						0
       with open(A_   ,							"""w"""   ,							encoding="""utf-8"""				) as writer:
        writer.write("""#version: 0.2\n"""				)
        for bpe_tokens, token_index in sorted(self.bpe_ranks.items()   ,							key=lambda A_				: kv[1]				):
         if index != token_index:
          logger.warning(
              F'''Saving vocabulary to {merge_file}: BPE merge indices are not consecutive.'''
              """ Please check that the tokenizer is not corrupted!"""				)
          __lowercase						=						token_index
         writer.write(""" """.join(A_				) + """\n"""				)
         index += 1

       return vocab_file, merge_file
      def SCREAMING_SNAKE_CASE_						(		self						:						Union[str, Any]   ,							A_						:						List[int]   ,							A_						:						Optional[List[int]] = None				):






       '''simple docstring'''


       if token_ids_a is None:
        return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
       __lowercase						=						[self.cls_token_id]
       __lowercase						=						[self.sep_token_id]
       return cls + token_ids_a + sep + sep + token_ids_a + sep
      def SCREAMING_SNAKE_CASE_						(		self						:						Tuple   ,							A_						:						List[int]   ,							A_						:						Optional[List[int]] = None   ,							A_						:						bool = False				):






       '''simple docstring'''


       if already_has_special_tokens:
        return super().get_special_tokens_mask(
            token_ids_a=A_   ,							token_ids_a=A_   ,							already_has_special_tokens=A_				)

       if token_ids_a is None:
        return [1] + ([0] * len(A_				)) + [1]
       return [1] + ([0] * len(A_				)) + [1, 1] + ([0] * len(A_				)) + [1]
      def SCREAMING_SNAKE_CASE_						(		self						:						Optional[int]   ,							A_						:						List[int]   ,							A_						:						Optional[List[int]] = None				):






       '''simple docstring'''


       __lowercase						=						[self.sep_token_id]
       __lowercase						=						[self.cls_token_id]

       if token_ids_a is None:
        return len(cls + token_ids_a + sep				) * [0]
       return len(cls + token_ids_a + sep + sep + token_ids_a + sep				) * [0]
      def SCREAMING_SNAKE_CASE_						(		self						:						Optional[Any]   ,							A_						:						List[str]   ,							A_						:						Optional[int]=False   ,							**A_						:						Union[str, Any]				):






       '''simple docstring'''


       __lowercase						=						kwargs.pop("""add_prefix_space"""   ,							self.add_prefix_space				)
       if (is_split_into_words or add_prefix_space) and (len(A_				) > 0 and not text[0].isspace()):
        __lowercase						=						""" """ + text
       return (text, kwargs)






      def SCREAMING_SNAKE_CASE_						(		self						:						Tuple   ,							A_						:						Union[Dict[str, EncodedInput], BatchEncoding]   ,							A_						:						Optional[int] = None   ,							A_						:						PaddingStrategy = PaddingStrategy.DO_NOT_PAD   ,							A_						:						Optional[int] = None   ,							A_						:						Optional[bool] = None   ,							):






       '''simple docstring'''


       __lowercase						=						super()._pad(
           encoded_inputs=A_   ,							max_length=A_   ,							padding_strategy=A_   ,							pad_to_multiple_of=A_   ,							return_attention_mask=A_   ,							)

       # Load from model defaults
       if return_attention_mask is None:
        __lowercase						=						"""attention_mask""" in self.model_input_names

       if return_attention_mask and "global_attention_mask" in encoded_inputs:
        __lowercase						=						encoded_inputs[self.model_input_names[0]]
        # `global_attention_mask` need to have the same length as other (sequential) inputs.
        __lowercase						=						len(encoded_inputs["""global_attention_mask"""]				) != len(A_				)

        if needs_to_be_padded:
         __lowercase						=						len(A_				) - len(encoded_inputs["""global_attention_mask"""]				)

         if self.padding_side == "right":
          # Use `-1` since `0` in `global_attention_mask` means `local attention` instead of `not to attend`
          __lowercase						=						(
              encoded_inputs["""global_attention_mask"""] + [-1] * difference
          )
         elif self.padding_side == "left":
          __lowercase						=						[-1] * difference + encoded_inputs[
              """global_attention_mask"""
          ]
         else:
          raise ValueError("""Invalid padding strategy:""" + str(self.padding_side				)				)

       return encoded_inputs




"""simple docstring"""

import os
import re
import shutil
import sys
import tempfile
import unittest

import black


UpperCAmelCase__					=os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, "utils"))

