


import gc
import unittest

from parameterized import parameterized

from diffusers import FlaxUNetaDConditionModel
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import load_hf_numpy, require_flax, slow


if is_flax_available():
   import jax
   import jax.numpy as jnp






@slow
@require_flax
class      UpperCamelCase					(		unittest.TestCase     ):


   '''simple docstring'''







   def 		UpperCamelCase  (     self   ,							UpperCamelCase_   ,							UpperCamelCase_		):
        return f"gaussian_noise_s={seed}_shape={'_'.join([str(UpperCamelCase_		) for s in shape]		)}.npy"
   def 		UpperCamelCase  (     self		):
        # clean up the VRAM after each test
        super().tearDown()
        gc.collect()
   def 		UpperCamelCase  (     self   ,							UpperCamelCase_=0   ,							UpperCamelCase_=(4, 4, 64, 64)   ,							UpperCamelCase_=False		):
        lowercase_       :Dict     =       jnp.bfloataa if fpaa else jnp.floataa
        lowercase_       :Dict     =       jnp.array(load_hf_numpy(self.get_file_format(UpperCamelCase_   ,							UpperCamelCase_		)		)   ,							dtype=UpperCamelCase_		)
        return image
   def 		UpperCamelCase  (     self   ,							UpperCamelCase_=False   ,							UpperCamelCase_="CompVis/stable-diffusion-v1-4"		):
        lowercase_       :Any     =       jnp.bfloataa if fpaa else jnp.floataa
        lowercase_       :Optional[int]     =       '''bf16''' if fpaa else None

        lowercase_       :int     =       FlaxUNetaDConditionModel.from_pretrained(
            UpperCamelCase_   ,							subfolder='''unet'''   ,							dtype=UpperCamelCase_   ,							revision=UpperCamelCase_		)
        return model, params
   def 		UpperCamelCase  (     self   ,							UpperCamelCase_=0   ,							UpperCamelCase_=(4, 77, 768)   ,							UpperCamelCase_=False		):
        lowercase_       :List[Any]     =       jnp.bfloataa if fpaa else jnp.floataa
        lowercase_       :Any     =       jnp.array(load_hf_numpy(self.get_file_format(UpperCamelCase_   ,							UpperCamelCase_		)		)   ,							dtype=UpperCamelCase_		)
        return hidden_states
   @parameterized.expand(
       [
           # fmt: off
           [83, 4, [-0.2323, -0.1304, 0.0813, -0.3093, -0.0919, -0.1571, -0.1125, -0.5806]],
           [17, 0.55, [-0.0831, -0.2443, 0.0901, -0.0919, 0.3396, 0.0103, -0.3743, 0.0701]],
           [8, 0.89, [-0.4863, 0.0859, 0.0875, -0.1658, 0.9199, -0.0114, 0.4839, 0.4639]],
           [3, 1000, [-0.5649, 0.2402, -0.5518, 0.1248, 1.1328, -0.2443, -0.0325, -1.0078]],
           # fmt: on
       ]		)
   def 		UpperCamelCase  (     self   ,							UpperCamelCase_   ,							UpperCamelCase_   ,							UpperCamelCase_		):
        lowercase_       :List[str]     =       self.get_unet_model(model_id='''CompVis/stable-diffusion-v1-4'''   ,							fpaa=UpperCamelCase_		)
        lowercase_       :Any     =       self.get_latents(UpperCamelCase_   ,							fpaa=UpperCamelCase_		)
        lowercase_       :Optional[int]     =       self.get_encoder_hidden_states(UpperCamelCase_   ,							fpaa=UpperCamelCase_		)

        lowercase_       :Optional[int]     =       model.apply(
            {'''params''': params}   ,							UpperCamelCase_   ,							jnp.array(UpperCamelCase_   ,							dtype=jnp.intaa		)   ,							encoder_hidden_states=UpperCamelCase_   ,							).sample

        assert sample.shape == latents.shape

        lowercase_       :Any     =       jnp.asarray(jax.device_get((sample[-1, -2:, -2:, :2].flatten())		)   ,							dtype=jnp.floataa		)
        lowercase_       :Any     =       jnp.array(UpperCamelCase_   ,							dtype=jnp.floataa		)

