





import unittest

import numpy as np

from transformers import (
    GPTSanJapaneseConfig,
    GPTSanJapaneseForConditionalGeneration,
    GPTSanJapaneseModel,
    GPTSanJapaneseTokenizer,
    is_torch_available,
)
from transformers.generation import GenerationConfig
from transformers.testing_utils import require_torch, slow, tooslow, torch_device

from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor
from ...test_pipeline_mixin import PipelineTesterMixin





class   lowercase__     :







  def __init__(						self     ,    _lowercase     ,    _lowercase=36_000     ,    _lowercase=13     ,    _lowercase=7     ,    _lowercase=True     ,    _lowercase=32     ,    _lowercase=42     ,    _lowercase=5     ,    _lowercase=2     ,    _lowercase=4     ,    _lowercase=2     ,    _lowercase=32     ,    _lowercase=80     ,    _lowercase=33     ,    _lowercase=0.0     ,    _lowercase=1e-6     ,    _lowercase=100     ,    _lowercase=0.0     ,    ):
       lowerCAmelCase_       :							Any			 =		vocab_size
       lowerCAmelCase_       :							Dict			 =		parent
       lowerCAmelCase_       :							Union[str, Any]			 =		batch_size
       lowerCAmelCase_       :							str			 =		num_contexts
       # For common tests
       lowerCAmelCase_       :							List[str]			 =		self.num_contexts
       lowerCAmelCase_       :							Tuple			 =		is_training
       lowerCAmelCase_       :							Union[str, Any]			 =		hidden_size
       lowerCAmelCase_       :							Any			 =		num_ext_layers
       lowerCAmelCase_       :							str			 =		ext_size
       lowerCAmelCase_       :							Dict			 =		num_hidden_layers
       lowerCAmelCase_       :							Dict			 =		num_attention_heads
       lowerCAmelCase_       :							Union[str, Any]			 =		num_experts
       lowerCAmelCase_       :							List[Any]			 =		d_ff
       lowerCAmelCase_       :							Dict			 =		d_ext
       lowerCAmelCase_       :							List[str]			 =		d_spout
       lowerCAmelCase_       :							int			 =		dropout_rate
       lowerCAmelCase_       :							Dict			 =		layer_norm_epsilon
       lowerCAmelCase_       :							Optional[int]			 =		expert_capacity
       lowerCAmelCase_       :							Dict			 =		router_jitter_noise







  def 						UpperCAmelCase__		(						self    ):
       return GPTSanJapaneseConfig.from_pretrained("""Tanrei/GPTSAN-japanese"""    )







  def 						UpperCAmelCase__		(						self    ):
       lowerCAmelCase_       :							Union[str, Any]			 =		ids_tensor([self.batch_size, self.seq_length]     ,    self.vocab_size    )

       lowerCAmelCase_       :							Optional[int]			 =		self.get_config()

       return (config, input_ids)







  def 						UpperCAmelCase__		(						self    ):
       lowerCAmelCase_       :							Union[str, Any]			 =		ids_tensor([self.batch_size, self.seq_length]     ,    self.vocab_size    )

       lowerCAmelCase_       :							List[str]			 =		self.get_config()

       return (config, {"input_ids": input_ids})







  def 						UpperCAmelCase__		(						self    ):
       return GPTSanJapaneseConfig(
           vocab_size=self.vocab_size     ,    num_contexts=self.seq_length     ,    d_model=self.hidden_size     ,    d_ff=self.d_ff     ,    d_ext=self.d_ext     ,    d_spout=self.d_spout     ,    num_switch_layers=self.num_hidden_layers - self.num_ext_layers     ,    num_ext_layers=self.num_ext_layers     ,    num_heads=self.num_attention_heads     ,    num_experts=self.num_experts     ,    expert_capacity=self.expert_capacity     ,    dropout_rate=self.dropout_rate     ,    layer_norm_epsilon=self.layer_norm_epsilon     ,    router_jitter_noise=self.router_jitter_noise     ,    )







  def 						UpperCAmelCase__		(						self     ,    _lowercase     ,    _lowercase     ,    ):
       lowerCAmelCase_       :							List[Any]			 =		GPTSanJapaneseForConditionalGeneration(config=_lowercase    )
       model.to(_lowercase    )
       model.eval()
       lowerCAmelCase_       :							Optional[Any]			 =		model(
           input_ids=_lowercase     ,    )
       self.parent.assertIsNotNone(_lowercase    )