import check_copies  # noqa: E402


# This is the reference code that will be used in the tests.
# If DDPMSchedulerOutput is changed in scheduling_ddpm.py, this code needs to be manually updated.
UpperCAmelCase__					="    \"\"\"\n    Output class for the scheduler's step function output.\n\n    Args:\n        prev_sample (`torch.FloatTensor` of shape `(batch_size, num_channels, height, width)` for images):\n            Computed sample (x_{t-1}) of previous timestep. `prev_sample` should be used as next model input in the\n            denoising loop.\n        pred_original_sample (`torch.FloatTensor` of shape `(batch_size, num_channels, height, width)` for images):\n            The predicted denoised sample (x_{0}) based on the model output from the current timestep.\n            `pred_original_sample` can be used to preview progress or for guidance.\n    \"\"\"\n\n    prev_sample: torch.FloatTensor\n    pred_original_sample: Optional[torch.FloatTensor] = None\n"





class  lowerCamelCase__    (		unittest.TestCase     ):
      def SCREAMING_SNAKE_CASE_						(		self						:						int				):






       '''simple docstring'''


       __lowercase						=						tempfile.mkdtemp()
       os.makedirs(os.path.join(self.diffusers_dir   ,							"""schedulers/"""				)				)
       __lowercase						=						self.diffusers_dir
       shutil.copy(
           os.path.join(A_   ,							"""src/diffusers/schedulers/scheduling_ddpm.py"""				)   ,							os.path.join(self.diffusers_dir   ,							"""schedulers/scheduling_ddpm.py"""				)   ,							)
      def SCREAMING_SNAKE_CASE_						(		self						:						str				):






       '''simple docstring'''


       __lowercase						=						"""src/diffusers"""
       shutil.rmtree(self.diffusers_dir				)
      def SCREAMING_SNAKE_CASE_						(		self						:						Optional[int]   ,							A_						:						List[str]   ,							A_						:						int   ,							A_						:						Optional[Any]   ,							A_						:						str=None				):






       '''simple docstring'''


       __lowercase						=						comment + F'''\nclass {class_name}(nn.Module):\n''' + class_code
       if overwrite_result is not None:
        __lowercase						=						comment + F'''\nclass {class_name}(nn.Module):\n''' + overwrite_result
       __lowercase						=						black.Mode(target_versions={black.TargetVersion.PYaa}   ,							line_length=1_1_9				)
       __lowercase						=						black.format_str(A_   ,							mode=A_				)
       __lowercase						=						os.path.join(self.diffusers_dir   ,							"""new_code.py"""				)
       with open(A_   ,							"""w"""   ,							newline="""\n"""				) as f:
        f.write(A_				)
       if overwrite_result is None:
        self.assertTrue(len(check_copies.is_copy_consistent(A_				)				) == 0				)
       else:
        check_copies.is_copy_consistent(f.name   ,							overwrite=A_				)
        with open(A_   ,							"""r"""				) as f:
         self.assertTrue(f.read()   ,							A_				)
      def SCREAMING_SNAKE_CASE_						(		self						:						str				):






       '''simple docstring'''


       __lowercase						=						check_copies.find_code_in_diffusers("""schedulers.scheduling_ddpm.DDPMSchedulerOutput"""				)
       self.assertEqual(A_   ,							A_				)






      def SCREAMING_SNAKE_CASE_						(		self						:						Dict				):






       '''simple docstring'''


       self.check_copy_consistency(
           """# Copied from diffusers.schedulers.scheduling_ddpm.DDPMSchedulerOutput"""   ,							"""DDPMSchedulerOutput"""   ,							REFERENCE_CODE + """\n"""   ,							)

       # With no empty line at the end
       self.check_copy_consistency(
           """# Copied from diffusers.schedulers.scheduling_ddpm.DDPMSchedulerOutput"""   ,							"""DDPMSchedulerOutput"""   ,							A_   ,							)

       # Copy consistency with rename
       self.check_copy_consistency(
           """# Copied from diffusers.schedulers.scheduling_ddpm.DDPMSchedulerOutput with DDPM->Test"""   ,							"""TestSchedulerOutput"""   ,							re.sub("""DDPM"""   ,							"""Test"""   ,							A_				)   ,							)

       # Copy consistency with a really long name
       __lowercase						=						"""TestClassWithAReallyLongNameBecauseSomePeopleLikeThatForSomeReason"""
       self.check_copy_consistency(
           F'''# Copied from diffusers.schedulers.scheduling_ddpm.DDPMSchedulerOutput with DDPM->{long_class_name}'''   ,							F'''{long_class_name}SchedulerOutput'''   ,							re.sub("""Bert"""   ,							A_   ,							A_				)   ,							)

       # Copy consistency with overwrite
       self.check_copy_consistency(
           """# Copied from diffusers.schedulers.scheduling_ddpm.DDPMSchedulerOutput with DDPM->Test"""   ,							"""TestSchedulerOutput"""   ,							A_   ,							overwrite_result=re.sub("""DDPM"""   ,							"""Test"""   ,							A_				)   ,							)