        # Found torch (float16) and flax (bfloat16) outputs to be within this tolerance, in the same hardware
        assert jnp.allclose(UpperCamelCase_   ,							UpperCamelCase_   ,							atol=1E-2		)




   @parameterized.expand(
       [
           # fmt: off
           [83, 4, [0.1514, 0.0807, 0.1624, 0.1016, -0.1896, 0.0263, 0.0677, 0.2310]],
           [17, 0.55, [0.1164, -0.0216, 0.0170, 0.1589, -0.3120, 0.1005, -0.0581, -0.1458]],
           [8, 0.89, [-0.1758, -0.0169, 0.1004, -0.1411, 0.1312, 0.1103, -0.1996, 0.2139]],
           [3, 1000, [0.1214, 0.0352, -0.0731, -0.1562, -0.0994, -0.0906, -0.2340, -0.0539]],
           # fmt: on
       ]		)
   def 		UpperCamelCase  (     self   ,							UpperCamelCase_   ,							UpperCamelCase_   ,							UpperCamelCase_		):
        lowercase_       :Any     =       self.get_unet_model(model_id='''stabilityai/stable-diffusion-2'''   ,							fpaa=UpperCamelCase_		)
        lowercase_       :List[Any]     =       self.get_latents(UpperCamelCase_   ,							shape=(4, 4, 96, 96)   ,							fpaa=UpperCamelCase_		)
        lowercase_       :Union[str, Any]     =       self.get_encoder_hidden_states(UpperCamelCase_   ,							shape=(4, 77, 1024)   ,							fpaa=UpperCamelCase_		)

        lowercase_       :int     =       model.apply(
            {'''params''': params}   ,							UpperCamelCase_   ,							jnp.array(UpperCamelCase_   ,							dtype=jnp.intaa		)   ,							encoder_hidden_states=UpperCamelCase_   ,							).sample

        assert sample.shape == latents.shape

        lowercase_       :Union[str, Any]     =       jnp.asarray(jax.device_get((sample[-1, -2:, -2:, :2].flatten())		)   ,							dtype=jnp.floataa		)
        lowercase_       :List[Any]     =       jnp.array(UpperCamelCase_   ,							dtype=jnp.floataa		)

        # Found torch (float16) and flax (bfloat16) outputs to be within this tolerance, on the same hardware
        assert jnp.allclose(UpperCamelCase_   ,							UpperCamelCase_   ,							atol=1E-2		)









import shutil
import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartTokenizer, MBartTokenizerFast, is_torch_available
from transformers.testing_utils import (
    get_tests_dir,
    nested_simplify,
    require_sentencepiece,
    require_tokenizers,
    require_torch,
)

from ...test_tokenization_common import TokenizerTesterMixin


SCREAMING_SNAKE_CASE       :		Dict         =				get_tests_dir("fixtures/test_sentencepiece.model")


if is_torch_available():
   from transformers.models.mbart.modeling_mbart import shift_tokens_right

SCREAMING_SNAKE_CASE       :		Any         =				250_004
SCREAMING_SNAKE_CASE       :		Optional[int]         =				250_020






@require_sentencepiece
@require_tokenizers
class      UpperCamelCase					(		lowercase__						,      unittest.TestCase     ):


   '''simple docstring'''







   lowercase					:	Union[str, Any]									=MBartTokenizer
   lowercase					:	Dict									=MBartTokenizerFast
   lowercase					:	Dict									=True
   lowercase					:	List[Any]									=True
   def 		UpperCamelCase  (     self		):
        super().setUp()

