
'''simple docstring'''





import gc
import tempfile
import unittest

import numpy as np
import torch

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


A							     = False



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



  '''simple docstring'''






  def 		_lowerCamelCase						(self	:			List[str]     ) ->							Tuple:
        # clean up the VRAM after each test
        super().tearDown()
        gc.collect()
        torch.cuda.empty_cache()

  def 		_lowerCamelCase						(self	:			Optional[Any]     ) ->							Dict:
        snake_case_    							=				VersatileDiffusionDualGuidedPipeline.from_pretrained("shi-labs/versatile-diffusion"     )
        # remove text_unet
        pipe.remove_unused_weights()
        pipe.to(lowerCAmelCase_     )
        pipe.set_progress_bar_config(disable=lowerCAmelCase_     )

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

        snake_case_    							=				torch.manual_seed(0     )
        snake_case_    							=				pipe(
            prompt="first prompt"						,			image=lowerCAmelCase_						,			text_to_image_strength=0.75						,			generator=lowerCAmelCase_						,			guidance_scale=7.5						,			num_inference_steps=2						,			output_type="numpy"						,			).images

        with tempfile.TemporaryDirectory() as tmpdirname:
              pipe.save_pretrained(lowerCAmelCase_     )
              snake_case_    							=				VersatileDiffusionDualGuidedPipeline.from_pretrained(lowerCAmelCase_     )

        pipe.to(lowerCAmelCase_     )
        pipe.set_progress_bar_config(disable=lowerCAmelCase_     )

        snake_case_    							=				generator.manual_seed(0     )
        snake_case_    							=				pipe(
            prompt="first prompt"						,			image=lowerCAmelCase_						,			text_to_image_strength=0.75						,			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	:			str     ) ->							Optional[int]:
        snake_case_    							=				VersatileDiffusionDualGuidedPipeline.from_pretrained("shi-labs/versatile-diffusion"     )
        pipe.remove_unused_weights()
        pipe.to(lowerCAmelCase_     )
        pipe.set_progress_bar_config(disable=lowerCAmelCase_     )

        snake_case_    							=				"cyberpunk 2077"
        snake_case_    							=				load_image(
            "https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/versatile_diffusion/benz.jpg"     )
        snake_case_    							=				torch.manual_seed(0     )
        snake_case_    							=				pipe(
            prompt=lowerCAmelCase_						,			image=lowerCAmelCase_						,			text_to_image_strength=0.75						,			generator=lowerCAmelCase_						,			guidance_scale=7.5						,			num_inference_steps=50						,			output_type="numpy"						,			).images

        snake_case_    							=				image[0, 2_53:2_56, 2_53:2_56, -1]

        assert image.shape == (1, 5_12, 5_12, 3)
        snake_case_    							=				np.array([0.0_787, 0.0_849, 0.0_826, 0.0_812, 0.0_807, 0.0_795, 0.0_818, 0.0_798, 0.0_779]     )

        assert np.abs(image_slice.flatten() - expected_slice     ).max() < 1E-2





"""simple docstring"""







import inspect
import json
import os
import tempfile
import unittest

from transformers.models.speech_to_text_a import SpeechaTextaTokenizer
from transformers.models.speech_to_text_a.tokenization_speech_to_text_a import VOCAB_FILES_NAMES

from ...test_tokenization_common import TokenizerTesterMixin
class 				lowerCamelCase							(      __SCREAMING_SNAKE_CASE					,       unittest.TestCase			):


							"""simple docstring"""
							SCREAMING_SNAKE_CASE              =   SpeechaTextaTokenizer
							SCREAMING_SNAKE_CASE              =   False






							def        lowerCAmelCase  (    self			:  Dict					):
													super().setUp()

													UpperCAmelCase__												=     '''<s> <pad> </s> <unk> here@@ a couple of@@ words for the he@@ re@@ vocab'''.split(''' '''					)
													UpperCAmelCase__												=     ['''he re</w> 123''', '''here a 1456''']
													UpperCAmelCase__												=     dict(zip(lowerCamelCase_		,			range(len(lowerCamelCase_					)					)					)					)

													UpperCAmelCase__												=     {'''pad_token''': '''<pad>''', '''unk_token''': '''<unk>''', '''bos_token''': '''<s>''', '''eos_token''': '''</s>'''}

													UpperCAmelCase__												=     tempfile.mkdtemp()
													UpperCAmelCase__												=     os.path.join(self.tmpdirname		,			VOCAB_FILES_NAMES['''vocab_file''']					)
													UpperCAmelCase__												=     os.path.join(self.tmpdirname		,			VOCAB_FILES_NAMES['''merges_file''']					)

													with open(self.vocab_file		,			'''w'''		,			encoding='''utf-8'''					) as fp:
																			fp.write(json.dumps(lowerCamelCase_					) + '''\n'''					)

													with open(self.merges_file		,			'''w'''					) as fp:
																			fp.write('''\n'''.join(lowerCamelCase_					)					)






							def        lowerCAmelCase  (    self			:  Union[str, Any]					):
													UpperCAmelCase__												=     list(self.get_tokenizer().get_vocab().keys()					)

													self.assertEqual(vocab_keys[0]		,			'''<s>'''					)
													self.assertEqual(vocab_keys[1]		,			'''<pad>'''					)
													self.assertEqual(vocab_keys[-1]		,			'''vocab'''					)
													self.assertEqual(len(lowerCamelCase_					)		,			14					)






							def        lowerCAmelCase  (    self			:  Optional[Any]					):
													self.assertEqual(self.get_tokenizer().vocab_size		,			14					)






							def        lowerCAmelCase  (    self			:  Any					):
													UpperCAmelCase__												=     SpeechaTextaTokenizer.from_pretrained(self.tmpdirname					)

													# make sure @@ is correctly concatenated
													UpperCAmelCase__												=     [4, 6, 8, 7, 10]  # ["here@@", "couple", "words", "of@@", "the"]
													UpperCAmelCase__												=     tokenizer.decode(lowerCamelCase_					)

													self.assertTrue(output_string == '''herecouple words ofthe'''					)






							def        lowerCAmelCase  (    self			:  int					):
													UpperCAmelCase__												=     SpeechaTextaTokenizer.from_pretrained(self.tmpdirname					)

													with tempfile.TemporaryDirectory() as tmp_dirname:
																			tokenizer.save_pretrained(lowerCamelCase_					)
																			os.remove(os.path.join(lowerCamelCase_		,			'''merges.txt'''					)					)

																			# load tokenizer without merges file should not throw an error
																			UpperCAmelCase__												=     SpeechaTextaTokenizer.from_pretrained(lowerCamelCase_					)

													with tempfile.TemporaryDirectory() as tmp_dirname:
																			# save tokenizer and load again
																			tokenizer.save_pretrained(lowerCamelCase_					)
																			UpperCAmelCase__												=     SpeechaTextaTokenizer.from_pretrained(lowerCamelCase_					)

													self.assertIsNotNone(lowerCamelCase_					)






							def        lowerCAmelCase  (    self			:  int					):
													if not self.test_slow_tokenizer:
																			return

													UpperCAmelCase__												=     inspect.signature(self.tokenizer_class.__init__					)
													UpperCAmelCase__												=     self.get_tokenizer()

													for parameter_name, parameter in signature.parameters.items():
																			if parameter.default != inspect.Parameter.empty and parameter_name != "merges_file":
																									self.assertIn(lowerCamelCase_		,			tokenizer.init_kwargs					)