




import unittest

from transformers import GPTSwaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin


_lowerCAmelCase						:   List[Any]		=   get_tests_dir("fixtures/test_sentencepiece_with_bytefallback.model")
@require_sentencepiece
@require_tokenizers
class 			_UpperCamelCase      (				A_	,       unittest.TestCase		):
      UpperCAmelCase_        =		GPTSwaTokenizer
      UpperCAmelCase_        =		False
      UpperCAmelCase_        =		True
      UpperCAmelCase_        =		False
      def 	UpperCAmelCase_						(			self   :str      )     ->			Union[str, Any]:
       super().setUp()

       # We have a SentencePiece fixture for testing
       UpperCAmelCase__							 =						GPTSwaTokenizer(lowerCamelCase ,      eos_token="<unk>" ,      bos_token="<unk>" ,      pad_token="<unk>"      )

       tokenizer.save_pretrained(self.tmpdirname      )
      def 	UpperCAmelCase_						(			self   :Optional[Any] ,      lowerCamelCase   :List[Any]      )     ->			str:
       UpperCAmelCase__							 =						"""This is a test"""
       UpperCAmelCase__							 =						"""This is a test"""
       return input_text, output_text
      def 	UpperCAmelCase_						(			self   :Union[str, Any]      )     ->			Optional[Any]:
       UpperCAmelCase__							 =						"""<s>"""
       UpperCAmelCase__							 =						1

       self.assertEqual(self.get_tokenizer()._convert_token_to_id(lowerCamelCase      ) ,      lowerCamelCase      )
       self.assertEqual(self.get_tokenizer()._convert_id_to_token(lowerCamelCase      ) ,      lowerCamelCase      )
      def 	UpperCAmelCase_						(			self   :Tuple      )     ->			int:
       UpperCAmelCase__							 =						list(self.get_tokenizer().get_vocab().keys()      )

       self.assertEqual(vocab_keys[0] ,      "<unk>"      )
       self.assertEqual(vocab_keys[1] ,      "<s>"      )
       self.assertEqual(vocab_keys[-1] ,      "j"      )
       self.assertEqual(len(lowerCamelCase      ) ,      2000      )
      def 	UpperCAmelCase_						(			self   :Any      )     ->			Optional[int]:
       self.assertEqual(self.get_tokenizer().vocab_size ,      2000      )
      def 	UpperCAmelCase_						(			self   :Union[str, Any]      )     ->			List[str]:
       UpperCAmelCase__							 =						GPTSwaTokenizer(lowerCamelCase      )

       UpperCAmelCase__							 =						tokenizer.tokenize("This is a test"      )
       self.assertListEqual(lowerCamelCase ,      ["▁This", "▁is", "▁a", "▁t", "est"]      )

       self.assertListEqual(tokenizer.convert_tokens_to_ids(lowerCamelCase      ) ,      [465, 287, 265, 631, 842]      )

       UpperCAmelCase__							 =						tokenizer.tokenize("I was born in 92000, and this is falsé."      )
       # fmt: off
       self.assertListEqual(
           lowerCamelCase ,      ["▁I", "▁was", "▁bor", "n", "▁in", "▁", "<0x39>", "2", "0", "0", "0", ",", "▁and", "▁this", "▁is", "▁f", "al", "s", "<0xC3>", "<0xA9>", "."] ,      )
       # fmt: on

       UpperCAmelCase__							 =						tokenizer.convert_tokens_to_ids(lowerCamelCase      )
       self.assertListEqual(
           lowerCamelCase ,      [262, 272, 1525, 286, 271, 268, 60, 916, 633, 633, 633, 259, 266, 301, 287, 384, 367, 263, 198, 172, 260] ,      )

       UpperCAmelCase__							 =						tokenizer.convert_ids_to_tokens(lowerCamelCase      )
       # fmt: off
       self.assertListEqual(
           lowerCamelCase ,      ["▁I", "▁was", "▁bor", "n", "▁in", "▁", "<0x39>", "2", "0", "0", "0", ",", "▁and", "▁this", "▁is", "▁f", "al", "s", "<0xC3>", "<0xA9>", "."]      )
       # fmt: on
      def 	UpperCAmelCase_						(			self   :Union[str, Any]      )     ->			int:
       UpperCAmelCase__							 =						GPTSwaTokenizer(lowerCamelCase      )
       UpperCAmelCase__							 =						["""This is a test""", """I was born in 92000, and this is falsé."""]
       UpperCAmelCase__							 =						[
           [465, 287, 265, 631, 842],
           [262, 272, 1525, 286, 271, 268, 60, 916, 633, 633, 633, 259, 266, 301, 287, 384, 367, 263, 198, 172, 260],
       ]

       # Test that encode_fast returns the same as tokenize + convert_tokens_to_ids
       for text, expected_ids in zip(lowerCamelCase ,      lowerCamelCase      ):
        self.assertListEqual(tokenizer.encode_fast(lowerCamelCase      ) ,      lowerCamelCase      )

       # Test that decode_fast returns the input text
       for text, token_ids in zip(lowerCamelCase ,      lowerCamelCase      ):
        self.assertEqual(tokenizer.decode_fast(lowerCamelCase      ) ,      lowerCamelCase      )