        # We have a SentencePiece fixture for testing
        lowercase_       :Optional[Any]     =       MBartTokenizer(UpperCamelCase_   ,							keep_accents=UpperCamelCase_		)
        tokenizer.save_pretrained(self.tmpdirname		)
   def 		UpperCamelCase  (     self		):
        lowercase_       :Optional[Any]     =       MBartTokenizer(UpperCamelCase_   ,							keep_accents=UpperCamelCase_		)

        lowercase_       :Union[str, Any]     =       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_       :List[str]     =       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_       :Dict     =       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]
                #                                       ^ unk: 2 + 1 = 3                  unk: 2 + 1 = 3 ^
            ]   ,							)

        lowercase_       :Optional[Any]     =       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>''',
                '''.''',
            ]   ,							)




   def 		UpperCamelCase  (     self		):
        if not self.test_slow_tokenizer:
             # as we don't have a slow version, we can't compare the outputs between slow and fast versions
             return

        lowercase_       :Optional[Any]     =       (self.rust_tokenizer_class, '''hf-internal-testing/tiny-random-mbart''', {})
        for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
             with self.subTest(f"{tokenizer.__class__.__name__} ({pretrained_name})"		):
                  lowercase_       :Optional[int]     =       self.rust_tokenizer_class.from_pretrained(UpperCamelCase_   ,							**UpperCamelCase_		)
                  lowercase_       :int     =       self.tokenizer_class.from_pretrained(UpperCamelCase_   ,							**UpperCamelCase_		)

                  lowercase_       :Optional[int]     =       tempfile.mkdtemp()

                  lowercase_       :Union[str, Any]     =       tokenizer_r.save_pretrained(UpperCamelCase_		)
                  lowercase_       :int     =       tokenizer_p.save_pretrained(UpperCamelCase_		)

                  # Checks it save with the same files + the tokenizer.json file for the fast one
                  self.assertTrue(any('''tokenizer.json''' in f for f in tokenizer_r_files		)		)
                  lowercase_       :Union[str, Any]     =       tuple(f for f in tokenizer_r_files if '''tokenizer.json''' not in f		)
                  self.assertSequenceEqual(UpperCamelCase_   ,							UpperCamelCase_		)

                  # Checks everything loads correctly in the same way
                  lowercase_       :str     =       tokenizer_r.from_pretrained(UpperCamelCase_		)
                  lowercase_       :Optional[Any]     =       tokenizer_p.from_pretrained(UpperCamelCase_		)

                  # Check special tokens are set accordingly on Rust and Python
                  for key in tokenizer_pp.special_tokens_map:
                       self.assertTrue(hasattr(UpperCamelCase_   ,							UpperCamelCase_		)		)
                       # self.assertEqual(getattr(tokenizer_rp, key), getattr(tokenizer_pp, key))
                       # self.assertEqual(getattr(tokenizer_rp, key + "_id"), getattr(tokenizer_pp, key + "_id"))

                  shutil.rmtree(UpperCamelCase_		)

                  # Save tokenizer rust, legacy_format=True
                  lowercase_       :int     =       tempfile.mkdtemp()

                  lowercase_       :Optional[Any]     =       tokenizer_r.save_pretrained(UpperCamelCase_   ,							legacy_format=UpperCamelCase_		)
                  lowercase_       :Any     =       tokenizer_p.save_pretrained(UpperCamelCase_		)

                  # Checks it save with the same files
                  self.assertSequenceEqual(UpperCamelCase_   ,							UpperCamelCase_		)

                  # Checks everything loads correctly in the same way
                  lowercase_       :Optional[int]     =       tokenizer_r.from_pretrained(UpperCamelCase_		)
                  lowercase_       :Dict     =       tokenizer_p.from_pretrained(UpperCamelCase_		)

                  # Check special tokens are set accordingly on Rust and Python
                  for key in tokenizer_pp.special_tokens_map:
                       self.assertTrue(hasattr(UpperCamelCase_   ,							UpperCamelCase_		)		)

                  shutil.rmtree(UpperCamelCase_		)

                  # Save tokenizer rust, legacy_format=False
                  lowercase_       :Tuple     =       tempfile.mkdtemp()

                  lowercase_       :Optional[int]     =       tokenizer_r.save_pretrained(UpperCamelCase_   ,							legacy_format=UpperCamelCase_		)
                  lowercase_       :Tuple     =       tokenizer_p.save_pretrained(UpperCamelCase_		)

                  # Checks it saved the tokenizer.json file
                  self.assertTrue(any('''tokenizer.json''' in f for f in tokenizer_r_files		)		)

