


import os
import shutil
import sys
import tempfile
import unittest
from pathlib import Path

import pytest

import transformers
from transformers import (
    BERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
    GPT2_PRETRAINED_CONFIG_ARCHIVE_MAP,
    AutoTokenizer,
    BertConfig,
    BertTokenizer,
    BertTokenizerFast,
    CTRLTokenizer,
    GPTaTokenizer,
    GPTaTokenizerFast,
    PreTrainedTokenizerFast,
    RobertaTokenizer,
    RobertaTokenizerFast,
    is_tokenizers_available,
)
from transformers.models.auto.configuration_auto import CONFIG_MAPPING, AutoConfig
from transformers.models.auto.tokenization_auto import (
    TOKENIZER_MAPPING,
    get_tokenizer_config,
    tokenizer_class_from_name,
)
from transformers.models.roberta.configuration_roberta import RobertaConfig
from transformers.testing_utils import (
    DUMMY_DIFF_TOKENIZER_IDENTIFIER,
    DUMMY_UNKNOWN_IDENTIFIER,
    SMALL_MODEL_IDENTIFIER,
    RequestCounter,
    require_tokenizers,
    slow,
)


sys.path.append(str(Path(__file__).parent.parent.parent.parent / "utils"))

from test_module.custom_configuration import CustomConfig  # noqa E402
from test_module.custom_tokenization import CustomTokenizer  # noqa E402


if is_tokenizers_available():
    from test_module.custom_tokenization_fast import CustomTokenizerFast


class     lowercase__  (					unittest.TestCase		):






  def 			_UpperCAmelCase  (					self      :					Optional[int] ):




         """simple docstring"""







         UpperCAmelCase__										=     0






  @slow
  def 			_UpperCAmelCase  (					self      :					Optional[int] ):




         """simple docstring"""







         for model_name in (x for x in BERT_PRETRAINED_CONFIG_ARCHIVE_MAP.keys() if "japanese" not in x):
                UpperCAmelCase__										=     AutoTokenizer.from_pretrained(_lowercase )
                self.assertIsNotNone(_lowercase )
                self.assertIsInstance(_lowercase		,						(BertTokenizer, BertTokenizerFast) )
                self.assertGreater(len(_lowercase )		,						0 )

         for model_name in GPT2_PRETRAINED_CONFIG_ARCHIVE_MAP.keys():
                UpperCAmelCase__										=     AutoTokenizer.from_pretrained(_lowercase )
                self.assertIsNotNone(_lowercase )
                self.assertIsInstance(_lowercase		,						(GPTaTokenizer, GPTaTokenizerFast) )
                self.assertGreater(len(_lowercase )		,						0 )






  def 			_UpperCAmelCase  (					self      :					str ):




         """simple docstring"""







         UpperCAmelCase__										=     AutoTokenizer.from_pretrained(_lowercase )
         self.assertIsInstance(_lowercase		,						(BertTokenizer, BertTokenizerFast) )
         self.assertEqual(tokenizer.vocab_size		,						12 )






  def 			_UpperCAmelCase  (					self      :					Optional[int] ):




         """simple docstring"""







         UpperCAmelCase__										=     AutoTokenizer.from_pretrained(_lowercase )
         self.assertIsInstance(_lowercase		,						(RobertaTokenizer, RobertaTokenizerFast) )
         self.assertEqual(tokenizer.vocab_size		,						20 )






  def 			_UpperCAmelCase  (					self      :					List[Any] ):




         """simple docstring"""







         UpperCAmelCase__										=     AutoConfig.from_pretrained(_lowercase )
         self.assertIsInstance(_lowercase		,						_lowercase )
         # Check that tokenizer_type ≠ model_type
         UpperCAmelCase__										=     AutoTokenizer.from_pretrained(_lowercase		,						config=_lowercase )
         self.assertIsInstance(_lowercase		,						(BertTokenizer, BertTokenizerFast) )
         self.assertEqual(tokenizer.vocab_size		,						12 )






  def 			_UpperCAmelCase  (					self      :					Dict ):




         """simple docstring"""







         with tempfile.TemporaryDirectory() as tmp_dir:
                shutil.copy("./tests/fixtures/vocab.txt"		,						os.path.join(_lowercase		,						"vocab.txt" ) )

