"""simple docstring"""






import os
import unittest

from huggingface_hub.utils import are_progress_bars_disabled

import transformers.models.bart.tokenization_bart
from transformers import logging
from transformers.testing_utils import CaptureLogger, mockenv, mockenv_context
from transformers.utils.logging import disable_progress_bar, enable_progress_bar
class        snake_case (				unittest.TestCase       ):




     """simple docstring"""

     def 	__lowerCAmelCase		(       self     :			List[str]    ):
         UpperCAmelCase__    =							logging.get_logger()

         # the current default level is logging.WARNING
         UpperCAmelCase__    =							logging.get_verbosity()

         logging.set_verbosity_error()
         self.assertEqual(logger.getEffectiveLevel()					,logging.get_verbosity()    )

         logging.set_verbosity_warning()
         self.assertEqual(logger.getEffectiveLevel()					,logging.get_verbosity()    )

         logging.set_verbosity_info()
         self.assertEqual(logger.getEffectiveLevel()					,logging.get_verbosity()    )

         logging.set_verbosity_debug()
         self.assertEqual(logger.getEffectiveLevel()					,logging.get_verbosity()    )

         # restore to the original level
         logging.set_verbosity(lowerCamelCase__    )







     def 	__lowerCAmelCase		(       self     :			int    ):
         UpperCAmelCase__    =							logging.get_verbosity()

         UpperCAmelCase__    =							logging.get_logger('transformers.models.bart.tokenization_bart'    )
         UpperCAmelCase__    =							'Testing 1, 2, 3'

         # should be able to log warnings (if default settings weren't overridden by `pytest --log-level-all`)
         if level_origin <= logging.WARNING:
             with CaptureLogger(lowerCamelCase__    ) as cl:
                 logger.warning(lowerCamelCase__    )
             self.assertEqual(cl.out					,msg + '\n'    )

         # this is setting the level for all of `transformers.*` loggers
         logging.set_verbosity_error()

         # should not be able to log warnings
         with CaptureLogger(lowerCamelCase__    ) as cl:
             logger.warning(lowerCamelCase__    )
         self.assertEqual(cl.out					,''    )

         # should be able to log warnings again
         logging.set_verbosity_warning()
         with CaptureLogger(lowerCamelCase__    ) as cl:
             logger.warning(lowerCamelCase__    )
         self.assertEqual(cl.out					,msg + '\n'    )

         # restore to the original level
         logging.set_verbosity(lowerCamelCase__    )







     @mockenv(TRANSFORMERS_VERBOSITY='error'    )
     def 	__lowerCAmelCase		(       self     :			str    ):
         # reset for the env var to take effect, next time some logger call is made
         transformers.utils.logging._reset_library_root_logger()
         # this action activates the env var
         UpperCAmelCase__    =							logging.get_logger('transformers.models.bart.tokenization_bart'    )

         UpperCAmelCase__    =							os.getenv('TRANSFORMERS_VERBOSITY'					,lowerCamelCase__    )
         UpperCAmelCase__    =							logging.log_levels[env_level_str]

         UpperCAmelCase__    =							logging.get_verbosity()
         self.assertEqual(
             lowerCamelCase__					,lowerCamelCase__					,f'''TRANSFORMERS_VERBOSITY={env_level_str}/{env_level}, but internal verbosity is {current_level}'''					,)

         # restore to the original level
         UpperCAmelCase__    =							''
         transformers.utils.logging._reset_library_root_logger()







     @mockenv(TRANSFORMERS_VERBOSITY='super-error'    )
     def 	__lowerCAmelCase		(       self     :			Any    ):
         # reset for the env var to take effect, next time some logger call is made
         transformers.utils.logging._reset_library_root_logger()
         UpperCAmelCase__    =							logging.logging.getLogger()
         with CaptureLogger(lowerCamelCase__    ) as cl:
             # this action activates the env var
             logging.get_logger('transformers.models.bart.tokenization_bart'    )
         self.assertIn('Unknown option TRANSFORMERS_VERBOSITY=super-error'					,cl.out    )

         # no need to restore as nothing was changed







     def 	__lowerCAmelCase		(       self     :			Optional[Any]    ):
         # testing `logger.warning_advice()`
         transformers.utils.logging._reset_library_root_logger()

         UpperCAmelCase__    =							logging.get_logger('transformers.models.bart.tokenization_bart'    )
         UpperCAmelCase__    =							'Testing 1, 2, 3'

         with mockenv_context(TRANSFORMERS_NO_ADVISORY_WARNINGS='1'    ):
             # nothing should be logged as env var disables this method
             with CaptureLogger(lowerCamelCase__    ) as cl:
                 logger.warning_advice(lowerCamelCase__    )
             self.assertEqual(cl.out					,''    )

         with mockenv_context(TRANSFORMERS_NO_ADVISORY_WARNINGS=''    ):
             # should log normally as TRANSFORMERS_NO_ADVISORY_WARNINGS is unset
             with CaptureLogger(lowerCamelCase__    ) as cl:
                 logger.warning_advice(lowerCamelCase__    )
             self.assertEqual(cl.out					,msg + '\n'    )






def 						a_		(      ):
    disable_progress_bar()
    assert are_progress_bars_disabled()

    enable_progress_bar()
    assert not are_progress_bars_disabled()




