



'''simple docstring'''




import unittest

from transformers import AlbertTokenizer, AlbertTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin


a      						=					get_tests_dir("""fixtures/spiece.model""")

@require_sentencepiece
@require_tokenizers
class     UpperCamelCase_				(							__magic_name__   ,  unittest.TestCase    ):
	lowercase    =				AlbertTokenizer
	lowercase    =				AlbertTokenizerFast
	lowercase    =				True
	lowercase    =				True
	lowercase    =				True





	def 				_lowercase(						self					)    ->    Tuple:
								super().setUp()

								# We have a SentencePiece fixture for testing
								UpperCAmelCase  :	Union[str, Any]							  =	AlbertTokenizer(A					)
								tokenizer.save_pretrained(self.tmpdirname					)





	def 				_lowercase(						self	,	A					)    ->    int:
								UpperCAmelCase  :	str							  =	"""this is a test"""
								UpperCAmelCase  :	Any							  =	"""this is a test"""
								return input_text, output_text





	def 				_lowercase(						self					)    ->    Optional[int]:
								UpperCAmelCase  :	int							  =	"""<pad>"""
								UpperCAmelCase  :	Any							  =	0

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





	def 				_lowercase(						self					)    ->    Union[str, Any]:
								UpperCAmelCase  :	str							  =	list(self.get_tokenizer().get_vocab().keys()					)

								self.assertEqual(vocab_keys[0]	,	"""<pad>"""					)
								self.assertEqual(vocab_keys[1]	,	"""<unk>"""					)
								self.assertEqual(vocab_keys[-1]	,	"""▁eloquent"""					)
								self.assertEqual(len(A					)	,	30000					)





	def 				_lowercase(						self					)    ->    str:
								self.assertEqual(self.get_tokenizer().vocab_size	,	30000					)





	def 				_lowercase(						self					)    ->    Optional[int]:
								if not self.test_rust_tokenizer:
															return

								UpperCAmelCase  :	Union[str, Any]							  =	self.get_tokenizer()
								UpperCAmelCase  :	Optional[int]							  =	self.get_rust_tokenizer()

								UpperCAmelCase  :	Optional[int]							  =	"""I was born in 92000, and this is falsé."""

								UpperCAmelCase  :	List[Any]							  =	tokenizer.tokenize(A					)
								UpperCAmelCase  :	Union[str, Any]							  =	rust_tokenizer.tokenize(A					)
								self.assertListEqual(A	,	A					)

								UpperCAmelCase  :	Optional[int]							  =	tokenizer.encode(A	,	add_special_tokens=A					)
								UpperCAmelCase  :	Tuple							  =	rust_tokenizer.encode(A	,	add_special_tokens=A					)
								self.assertListEqual(A	,	A					)

								UpperCAmelCase  :	Union[str, Any]							  =	self.get_rust_tokenizer()
								UpperCAmelCase  :	Dict							  =	tokenizer.encode(A					)
								UpperCAmelCase  :	List[Any]							  =	rust_tokenizer.encode(A					)
								self.assertListEqual(A	,	A					)





	def 				_lowercase(						self					)    ->    Optional[int]:
								UpperCAmelCase  :	List[Any]							  =	AlbertTokenizer(A	,	keep_accents=A					)

								UpperCAmelCase  :	Union[str, Any]							  =	tokenizer.tokenize("""This is a test"""					)
								self.assertListEqual(A	,	["""▁this""", """▁is""", """▁a""", """▁test"""]					)

								self.assertListEqual(tokenizer.convert_tokens_to_ids(A					)	,	[48, 25, 21, 1289]					)

								UpperCAmelCase  :	List[str]							  =	tokenizer.tokenize("""I was born in 92000, and this is falsé."""					)
								self.assertListEqual(
								    A	,	["""▁i""", """▁was""", """▁born""", """▁in""", """▁9""", """2000""", """,""", """▁and""", """▁this""", """▁is""", """▁fal""", """s""", """é""", """."""]					)
								UpperCAmelCase  :	Tuple							  =	tokenizer.convert_tokens_to_ids(A					)
								self.assertListEqual(A	,	[31, 23, 386, 19, 561, 3050, 15, 17, 48, 25, 8256, 18, 1, 9]					)