                UpperCAmelCase__										=     AutoTokenizer.from_pretrained(_lowercase		,						tokenizer_type="bert"		,						use_fast=_lowercase )
                self.assertIsInstance(_lowercase		,						_lowercase )

         with tempfile.TemporaryDirectory() as tmp_dir:
                shutil.copy("./tests/fixtures/vocab.json"		,						os.path.join(_lowercase		,						"vocab.json" ) )
                shutil.copy("./tests/fixtures/merges.txt"		,						os.path.join(_lowercase		,						"merges.txt" ) )

                UpperCAmelCase__										=     AutoTokenizer.from_pretrained(_lowercase		,						tokenizer_type="gpt2"		,						use_fast=_lowercase )
                self.assertIsInstance(_lowercase		,						_lowercase )






  @require_tokenizers
  def 			_UpperCAmelCase  (					self      :					Tuple ):




         """simple docstring"""







         with tempfile.TemporaryDirectory() as tmp_dir:
                shutil.copy("./tests/fixtures/vocab.txt"		,						os.path.join(_lowercase		,						"vocab.txt" ) )

                UpperCAmelCase__										=     AutoTokenizer.from_pretrained(_lowercase		,						tokenizer_type="bert" )
                self.assertIsInstance(_lowercase		,						_lowercase )

         with tempfile.TemporaryDirectory() as tmp_dir:
                shutil.copy("./tests/fixtures/vocab.json"		,						os.path.join(_lowercase		,						"vocab.json" ) )
                shutil.copy("./tests/fixtures/merges.txt"		,						os.path.join(_lowercase		,						"merges.txt" ) )

                UpperCAmelCase__										=     AutoTokenizer.from_pretrained(_lowercase		,						tokenizer_type="gpt2" )
                self.assertIsInstance(_lowercase		,						_lowercase )






  def 			_UpperCAmelCase  (					self      :					str ):




         """simple docstring"""







         with pytest.raises(_lowercase ):
                AutoTokenizer.from_pretrained("./"		,						tokenizer_type="xxx" )






  @require_tokenizers
  def 			_UpperCAmelCase  (					self      :					Union[str, Any] ):




         """simple docstring"""







         for tokenizer_class in [BertTokenizer, BertTokenizerFast, AutoTokenizer]:
                UpperCAmelCase__										=     tokenizer_class.from_pretrained("wietsedv/bert-base-dutch-cased" )
                self.assertIsInstance(_lowercase		,						(BertTokenizer, BertTokenizerFast) )

                if isinstance(_lowercase		,						_lowercase ):
                       self.assertEqual(tokenizer.basic_tokenizer.do_lower_case		,						_lowercase )
                else:
                       self.assertEqual(tokenizer.do_lower_case		,						_lowercase )

                self.assertEqual(tokenizer.model_max_length		,						5_12 )






  @require_tokenizers
  def 			_UpperCAmelCase  (					self      :					Optional[Any] ):




         """simple docstring"""







         for tokenizer_class in [BertTokenizer, BertTokenizerFast, AutoTokenizer]:
                with self.assertRaisesRegex(
                    _lowercase		,						"julien-c/herlolip-not-exists is not a local folder and is not a valid model identifier"		,						):
                       UpperCAmelCase__										=     tokenizer_class.from_pretrained("julien-c/herlolip-not-exists" )






  def 			_UpperCAmelCase  (					self      :					Tuple ):




         """simple docstring"""







         UpperCAmelCase__										=     TOKENIZER_MAPPING.values()
         UpperCAmelCase__										=     []

         for slow_tok, fast_tok in tokenizers:
                if slow_tok is not None:
                       tokenizer_names.append(slow_tok.__name__ )

                if fast_tok is not None:
                       tokenizer_names.append(fast_tok.__name__ )

         for tokenizer_name in tokenizer_names:
                # must find the right class
                tokenizer_class_from_name(_lowercase )






  @require_tokenizers
  def 			_UpperCAmelCase  (					self      :					Optional[Any] ):




         """simple docstring"""







         self.assertIsInstance(AutoTokenizer.from_pretrained("bert-base-cased"		,						use_fast=_lowercase )		,						_lowercase )
         self.assertIsInstance(AutoTokenizer.from_pretrained("bert-base-cased" )		,						_lowercase )






  @require_tokenizers
  def 			_UpperCAmelCase  (					self      :					List[Any] ):