@require_torch
class   lowercase__     (				__A  ,       __A  ,       unittest.TestCase	):
  __UpperCamelCase						  =	(GPTSanJapaneseModel,) if is_torch_available() else ()
  __UpperCamelCase						  =	(
      {
          """conversational""": GPTSanJapaneseForConditionalGeneration,
          """feature-extraction""": GPTSanJapaneseForConditionalGeneration,
          """summarization""": GPTSanJapaneseForConditionalGeneration,
          """text2text-generation""": GPTSanJapaneseForConditionalGeneration,
          """translation""": GPTSanJapaneseForConditionalGeneration,
      }
      if is_torch_available()
      else {}
  )
  __UpperCamelCase						  =	False
  __UpperCamelCase						  =	False
  __UpperCamelCase						  =	False
  __UpperCamelCase						  =	False
  __UpperCamelCase						  =	False
  __UpperCamelCase						  =	False
  __UpperCamelCase						  =	False
  __UpperCamelCase						  =	False
  # The small GPTSAN_JAPANESE model needs higher percentages for CPU/MP tests
  __UpperCamelCase						  =	[0.8, 0.9]







  def 						UpperCAmelCase__		(						self     ,    _lowercase     ,    _lowercase     ,    _lowercase     ,    _lowercase     ,    _lowercase    ):
       if pipeline_test_casse_name == "SummarizationPipelineTests":
            # TODO: fix `_reorder_cache` is not implemented for this model
            return True
       elif pipeline_test_casse_name == "Text2TextGenerationPipelineTests":
            # TODO: check this.
            return True

       return False







  def 						UpperCAmelCase__		(						self    ):
       lowerCAmelCase_       :							Tuple			 =		GPTSanJapaneseTester(self    )
       lowerCAmelCase_       :							Optional[Any]			 =		ConfigTester(self     ,    config_class=_lowercase     ,    d_model=37    )







  def 						UpperCAmelCase__		(						self    ):
       GPTSanJapaneseConfig()







  def 						UpperCAmelCase__		(						self    ):
       lowerCAmelCase_       :							Dict			 =		self.model_tester.prepare_config_and_inputs()
       self.model_tester.create_and_check_model(*_lowercase    )







  @unittest.skip(
      reason="""skip for now as the computed `max_memory` by `model_split_percents` in the test method will be changed inside `from_pretrained`"""    )
  def 						UpperCAmelCase__		(						self    ):
       super().test_model_parallelism()







  @unittest.skip("""Will be fixed soon by reducing the size of the model used for common tests."""    )
  def 						UpperCAmelCase__		(						self    ):
       pass





@require_torch
class   lowercase__     (				__A  ,       __A  ,       unittest.TestCase	):
  __UpperCamelCase						  =	(GPTSanJapaneseForConditionalGeneration,) if is_torch_available() else ()
  __UpperCamelCase						  =	False
  __UpperCamelCase						  =	False
  __UpperCamelCase						  =	False
  __UpperCamelCase						  =	False
  __UpperCamelCase						  =	False
  __UpperCamelCase						  =	False
  # The small GPTSAN_JAPANESE model needs higher percentages for CPU/MP tests
  __UpperCamelCase						  =	[0.8, 0.9]







  def 						UpperCAmelCase__		(						self    ):
       lowerCAmelCase_       :							List[str]			 =		GPTSanJapaneseTester(self    )
       lowerCAmelCase_       :							Optional[int]			 =		ConfigTester(self     ,    config_class=_lowercase     ,    d_model=37    )







  def 						UpperCAmelCase__		(						self    ):
       GPTSanJapaneseConfig()







  def 						UpperCAmelCase__		(						self    ):
       lowerCAmelCase_       :							Optional[int]			 =		self.model_tester.prepare_config_and_inputs()
       self.model_tester.create_and_check_model(*_lowercase    )







