"""simple docstring"""


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 							a					(		unittest.TestCase ):


    @property
    def   lowerCAmelCase_	(       self						:	List[str]       ):
      return (
          "CUDAExecutionProvider",
          {
              "gpu_mem_limit": "15000000000",  # 15GB
              "arena_extend_strategy": "kSameAsRequested",
          },
      )


    @property
    def   lowerCAmelCase_	(       self						:	List[str]       ):
      _UpperCAmelCase    			=   ort.SessionOptions()
      _UpperCAmelCase    			=   False
      return options


    def   lowerCAmelCase_	(       self						:	Any       ):
      _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=__lowerCAmelCase ,					feature_extractor=__lowerCAmelCase ,					provider=self.gpu_provider ,					sess_options=self.gpu_options ,					)
      pipe.set_progress_bar_config(disable=__lowerCAmelCase       )

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

      _UpperCAmelCase    			=   np.random.RandomState(0       )
      _UpperCAmelCase    			=   pipe(
          prompt=__lowerCAmelCase ,					image=__lowerCAmelCase ,					mask_image=__lowerCAmelCase ,					strength=0.75 ,					guidance_scale=7.5 ,					num_inference_steps=15 ,					generator=__lowerCAmelCase ,					output_type="""np""" ,					)

      _UpperCAmelCase    			=   output.images[0]

      assert image.shape == (512, 512, 3)
      assert np.abs(expected_image - image       ).max() < 1e-2

"""simple docstring"""


import json
import os
import unittest

from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin


@require_tokenizers
class 							a					(		lowerCAmelCase_						,				unittest.TestCase ):
    _snake_case  :	Dict  				=				MgpstrTokenizer
    _snake_case  :	Any  				=				False
    _snake_case  :	str  				=				{}
    _snake_case  :	Dict  				=				False


    def   lowerCAmelCase_	(       self						:	int       ):
      super().setUp()

      # fmt: off
      _UpperCAmelCase    			=   ["""[GO]""", """[s]""", """0""", """1""", """2""", """3""", """4""", """5""", """6""", """7""", """8""", """9""", """a""", """b""", """c""", """d""", """e""", """f""", """g""", """h""", """i""", """j""", """k""", """l""", """m""", """n""", """o""", """p""", """q""", """r""", """s""", """t""", """u""", """v""", """w""", """x""", """y""", """z"""]
      # fmt: on
      _UpperCAmelCase    			=   dict(zip(__lowerCAmelCase ,					range(len(__lowerCAmelCase       )       )       )       )

      _UpperCAmelCase    			=   os.path.join(self.tmpdirname ,					VOCAB_FILES_NAMES["""vocab_file"""]       )
      with open(self.vocab_file ,					"""w""" ,					encoding="""utf-8"""       ) as fp:
        fp.write(json.dumps(__lowerCAmelCase       ) + """\n"""       )


    def   lowerCAmelCase_	(       self						:	Tuple ,					**__lowerCAmelCase						:	Dict       ):
      return MgpstrTokenizer.from_pretrained(self.tmpdirname ,					**__lowerCAmelCase       )


    def   lowerCAmelCase_	(       self						:	List[str] ,					__lowerCAmelCase						:	int       ):
      _UpperCAmelCase    			=   """tester"""
      _UpperCAmelCase    			=   """tester"""
      return input_text, output_text


    @unittest.skip("""MGP-STR always lower cases letters."""       )
    def   lowerCAmelCase_	(       self						:	Tuple       ):
      pass


    def   lowerCAmelCase_	(       self						:	Any       ):
      _UpperCAmelCase    			=   self.get_tokenizers(do_lower_case=__lowerCAmelCase       )
      for tokenizer in tokenizers:
        with self.subTest(f'''{tokenizer.__class__.__name__}'''       ):
          _UpperCAmelCase    			=   """[SPECIAL_TOKEN]"""

          tokenizer.add_special_tokens({"""cls_token""": special_token}       )
          _UpperCAmelCase    			=   tokenizer.encode([special_token] ,					add_special_tokens=__lowerCAmelCase       )
          self.assertEqual(len(__lowerCAmelCase       ) ,					1       )

          _UpperCAmelCase    			=   tokenizer.decode(__lowerCAmelCase ,					skip_special_tokens=__lowerCAmelCase       )
          self.assertTrue(special_token not in decoded       )


    def   lowerCAmelCase_	(       self						:	List[str]       ):
      _UpperCAmelCase    			=   self.get_tokenizers()
      for tokenizer in tokenizers:
        with self.subTest(f'''{tokenizer.__class__.__name__}'''       ):
          _UpperCAmelCase			,					_UpperCAmelCase    			=   self.get_input_output_texts(__lowerCAmelCase       )

          _UpperCAmelCase    			=   tokenizer.tokenize(__lowerCAmelCase       )
          _UpperCAmelCase    			=   tokenizer.convert_tokens_to_ids(__lowerCAmelCase       )
          _UpperCAmelCase    			=   tokenizer.encode(__lowerCAmelCase ,					add_special_tokens=__lowerCAmelCase       )
          self.assertListEqual(__lowerCAmelCase ,					__lowerCAmelCase       )

          _UpperCAmelCase    			=   tokenizer.convert_ids_to_tokens(__lowerCAmelCase       )
          self.assertNotEqual(len(__lowerCAmelCase       ) ,					0       )
          _UpperCAmelCase    			=   tokenizer.decode(__lowerCAmelCase       )
          self.assertIsInstance(__lowerCAmelCase ,					__lowerCAmelCase       )

          self.assertEqual(text_a.replace(""" """ ,					""""""       ) ,					__lowerCAmelCase       )


    @unittest.skip("""MGP-STR tokenizer only handles one sequence."""       )
    def   lowerCAmelCase_	(       self						:	List[str]       ):
      pass


    @unittest.skip("""inputs cannot be pretokenized in MgpstrTokenizer"""       )
    def   lowerCAmelCase_	(       self						:	Optional[int]       ):
      pass