                  # Checks everything loads correctly in the same way
                  lowercase_       :int     =       tokenizer_r.from_pretrained(UpperCamelCase_		)
                  lowercase_       :Any     =       tokenizer_p.from_pretrained(UpperCamelCase_		)

                  # Check special tokens are set accordingly on Rust and Python
                  for key in tokenizer_pp.special_tokens_map:
                       self.assertTrue(hasattr(UpperCamelCase_   ,							UpperCamelCase_		)		)

                  shutil.rmtree(UpperCamelCase_		)






@require_torch
@require_sentencepiece
@require_tokenizers
class      UpperCamelCase					(		unittest.TestCase     ):


   '''simple docstring'''







   lowercase					:	List[Any]									="""facebook/mbart-large-en-ro"""
   lowercase					:	Optional[Any]									=[
       """ UN Chief Says There Is No Military Solution in Syria""",
       """ Secretary-General Ban Ki-moon says his response to Russia's stepped up military support for Syria is that \"there is no military solution\" to the nearly five-year conflict and more weapons will only worsen the violence and misery for millions of people.""",
   ]
   lowercase					:	Dict									=[
       """Şeful ONU declară că nu există o soluţie militară în Siria""",
       """Secretarul General Ban Ki-moon declară că răspunsul său la intensificarea sprijinului militar al Rusiei"""
       """ pentru Siria este că \"nu există o soluţie militară\" la conflictul de aproape cinci ani şi că noi arme nu vor"""
       """ face decât să înrăutăţească violenţele şi mizeria pentru milioane de oameni.""",
   ]
   lowercase					:	Tuple									=[8274, 127873, 25916, 7, 8622, 2071, 438, 67485, 53, 187895, 23, 51712, 2, EN_CODE]
   @classmethod
   def 		UpperCamelCase  (     cls		):
        lowercase_       :MBartTokenizer     =       MBartTokenizer.from_pretrained(
            cls.checkpoint_name   ,							src_lang='''en_XX'''   ,							tgt_lang='''ro_RO'''		)
        lowercase_       :Optional[int]     =       1
        return cls
   def 		UpperCamelCase  (     self		):
        self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['''ar_AR''']   ,							25_0001		)
        self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['''en_EN''']   ,							25_0004		)
        self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['''ro_RO''']   ,							25_0020		)
   def 		UpperCamelCase  (     self		):
        lowercase_       :Dict     =       self.tokenizer.batch_encode_plus(self.src_text		).input_ids[0]
        self.assertListEqual(self.expected_src_tokens   ,							UpperCamelCase_		)
   def 		UpperCamelCase  (     self		):
        self.assertIn(UpperCamelCase_   ,							self.tokenizer.all_special_ids		)
        lowercase_       :List[Any]     =       [RO_CODE, 884, 9019, 96, 9, 916, 8_6792, 36, 1_8743, 1_5596, 5, 2]
        lowercase_       :str     =       self.tokenizer.decode(UpperCamelCase_   ,							skip_special_tokens=UpperCamelCase_		)
        lowercase_       :List[str]     =       self.tokenizer.decode(generated_ids[1:]   ,							skip_special_tokens=UpperCamelCase_		)
        self.assertEqual(UpperCamelCase_   ,							UpperCamelCase_		)
        self.assertNotIn(self.tokenizer.eos_token   ,							UpperCamelCase_		)
   def 		UpperCamelCase  (     self		):
        lowercase_       :Dict     =       ['''this is gunna be a long sentence ''' * 20]
        assert isinstance(src_text[0]   ,							UpperCamelCase_		)
        lowercase_       :Dict     =       10
        lowercase_       :Any     =       self.tokenizer(UpperCamelCase_   ,							max_length=UpperCamelCase_   ,							truncation=UpperCamelCase_		).input_ids[0]
        self.assertEqual(ids[-2]   ,							2		)
        self.assertEqual(ids[-1]   ,							UpperCamelCase_		)
        self.assertEqual(len(UpperCamelCase_		)   ,							UpperCamelCase_		)
   def 		UpperCamelCase  (     self		):
        self.assertListEqual(self.tokenizer.convert_tokens_to_ids(['''<mask>''', '''ar_AR''']		)   ,							[25_0026, 25_0001]		)
   def 		UpperCamelCase  (     self		):
        lowercase_       :List[Any]     =       tempfile.mkdtemp()
        lowercase_       :List[Any]     =       self.tokenizer.fairseq_tokens_to_ids
        self.tokenizer.save_pretrained(UpperCamelCase_		)
        lowercase_       :Tuple     =       MBartTokenizer.from_pretrained(UpperCamelCase_		)
        self.assertDictEqual(new_tok.fairseq_tokens_to_ids   ,							UpperCamelCase_		)
   @require_torch
   def 		UpperCamelCase  (     self		):
        lowercase_       :str     =       self.tokenizer(self.src_text   ,							text_target=self.tgt_text   ,							padding=UpperCamelCase_   ,							return_tensors='''pt'''		)
        lowercase_       :Union[str, Any]     =       shift_tokens_right(batch['''labels''']   ,							self.tokenizer.pad_token_id		)

