
import os
import unittest

from transformers import BatchEncoding
from transformers.models.bert.tokenization_bert import (
    BasicTokenizer,
    WordpieceTokenizer,
    _is_control,
    _is_punctuation,
    _is_whitespace,
)
from transformers.models.prophetnet.tokenization_prophetnet import VOCAB_FILES_NAMES, ProphetNetTokenizer
from transformers.testing_utils import require_torch, slow

from ...test_tokenization_common import TokenizerTesterMixin



class       _snake_case   (	UpperCAmelCase_  ,						unittest.TestCase							):
	__lowerCAmelCase  :     Optional[Any]        =			ProphetNetTokenizer
	__lowerCAmelCase  :     Union[str, Any]        =			False


	def      lowercase__     (					self):


			'''simple docstring'''




			super().setUp()

			lowercase__  :   Tuple    		=      [
			    """[UNK]""",
			    """[CLS]""",
			    """[SEP]""",
			    """[PAD]""",
			    """[MASK]""",
			    """want""",
			    """##want""",
			    """##ed""",
			    """wa""",
			    """un""",
			    """runn""",
			    """##ing""",
			    """,""",
			    """low""",
			    """lowest""",
			]
			lowercase__  :   Optional[Any]    		=      os.path.join(self.tmpdirname					,  VOCAB_FILES_NAMES["""vocab_file"""])
			with open(self.vocab_file					,  """w"""					,  encoding="""utf-8""") as vocab_writer:
					vocab_writer.write("""""".join([x + """\n""" for x in vocab_tokens]))


	def      lowercase__     (					self					,  SCREAMING_SNAKE_CASE_):


			'''simple docstring'''




			lowercase__  :   List[Any]    		=      """UNwant\u00E9d,running"""
			lowercase__  :   Tuple    		=      """unwanted, running"""
			return input_text, output_text


	def      lowercase__     (					self):


			'''simple docstring'''




			lowercase__  :   Union[str, Any]    		=      self.tokenizer_class(self.vocab_file)

			lowercase__  :   Dict    		=      tokenizer.tokenize("""UNwant\u00E9d,running""")
			self.assertListEqual(SCREAMING_SNAKE_CASE_					,  ["""un""", """##want""", """##ed""", """,""", """runn""", """##ing"""])
			self.assertListEqual(tokenizer.convert_tokens_to_ids(SCREAMING_SNAKE_CASE_)					,  [9, 6, 7, 12, 10, 11])


	def      lowercase__     (					self):


			'''simple docstring'''




			lowercase__  :   Any    		=      BasicTokenizer()

			self.assertListEqual(tokenizer.tokenize("""ah\u535A\u63A8zz""")					,  ["""ah""", """\u535A""", """\u63A8""", """zz"""])


	def      lowercase__     (					self):


			'''simple docstring'''




			lowercase__  :   Union[str, Any]    		=      BasicTokenizer(do_lower_case=SCREAMING_SNAKE_CASE_)

			self.assertListEqual(
			    tokenizer.tokenize(""" \tHeLLo!how  \n Are yoU?  """)					,  ["""hello""", """!""", """how""", """are""", """you""", """?"""])
			self.assertListEqual(tokenizer.tokenize("""H\u00E9llo""")					,  ["""hello"""])


	def      lowercase__     (					self):


			'''simple docstring'''




			lowercase__  :   Union[str, Any]    		=      BasicTokenizer(do_lower_case=SCREAMING_SNAKE_CASE_					,  strip_accents=SCREAMING_SNAKE_CASE_)

			self.assertListEqual(
			    tokenizer.tokenize(""" \tHäLLo!how  \n Are yoU?  """)					,  ["""hällo""", """!""", """how""", """are""", """you""", """?"""])
			self.assertListEqual(tokenizer.tokenize("""H\u00E9llo""")					,  ["""h\u00E9llo"""])


	def      lowercase__     (					self):


			'''simple docstring'''




			lowercase__  :   Any    		=      BasicTokenizer(do_lower_case=SCREAMING_SNAKE_CASE_					,  strip_accents=SCREAMING_SNAKE_CASE_)

			self.assertListEqual(
			    tokenizer.tokenize(""" \tHäLLo!how  \n Are yoU?  """)					,  ["""hallo""", """!""", """how""", """are""", """you""", """?"""])
			self.assertListEqual(tokenizer.tokenize("""H\u00E9llo""")					,  ["""hello"""])


	def      lowercase__     (					self):


			'''simple docstring'''




			lowercase__  :   Optional[Any]    		=      BasicTokenizer(do_lower_case=SCREAMING_SNAKE_CASE_)

			self.assertListEqual(
			    tokenizer.tokenize(""" \tHäLLo!how  \n Are yoU?  """)					,  ["""hallo""", """!""", """how""", """are""", """you""", """?"""])
			self.assertListEqual(tokenizer.tokenize("""H\u00E9llo""")					,  ["""hello"""])


	def      lowercase__     (					self):


