



import gc
import unittest

import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer

from diffusers import (
    AutoencoderKL,
    DDIMScheduler,
    StableDiffusionSAGPipeline,
    UNetaDConditionModel,
)
from diffusers.utils import slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu

from ..pipeline_params import TEXT_TO_IMAGE_BATCH_PARAMS, TEXT_TO_IMAGE_IMAGE_PARAMS, TEXT_TO_IMAGE_PARAMS
from ..test_pipelines_common import PipelineLatentTesterMixin, PipelineTesterMixin


enable_full_determinism()



class       UpperCAmelCase__(							lowerCamelCase     ,							lowerCamelCase     ,							unittest.TestCase	):

   '''simple docstring'''




   A    :  Union[str, Any]       				=    StableDiffusionSAGPipeline
   A    :  str       				=    TEXT_TO_IMAGE_PARAMS
   A    :  Tuple       				=    TEXT_TO_IMAGE_BATCH_PARAMS
   A    :  Any       				=    TEXT_TO_IMAGE_IMAGE_PARAMS
   A    :  Dict       				=    TEXT_TO_IMAGE_IMAGE_PARAMS
   A    :  Any       				=    False


   def 			UpperCAmelCase		(						self  :			Tuple)	->				Optional[int]:




         """simple docstring"""

         torch.manual_seed(0)
         lowercase__     =  UNetaDConditionModel(
             block_out_channels=(32, 64)			,				layers_per_block=2			,				sample_size=32			,				in_channels=4			,				out_channels=4			,				down_block_types=('DownBlock2D', 'CrossAttnDownBlock2D')			,				up_block_types=('CrossAttnUpBlock2D', 'UpBlock2D')			,				cross_attention_dim=32			,				)
         lowercase__     =  DDIMScheduler(
             beta_start=0.0_00_85			,				beta_end=0.0_12			,				beta_schedule='scaled_linear'			,				clip_sample=lowerCAmelCase			,				set_alpha_to_one=lowerCAmelCase			,				)
         torch.manual_seed(0)
         lowercase__     =  AutoencoderKL(
             block_out_channels=[32, 64]			,				in_channels=3			,				out_channels=3			,				down_block_types=['DownEncoderBlock2D', 'DownEncoderBlock2D']			,				up_block_types=['UpDecoderBlock2D', 'UpDecoderBlock2D']			,				latent_channels=4			,				)
         torch.manual_seed(0)
         lowercase__     =  CLIPTextConfig(
             bos_token_id=0			,				eos_token_id=2			,				hidden_size=32			,				intermediate_size=37			,				layer_norm_eps=1E-0_5			,				num_attention_heads=4			,				num_hidden_layers=5			,				pad_token_id=1			,				vocab_size=10_00			,				)
         lowercase__     =  CLIPTextModel(lowerCAmelCase)
         lowercase__     =  CLIPTokenizer.from_pretrained('hf-internal-testing/tiny-random-clip')

         lowercase__     =  {
             'unet': unet,
             'scheduler': scheduler,
             'vae': vae,
             'text_encoder': text_encoder,
             'tokenizer': tokenizer,
             'safety_checker': None,
             'feature_extractor': None,
         }
         return components


   def 			UpperCAmelCase		(						self  :			Any			,				lowerCAmelCase  :			str			,				lowerCAmelCase  :			Dict=0)	->				Optional[int]:




         """simple docstring"""

         if str(lowerCAmelCase).startswith('mps'):
               lowercase__     =  torch.manual_seed(lowerCAmelCase)
         else:
               lowercase__     =  torch.Generator(device=lowerCAmelCase).manual_seed(lowerCAmelCase)
         lowercase__     =  {
             'prompt': '.',
             'generator': generator,
             'num_inference_steps': 2,
             'guidance_scale': 1.0,
             'sag_scale': 1.0,
             'output_type': 'numpy',
         }
         return inputs



   def 			UpperCAmelCase		(						self  :			Optional[int])	->				List[str]:




         """simple docstring"""

         super().test_inference_batch_single_identical(expected_max_diff=3E-3)



@slow
@require_torch_gpu
class       UpperCAmelCase__(							unittest.TestCase	):

   '''simple docstring'''




   def 			UpperCAmelCase		(						self  :			Optional[Any])	->				List[str]:




         """simple docstring"""

         super().tearDown()
         gc.collect()
         torch.cuda.empty_cache()


   def 			UpperCAmelCase		(						self  :			Optional[Any])	->				Any:




         """simple docstring"""

         lowercase__     =  StableDiffusionSAGPipeline.from_pretrained('CompVis/stable-diffusion-v1-4')
         lowercase__     =  sag_pipe.to(lowerCAmelCase)
         sag_pipe.set_progress_bar_config(disable=lowerCAmelCase)

         lowercase__     =  '.'
         lowercase__     =  torch.manual_seed(0)
         lowercase__     =  sag_pipe(
             [prompt]			,				generator=lowerCAmelCase			,				guidance_scale=7.5			,				sag_scale=1.0			,				num_inference_steps=20			,				output_type='np')

         lowercase__     =  output.images

         lowercase__     =  image[0, -3:, -3:, -1]

         assert image.shape == (1, 5_12, 5_12, 3)
         lowercase__     =  np.array([0.15_68, 0.17_38, 0.16_95, 0.16_93, 0.15_07, 0.17_05, 0.15_47, 0.17_51, 0.19_49])

         assert np.abs(image_slice.flatten() - expected_slice).max() < 5E-2


   def 			UpperCAmelCase		(						self  :			Union[str, Any])	->				int:




         """simple docstring"""

         lowercase__     =  StableDiffusionSAGPipeline.from_pretrained('stabilityai/stable-diffusion-2-1-base')
         lowercase__     =  sag_pipe.to(lowerCAmelCase)
         sag_pipe.set_progress_bar_config(disable=lowerCAmelCase)

         lowercase__     =  '.'
         lowercase__     =  torch.manual_seed(0)
         lowercase__     =  sag_pipe(
             [prompt]			,				generator=lowerCAmelCase			,				guidance_scale=7.5			,				sag_scale=1.0			,				num_inference_steps=20			,				output_type='np')

         lowercase__     =  output.images

         lowercase__     =  image[0, -3:, -3:, -1]

         assert image.shape == (1, 5_12, 5_12, 3)
         lowercase__     =  np.array([0.34_59, 0.28_76, 0.25_37, 0.30_02, 0.26_71, 0.21_60, 0.30_26, 0.22_62, 0.23_71])

         assert np.abs(image_slice.flatten() - expected_slice).max() < 5E-2



   def 			UpperCAmelCase		(						self  :			Union[str, Any])	->				int:




         """simple docstring"""

         lowercase__     =  StableDiffusionSAGPipeline.from_pretrained('stabilityai/stable-diffusion-2-1-base')
         lowercase__     =  sag_pipe.to(lowerCAmelCase)
         sag_pipe.set_progress_bar_config(disable=lowerCAmelCase)

         lowercase__     =  '.'
         lowercase__     =  torch.manual_seed(0)
         lowercase__     =  sag_pipe(
             [prompt]			,				width=7_68			,				height=5_12			,				generator=lowerCAmelCase			,				guidance_scale=7.5			,				sag_scale=1.0			,				num_inference_steps=20			,				output_type='np'			,				)

         lowercase__     =  output.images

         assert image.shape == (1, 5_12, 7_68, 3)





import pickle
import shutil
import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, XGLMTokenizer, XGLMTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


a__      :				Any   	=			get_tests_dir("fixtures/test_sentencepiece.model")



@require_sentencepiece
@require_tokenizers
class       UpperCAmelCase__(							lowerCamelCase     ,							unittest.TestCase	):

   '''simple docstring'''




   A    :  str       				=    XGLMTokenizer
   A    :  List[Any]       				=    XGLMTokenizerFast
   A    :  int       				=    True
   A    :  Optional[Any]       				=    True


   def 			UpperCAmelCase		(						self  :			Optional[int])	->				Optional[Any]:




         """simple docstring"""

         super().setUp()

         # We have a SentencePiece fixture for testing
         lowercase__     =  XGLMTokenizer(lowerCAmelCase			,				keep_accents=lowerCAmelCase)
         tokenizer.save_pretrained(self.tmpdirname)


   def 			UpperCAmelCase		(						self  :			Union[str, Any])	->				str:




         """simple docstring"""

         lowercase__     =  '<pad>'
         lowercase__     =  1

         self.assertEqual(self.get_tokenizer()._convert_token_to_id(lowerCAmelCase)			,				lowerCAmelCase)
         self.assertEqual(self.get_tokenizer()._convert_id_to_token(lowerCAmelCase)			,				lowerCAmelCase)


   def 			UpperCAmelCase		(						self  :			str)	->				List[str]:




         """simple docstring"""

         lowercase__     =  list(self.get_tokenizer().get_vocab().keys())

         self.assertEqual(vocab_keys[0]			,				'<s>')
         self.assertEqual(vocab_keys[1]			,				'<pad>')
         self.assertEqual(len(lowerCAmelCase)			,				10_08)


   def 			UpperCAmelCase		(						self  :			List[str])	->				str:




         """simple docstring"""

         self.assertEqual(self.get_tokenizer().vocab_size			,				10_08)


   def 			UpperCAmelCase		(						self  :			Optional[Any])	->				List[str]:




         """simple docstring"""

         lowercase__     =  XGLMTokenizer(lowerCAmelCase			,				keep_accents=lowerCAmelCase)

         lowercase__     =  tokenizer.tokenize('This is a test')
         self.assertListEqual(lowerCAmelCase			,				['▁This', '▁is', '▁a', '▁t', 'est'])

         self.assertListEqual(
             tokenizer.convert_tokens_to_ids(lowerCAmelCase)			,				[value + tokenizer.fairseq_offset for value in [2_85, 46, 10, 1_70, 3_82]]			,				)

         lowercase__     =  tokenizer.tokenize('I was born in 92000, and this is falsé.')
         self.assertListEqual(
             lowerCAmelCase			,				[
                 SPIECE_UNDERLINE + 'I',
                 SPIECE_UNDERLINE + 'was',
                 SPIECE_UNDERLINE + 'b',
                 'or',
                 'n',
                 SPIECE_UNDERLINE + 'in',
                 SPIECE_UNDERLINE + '',
                 '9',
                 '2',
                 '0',
                 '0',
                 '0',
                 ',',
                 SPIECE_UNDERLINE + 'and',
                 SPIECE_UNDERLINE + 'this',
                 SPIECE_UNDERLINE + 'is',
                 SPIECE_UNDERLINE + 'f',
                 'al',
                 's',
                 'é',
                 '.',
             ]			,				)
         lowercase__     =  tokenizer.convert_tokens_to_ids(lowerCAmelCase)
         self.assertListEqual(
             lowerCAmelCase			,				[
                 value + tokenizer.fairseq_offset
                 for value in [8, 21, 84, 55, 24, 19, 7, 2, 6_02, 3_47, 3_47, 3_47, 3, 12, 66, 46, 72, 80, 6, 2, 4]
             ]			,				)

         lowercase__     =  tokenizer.convert_ids_to_tokens(lowerCAmelCase)
         self.assertListEqual(
             lowerCAmelCase			,				[
                 SPIECE_UNDERLINE + 'I',
                 SPIECE_UNDERLINE + 'was',
                 SPIECE_UNDERLINE + 'b',
                 'or',
                 'n',
                 SPIECE_UNDERLINE + 'in',
                 SPIECE_UNDERLINE + '',
                 '<unk>',
                 '2',
                 '0',
                 '0',
                 '0',
                 ',',
                 SPIECE_UNDERLINE + 'and',
                 SPIECE_UNDERLINE + 'this',
                 SPIECE_UNDERLINE + 'is',
                 SPIECE_UNDERLINE + 'f',
                 'al',
                 's',
                 '<unk>',
                 '.',
             ]			,				)


   @cached_property
   def 			UpperCAmelCase		(						self  :			int)	->				Dict:




         """simple docstring"""

         return XGLMTokenizer.from_pretrained('facebook/xglm-564M')


   def 			UpperCAmelCase		(						self  :			Optional[int])	->				Dict:




         """simple docstring"""

         with tempfile.NamedTemporaryFile() as f:
               shutil.copyfile(lowerCAmelCase			,				f.name)
               lowercase__     =  XGLMTokenizer(f.name			,				keep_accents=lowerCAmelCase)
               lowercase__     =  pickle.dumps(lowerCAmelCase)
         pickle.loads(lowerCAmelCase)


   def 			UpperCAmelCase		(						self  :			Optional[Any])	->				str:




         """simple docstring"""

         if not self.test_rust_tokenizer:
               return

         lowercase__     =  self.get_tokenizer()
         lowercase__     =  self.get_rust_tokenizer()

         lowercase__     =  'I was born in 92000, and this is falsé.'