  @unittest.skip(
      reason="""skip for now as the computed `max_memory` by `model_split_percents` in the test method will be changed inside `from_pretrained`"""    )
  def 						UpperCAmelCase__		(						self    ):
       super().test_model_parallelism()







  @unittest.skip("""Will be fixed soon by reducing the size of the model used for common tests."""    )
  def 						UpperCAmelCase__		(						self    ):
       pass







  @slow
  def 						UpperCAmelCase__		(						self    ):
       lowerCAmelCase_       :							Tuple			 =		GPTSanJapaneseForConditionalGeneration.from_pretrained("""Tanrei/GPTSAN-japanese"""    )
       lowerCAmelCase_       :							int			 =		GPTSanJapaneseTokenizer.from_pretrained("""Tanrei/GPTSAN-japanese"""    )
       lowerCAmelCase_       :							Optional[Any]			 =		tokenizer.encode("""武田信玄は"""     ,    return_tensors="""pt"""    )
       lowerCAmelCase_       :							Any			 =		model(_lowercase    )
       lowerCAmelCase_       :							Dict			 =		outputs.logits.detach().cpu().numpy()
       # Output of original model created with mesh-tensoflow
       lowerCAmelCase_       :							Dict			 =		[
           # fmt: off
           [-12.037_8398_8952_6367, -12.433_0615_9973_1445, -14.333_8403_7017_8223, -12.450_3459_9304_1992, -11.1_6613_7695_3125,
           -11.930_1376_3427_7344, -10.659_7404_4799_8047, -12.909_5745_0866_6992, -13.241_0430_9082_0312, -13.398_5795_9747_3145,
           -11.107_5248_7182_6172, -12.3_6859_4169_6167, -22.97_9431_1523_4375, -10.481_0676_5747_0703, -12.484_0307_2357_1777,
           -12.807_3606_4910_8887, -14.769_7000_5035_4004, -12.233_5796_3562_0117, -13.428_1454_0863_0371, -22.624_1779_3273_9258],
           [-7.511_1498_8327_0264, -8.281_8517_6849_3652, -7.943_1271_5530_3955, -7.55_0213_3369_4458, -6.49_8699_6650_6958,
           -7.586_7962_8372_1924, -6.978_0859_9472_0459, -7.839_1451_8356_3232, -8.21_9641_6854_8584, -8.695_0912_4755_8594,
           -6.706_9106_1019_8975, -6.6585_7982_6354_9805, -19.565_6986_2365_7227, -5.353_8427_3529_0527, -8.350_6860_7330_3223,
           -8.039_3886_5661_6211, -10.856_5692_9016_1133, -7.75_1544_4755_5542, -8.819_0221_7864_9902, -19.51_5327_4536_1328],
           [-9.73_0662_3458_8623, -10.223_9227_2949_2188, -9.932_9814_9108_8867, -11.857_8367_2332_7637, -7.662_6262_6647_9492,
           -11.13_5291_0995_4834, -7.765_0976_1810_3027, -11.472_9232_7880_8594, -9.543_1499_4812_0117, -11.905_6339_2639_1602,
           -9.366_1642_0745_8496, -11.5_7342_8153_9917, -23.699_0032_1960_4492, -9.429_5902_2521_9727, -10.42_8392_4102_7832,
           -10.585_2403_6407_4707, -10.94_7719_5739_7461, -11.095_4160_6903_0762, -10.390_2406_6925_0488, -23.769_3729_4006_3477],
           [-9.728_2657_6232_9102, -9.859_7126_0070_8008, -10.09_7292_9000_8545, -9.678_5221_0998_5352, -6.879_5199_3942_2607,
           -9.68_4875_4882_8125, -4.2803_4257_8887_9395, -10.018_9142_2271_7285, -9.308_4459_3048_0957, -10.63_3945_4650_8789,
           -8.083_6467_7429_1992, -9.06_3014_9841_3086, -21.904_2663_5742_1875, -8.90_1608_4671_0205, -8.841_8760_2996_8262,
           -11.856_7199_7070_3125, -12.079_3981_5521_2402, -11.233_7532_0434_5703, -10.177_3386_0015_8691, -21.87_2566_2231_4453],
           [-9.669_7645_1873_7793, -9.614_1986_8469_2383, -9.814_5103_4545_8984, -9.996_5019_2260_7422, -11.375_6904_6020_5078,
           -10.113_4052_2766_1133, -10.546_8673_7060_5469, -10.04_3690_6814_5752, -10.907_8092_5750_7324, -10.504_2161_9415_2832,
           -11.129_1990_2801_5137, -10.151_1240_0054_9316, -21.96_5867_9962_1582, -9.086_3494_8730_4688, -11.730_3390_5029_2969,
           -10.460_6676_1016_8457, -10.298_0499_2675_7812, -10.784_1482_1624_7559, -10.840_6934_7381_5918, -22.03_1528_4729_0039],
           # fmt: on
       ]
       lowerCAmelCase_       :							List[Any]			 =		np.array(_lowercase    ).flatten()
       lowerCAmelCase_       :							Any			 =		output_logits[0, :, :20].flatten()