			'''simple docstring'''




			lowercase__  :   Dict    		=      BasicTokenizer(do_lower_case=SCREAMING_SNAKE_CASE_)

			self.assertListEqual(
			    tokenizer.tokenize(""" \tHeLLo!how  \n Are yoU?  """)					,  ["""HeLLo""", """!""", """how""", """Are""", """yoU""", """?"""])


	def      lowercase__     (					self):


			'''simple docstring'''




			lowercase__  :   Optional[int]    		=      BasicTokenizer(do_lower_case=SCREAMING_SNAKE_CASE_					,  strip_accents=SCREAMING_SNAKE_CASE_)

			self.assertListEqual(
			    tokenizer.tokenize(""" \tHäLLo!how  \n Are yoU?  """)					,  ["""HäLLo""", """!""", """how""", """Are""", """yoU""", """?"""])


	def      lowercase__     (					self):


			'''simple docstring'''




			lowercase__  :   str    		=      BasicTokenizer(do_lower_case=SCREAMING_SNAKE_CASE_					,  strip_accents=SCREAMING_SNAKE_CASE_)

			self.assertListEqual(
			    tokenizer.tokenize(""" \tHäLLo!how  \n Are yoU?  """)					,  ["""HaLLo""", """!""", """how""", """Are""", """yoU""", """?"""])


	def      lowercase__     (					self):


			'''simple docstring'''




			lowercase__  :   Tuple    		=      BasicTokenizer(do_lower_case=SCREAMING_SNAKE_CASE_					,  never_split=["""[UNK]"""])

			self.assertListEqual(
			    tokenizer.tokenize(""" \tHeLLo!how  \n Are yoU? [UNK]""")					,  ["""HeLLo""", """!""", """how""", """Are""", """yoU""", """?""", """[UNK]"""])


	def      lowercase__     (					self):


			'''simple docstring'''




			lowercase__  :   Optional[Any]    		=      ["""[UNK]""", """[CLS]""", """[SEP]""", """want""", """##want""", """##ed""", """wa""", """un""", """runn""", """##ing"""]

			lowercase__  :   List[str]    		=      {}
			for i, token in enumerate(SCREAMING_SNAKE_CASE_):
					lowercase__  :   Union[str, Any]    		=      i
			lowercase__  :   Optional[Any]    		=      WordpieceTokenizer(vocab=SCREAMING_SNAKE_CASE_					,  unk_token="""[UNK]""")

			self.assertListEqual(tokenizer.tokenize("""""")					,  [])

			self.assertListEqual(tokenizer.tokenize("""unwanted running""")					,  ["""un""", """##want""", """##ed""", """runn""", """##ing"""])

			self.assertListEqual(tokenizer.tokenize("""unwantedX running""")					,  ["""[UNK]""", """runn""", """##ing"""])


	@require_torch
	def      lowercase__     (					self):


			'''simple docstring'''




			lowercase__  :   List[Any]    		=      self.tokenizer_class.from_pretrained("""microsoft/prophetnet-large-uncased""")

			lowercase__  :   Optional[int]    		=      ["""A long paragraph for summarization.""", """Another paragraph for summarization."""]
			lowercase__  :   Tuple    		=      [10_37, 21_46, 2_04_23, 20_05, 76_80, 78_49, 39_89, 10_12, 1_02]
			lowercase__  :   Union[str, Any]    		=      tokenizer(SCREAMING_SNAKE_CASE_					,  padding=SCREAMING_SNAKE_CASE_					,  return_tensors="""pt""")
			self.assertIsInstance(SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_)
			lowercase__  :   int    		=      list(batch.input_ids.numpy()[0])
			self.assertListEqual(SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_)

			self.assertEqual((2, 9)					,  batch.input_ids.shape)
			self.assertEqual((2, 9)					,  batch.attention_mask.shape)


	def      lowercase__     (					self):


			'''simple docstring'''




			self.assertTrue(_is_whitespace(""" """))
			self.assertTrue(_is_whitespace("""\t"""))
			self.assertTrue(_is_whitespace("""\r"""))
			self.assertTrue(_is_whitespace("""\n"""))
			self.assertTrue(_is_whitespace("""\u00A0"""))

			self.assertFalse(_is_whitespace("""A"""))
			self.assertFalse(_is_whitespace("""-"""))


	def      lowercase__     (					self):


			'''simple docstring'''




			self.assertTrue(_is_control("""\u0005"""))

			self.assertFalse(_is_control("""A"""))
			self.assertFalse(_is_control(""" """))
			self.assertFalse(_is_control("""\t"""))
			self.assertFalse(_is_control("""\r"""))


	def      lowercase__     (					self):


			'''simple docstring'''




			self.assertTrue(_is_punctuation("""-"""))
			self.assertTrue(_is_punctuation("""$"""))
			self.assertTrue(_is_punctuation("""`"""))
			self.assertTrue(_is_punctuation("""."""))

			self.assertFalse(_is_punctuation("""A"""))
			self.assertFalse(_is_punctuation(""" """))



	@slow
	def      lowercase__     (					self):


