


import tempfile
import unittest
from pathlib import Path
from shutil import copyfile

from transformers import BatchEncoding, MarianTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import is_sentencepiece_available, is_tf_available, is_torch_available


if is_sentencepiece_available():
    from transformers.models.marian.tokenization_marian import VOCAB_FILES_NAMES, save_json

from ...test_tokenization_common import TokenizerTesterMixin


A      = get_tests_dir("fixtures/test_sentencepiece.model")

A      = {"target_lang": "fi", "source_lang": "en"}
A      = ">>zh<<"
A      = "Helsinki-NLP/"

if is_torch_available():
    A      = "pt"
elif is_tf_available():
    A      = "tf"
else:
    A      = "jax"


@require_sentencepiece
class     lowercase__  (					__SCREAMING_SNAKE_CASE					,							unittest.TestCase		):
  A__=  MarianTokenizer
  A__=  False
  A__=  True






  def 			_UpperCAmelCase  (					self      :					Optional[int] ):




         """simple docstring"""







         super().setUp()
         UpperCAmelCase__										=     ["</s>", "<unk>", "▁This", "▁is", "▁a", "▁t", "est", "\u0120", "<pad>"]
         UpperCAmelCase__										=     dict(zip(_lowercase		,						range(len(_lowercase ) ) ) )
         UpperCAmelCase__										=     Path(self.tmpdirname )
         save_json(_lowercase		,						save_dir / VOCAB_FILES_NAMES["vocab"] )
         save_json(_lowercase		,						save_dir / VOCAB_FILES_NAMES["tokenizer_config_file"] )
         if not (save_dir / VOCAB_FILES_NAMES["source_spm"]).exists():
                copyfile(_lowercase		,						save_dir / VOCAB_FILES_NAMES["source_spm"] )
                copyfile(_lowercase		,						save_dir / VOCAB_FILES_NAMES["target_spm"] )

         UpperCAmelCase__										=     MarianTokenizer.from_pretrained(self.tmpdirname )
         tokenizer.save_pretrained(self.tmpdirname )






  def 			_UpperCAmelCase  (					self      :					List[str]		,						**_lowercase      :					Tuple ):




         """simple docstring"""







         return MarianTokenizer.from_pretrained(self.tmpdirname		,						**_lowercase )






  def 			_UpperCAmelCase  (					self      :					int		,						_lowercase      :					Optional[int] ):




         """simple docstring"""







         return (
             "This is a test",
             "This is a test",
         )






  def 			_UpperCAmelCase  (					self      :					Dict ):




         """simple docstring"""







         UpperCAmelCase__										=     "</s>"
         UpperCAmelCase__										=     0

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






  def 			_UpperCAmelCase  (					self      :					Optional[int] ):




         """simple docstring"""







         UpperCAmelCase__										=     list(self.get_tokenizer().get_vocab().keys() )

         self.assertEqual(vocab_keys[0]		,						"</s>" )
         self.assertEqual(vocab_keys[1]		,						"<unk>" )
         self.assertEqual(vocab_keys[-1]		,						"<pad>" )
         self.assertEqual(len(_lowercase )		,						9 )






  def 			_UpperCAmelCase  (					self      :					List[Any] ):




         """simple docstring"""







         self.assertEqual(self.get_tokenizer().vocab_size		,						9 )






  def 			_UpperCAmelCase  (					self      :					List[str] ):




         """simple docstring"""







         UpperCAmelCase__										=     MarianTokenizer.from_pretrained(F"""{ORG_NAME}opus-mt-en-de""" )
         UpperCAmelCase__										=     en_de_tokenizer(["I am a small frog"]		,						return_tensors=_lowercase )
         self.assertIsInstance(_lowercase		,						_lowercase )
         UpperCAmelCase__										=     [38, 1_21, 14, 6_97, 3_88_48, 0]
         self.assertListEqual(_lowercase		,						batch.input_ids[0] )

         UpperCAmelCase__										=     tempfile.mkdtemp()
         en_de_tokenizer.save_pretrained(_lowercase )
         UpperCAmelCase__										=     [x.name for x in Path(_lowercase ).glob("*" )]
         self.assertIn("source.spm"		,						_lowercase )
         MarianTokenizer.from_pretrained(_lowercase )






  def 			_UpperCAmelCase  (					self      :					List[Any] ):