       def check(_lowercase     ,    _lowercase     ,    _lowercase=5e-4    ):
            return abs(a - b    ) < epsilon * max(abs(_lowercase    )     ,    abs(_lowercase    )    )

       self.assertTrue(np.all([check(target[i]     ,    predict[i]    ) for i in range(len(_lowercase    )    )]    )    )







  @slow
  def 						UpperCAmelCase__		(						self    ):
       lowerCAmelCase_       :							Tuple			 =		GPTSanJapaneseForConditionalGeneration.from_pretrained("""Tanrei/GPTSAN-japanese"""    )
       lowerCAmelCase_       :							List[str]			 =		GPTSanJapaneseTokenizer.from_pretrained("""Tanrei/GPTSAN-japanese"""    )
       model.to(_lowercase    )

       # set deterministically
       lowerCAmelCase_       :							Any			 =		GenerationConfig.from_pretrained("""Tanrei/GPTSAN-japanese"""    )
       lowerCAmelCase_       :							List[Any]			 =		1

       # use different length sentences to test batching
       lowerCAmelCase_       :							int			 =		[
           """甲斐なら武田と言うほど""",
           """織田信長は、""",
       ]

       lowerCAmelCase_       :							str			 =		"""left"""
       lowerCAmelCase_       :							Optional[Any]			 =		tokenizer(_lowercase     ,    return_tensors="""pt"""     ,    padding=_lowercase    )
       lowerCAmelCase_       :							Optional[int]			 =		inputs["""input_ids"""].to(_lowercase    )

       self.assertNotEqual(inputs["""attention_mask"""][0].numpy().tolist()     ,    inputs["""attention_mask"""][1].numpy().tolist()    )

       lowerCAmelCase_       :							List[str]			 =		model.generate(
           input_ids=_lowercase     ,    attention_mask=inputs["""attention_mask"""].to(_lowercase    )     ,    max_new_tokens=3     ,    generation_config=_lowercase     ,    )

       lowerCAmelCase_       :							Tuple			 =		tokenizer(sentences[0]     ,    return_tensors="""pt"""    ).input_ids.to(_lowercase    )
       lowerCAmelCase_       :							List[Any]			 =		model.generate(
           input_ids=_lowercase     ,    max_new_tokens=3     ,    generation_config=_lowercase    )

       lowerCAmelCase_       :							str			 =		tokenizer(sentences[1]     ,    return_tensors="""pt"""    ).input_ids.to(_lowercase    )
       lowerCAmelCase_       :							Optional[int]			 =		model.generate(input_ids=_lowercase     ,    max_new_tokens=3     ,    generation_config=_lowercase    )