								UpperCAmelCase  :	Any							  =	tokenizer.convert_ids_to_tokens(A					)
								self.assertListEqual(
								    A	,	["""▁i""", """▁was""", """▁born""", """▁in""", """▁9""", """2000""", """,""", """▁and""", """▁this""", """▁is""", """▁fal""", """s""", """<unk>""", """."""]	,	)





	def 				_lowercase(						self					)    ->    Optional[Any]:
								UpperCAmelCase  :	int							  =	AlbertTokenizer(A					)

								UpperCAmelCase  :	Dict							  =	tokenizer.encode("""sequence builders"""					)
								UpperCAmelCase  :	int							  =	tokenizer.encode("""multi-sequence build"""					)

								UpperCAmelCase  :	List[Any]							  =	tokenizer.build_inputs_with_special_tokens(A					)
								UpperCAmelCase  :	List[Any]							  =	tokenizer.build_inputs_with_special_tokens(A	,	A					)

								assert encoded_sentence == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id]
								assert encoded_pair == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id] + text_a + [
								    tokenizer.sep_token_id
								]






	@slow
	def 				_lowercase(						self					)    ->    Union[str, Any]:
								# fmt: off
								UpperCAmelCase  :	Union[str, Any]							  =	{"""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, 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], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 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]], """input_ids""": [[2, 21970, 13, 5, 6092, 167, 28, 7103, 2153, 673, 8, 7028, 12051, 18, 17, 7103, 2153, 673, 8, 3515, 18684, 8, 4461, 6, 1927, 297, 8, 12060, 2607, 18, 13, 5, 4461, 15, 10538, 38, 8, 135, 15, 822, 58, 15, 993, 10363, 15, 1460, 8005, 4461, 15, 993, 255, 2328, 9, 9, 9, 6, 26, 1112, 816, 3260, 13, 5, 103, 2377, 6, 17, 1112, 816, 2782, 13, 5, 103, 10641, 6, 29, 84, 2512, 2430, 782, 18684, 2761, 19, 808, 2430, 2556, 17, 855, 1480, 9477, 4091, 128, 11712, 15, 7103, 2153, 673, 17, 24883, 9990, 9, 3], [2, 11502, 25, 1006, 20, 782, 8, 11809, 855, 1732, 19393, 18667, 37, 367, 21018, 69, 1854, 34, 11860, 19124, 27, 156, 225, 17, 193, 4141, 19, 65, 9124, 9, 3, 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], [2, 14, 2231, 886, 2385, 17659, 84, 14, 16792, 1952, 9, 3, 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]], """token_type_ids""": [[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, 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, 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]]}  # noqa: E501
								# fmt: on

								self.tokenizer_integration_test_util(
								    expected_encoding=A	,	model_name="""albert-base-v2"""	,	revision="""6b6560eaf5ff2e250b00c50f380c5389a9c2d82e"""	,	)






'''simple docstring'''




import unittest

import numpy as np
import torch

from diffusers import VersatileDiffusionImageVariationPipeline
from diffusers.utils.testing_utils import load_image, require_torch_gpu, slow, torch_device


a     :    Tuple      						=					False

class     UpperCamelCase_				(							unittest.TestCase    ):
	pass




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





	def 				_lowercase(						self					)    ->    Optional[Any]:
								UpperCAmelCase  :	Any							  =	VersatileDiffusionImageVariationPipeline.from_pretrained("""shi-labs/versatile-diffusion"""					)
								pipe.to(A					)
								pipe.set_progress_bar_config(disable=A					)

								UpperCAmelCase  :	List[str]							  =	load_image(
								    """https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/versatile_diffusion/benz.jpg"""					)
								UpperCAmelCase  :	List[Any]							  =	torch.manual_seed(0					)
								UpperCAmelCase  :	List[str]							  =	pipe(
								    image=A	,	generator=A	,	guidance_scale=7.5	,	num_inference_steps=50	,	output_type="""numpy"""	,	).images

								UpperCAmelCase  :	Tuple							  =	image[0, 253:256, 253:256, -1]

								assert image.shape == (1, 512, 512, 3)
								UpperCAmelCase  :	List[str]							  =	np.array([0.0_4_4_1, 0.0_4_6_9, 0.0_5_0_7, 0.0_5_7_5, 0.0_6_3_2, 0.0_6_5_0, 0.0_8_6_5, 0.0_9_0_9, 0.0_9_4_5]					)

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