         """simple docstring"""







         UpperCAmelCase__										=     AutoTokenizer.from_pretrained("distilbert-base-uncased"		,						do_lower_case=_lowercase )
         UpperCAmelCase__										=     "Hello, world. How are you?"
         UpperCAmelCase__										=     tokenizer.tokenize(_lowercase )
         self.assertEqual("[UNK]"		,						tokens[0] )

         UpperCAmelCase__										=     AutoTokenizer.from_pretrained("microsoft/mpnet-base"		,						do_lower_case=_lowercase )
         UpperCAmelCase__										=     tokenizer.tokenize(_lowercase )
         self.assertEqual("[UNK]"		,						tokens[0] )






  @require_tokenizers
  def 			_UpperCAmelCase  (					self      :					Optional[int] ):




         """simple docstring"""







         UpperCAmelCase__										=     AutoTokenizer.from_pretrained("robot-test/dummy-tokenizer-fast-with-model-config" )
         self.assertEqual(type(_lowercase )		,						_lowercase )
         self.assertEqual(tokenizer.model_max_length		,						5_12 )
         self.assertEqual(tokenizer.vocab_size		,						3_00_00 )
         self.assertEqual(tokenizer.unk_token		,						"[UNK]" )
         self.assertEqual(tokenizer.padding_side		,						"right" )
         self.assertEqual(tokenizer.truncation_side		,						"right" )






  def 			_UpperCAmelCase  (					self      :					str ):




         """simple docstring"""







         UpperCAmelCase__										=     AutoTokenizer.from_pretrained(_lowercase )
         self.assertIsInstance(_lowercase		,						(BertTokenizer, BertTokenizerFast) )
         with tempfile.TemporaryDirectory() as tmp_dir:
                tokenizer.save_pretrained(_lowercase )
                UpperCAmelCase__										=     AutoTokenizer.from_pretrained(_lowercase )

         self.assertIsInstance(_lowercase		,						tokenizer.__class__ )
         self.assertEqual(tokenizera.vocab_size		,						12 )






  def 			_UpperCAmelCase  (					self      :					Tuple ):




         """simple docstring"""







         UpperCAmelCase__										=     AutoTokenizer.from_pretrained("ctrl" )
         # There is no fast CTRL so this always gives us a slow tokenizer.
         self.assertIsInstance(_lowercase		,						_lowercase )






  def 			_UpperCAmelCase  (					self      :					int ):




         """simple docstring"""







         UpperCAmelCase__										=     get_tokenizer_config("bert-base-cased" )
         UpperCAmelCase__										=     config.pop("_commit_hash"		,						_lowercase )
         # If we ever update bert-base-cased tokenizer config, this dict here will need to be updated.
         self.assertEqual(_lowercase		,						{"do_lower_case": False} )

         # This model does not have a tokenizer_config so we get back an empty dict.
         UpperCAmelCase__										=     get_tokenizer_config(_lowercase )
         self.assertDictEqual(_lowercase		,						{} )

         # A tokenizer saved with `save_pretrained` always creates a tokenizer config.
         UpperCAmelCase__										=     AutoTokenizer.from_pretrained(_lowercase )
         with tempfile.TemporaryDirectory() as tmp_dir:
                tokenizer.save_pretrained(_lowercase )
                UpperCAmelCase__										=     get_tokenizer_config(_lowercase )

         # Check the class of the tokenizer was properly saved (note that it always saves the slow class).
         self.assertEqual(config["tokenizer_class"]		,						"BertTokenizer" )






  def 			_UpperCAmelCase  (					self      :					List[str] ):




         """simple docstring"""







         try:
                AutoConfig.register("custom"		,						_lowercase )

                AutoTokenizer.register(_lowercase		,						slow_tokenizer_class=_lowercase )
                # Trying to register something existing in the Transformers library will raise an error
                with self.assertRaises(_lowercase ):
                       AutoTokenizer.register(_lowercase		,						slow_tokenizer_class=_lowercase )

                UpperCAmelCase__										=     CustomTokenizer.from_pretrained(_lowercase )
                with tempfile.TemporaryDirectory() as tmp_dir:
                       tokenizer.save_pretrained(_lowercase )