       self.assertNotEqual(inputs_non_padded.shape     ,    inputs_padded.shape    )

       lowerCAmelCase_       :							Any			 =		tokenizer.batch_decode(_lowercase     ,    skip_special_tokens=_lowercase    )
       lowerCAmelCase_       :							Any			 =		tokenizer.decode(output_non_padded[0]     ,    skip_special_tokens=_lowercase    )
       lowerCAmelCase_       :							str			 =		tokenizer.decode(output_padded[0]     ,    skip_special_tokens=_lowercase    )

       lowerCAmelCase_       :							Optional[int]			 =		[
           """甲斐なら武田と言うほど甲斐の武田""",
           """織田信長は、このような""",
       ]
       self.assertListEqual(_lowercase     ,    _lowercase    )
       self.assertListEqual(_lowercase     ,    [non_padded_sentence, padded_sentence]    )







  @tooslow
  def 						UpperCAmelCase__		(						self    ):
       lowerCAmelCase_       :							Any			 =		GPTSanJapaneseForConditionalGeneration.from_pretrained("""Tanrei/GPTSAN-japanese"""    )
       lowerCAmelCase_       :							int			 =		GPTSanJapaneseTokenizer.from_pretrained("""Tanrei/GPTSAN-japanese"""    )
       # Output of original model created with mesh-tensoflow
       lowerCAmelCase_       :							List[Any]			 =		[
           ("""武田信玄は""", 35_675),
           ("""武田信玄は、""", 45),
           ("""武田信玄は、この""", 29),
           ("""武田信玄は、このよう""", 30_642),
           ("""武田信玄は、このような""", 35_680),
           ("""武田信玄は、このような「""", 8_640),
           ("""武田信玄は、このような「武田""", 31_617),
           ("""武田信玄は、このような「武田家""", 30_646),
           ("""武田信玄は、このような「武田家の""", 31_617),
           ("""武田信玄は、このような「武田家の家""", 31_381),
       ]
       for input, output in target:
            lowerCAmelCase_       :							Union[str, Any]			 =		tokenizer.encode(_lowercase     ,    return_tensors="""pt"""    )
            lowerCAmelCase_       :							Union[str, Any]			 =		model(_lowercase    )
            lowerCAmelCase_       :							List[Any]			 =		outputs.logits.detach().cpu().numpy()[0]
            lowerCAmelCase_       :							Optional[Any]			 =		np.argmax(output_logits[-1]    )
            self.assertEqual(_lowercase     ,    _lowercase    )







  @slow
  def 						UpperCAmelCase__		(						self    ):
       lowerCAmelCase_       :							Any			 =		GPTSanJapaneseForConditionalGeneration.from_pretrained("""Tanrei/GPTSAN-japanese"""    )
       lowerCAmelCase_       :							Dict			 =		GPTSanJapaneseTokenizer.from_pretrained("""Tanrei/GPTSAN-japanese"""    )
       model.to(_lowercase    )

       # set deterministically
       lowerCAmelCase_       :							Tuple			 =		GenerationConfig.from_pretrained("""Tanrei/GPTSAN-japanese"""    )
       lowerCAmelCase_       :							Dict			 =		1

       lowerCAmelCase_       :							List[str]			 =		"""武田信玄は、"""
       lowerCAmelCase_       :							List[Any]			 =		tokenizer(_lowercase     ,    return_tensors="""pt"""    ).input_ids.to(_lowercase    )
       lowerCAmelCase_       :							Optional[Any]			 =		tokenizer([input_text, input_text]     ,    return_tensors="""pt"""    ).input_ids.to(_lowercase    )

