





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_    =				get_tests_dir('''fixtures/test_sentencepiece_with_bytefallback.model''')



@require_sentencepiece
@require_tokenizers
class 					__lowerCAmelCase       (			_a,     unittest.TestCase     ):
			lowerCamelCase_     :     int       			=      GPTSwaTokenizer
			lowerCamelCase_     :     Dict       			=      False
			lowerCamelCase_     :     List[str]       			=      True
			lowerCamelCase_     :     Dict       			=      False






			def 			lowerCamelCase  (self    )     ->   Dict:


							'''simple docstring'''



							super().setUp()

							# We have a SentencePiece fixture for testing
							snake_case_						:    Any				=  GPTSwaTokenizer(__magic_name__					,							eos_token='''<unk>'''					,							bos_token='''<unk>'''					,							pad_token='''<unk>'''    )

							tokenizer.save_pretrained(self.tmpdirname    )






			def 			lowerCamelCase  (self					,							__magic_name__    )     ->   Dict:


							'''simple docstring'''



							snake_case_						:    List[Any]				=  '''This is a test'''
							snake_case_						:    int				=  '''This is a test'''
							return input_text, output_text






			def 			lowerCamelCase  (self    )     ->   Optional[Any]:


							'''simple docstring'''



							snake_case_						:    Tuple				=  '''<s>'''
							snake_case_						:    Tuple				=  1

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






			def 			lowerCamelCase  (self    )     ->   List[str]:


							'''simple docstring'''



							snake_case_						:    List[Any]				=  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(__magic_name__    )					,							2000    )






			def 			lowerCamelCase  (self    )     ->   int:


							'''simple docstring'''



							self.assertEqual(self.get_tokenizer().vocab_size					,							2000    )






			def 			lowerCamelCase  (self    )     ->   List[Any]:


							'''simple docstring'''



							snake_case_						:    int				=  GPTSwaTokenizer(__magic_name__    )

							snake_case_						:    Dict				=  tokenizer.tokenize('''This is a test'''    )
							self.assertListEqual(__magic_name__					,							['''▁This''', '''▁is''', '''▁a''', '''▁t''', '''est''']    )

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

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

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

							snake_case_						:    List[Any]				=  tokenizer.convert_ids_to_tokens(__magic_name__    )
							# fmt: off
							self.assertListEqual(
							    __magic_name__					,							['''▁I''', '''▁was''', '''▁bor''', '''n''', '''▁in''', '''▁''', '''<0x39>''', '''2''', '''0''', '''0''', '''0''', ''',''', '''▁and''', '''▁this''', '''▁is''', '''▁f''', '''al''', '''s''', '''<0xC3>''', '''<0xA9>''', '''.''']    )
							# fmt: on






			def 			lowerCamelCase  (self    )     ->   Any:


							'''simple docstring'''



							snake_case_						:    List[Any]				=  GPTSwaTokenizer(__magic_name__    )
							snake_case_						:    Optional[int]				=  ['''This is a test''', '''I was born in 92000, and this is falsé.''']
							snake_case_						:    Union[str, Any]				=  [
							    [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(__magic_name__					,							__magic_name__    ):
											self.assertListEqual(tokenizer.encode_fast(__magic_name__    )					,							__magic_name__    )

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






			@slow
			def 			lowerCamelCase  (self    )     ->   List[Any]:


							'''simple docstring'''



							snake_case_						:    Dict				=  [
							    '''<|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
							snake_case_						:    Optional[int]				=  {'''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=__magic_name__					,							model_name='''AI-Sweden/gpt-sw3-126m'''					,							sequences=__magic_name__					,							)







import argparse

from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection

from diffusers import UnCLIPImageVariationPipeline, UnCLIPPipeline


if __name__ == "__main__":
	lowerCAmelCase_    =				argparse.ArgumentParser()

	parser.add_argument('''--dump_path''', default=None, type=str, required=True, help='''Path to the output model.''')

	parser.add_argument(
	    '''--txt2img_unclip''',
	    default='''kakaobrain/karlo-v1-alpha''',
	    type=str,
	    required=False,
	    help='''The pretrained txt2img unclip.''',
	)

	lowerCAmelCase_    =				parser.parse_args()

	lowerCAmelCase_    =				UnCLIPPipeline.from_pretrained(args.txtaimg_unclip)

	lowerCAmelCase_    =				CLIPImageProcessor()
	lowerCAmelCase_    =				CLIPVisionModelWithProjection.from_pretrained('''openai/clip-vit-large-patch14''')

	lowerCAmelCase_    =				UnCLIPImageVariationPipeline(
	    decoder=txtaimg.decoder,
	    text_encoder=txtaimg.text_encoder,
	    tokenizer=txtaimg.tokenizer,
	    text_proj=txtaimg.text_proj,
	    feature_extractor=feature_extractor,
	    image_encoder=image_encoder,
	    super_res_first=txtaimg.super_res_first,
	    super_res_last=txtaimg.super_res_last,
	    decoder_scheduler=txtaimg.decoder_scheduler,
	    super_res_scheduler=txtaimg.super_res_scheduler,
	)

	imgaimg.save_pretrained(args.dump_path)