                       UpperCAmelCase__										=     AutoTokenizer.from_pretrained(_lowercase )
                       self.assertIsInstance(_lowercase		,						_lowercase )

         finally:
                if "custom" in CONFIG_MAPPING._extra_content:
                       del CONFIG_MAPPING._extra_content["custom"]
                if CustomConfig in TOKENIZER_MAPPING._extra_content:
                       del TOKENIZER_MAPPING._extra_content[CustomConfig]






  @require_tokenizers
  def 			_UpperCAmelCase  (					self      :					Union[str, Any] ):




         """simple docstring"""







         try:
                AutoConfig.register("custom"		,						_lowercase )

                # Can register in two steps
                AutoTokenizer.register(_lowercase		,						slow_tokenizer_class=_lowercase )
                self.assertEqual(TOKENIZER_MAPPING[CustomConfig]		,						(CustomTokenizer, None) )
                AutoTokenizer.register(_lowercase		,						fast_tokenizer_class=_lowercase )
                self.assertEqual(TOKENIZER_MAPPING[CustomConfig]		,						(CustomTokenizer, CustomTokenizerFast) )

                del TOKENIZER_MAPPING._extra_content[CustomConfig]
                # Can register in one step
                AutoTokenizer.register(
                    _lowercase		,						slow_tokenizer_class=_lowercase		,						fast_tokenizer_class=_lowercase )
                self.assertEqual(TOKENIZER_MAPPING[CustomConfig]		,						(CustomTokenizer, CustomTokenizerFast) )

                # Trying to register something existing in the Transformers library will raise an error
                with self.assertRaises(_lowercase ):
                       AutoTokenizer.register(_lowercase		,						fast_tokenizer_class=_lowercase )

                # We pass through a bert tokenizer fast cause there is no converter slow to fast for our new toknizer
                # and that model does not have a tokenizer.json
                with tempfile.TemporaryDirectory() as tmp_dir:
                       UpperCAmelCase__										=     BertTokenizerFast.from_pretrained(_lowercase )
                       bert_tokenizer.save_pretrained(_lowercase )
                       UpperCAmelCase__										=     CustomTokenizerFast.from_pretrained(_lowercase )

                with tempfile.TemporaryDirectory() as tmp_dir:
                       tokenizer.save_pretrained(_lowercase )

                       UpperCAmelCase__										=     AutoTokenizer.from_pretrained(_lowercase )
                       self.assertIsInstance(_lowercase		,						_lowercase )

                       UpperCAmelCase__										=     AutoTokenizer.from_pretrained(_lowercase		,						use_fast=_lowercase )
                       self.assertIsInstance(_lowercase		,						_lowercase )

         finally:
                if "custom" in CONFIG_MAPPING._extra_content:
                       del CONFIG_MAPPING._extra_content["custom"]
                if CustomConfig in TOKENIZER_MAPPING._extra_content:
                       del TOKENIZER_MAPPING._extra_content[CustomConfig]






  def 			_UpperCAmelCase  (					self      :					List[str] ):




         """simple docstring"""







         with self.assertRaises(_lowercase ):
                UpperCAmelCase__										=     AutoTokenizer.from_pretrained("hf-internal-testing/test_dynamic_tokenizer" )
         # If remote code is disabled, we can't load this config.
         with self.assertRaises(_lowercase ):
                UpperCAmelCase__										=     AutoTokenizer.from_pretrained(
                    "hf-internal-testing/test_dynamic_tokenizer"		,						trust_remote_code=_lowercase )

         UpperCAmelCase__										=     AutoTokenizer.from_pretrained("hf-internal-testing/test_dynamic_tokenizer"		,						trust_remote_code=_lowercase )
         self.assertTrue(tokenizer.special_attribute_present )
         # Test tokenizer can be reloaded.
         with tempfile.TemporaryDirectory() as tmp_dir:
                tokenizer.save_pretrained(_lowercase )
                UpperCAmelCase__										=     AutoTokenizer.from_pretrained(_lowercase		,						trust_remote_code=_lowercase )
         self.assertTrue(reloaded_tokenizer.special_attribute_present )

         if is_tokenizers_available():
                self.assertEqual(tokenizer.__class__.__name__		,						"NewTokenizerFast" )
                self.assertEqual(reloaded_tokenizer.__class__.__name__		,						"NewTokenizerFast" )

