


"""simple docstring"""




import pickle
import shutil
import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, XGLMTokenizer, XGLMTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


__lowerCAmelCase			=							get_tests_dir('''fixtures/test_sentencepiece.model''')





@require_sentencepiece
@require_tokenizers
class   __a      (   __lowercase	,	unittest.TestCase				):
 __lowercase			:							Optional[Any]       					=			XGLMTokenizer
 __lowercase			:							Any       					=			XGLMTokenizerFast
 __lowercase			:							Dict       					=			True
 __lowercase			:							int       					=			True
 def 		SCREAMING_SNAKE_CASE__       (       self			) ->    Optional[Any]:




        '''simple docstring'''
        super().setUp()

        # We have a SentencePiece fixture for testing
        lowercase__:       Optional[int]        =       XGLMTokenizer(UpperCAmelCase__    ,			keep_accents=UpperCAmelCase__			)
        tokenizer.save_pretrained(self.tmpdirname			)
 def 		SCREAMING_SNAKE_CASE__       (       self			) ->    Any:




        '''simple docstring'''
        lowercase__:       int        =       '<pad>'
        lowercase__:       str        =       1

        self.assertEqual(self.get_tokenizer()._convert_token_to_id(UpperCAmelCase__			)    ,			UpperCAmelCase__			)
        self.assertEqual(self.get_tokenizer()._convert_id_to_token(UpperCAmelCase__			)    ,			UpperCAmelCase__			)
 def 		SCREAMING_SNAKE_CASE__       (       self			) ->    Dict:




        '''simple docstring'''
        lowercase__:       Tuple        =       list(self.get_tokenizer().get_vocab().keys()			)

        self.assertEqual(vocab_keys[0]    ,			'<s>'			)
        self.assertEqual(vocab_keys[1]    ,			'<pad>'			)
        self.assertEqual(len(UpperCAmelCase__			)    ,			1_008			)
 def 		SCREAMING_SNAKE_CASE__       (       self			) ->    Dict:




        '''simple docstring'''
        self.assertEqual(self.get_tokenizer().vocab_size    ,			1_008			)
 def 		SCREAMING_SNAKE_CASE__       (       self			) ->    str:




        '''simple docstring'''
        lowercase__:       Optional[Any]        =       XGLMTokenizer(UpperCAmelCase__    ,			keep_accents=UpperCAmelCase__			)

        lowercase__:       int        =       tokenizer.tokenize('This is a test'			)
        self.assertListEqual(UpperCAmelCase__    ,			['▁This', '▁is', '▁a', '▁t', 'est']			)

        self.assertListEqual(
            tokenizer.convert_tokens_to_ids(UpperCAmelCase__			)    ,			[value + tokenizer.fairseq_offset for value in [285, 46, 10, 170, 382]]    ,			)

        lowercase__:       int        =       tokenizer.tokenize('I was born in 92000, and this is falsé.'			)
        self.assertListEqual(
            UpperCAmelCase__    ,			[
                SPIECE_UNDERLINE + 'I',
                SPIECE_UNDERLINE + 'was',
                SPIECE_UNDERLINE + 'b',
                'or',
                'n',
                SPIECE_UNDERLINE + 'in',
                SPIECE_UNDERLINE + '',
                '9',
                '2',
                '0',
                '0',
                '0',
                ',',
                SPIECE_UNDERLINE + 'and',
                SPIECE_UNDERLINE + 'this',
                SPIECE_UNDERLINE + 'is',
                SPIECE_UNDERLINE + 'f',
                'al',
                's',
                'é',
                '.',
            ]    ,			)
        lowercase__:       Any        =       tokenizer.convert_tokens_to_ids(UpperCAmelCase__			)
        self.assertListEqual(
            UpperCAmelCase__    ,			[
                value + tokenizer.fairseq_offset
                for value in [8, 21, 84, 55, 24, 19, 7, 2, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 2, 4]
            ]    ,			)

        lowercase__:       Tuple        =       tokenizer.convert_ids_to_tokens(UpperCAmelCase__			)
        self.assertListEqual(
            UpperCAmelCase__    ,			[
                SPIECE_UNDERLINE + 'I',
                SPIECE_UNDERLINE + 'was',
                SPIECE_UNDERLINE + 'b',
                'or',
                'n',
                SPIECE_UNDERLINE + 'in',
                SPIECE_UNDERLINE + '',
                '<unk>',
                '2',
                '0',
                '0',
                '0',
                ',',
                SPIECE_UNDERLINE + 'and',
                SPIECE_UNDERLINE + 'this',
                SPIECE_UNDERLINE + 'is',
                SPIECE_UNDERLINE + 'f',
                'al',
                's',
                '<unk>',
                '.',
            ]    ,			)
 @cached_property
 def 		SCREAMING_SNAKE_CASE__       (       self			) ->    int:




        '''simple docstring'''
        return XGLMTokenizer.from_pretrained('facebook/xglm-564M'			)
 def 		SCREAMING_SNAKE_CASE__       (       self			) ->    Tuple:




        '''simple docstring'''
        with tempfile.NamedTemporaryFile() as f:
               shutil.copyfile(UpperCAmelCase__    ,			f.name			)
               lowercase__:       Union[str, Any]        =       XGLMTokenizer(f.name    ,			keep_accents=UpperCAmelCase__			)
               lowercase__:       List[Any]        =       pickle.dumps(UpperCAmelCase__			)
        pickle.loads(UpperCAmelCase__			)
 def 		SCREAMING_SNAKE_CASE__       (       self			) ->    Optional[Any]:




        '''simple docstring'''
        if not self.test_rust_tokenizer:
               return

        lowercase__:       List[str]        =       self.get_tokenizer()
        lowercase__:       Optional[int]        =       self.get_rust_tokenizer()

        lowercase__:       List[Any]        =       'I was born in 92000, and this is falsé.'

        lowercase__:       List[str]        =       tokenizer.tokenize(UpperCAmelCase__			)
        lowercase__:       Tuple        =       rust_tokenizer.tokenize(UpperCAmelCase__			)
        self.assertListEqual(UpperCAmelCase__    ,			UpperCAmelCase__			)

        lowercase__:       List[Any]        =       tokenizer.encode(UpperCAmelCase__    ,			add_special_tokens=UpperCAmelCase__			)
        lowercase__:       List[str]        =       rust_tokenizer.encode(UpperCAmelCase__    ,			add_special_tokens=UpperCAmelCase__			)
        self.assertListEqual(UpperCAmelCase__    ,			UpperCAmelCase__			)

        lowercase__:       Optional[Any]        =       self.get_rust_tokenizer()
        lowercase__:       Any        =       tokenizer.encode(UpperCAmelCase__			)
        lowercase__:       Dict        =       rust_tokenizer.encode(UpperCAmelCase__			)
        self.assertListEqual(UpperCAmelCase__    ,			UpperCAmelCase__			)
 @slow
 def 		SCREAMING_SNAKE_CASE__       (       self			) ->    List[str]:




        '''simple docstring'''
        lowercase__:       Dict        =       'Hello World!'
        lowercase__:       Tuple        =       [2, 31_227, 4_447, 35]

        self.assertListEqual(UpperCAmelCase__    ,			self.big_tokenizer.encode(UpperCAmelCase__			)			)
 @slow
 def 		SCREAMING_SNAKE_CASE__       (       self			) ->    Any:




        '''simple docstring'''
        lowercase__:       str        =       (
            'This is a very long text with a lot of weird characters, such as: . , ~ ? ( ) " [ ] ! : - . Also we will'
            ' add words that should not exsist and be tokenized to unk, such as saoneuhaoesuth'
        )
        # fmt: off
        lowercase__:       Tuple        =       [2, 1_018, 67, 11, 1_988, 2_617, 5_631, 278, 11, 3_407, 48, 71_630, 28_085, 4, 3_234, 157, 13, 6, 5, 6, 4, 3_526, 768, 15, 659, 57, 298, 3_983, 864, 129, 21, 6, 5, 13_675, 377, 652, 7_580, 10_341, 155, 2_817, 422, 1_666, 7, 1_674, 53, 113, 202_277, 17_892, 33, 60, 87, 4, 3_234, 157, 61, 2_667, 52_376, 19, 88, 23, 735]
        # fmt: on

        self.assertListEqual(UpperCAmelCase__    ,			self.big_tokenizer.encode(UpperCAmelCase__			)			)
 @slow
 def 		SCREAMING_SNAKE_CASE__       (       self			) ->    int:




        '''simple docstring'''
        # fmt: off
        lowercase__:       int        =       {
            'input_ids': [[2, 108_825, 1_163, 15, 88_010, 473, 15_898, 157, 13_672, 1_857, 312, 8, 238_021, 1_163, 53, 13_672, 1_857, 312, 8, 53_283, 182_396, 8, 18_566, 16, 36_733, 4_101, 8, 230, 244_017, 122_553, 7, 15, 132_597, 4, 293, 12_511, 7_610, 4, 3_414, 132_597, 9, 4, 32_361, 362, 4, 734, 28_512, 32_569, 18, 4, 32_361, 26_096, 14_982, 73, 18_715, 21_433, 235_261, 15, 492, 12_427, 16, 53, 18_715, 21_433, 65_454, 15, 23_659, 563, 16, 278, 597, 2_843, 595, 7_931, 182_396, 64_186, 22, 886, 595, 132_981, 53, 25_540, 3_449, 43_982, 39_901, 5_951, 878, 330, 4, 27_694, 80_269, 312, 53, 6_517, 11_780, 611, 20_408, 5], [2, 6, 132_597, 67, 42_897, 33, 592, 8, 163_729, 25_540, 361, 136_997, 109_514, 173_230, 7, 501, 60, 102_913, 196, 5_631, 235, 63_243, 473, 6, 231_757, 74, 5_277, 7_905, 53, 3_095, 37_317, 22, 454, 183_874, 5], [2, 268, 31_298, 46_530, 6, 132_935, 43_831, 7, 597, 32, 24, 3_688, 9_865, 5]],
            '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], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]
        }  # noqa: E501
        # fmt: on

        self.tokenizer_integration_test_util(
            expected_encoding=UpperCAmelCase__    ,			model_name='facebook/xglm-564M'    ,			padding=UpperCAmelCase__    ,			)






import torch

from diffusers import StableDiffusionPipeline


__lowerCAmelCase			=							'''path-to-your-trained-model'''
__lowerCAmelCase			=							StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.floataa).to('''cuda''')

__lowerCAmelCase			=							'''A photo of sks dog in a bucket'''
__lowerCAmelCase			=							pipe(prompt, num_inference_steps=50, guidance_scale=7.5).images[0]

image.save('''dog-bucket.png''')