         """simple docstring"""







         UpperCAmelCase__										=     self.get_tokenizer()

         UpperCAmelCase__										=     tok(
             ["I am a small frog" * 10_00, "I am a small frog"]		,						padding=_lowercase		,						truncation=_lowercase		,						return_tensors=_lowercase )
         self.assertIsInstance(_lowercase		,						_lowercase )
         self.assertEqual(batch.input_ids.shape		,						(2, 5_12) )






  def 			_UpperCAmelCase  (					self      :					Any ):




         """simple docstring"""







         UpperCAmelCase__										=     self.get_tokenizer()
         UpperCAmelCase__										=     tok(["I am a tiny frog", "I am a small frog"]		,						padding=_lowercase		,						return_tensors=_lowercase )
         self.assertIsInstance(_lowercase		,						_lowercase )
         self.assertEqual(batch_smaller.input_ids.shape		,						(2, 10) )






  @slow
  def 			_UpperCAmelCase  (					self      :					List[str] ):




         """simple docstring"""







         UpperCAmelCase__										=     {"input_ids": [[4_34_95, 4_62, 20, 4_21_64, 13_69, 52, 4_64, 1_32, 17_03, 4_92, 13, 74_91, 3_89_99, 6, 8, 4_64, 1_32, 17_03, 4_92, 13, 46_69, 3_78_67, 13, 75_25, 27, 15_93, 9_88, 13, 3_39_72, 70_29, 6, 20, 82_51, 3_83, 2, 2_70, 58_66, 37_88, 2, 23_53, 82_51, 1_23_38, 2, 1_39_58, 3_87, 2, 36_29, 69_53, 1_88, 29_00, 2, 1_39_58, 80_11, 1_15_01, 23, 84_60, 40_73, 3_40_09, 20, 4_35, 1_14_39, 27, 8, 84_60, 40_73, 60_04, 20, 99_88, 3_75, 27, 33, 2_66, 19_45, 10_76, 13_50, 3_78_67, 32_88, 5, 5_77, 10_76, 43_74, 8, 50_82, 5, 2_64_53, 2_57, 5_56, 4_03, 2, 2_42, 1_32, 3_83, 3_16, 4_92, 8, 1_07_67, 6, 3_16, 3_04, 42_39, 3, 0], [1_48, 1_57_22, 19, 18_39, 12, 13_50, 13, 2_23_27, 50_82, 54_18, 4_75_67, 3_59_38, 59, 3_18, 1_95_52, 1_08, 21_83, 54, 1_49_76, 48_35, 32, 5_47, 11_14, 8, 3_15, 24_17, 5, 92, 1_90_88, 3, 0, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00], [36, 63_95, 1_25_70, 3_91_47, 1_15_97, 6, 2_66, 4, 4_54_05, 72_96, 3, 0, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00]], "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, 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], [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, 0]]}  # noqa: E501
         # fmt: on

         self.tokenizer_integration_test_util(
             expected_encoding=_lowercase		,						model_name="Helsinki-NLP/opus-mt-en-de"		,						revision="1a8c2263da11e68e50938f97e10cd57820bd504c"		,						decode_kwargs={"use_source_tokenizer": True}		,						)






  def 			_UpperCAmelCase  (					self      :					List[Any] ):




         """simple docstring"""







         UpperCAmelCase__										=     MarianTokenizer.from_pretrained("hf-internal-testing/test-marian-two-vocabs" )

         UpperCAmelCase__										=     "Tämä on testi"
         UpperCAmelCase__										=     "This is a test"

         UpperCAmelCase__										=     [76, 7, 20_47, 2]
         UpperCAmelCase__										=     [69, 12, 11, 9_40, 2]

         UpperCAmelCase__										=     tokenizer(_lowercase ).input_ids
         self.assertListEqual(_lowercase		,						_lowercase )

         UpperCAmelCase__										=     tokenizer(text_target=_lowercase ).input_ids
         self.assertListEqual(_lowercase		,						_lowercase )

         UpperCAmelCase__										=     tokenizer.decode(_lowercase		,						skip_special_tokens=_lowercase )
         self.assertEqual(_lowercase		,						_lowercase )









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