			'''simple docstring'''




			lowercase__  :   Any    		=      self.tokenizer_class.from_pretrained("""microsoft/prophetnet-large-uncased""")

			lowercase__  :   List[Any]    		=      tokenizer.encode("""sequence builders"""					,  add_special_tokens=SCREAMING_SNAKE_CASE_)
			lowercase__  :   List[str]    		=      tokenizer.encode("""multi-sequence build"""					,  add_special_tokens=SCREAMING_SNAKE_CASE_)

			lowercase__  :   List[Any]    		=      tokenizer.build_inputs_with_special_tokens(SCREAMING_SNAKE_CASE_)
			lowercase__  :   Optional[int]    		=      tokenizer.build_inputs_with_special_tokens(SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_)

			assert encoded_sentence == text + [1_02]
			assert encoded_pair == text + [1_02] + text_a + [1_02]








from dataclasses import dataclass
from typing import Optional, Tuple, Union

import numpy as np
import torch

from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin



@dataclass
class       _snake_case   (	UpperCAmelCase_							):
 __lowerCAmelCase  :     torch.FloatTensor
 __lowerCAmelCase  :     torch.FloatTensor
 __lowerCAmelCase  :     Optional[torch.FloatTensor]        =			None



class       _snake_case   (	UpperCAmelCase_  ,						UpperCAmelCase_							):
 __lowerCAmelCase  :     Union[str, Any]        =			2


 @register_to_config
 def __init__(					self					,  SCREAMING_SNAKE_CASE_ = 0.0_2					,  SCREAMING_SNAKE_CASE_ = 1_00					,  SCREAMING_SNAKE_CASE_ = 1.0_0_7					,  SCREAMING_SNAKE_CASE_ = 80					,  SCREAMING_SNAKE_CASE_ = 0.0_5					,  SCREAMING_SNAKE_CASE_ = 50					,  ):


   '''simple docstring'''




   lowercase__  :   List[Any]    		=      sigma_max

   # setable values
   lowercase__  :   int    		=      None
   lowercase__  :   np.IntTensor    		=      None
   lowercase__  :   torch.FloatTensor    		=      None  # sigma(t_i)


 def      lowercase__     (					self					,  SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_ = None):


   '''simple docstring'''




   return sample


 def      lowercase__     (					self					,  SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_ = None):


   '''simple docstring'''




   lowercase__  :   Dict    		=      num_inference_steps
   lowercase__  :   List[Any]    		=      np.arange(0					,  self.num_inference_steps)[::-1].copy()
   lowercase__  :   Optional[Any]    		=      torch.from_numpy(SCREAMING_SNAKE_CASE_).to(SCREAMING_SNAKE_CASE_)
   lowercase__  :   str    		=      [
       (
           self.config.sigma_max**2
           * (self.config.sigma_min**2 / self.config.sigma_max**2) ** (i / (num_inference_steps - 1))
       )
       for i in self.timesteps
   ]
   lowercase__  :   int    		=      torch.tensor(SCREAMING_SNAKE_CASE_					,  dtype=torch.floataa					,  device=SCREAMING_SNAKE_CASE_)


 def      lowercase__     (					self					,  SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_ = None):


   '''simple docstring'''




   if self.config.s_min <= sigma <= self.config.s_max:
     lowercase__  :   Optional[Any]    		=      min(self.config.s_churn / self.num_inference_steps					,  2**0.5 - 1)
   else:
     lowercase__  :   Tuple    		=      0

   # sample eps ~ N(0, S_noise^2 * I)
   lowercase__  :   Dict    		=      self.config.s_noise * randn_tensor(sample.shape					,  generator=SCREAMING_SNAKE_CASE_).to(sample.device)
   lowercase__  :   int    		=      sigma + gamma * sigma
   lowercase__  :   Optional[int]    		=      sample + ((sigma_hat**2 - sigma**2) ** 0.5 * eps)

   return sample_hat, sigma_hat


 def      lowercase__     (					self					,  SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_ = True					,  ):


   '''simple docstring'''




   lowercase__  :   str    		=      sample_hat + sigma_hat * model_output
   lowercase__  :   str    		=      (sample_hat - pred_original_sample) / sigma_hat
   lowercase__  :   Optional[Any]    		=      sample_hat + (sigma_prev - sigma_hat) * derivative

   if not return_dict:
     return (sample_prev, derivative)

   return KarrasVeOutput(
       prev_sample=SCREAMING_SNAKE_CASE_					,  derivative=SCREAMING_SNAKE_CASE_					,  pred_original_sample=SCREAMING_SNAKE_CASE_)


 def      lowercase__     (					self					,  SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_ = True					,  ):


   '''simple docstring'''




   lowercase__  :   str    		=      sample_prev + sigma_prev * model_output
   lowercase__  :   Dict    		=      (sample_prev - pred_original_sample) / sigma_prev
   lowercase__  :   Optional[int]    		=      sample_hat + (sigma_prev - sigma_hat) * (0.5 * derivative + 0.5 * derivative_corr)

   if not return_dict:
     return (sample_prev, derivative)

   return KarrasVeOutput(
       prev_sample=SCREAMING_SNAKE_CASE_					,  derivative=SCREAMING_SNAKE_CASE_					,  pred_original_sample=SCREAMING_SNAKE_CASE_)



 def      lowercase__     (					self					,  SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   raise NotImplementedError()