                # Test we can also load the slow version
                UpperCAmelCase__										=     AutoTokenizer.from_pretrained(
                    "hf-internal-testing/test_dynamic_tokenizer"		,						trust_remote_code=_lowercase		,						use_fast=_lowercase )
                self.assertTrue(tokenizer.special_attribute_present )
                self.assertEqual(tokenizer.__class__.__name__		,						"NewTokenizer" )
                # Test tokenizer can be reloaded.
                with tempfile.TemporaryDirectory() as tmp_dir:
                       tokenizer.save_pretrained(_lowercase )
                       UpperCAmelCase__										=     AutoTokenizer.from_pretrained(_lowercase		,						trust_remote_code=_lowercase		,						use_fast=_lowercase )
                self.assertEqual(reloaded_tokenizer.__class__.__name__		,						"NewTokenizer" )
                self.assertTrue(reloaded_tokenizer.special_attribute_present )
         else:
                self.assertEqual(tokenizer.__class__.__name__		,						"NewTokenizer" )
                self.assertEqual(reloaded_tokenizer.__class__.__name__		,						"NewTokenizer" )






  @require_tokenizers
  def 			_UpperCAmelCase  (					self      :					Dict ):




         """simple docstring"""







         class     lowercase__  (					__SCREAMING_SNAKE_CASE		):
           A__=  False




         class     lowercase__  (					__SCREAMING_SNAKE_CASE		):
           A__=  NewTokenizer
           A__=  False

         try:
                AutoConfig.register("custom"		,						_lowercase )
                AutoTokenizer.register(_lowercase		,						slow_tokenizer_class=_lowercase )
                AutoTokenizer.register(_lowercase		,						fast_tokenizer_class=_lowercase )
                # If remote code is not set, the default is to use local
                UpperCAmelCase__										=     AutoTokenizer.from_pretrained("hf-internal-testing/test_dynamic_tokenizer" )
                self.assertEqual(tokenizer.__class__.__name__		,						"NewTokenizerFast" )
                self.assertFalse(tokenizer.special_attribute_present )
                UpperCAmelCase__										=     AutoTokenizer.from_pretrained("hf-internal-testing/test_dynamic_tokenizer"		,						use_fast=_lowercase )
                self.assertEqual(tokenizer.__class__.__name__		,						"NewTokenizer" )
                self.assertFalse(tokenizer.special_attribute_present )

                # If remote code is disabled, we load the local one.
                UpperCAmelCase__										=     AutoTokenizer.from_pretrained(
                    "hf-internal-testing/test_dynamic_tokenizer"		,						trust_remote_code=_lowercase )
                self.assertEqual(tokenizer.__class__.__name__		,						"NewTokenizerFast" )
                self.assertFalse(tokenizer.special_attribute_present )
                UpperCAmelCase__										=     AutoTokenizer.from_pretrained(
                    "hf-internal-testing/test_dynamic_tokenizer"		,						trust_remote_code=_lowercase		,						use_fast=_lowercase )
                self.assertEqual(tokenizer.__class__.__name__		,						"NewTokenizer" )
                self.assertFalse(tokenizer.special_attribute_present )

                # If remote is enabled, we load from the Hub
                UpperCAmelCase__										=     AutoTokenizer.from_pretrained(
                    "hf-internal-testing/test_dynamic_tokenizer"		,						trust_remote_code=_lowercase )
                self.assertEqual(tokenizer.__class__.__name__		,						"NewTokenizerFast" )
                self.assertTrue(tokenizer.special_attribute_present )
                UpperCAmelCase__										=     AutoTokenizer.from_pretrained(
                    "hf-internal-testing/test_dynamic_tokenizer"		,						trust_remote_code=_lowercase		,						use_fast=_lowercase )
                self.assertEqual(tokenizer.__class__.__name__		,						"NewTokenizer" )
                self.assertTrue(tokenizer.special_attribute_present )

         finally:
                if "custom" in CONFIG_MAPPING._extra_content:
                       del CONFIG_MAPPING._extra_content["custom"]
                if CustomConfig in TOKENIZER_MAPPING._extra_content:
                       del TOKENIZER_MAPPING._extra_content[CustomConfig]






  def 			_UpperCAmelCase  (					self      :					List[Any] ):




         """simple docstring"""