      @slow
      def 	UpperCAmelCase_						(			self   :Dict      )     ->			Any:
       UpperCAmelCase__							 =						[
           """<|python|>def fibonacci(n)\n    if n < 0:\n        print('Incorrect input')""",
           """Hey there, how are you doing this fine day?""",
           """This is a text with a trailing spaces followed by a dot     .""",
           """Häj sväjs lillebrör! =)""",
           """Det är inget fel på Mr. Cool""",
       ]

       # fmt: off
       UpperCAmelCase__							 =						{"""input_ids""": [[6_3423, 5, 6811, 1_4954, 282, 816, 3821, 6_3466, 6_3425, 6_3462, 18, 6_3978, 678, 301, 1320, 6_3423, 6_3455, 6_3458, 18, 6_3982, 4246, 3940, 1901, 4_7789, 5547, 1_8994], [1_9630, 1100, 6_3446, 1342, 633, 544, 4488, 593, 5102, 2416, 6_3495, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1652, 428, 268, 1936, 515, 268, 5_8593, 2_2413, 9106, 546, 268, 3_3213, 6_3979, 698, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [5_5130, 6_3450, 924, 6_3449, 2249, 4062, 1558, 318, 6_3504, 2_1498, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [509, 377, 2827, 2559, 332, 6575, 6_3443, 2_6801, 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]], """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, 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, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [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], [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]]}
       # fmt: on
       self.tokenizer_integration_test_util(
           expected_encoding=lowerCamelCase ,      model_name="AI-Sweden/gpt-sw3-126m" ,      sequences=lowerCamelCase ,      )











import random
import unittest

import torch

from diffusers import IFInpaintingSuperResolutionPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device

from ..pipeline_params import (
    TEXT_GUIDED_IMAGE_INPAINTING_BATCH_PARAMS,
    TEXT_GUIDED_IMAGE_INPAINTING_PARAMS,
)
from ..test_pipelines_common import PipelineTesterMixin
from . import IFPipelineTesterMixin
@skip_mps
class 			_UpperCamelCase      (				lowerCAmelCase	,       lowerCAmelCase	,       unittest.TestCase		):
      UpperCAmelCase_        =		IFInpaintingSuperResolutionPipeline
      UpperCAmelCase_        =		TEXT_GUIDED_IMAGE_INPAINTING_PARAMS - {"""width""", """height"""}
      UpperCAmelCase_        =		TEXT_GUIDED_IMAGE_INPAINTING_BATCH_PARAMS.union({"""original_image"""}		)
      UpperCAmelCase_        =		PipelineTesterMixin.required_optional_params - {"""latents"""}
      def 	UpperCAmelCase_						(			self   :str      )     ->			Optional[Any]:
       return self._get_superresolution_dummy_components()
      def 	UpperCAmelCase_						(			self   :List[str] ,      lowerCamelCase   :Dict ,      lowerCamelCase   :Optional[Any]=0      )     ->			int:
       if str(lowerCamelCase      ).startswith("mps"      ):
        UpperCAmelCase__							 =						torch.manual_seed(lowerCamelCase      )
       else:
        UpperCAmelCase__							 =						torch.Generator(device=lowerCamelCase      ).manual_seed(lowerCamelCase      )

       UpperCAmelCase__							 =						floats_tensor((1, 3, 16, 16) ,      rng=random.Random(lowerCamelCase      )      ).to(lowerCamelCase      )
       UpperCAmelCase__							 =						floats_tensor((1, 3, 32, 32) ,      rng=random.Random(lowerCamelCase      )      ).to(lowerCamelCase      )
       UpperCAmelCase__							 =						floats_tensor((1, 3, 32, 32) ,      rng=random.Random(lowerCamelCase      )      ).to(lowerCamelCase      )

       UpperCAmelCase__							 =						{
           "prompt": "A painting of a squirrel eating a burger",
           "image": image,
           "original_image": original_image,
           "mask_image": mask_image,
           "generator": generator,
           "num_inference_steps": 2,
           "output_type": "numpy",
       }

       return inputs
      @unittest.skipIf(
          torch_device != "cuda" or not is_xformers_available() ,      reason="XFormers attention is only available with CUDA and `xformers` installed" ,      )
      def 	UpperCAmelCase_						(			self   :Union[str, Any]      )     ->			Dict:
       self._test_xformers_attention_forwardGenerator_pass(expected_max_diff=1e-3      )
      def 	UpperCAmelCase_						(			self   :List[str]      )     ->			Dict:
       self._test_save_load_optional_components()
      @unittest.skipIf(torch_device != "cuda" ,      reason="float16 requires CUDA"      )
      def 	UpperCAmelCase_						(			self   :Tuple      )     ->			Dict:
       # Due to non-determinism in save load of the hf-internal-testing/tiny-random-t5 text encoder
       super().test_save_load_floataa(expected_max_diff=1e-1      )
      def 	UpperCAmelCase_						(			self   :Dict      )     ->			str:
       self._test_attention_slicing_forward_pass(expected_max_diff=1e-2      )
      def 	UpperCAmelCase_						(			self   :Dict      )     ->			str:
       self._test_save_load_local()







      def 	UpperCAmelCase_						(			self   :List[str]      )     ->			List[str]:
       self._test_inference_batch_single_identical(
           expected_max_diff=1e-2 ,      )