         lowercase__     =  tokenizer.tokenize(lowerCAmelCase)
         lowercase__     =  rust_tokenizer.tokenize(lowerCAmelCase)
         self.assertListEqual(lowerCAmelCase			,				lowerCAmelCase)

         lowercase__     =  tokenizer.encode(lowerCAmelCase			,				add_special_tokens=lowerCAmelCase)
         lowercase__     =  rust_tokenizer.encode(lowerCAmelCase			,				add_special_tokens=lowerCAmelCase)
         self.assertListEqual(lowerCAmelCase			,				lowerCAmelCase)

         lowercase__     =  self.get_rust_tokenizer()
         lowercase__     =  tokenizer.encode(lowerCAmelCase)
         lowercase__     =  rust_tokenizer.encode(lowerCAmelCase)
         self.assertListEqual(lowerCAmelCase			,				lowerCAmelCase)


   @slow
   def 			UpperCAmelCase		(						self  :			List[str])	->				List[str]:




         """simple docstring"""

         lowercase__     =  'Hello World!'
         lowercase__     =  [2, 3_12_27, 44_47, 35]

         self.assertListEqual(lowerCAmelCase			,				self.big_tokenizer.encode(lowerCAmelCase))


   @slow
   def 			UpperCAmelCase		(						self  :			List[str])	->				Union[str, Any]:




         """simple docstring"""

         lowercase__     =  (
             'This is a very long text with a lot of weird characters, such as: . , ~ ? ( ) " [ ] ! : - . Also we will'
             ' add words that should not exsist and be tokenized to unk, such as saoneuhaoesuth'
         )
         # fmt: off
         lowercase__     =  [2, 10_18, 67, 11, 19_88, 26_17, 56_31, 2_78, 11, 34_07, 48, 7_16_30, 2_80_85, 4, 32_34, 1_57, 13, 6, 5, 6, 4, 35_26, 7_68, 15, 6_59, 57, 2_98, 39_83, 8_64, 1_29, 21, 6, 5, 1_36_75, 3_77, 6_52, 75_80, 1_03_41, 1_55, 28_17, 4_22, 16_66, 7, 16_74, 53, 1_13, 20_22_77, 1_78_92, 33, 60, 87, 4, 32_34, 1_57, 61, 26_67, 5_23_76, 19, 88, 23, 7_35]
         # fmt: on

         self.assertListEqual(lowerCAmelCase			,				self.big_tokenizer.encode(lowerCAmelCase))



   @slow
   def 			UpperCAmelCase		(						self  :			str)	->				Dict:




         """simple docstring"""

         lowercase__     =  {
             'input_ids': [[2, 10_88_25, 11_63, 15, 8_80_10, 4_73, 1_58_98, 1_57, 1_36_72, 18_57, 3_12, 8, 23_80_21, 11_63, 53, 1_36_72, 18_57, 3_12, 8, 5_32_83, 18_23_96, 8, 1_85_66, 16, 3_67_33, 41_01, 8, 2_30, 24_40_17, 12_25_53, 7, 15, 13_25_97, 4, 2_93, 1_25_11, 76_10, 4, 34_14, 13_25_97, 9, 4, 3_23_61, 3_62, 4, 7_34, 2_85_12, 3_25_69, 18, 4, 3_23_61, 2_60_96, 1_49_82, 73, 1_87_15, 2_14_33, 23_52_61, 15, 4_92, 1_24_27, 16, 53, 1_87_15, 2_14_33, 6_54_54, 15, 2_36_59, 5_63, 16, 2_78, 5_97, 28_43, 5_95, 79_31, 18_23_96, 6_41_86, 22, 8_86, 5_95, 13_29_81, 53, 2_55_40, 34_49, 4_39_82, 3_99_01, 59_51, 8_78, 3_30, 4, 2_76_94, 8_02_69, 3_12, 53, 65_17, 1_17_80, 6_11, 2_04_08, 5], [2, 6, 13_25_97, 67, 4_28_97, 33, 5_92, 8, 16_37_29, 2_55_40, 3_61, 13_69_97, 10_95_14, 17_32_30, 7, 5_01, 60, 10_29_13, 1_96, 56_31, 2_35, 6_32_43, 4_73, 6, 23_17_57, 74, 52_77, 79_05, 53, 30_95, 3_73_17, 22, 4_54, 18_38_74, 5], [2, 2_68, 3_12_98, 4_65_30, 6, 13_29_35, 4_38_31, 7, 5_97, 32, 24, 36_88, 98_65, 5]],
             'attention_mask': [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]
         }  # noqa: E501
         # fmt: on

         self.tokenizer_integration_test_util(
             expected_encoding=lowerCAmelCase			,				model_name='facebook/xglm-564M'			,				padding=lowerCAmelCase			,				)