       # spout from uniform and one-hot
       lowerCAmelCase_       :							Union[str, Any]			 =		[
           # fmt: off
           [0.8788_2208, 0.3842_6396, 0.3322_0248, 0.4389_0406, 0.1656_2252,
           0.0480_3985, 0.21_1572  , 0.2318_8473, 0.3715_3068, 0.783_6377 ,
           0.0216_0172, 0.3876_1719, 0.7529_0772, 0.9019_8857, 0.3436_5777,
           0.6416_8169, 0.4431_8471, 0.1457_5746, 0.9256_2881, 0.4081_2148,
           0.2901_9122, 0.8886_1599, 0.6552_4846, 0.4356_3456, 0.3817_7187,
           0.7083_2965, 0.8152_7892, 0.6883_2812, 0.3883_3192, 0.456_1522 ,
           0.1482_8817, 0.4724_8213, 0.5435_7335, 0.8200_9566, 0.133_8884 ,
           0.0275_5417, 0.1976_4677, 0.242_2084 , 0.0475_7674, 0.6540_9606,
           0.082_4589 , 0.0330_4383, 0.9438_7689, 0.9876_4509, 0.8243_3901,
           0.2764_6741, 0.6490_7493, 0.7600_9406, 0.3008_7915, 0.1790_4689,
           0.4160_1714, 0.6704_6398, 0.1042_2822, 0.0844_7374, 0.0735_4344,
           0.6142_3565, 0.7028_4866, 0.753_2333 , 0.197_2038 , 0.2957_5659,
           0.9058_3886, 0.2926_5307, 0.5000_0175, 0.7040_7655, 0.88_9363  ,
           0.8190_4418, 0.6682_9128, 0.6446_8815, 0.5656_3723, 0.8560_1875,
           0.9492_4672, 0.0016_6762, 0.2522_0643, 0.7454_0219, 0.6799_3247,
           0.154_9675 , 0.3938_5352, 0.9215_3607, 0.6374_5931, 0.2775_9043,
           0.8470_2295, 0.6590_4271, 0.5867_6614, 0.866_6936 , 0.3960_7438,
           0.7995_4983, 0.4222_0697, 0.3965_0381, 0.784_9864 , 0.5615_0201,
           0.1567_8925, 0.1474_6032, 0.3454_2114, 0.4702_6783, 0.1195_6489,
           0.2542_1435, 0.3378_8901, 0.6893_4842, 0.3642_4685, 0.7173_7898,
           0.3898_3449, 0.9439_3779, 0.3957_5588, 0.3661_6553, 0.8710_4665,
           0.6463_0203, 0.2251_6905, 0.8827_0804, 0.1503_1338, 0.7514_4345,
           0.4645_9025, 0.8539_6454, 0.8635_5643, 0.6513_9851, 0.7026_6061,
           0.3024_1389, 0.8105_6497, 0.8886_5969, 0.3877_3807, 0.7063_5849,
           0.9071_8459, 0.4324_5789, 0.2800_0654, 0.4593_5562, 0.0877_3519,
           0.955_2151 , 0.9390_1511, 0.2248_9288], # uniform
           [1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
            0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
            0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
            0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
            0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
            0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
            0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
            0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
            0., 0., 0., 0., 0., 0., 0., 0.],
           # fmt: on
       ]

       lowerCAmelCase_       :							Tuple			 =		model.generate(
           input_ids=_lowercase     ,    spout=spouts[0]     ,    max_new_tokens=20     ,    generation_config=_lowercase     ,    )

       lowerCAmelCase_       :							int			 =		model.generate(
           input_ids=_lowercase     ,    spout=spouts[1]     ,    max_new_tokens=20     ,    generation_config=_lowercase     ,    )

       lowerCAmelCase_       :							Optional[int]			 =		model.generate(
           input_ids=_lowercase     ,    spout=_lowercase     ,    max_new_tokens=20     ,    generation_config=_lowercase     ,    )

       lowerCAmelCase_       :							Dict			 =		tokenizer.decode(outputa[0]    )
       lowerCAmelCase_       :							Any			 =		tokenizer.decode(outputa[0]    )
       lowerCAmelCase_       :							int			 =		tokenizer.batch_decode(_lowercase    )

       lowerCAmelCase_       :							List[Any]			 =		[
           """武田信玄は、武田氏の滅亡後、武田氏の居城であった甲斐武田氏の居城である""",
           """武田信玄は、武田家の滅亡を防ぐため、武田家の家臣である武田信虎を討""",
       ]
       self.assertListEqual(_lowercase     ,    _lowercase    )
       self.assertListEqual(_lowercase     ,    [outa_sentence, outa_sentence]    )







