



"""simple docstring"""
import json
import os
import unittest

from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES, XLMTokenizer
from transformers.testing_utils import slow

from ...test_tokenization_common import TokenizerTesterMixin


class    SCREAMING_SNAKE_CASE__ (							__UpperCAmelCase      ,  unittest.TestCase   ):
    lowercase__      =   XLMTokenizer
    lowercase__      =   False

    def 					_UpperCAmelCase	(				self			:				Any):







      """simple docstring"""







      super().setUp()

      # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
      lowercase_								= [
          """l""",
          """o""",
          """w""",
          """e""",
          """r""",
          """s""",
          """t""",
          """i""",
          """d""",
          """n""",
          """w</w>""",
          """r</w>""",
          """t</w>""",
          """lo""",
          """low""",
          """er</w>""",
          """low</w>""",
          """lowest</w>""",
          """newer</w>""",
          """wider</w>""",
          """<unk>""",
      ]
      lowercase_								= dict(zip(lowerCAmelCase_ ,  range(len(lowerCAmelCase_))))
      lowercase_								= ["""l o 123""", """lo w 1456""", """e r</w> 1789""", """"""]

      lowercase_								= os.path.join(self.tmpdirname ,  VOCAB_FILES_NAMES["""vocab_file"""])
      lowercase_								= os.path.join(self.tmpdirname ,  VOCAB_FILES_NAMES["""merges_file"""])
      with open(self.vocab_file ,  """w""") as fp:
        fp.write(json.dumps(lowerCAmelCase_))
      with open(self.merges_file ,  """w""") as fp:
        fp.write("""\n""".join(lowerCAmelCase_))

    def 					_UpperCAmelCase	(				self			:				Optional[int] ,  lowerCAmelCase_			:				Optional[Any]):







      """simple docstring"""







      lowercase_								= """lower newer"""
      lowercase_								= """lower newer"""
      return input_text, output_text

    def 					_UpperCAmelCase	(				self			:				Any):







      """simple docstring"""







      lowercase_								= XLMTokenizer(self.vocab_file ,  self.merges_file)

      lowercase_								= """lower"""
      lowercase_								= ["""low""", """er</w>"""]
      lowercase_								= tokenizer.tokenize(lowerCAmelCase_)
      self.assertListEqual(lowerCAmelCase_ ,  lowerCAmelCase_)

      lowercase_								= tokens + ["""<unk>"""]
      lowercase_								= [1_4, 1_5, 2_0]
      self.assertListEqual(tokenizer.convert_tokens_to_ids(lowerCAmelCase_) ,  lowerCAmelCase_)




    @slow
    def 					_UpperCAmelCase	(				self			:				Union[str, Any]):







      """simple docstring"""







      lowercase_								= XLMTokenizer.from_pretrained("""xlm-mlm-en-2048""")

      lowercase_								= tokenizer.encode("""sequence builders""" ,  add_special_tokens=lowerCAmelCase_)
      lowercase_								= tokenizer.encode("""multi-sequence build""" ,  add_special_tokens=lowerCAmelCase_)

      lowercase_								= tokenizer.build_inputs_with_special_tokens(lowerCAmelCase_)
      lowercase_								= tokenizer.build_inputs_with_special_tokens(lowerCAmelCase_ ,  lowerCAmelCase_)

      assert encoded_sentence == [0] + text + [1]
      assert encoded_pair == [0] + text + [1] + text_a + [1]






"""simple docstring"""
from dataclasses import dataclass
from typing import Optional, Tuple, Union

import flax
import jax.numpy as jnp
from jax import random

from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .scheduling_utils_flax import FlaxSchedulerMixin


@flax.struct.dataclass
class    SCREAMING_SNAKE_CASE__ :
    # setable values
    lowercase__      =   None
    lowercase__      =   None
    lowercase__      =   None  # sigma(t_i)

    @classmethod
    def 					_UpperCAmelCase	(				cls			:				Any):







      """simple docstring"""







      return cls()







@dataclass
class    SCREAMING_SNAKE_CASE__ (							__UpperCAmelCase   ):
    lowercase__      =   42
    lowercase__      =   42
    lowercase__      =   42







class    SCREAMING_SNAKE_CASE__ (							__UpperCAmelCase      ,  __UpperCAmelCase   ):

    @property
    def 					_UpperCAmelCase	(				self			:				int):