         UpperCAmelCase__										=     AutoTokenizer.from_pretrained(
             "hf-internal-testing/test_dynamic_tokenizer_legacy"		,						trust_remote_code=_lowercase )
         self.assertTrue(tokenizer.special_attribute_present )
         if is_tokenizers_available():
                self.assertEqual(tokenizer.__class__.__name__		,						"NewTokenizerFast" )

                # Test we can also load the slow version
                UpperCAmelCase__										=     AutoTokenizer.from_pretrained(
                    "hf-internal-testing/test_dynamic_tokenizer_legacy"		,						trust_remote_code=_lowercase		,						use_fast=_lowercase )
                self.assertTrue(tokenizer.special_attribute_present )
                self.assertEqual(tokenizer.__class__.__name__		,						"NewTokenizer" )
         else:
                self.assertEqual(tokenizer.__class__.__name__		,						"NewTokenizer" )






  def 			_UpperCAmelCase  (					self      :					str ):




         """simple docstring"""







         with self.assertRaisesRegex(
             _lowercase		,						"bert-base is not a local folder and is not a valid model identifier" ):
                UpperCAmelCase__										=     AutoTokenizer.from_pretrained("bert-base" )






  def 			_UpperCAmelCase  (					self      :					Tuple ):




         """simple docstring"""







         with self.assertRaisesRegex(
             _lowercase		,						r"aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)" ):
                UpperCAmelCase__										=     AutoTokenizer.from_pretrained(_lowercase		,						revision="aaaaaa" )






  def 			_UpperCAmelCase  (					self      :					List[str] ):




         """simple docstring"""







         UpperCAmelCase__										=     AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-bert" )
         with RequestCounter() as counter:
                UpperCAmelCase__										=     AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-bert" )
                self.assertEqual(counter.get_request_count		,						0 )
                self.assertEqual(counter.head_request_count		,						1 )
                self.assertEqual(counter.other_request_count		,						0 )









import unittest

import numpy as np

from diffusers import OnnxStableDiffusionInpaintPipelineLegacy
from diffusers.utils.testing_utils import (
    is_onnx_available,
    load_image,
    load_numpy,
    nightly,
    require_onnxruntime,
    require_torch_gpu,
)


if is_onnx_available():
    import onnxruntime as ort


@nightly
@require_onnxruntime
@require_torch_gpu
class     lowercase__  (					unittest.TestCase		):






  @property
  def 			_UpperCAmelCase  (					self      :					Union[str, Any] ):




         """simple docstring"""







         return (
             "CUDAExecutionProvider",
             {
                 "gpu_mem_limit": "15000000000",  # 15GB
                 "arena_extend_strategy": "kSameAsRequested",
             },
         )






  @property
  def 			_UpperCAmelCase  (					self      :					Optional[Any] ):




         """simple docstring"""







         UpperCAmelCase__										=     ort.SessionOptions()
         UpperCAmelCase__										=     False
         return options






  def 			_UpperCAmelCase  (					self      :					Dict ):




         """simple docstring"""







         UpperCAmelCase__										=     load_image(
             "https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main"
             "/in_paint/overture-creations-5sI6fQgYIuo.png" )
         UpperCAmelCase__										=     load_image(
             "https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main"
             "/in_paint/overture-creations-5sI6fQgYIuo_mask.png" )
         UpperCAmelCase__										=     load_numpy(
             "https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main"
             "/in_paint/red_cat_sitting_on_a_park_bench_onnx.npy" )

         # using the PNDM scheduler by default
         UpperCAmelCase__										=     OnnxStableDiffusionInpaintPipelineLegacy.from_pretrained(
             "CompVis/stable-diffusion-v1-4"		,						revision="onnx"		,						safety_checker=_lowercase		,						feature_extractor=_lowercase		,						provider=self.gpu_provider		,						sess_options=self.gpu_options		,						)
         pipe.set_progress_bar_config(disable=_lowercase )

         UpperCAmelCase__										=     "A red cat sitting on a park bench"

         UpperCAmelCase__										=     np.random.RandomState(0 )
         UpperCAmelCase__										=     pipe(
             prompt=_lowercase		,						image=_lowercase		,						mask_image=_lowercase		,						strength=0.7_5		,						guidance_scale=7.5		,						num_inference_steps=15		,						generator=_lowercase		,						output_type="np"		,						)

         UpperCAmelCase__										=     output.images[0]

         assert image.shape == (5_12, 5_12, 3)
         assert np.abs(expected_image - image ).max() < 1E-2