  @slow
  def 						UpperCAmelCase__		(						self    ):
       lowerCAmelCase_       :							int			 =		GPTSanJapaneseForConditionalGeneration.from_pretrained("""Tanrei/GPTSAN-japanese"""    )
       lowerCAmelCase_       :							Union[str, Any]			 =		GPTSanJapaneseTokenizer.from_pretrained("""Tanrei/GPTSAN-japanese"""    )
       model.to(_lowercase    )

       # set deterministically
       lowerCAmelCase_       :							int			 =		GenerationConfig.from_pretrained("""Tanrei/GPTSAN-japanese"""    )
       lowerCAmelCase_       :							List[str]			 =		1

       lowerCAmelCase_       :							Optional[int]			 =		"""武田信玄"""
       lowerCAmelCase_       :							Optional[int]			 =		"""織田信長"""
       lowerCAmelCase_       :							str			 =		"""は、"""
       lowerCAmelCase_       :							Tuple			 =		"""が、"""
       lowerCAmelCase_       :							Dict			 =		tokenizer(_lowercase     ,    prefix_text=_lowercase     ,    return_tensors="""pt"""    )
       lowerCAmelCase_       :							Any			 =		tokenizer(_lowercase     ,    prefix_text=_lowercase     ,    return_tensors="""pt"""    )
       lowerCAmelCase_       :							Union[str, Any]			 =		tokenizer([[prefix_text_a, input_text_a], [prefix_text_a, input_text_a]]     ,    return_tensors="""pt"""    )

       lowerCAmelCase_       :							Dict			 =		model.generate(
           input_ids=input_tok_a.input_ids.to(_lowercase    )     ,    token_type_ids=input_tok_a.token_type_ids.to(_lowercase    )     ,    max_new_tokens=20     ,    generation_config=_lowercase     ,    )

       lowerCAmelCase_       :							Dict			 =		model.generate(
           input_ids=input_tok_a.input_ids.to(_lowercase    )     ,    token_type_ids=input_tok_a.token_type_ids.to(_lowercase    )     ,    max_new_tokens=20     ,    generation_config=_lowercase     ,    )

       lowerCAmelCase_       :							Union[str, Any]			 =		model.generate(
           input_ids=input_tok_a.input_ids.to(_lowercase    )     ,    token_type_ids=input_tok_a.token_type_ids.to(_lowercase    )     ,    attention_mask=input_tok_a.attention_mask.to(_lowercase    )     ,    max_new_tokens=20     ,    generation_config=_lowercase     ,    )

       lowerCAmelCase_       :							Optional[Any]			 =		tokenizer.decode(outputa[0]    )
       lowerCAmelCase_       :							Optional[int]			 =		tokenizer.decode(outputa[0]    )
       lowerCAmelCase_       :							List[str]			 =		tokenizer.batch_decode(_lowercase    )

       lowerCAmelCase_       :							str			 =		[
           """武田信玄は、武田氏の祖である武田信虎を、その子・武田信友を擁して""",
           """織田信長が、織田信長の妻・お市の方を妻として迎えたという逸話が残""",
       ]
       self.assertListEqual(_lowercase     ,    _lowercase    )
       self.assertListEqual(_lowercase     ,    [outa_sentence, outa_sentence]    )







import math





class   lowercase__     :







  def __init__(						self     ,    _lowercase    ):
       lowerCAmelCase_       :							Optional[Any]			 =		len(_lowercase    )
       lowerCAmelCase_       :							Union[str, Any]			 =		[0] * (
           4 * self.N
       )  # approximate the overall size of segment tree with array N
       self.build(1     ,    0     ,    self.N - 1    )