      """simple docstring"""







      return True

    @register_to_config
    def __init__(				self			:				Union[str, Any] ,  lowerCAmelCase_			:				float = 0.02 ,  lowerCAmelCase_			:				float = 1_0_0 ,  lowerCAmelCase_			:				float = 1.007 ,  lowerCAmelCase_			:				float = 8_0 ,  lowerCAmelCase_			:				float = 0.05 ,  lowerCAmelCase_			:				float = 5_0 ,  ):







      """simple docstring"""







      pass

    def 					_UpperCAmelCase	(				self			:				Optional[int]):







      """simple docstring"""







      return KarrasVeSchedulerState.create()

    def 					_UpperCAmelCase	(				self			:				Union[str, Any] ,  lowerCAmelCase_			:				KarrasVeSchedulerState ,  lowerCAmelCase_			:				int ,  lowerCAmelCase_			:				Tuple = ()):







      """simple docstring"""







      lowercase_								= jnp.arange(0 ,  lowerCAmelCase_)[::-1].copy()
      lowercase_								= [
          (
              self.config.sigma_max**2
              * (self.config.sigma_min**2 / self.config.sigma_max**2) ** (i / (num_inference_steps - 1))
          )
          for i in timesteps
      ]

      return state.replace(
          num_inference_steps=lowerCAmelCase_ ,  schedule=jnp.array(lowerCAmelCase_ ,  dtype=jnp.floataa) ,  timesteps=lowerCAmelCase_ ,  )

    def 					_UpperCAmelCase	(				self			:				Optional[int] ,  lowerCAmelCase_			:				KarrasVeSchedulerState ,  lowerCAmelCase_			:				jnp.ndarray ,  lowerCAmelCase_			:				float ,  lowerCAmelCase_			:				random.KeyArray ,  ):







      """simple docstring"""







      if self.config.s_min <= sigma <= self.config.s_max:
        lowercase_								= min(self.config.s_churn / state.num_inference_steps ,  2**0.5 - 1)
      else:
        lowercase_								= 0

      # sample eps ~ N(0, S_noise^2 * I)
      lowercase_								= random.split(lowerCAmelCase_ ,  num=1)
      lowercase_								= self.config.s_noise * random.normal(key=lowerCAmelCase_ ,  shape=sample.shape)
      lowercase_								= sigma + gamma * sigma
      lowercase_								= sample + ((sigma_hat**2 - sigma**2) ** 0.5 * eps)

      return sample_hat, sigma_hat

    def 					_UpperCAmelCase	(				self			:				Tuple ,  lowerCAmelCase_			:				KarrasVeSchedulerState ,  lowerCAmelCase_			:				jnp.ndarray ,  lowerCAmelCase_			:				float ,  lowerCAmelCase_			:				float ,  lowerCAmelCase_			:				jnp.ndarray ,  lowerCAmelCase_			:				bool = True ,  ):







      """simple docstring"""







      lowercase_								= sample_hat + sigma_hat * model_output
      lowercase_								= (sample_hat - pred_original_sample) / sigma_hat
      lowercase_								= sample_hat + (sigma_prev - sigma_hat) * derivative

      if not return_dict:
        return (sample_prev, derivative, state)

      return FlaxKarrasVeOutput(prev_sample=lowerCAmelCase_ ,  derivative=lowerCAmelCase_ ,  state=lowerCAmelCase_)

    def 					_UpperCAmelCase	(				self			:				Dict ,  lowerCAmelCase_			:				KarrasVeSchedulerState ,  lowerCAmelCase_			:				jnp.ndarray ,  lowerCAmelCase_			:				float ,  lowerCAmelCase_			:				float ,  lowerCAmelCase_			:				jnp.ndarray ,  lowerCAmelCase_			:				jnp.ndarray ,  lowerCAmelCase_			:				jnp.ndarray ,  lowerCAmelCase_			:				bool = True ,  ):







      """simple docstring"""







      lowercase_								= sample_prev + sigma_prev * model_output
      lowercase_								= (sample_prev - pred_original_sample) / sigma_prev
      lowercase_								= sample_hat + (sigma_prev - sigma_hat) * (0.5 * derivative + 0.5 * derivative_corr)

      if not return_dict:
        return (sample_prev, derivative, state)

      return FlaxKarrasVeOutput(prev_sample=lowerCAmelCase_ ,  derivative=lowerCAmelCase_ ,  state=lowerCAmelCase_)




    def 					_UpperCAmelCase	(				self			:				List[Any] ,  lowerCAmelCase_			:				KarrasVeSchedulerState ,  lowerCAmelCase_			:				int ,  lowerCAmelCase_			:				Optional[int] ,  lowerCAmelCase_			:				List[Any]):







      """simple docstring"""







      raise NotImplementedError()