"""simple docstring"""






import gc
import tempfile
import unittest

import numpy as np
import torch

from diffusers import VersatileDiffusionPipeline
from diffusers.utils.testing_utils import load_image, nightly, require_torch_gpu, torch_device


lowerCAmelCase__						:						Union[str, Any]		  =			False
class        snake_case (				unittest.TestCase       ):




					"""simple docstring"""

					pass






@nightly
@require_torch_gpu
class        snake_case (				unittest.TestCase       ):




					"""simple docstring"""

					def 	__lowerCAmelCase		(       self     :			Any    ):
									# clean up the VRAM after each test
									super().tearDown()
									gc.collect()
									torch.cuda.empty_cache()







					def 	__lowerCAmelCase		(       self     :			Any    ):
									UpperCAmelCase__    =							VersatileDiffusionPipeline.from_pretrained('shi-labs/versatile-diffusion'					,torch_dtype=torch.floataa    )
									pipe.to(lowerCamelCase__    )
									pipe.set_progress_bar_config(disable=lowerCamelCase__    )

									UpperCAmelCase__    =							load_image(
									    'https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/versatile_diffusion/benz.jpg'    )

									UpperCAmelCase__    =							torch.manual_seed(0    )
									UpperCAmelCase__    =							pipe.dual_guided(
									    prompt='first prompt'					,image=lowerCamelCase__					,text_to_image_strength=0.7_5					,generator=lowerCamelCase__					,guidance_scale=7.5					,num_inference_steps=2					,output_type='numpy'					,).images

									with tempfile.TemporaryDirectory() as tmpdirname:
													pipe.save_pretrained(lowerCamelCase__    )
													UpperCAmelCase__    =							VersatileDiffusionPipeline.from_pretrained(lowerCamelCase__					,torch_dtype=torch.floataa    )
									pipe.to(lowerCamelCase__    )
									pipe.set_progress_bar_config(disable=lowerCamelCase__    )

									UpperCAmelCase__    =							generator.manual_seed(0    )
									UpperCAmelCase__    =							pipe.dual_guided(
									    prompt='first prompt'					,image=lowerCamelCase__					,text_to_image_strength=0.7_5					,generator=lowerCamelCase__					,guidance_scale=7.5					,num_inference_steps=2					,output_type='numpy'					,).images

									assert np.abs(image - new_image    ).sum() < 1e-5, "Models don't have the same forward pass"







					def 	__lowerCAmelCase		(       self     :			Optional[int]    ):
									UpperCAmelCase__    =							VersatileDiffusionPipeline.from_pretrained('shi-labs/versatile-diffusion'					,torch_dtype=torch.floataa    )
									pipe.to(lowerCamelCase__    )
									pipe.set_progress_bar_config(disable=lowerCamelCase__    )

									UpperCAmelCase__    =							'cyberpunk 2077'
									UpperCAmelCase__    =							load_image(
									    'https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/versatile_diffusion/benz.jpg'    )
									UpperCAmelCase__    =							torch.manual_seed(0    )
									UpperCAmelCase__    =							pipe.dual_guided(
									    prompt=lowerCamelCase__					,image=lowerCamelCase__					,text_to_image_strength=0.7_5					,generator=lowerCamelCase__					,guidance_scale=7.5					,num_inference_steps=50					,output_type='numpy'					,).images

									UpperCAmelCase__    =							image[0, 253:256, 253:256, -1]

									assert image.shape == (1, 512, 512, 3)
									UpperCAmelCase__    =							np.array([0.1_4_4_8, 0.1_6_1_9, 0.1_7_4_1, 0.1_0_8_6, 0.1_1_4_7, 0.1_1_2_8, 0.1_1_9_9, 0.1_1_6_5, 0.1_0_0_1]    )

									assert np.abs(image_slice.flatten() - expected_slice    ).max() < 1e-1

									UpperCAmelCase__    =							'A painting of a squirrel eating a burger '
									UpperCAmelCase__    =							torch.manual_seed(0    )
									UpperCAmelCase__    =							pipe.text_to_image(
									    prompt=lowerCamelCase__					,generator=lowerCamelCase__					,guidance_scale=7.5					,num_inference_steps=50					,output_type='numpy'    ).images

									UpperCAmelCase__    =							image[0, 253:256, 253:256, -1]

									assert image.shape == (1, 512, 512, 3)
									UpperCAmelCase__    =							np.array([0.3_3_6_7, 0.3_1_6_9, 0.2_6_5_6, 0.3_8_7_0, 0.4_7_9_0, 0.3_7_9_6, 0.4_0_0_9, 0.4_8_7_8, 0.4_7_7_8]    )

									assert np.abs(image_slice.flatten() - expected_slice    ).max() < 1e-1

									UpperCAmelCase__    =							pipe.image_variation(lowerCamelCase__					,generator=lowerCamelCase__					,output_type='numpy'    ).images

									UpperCAmelCase__    =							image[0, 253:256, 253:256, -1]

									assert image.shape == (1, 512, 512, 3)
									UpperCAmelCase__    =							np.array([0.3_0_7_6, 0.3_1_2_3, 0.3_2_8_4, 0.3_7_8_2, 0.3_7_7_0, 0.3_8_9_4, 0.4_2_9_7, 0.4_3_3_1, 0.4_4_5_6]    )

									assert np.abs(image_slice.flatten() - expected_slice    ).max() < 1e-1