        # fairseq batch: https://gist.github.com/sshleifer/cba08bc2109361a74ac3760a7e30e4f4
        assert batch.input_ids[1][-2:].tolist() == [2, EN_CODE]
        assert batch.decoder_input_ids[1][0].tolist() == RO_CODE
        assert batch.decoder_input_ids[1][-1] == 2
        assert batch.labels[1][-2:].tolist() == [2, RO_CODE]
   @require_torch
   def 		UpperCamelCase  (     self		):
        lowercase_       :Any     =       self.tokenizer(
            self.src_text   ,							text_target=self.tgt_text   ,							padding=UpperCamelCase_   ,							truncation=UpperCamelCase_   ,							max_length=len(self.expected_src_tokens		)   ,							return_tensors='''pt'''   ,							)

        lowercase_       :Tuple     =       shift_tokens_right(batch['''labels''']   ,							self.tokenizer.pad_token_id		)

        self.assertIsInstance(UpperCamelCase_   ,							UpperCamelCase_		)

        self.assertEqual((2, 14)   ,							batch.input_ids.shape		)
        self.assertEqual((2, 14)   ,							batch.attention_mask.shape		)
        lowercase_       :List[str]     =       batch.input_ids.tolist()[0]
        self.assertListEqual(self.expected_src_tokens   ,							UpperCamelCase_		)
        self.assertEqual(2   ,							batch.decoder_input_ids[0, -1]		)  # EOS
        # Test that special tokens are reset
        self.assertEqual(self.tokenizer.prefix_tokens   ,							[]		)
        self.assertEqual(self.tokenizer.suffix_tokens   ,							[self.tokenizer.eos_token_id, EN_CODE]		)
   def 		UpperCamelCase  (     self		):
        lowercase_       :Any     =       self.tokenizer(self.src_text   ,							padding=UpperCamelCase_   ,							truncation=UpperCamelCase_   ,							max_length=3   ,							return_tensors='''pt'''		)
        lowercase_       :int     =       self.tokenizer(
            text_target=self.tgt_text   ,							padding=UpperCamelCase_   ,							truncation=UpperCamelCase_   ,							max_length=10   ,							return_tensors='''pt'''		)
        lowercase_       :Optional[int]     =       targets['''input_ids''']
        lowercase_       :List[Any]     =       shift_tokens_right(UpperCamelCase_   ,							self.tokenizer.pad_token_id		)

        self.assertEqual(batch.input_ids.shape[1]   ,							3		)
        self.assertEqual(batch.decoder_input_ids.shape[1]   ,							10		)




   @require_torch
   def 		UpperCamelCase  (     self		):
        lowercase_       :int     =       self.tokenizer._build_translation_inputs(
            '''A test'''   ,							return_tensors='''pt'''   ,							src_lang='''en_XX'''   ,							tgt_lang='''ar_AR'''		)

        self.assertEqual(
            nested_simplify(UpperCamelCase_		)   ,							{
                # A, test, EOS, en_XX
                '''input_ids''': [[62, 3034, 2, 25_0004]],
                '''attention_mask''': [[1, 1, 1, 1]],
                # ar_AR
                '''forced_bos_token_id''': 25_0001,
            }   ,							)