  def 						UpperCAmelCase__		(						self     ,    _lowercase    ):
       return idx * 2







  def 						UpperCAmelCase__		(						self     ,    _lowercase    ):
       return idx * 2 + 1







  def 						UpperCAmelCase__		(						self     ,    _lowercase     ,    _lowercase     ,    _lowercase    ):  # noqa: E741
       if l == r:
            lowerCAmelCase_       :							Dict			 =		A[l]
       else:
            lowerCAmelCase_       :							List[str]			 =		(l + r) // 2
            self.build(self.left(_lowercase    )     ,    _lowercase     ,    _lowercase    )
            self.build(self.right(_lowercase    )     ,    mid + 1     ,    _lowercase    )
            lowerCAmelCase_       :							Dict			 =		max(self.st[self.left(_lowercase    )]     ,    self.st[self.right(_lowercase    )]    )







  def 						UpperCAmelCase__		(						self     ,    _lowercase     ,    _lowercase     ,    _lowercase    ):
       return self.update_recursive(1     ,    0     ,    self.N - 1     ,    a - 1     ,    b - 1     ,    _lowercase    )







  def 						UpperCAmelCase__		(						self     ,    _lowercase     ,    _lowercase     ,    _lowercase     ,    _lowercase     ,    _lowercase     ,    _lowercase    ):  # noqa: E741
       if r < a or l > b:
            return True
       if l == r:
            lowerCAmelCase_       :							List[str]			 =		val
            return True
       lowerCAmelCase_       :							List[str]			 =		(l + r) // 2
       self.update_recursive(self.left(_lowercase    )     ,    _lowercase     ,    _lowercase     ,    _lowercase     ,    _lowercase     ,    _lowercase    )
       self.update_recursive(self.right(_lowercase    )     ,    mid + 1     ,    _lowercase     ,    _lowercase     ,    _lowercase     ,    _lowercase    )
       lowerCAmelCase_       :							List[Any]			 =		max(self.st[self.left(_lowercase    )]     ,    self.st[self.right(_lowercase    )]    )
       return True







  def 						UpperCAmelCase__		(						self     ,    _lowercase     ,    _lowercase    ):
       return self.query_recursive(1     ,    0     ,    self.N - 1     ,    a - 1     ,    b - 1    )







  def 						UpperCAmelCase__		(						self     ,    _lowercase     ,    _lowercase     ,    _lowercase     ,    _lowercase     ,    _lowercase    ):  # noqa: E741
       if r < a or l > b:
            return -math.inf
       if l >= a and r <= b:
            return self.st[idx]
       lowerCAmelCase_       :							int			 =		(l + r) // 2
       lowerCAmelCase_       :							List[Any]			 =		self.query_recursive(self.left(_lowercase    )     ,    _lowercase     ,    _lowercase     ,    _lowercase     ,    _lowercase    )
       lowerCAmelCase_       :							List[str]			 =		self.query_recursive(self.right(_lowercase    )     ,    mid + 1     ,    _lowercase     ,    _lowercase     ,    _lowercase    )
       return max(_lowercase     ,    _lowercase    )







  def 						UpperCAmelCase__		(						self    ):
       lowerCAmelCase_       :							List[Any]			 =		[]
       for i in range(1     ,    N + 1    ):
            show_list += [self.query(_lowercase     ,    _lowercase    )]
       print(_lowercase    )


if __name__ == "__main__":
      UpperCAmelCase_       : Any							=    [1, 2, -4, 7, 3, -5, 6, 11, -20, 9, 14, 15, 5, 2, -8]
      UpperCAmelCase_       : Optional[Any]							=    15
      UpperCAmelCase_       : List[Any]							=    SegmentTree(A)
      print(segt.query(4, 6))
      print(segt.query(7, 11))
      print(segt.query(7, 12))
      segt.update(1, 3, 1_11)
      print(segt.query(1, 15))
      segt.update(7, 8, 2_35)
      segt.show_data()
