
"""simple docstring"""






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 					__a     ( unittest.TestCase       ):



							'''simple docstring'''







							def   SCREAMING_SNAKE_CASE						(     self  ,    _lowerCamelCase  ,    _lowerCamelCase       )			->							Any:




										'''simple docstring'''
										return f'''gaussian_noise_s={seed}_shape={'_'.join([str(_lowerCamelCase       ) for s in shape]       )}.npy'''
							def   SCREAMING_SNAKE_CASE						(     self       )			->							List[Any]:




										'''simple docstring'''
										# clean up the VRAM after each test
										super().tearDown()
										gc.collect()
							def   SCREAMING_SNAKE_CASE						(     self  ,    _lowerCamelCase=0  ,    _lowerCamelCase=(4, 4, 64, 64)  ,    _lowerCamelCase=False       )			->							Optional[int]:




										'''simple docstring'''
										__lowercase       =       jnp.bfloataa if fpaa else jnp.floataa
										__lowercase       =       jnp.array(load_hf_numpy(self.get_file_format(_lowerCamelCase  ,    _lowerCamelCase       )       )  ,    dtype=_lowerCamelCase       )
										return image
							def   SCREAMING_SNAKE_CASE						(     self  ,    _lowerCamelCase=False  ,    _lowerCamelCase="CompVis/stable-diffusion-v1-4"       )			->							Tuple:




										'''simple docstring'''
										__lowercase       =       jnp.bfloataa if fpaa else jnp.floataa
										__lowercase       =       "bf16" if fpaa else None

										__lowercase   ,					__lowercase       =       FlaxUNetaDConditionModel.from_pretrained(
										    _lowerCamelCase  ,    subfolder="unet"  ,    dtype=_lowerCamelCase  ,    revision=_lowerCamelCase       )
										return model, params
							def   SCREAMING_SNAKE_CASE						(     self  ,    _lowerCamelCase=0  ,    _lowerCamelCase=(4, 77, 768)  ,    _lowerCamelCase=False       )			->							Any:




										'''simple docstring'''
										__lowercase       =       jnp.bfloataa if fpaa else jnp.floataa
										__lowercase       =       jnp.array(load_hf_numpy(self.get_file_format(_lowerCamelCase  ,    _lowerCamelCase       )       )  ,    dtype=_lowerCamelCase       )
										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, 1_000, [-0.5649, 0.2402, -0.5518, 0.1248, 1.1328, -0.2443, -0.0325, -1.0078]],
							        # fmt: on
							    ]       )
							def   SCREAMING_SNAKE_CASE						(     self  ,    _lowerCamelCase  ,    _lowerCamelCase  ,    _lowerCamelCase       )			->							int:




										'''simple docstring'''
										__lowercase   ,					__lowercase       =       self.get_unet_model(model_id="CompVis/stable-diffusion-v1-4"  ,    fpaa=_lowerCamelCase       )
										__lowercase       =       self.get_latents(_lowerCamelCase  ,    fpaa=_lowerCamelCase       )
										__lowercase       =       self.get_encoder_hidden_states(_lowerCamelCase  ,    fpaa=_lowerCamelCase       )

										__lowercase       =       model.apply(
										    {"params": params}  ,    _lowerCamelCase  ,    jnp.array(_lowerCamelCase  ,    dtype=jnp.intaa       )  ,    encoder_hidden_states=_lowerCamelCase  ,    ).sample

										assert sample.shape == latents.shape

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

										# Found torch (float16) and flax (bfloat16) outputs to be within this tolerance, in the same hardware
										assert jnp.allclose(_lowerCamelCase  ,    _lowerCamelCase  ,    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, 1_000, [0.1214, 0.0352, -0.0731, -0.1562, -0.0994, -0.0906, -0.2340, -0.0539]],
							        # fmt: on
							    ]       )
							def   SCREAMING_SNAKE_CASE						(     self  ,    _lowerCamelCase  ,    _lowerCamelCase  ,    _lowerCamelCase       )			->							Dict:




										'''simple docstring'''
										__lowercase   ,					__lowercase       =       self.get_unet_model(model_id="stabilityai/stable-diffusion-2"  ,    fpaa=_lowerCamelCase       )
										__lowercase       =       self.get_latents(_lowerCamelCase  ,    shape=(4, 4, 96, 96)  ,    fpaa=_lowerCamelCase       )
										__lowercase       =       self.get_encoder_hidden_states(_lowerCamelCase  ,    shape=(4, 77, 1_024)  ,    fpaa=_lowerCamelCase       )

										__lowercase       =       model.apply(
										    {"params": params}  ,    _lowerCamelCase  ,    jnp.array(_lowerCamelCase  ,    dtype=jnp.intaa       )  ,    encoder_hidden_states=_lowerCamelCase  ,    ).sample

										assert sample.shape == latents.shape

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

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







"""simple docstring"""






import os
from tempfile import TemporaryDirectory
from unittest import TestCase

import pytest
from absl.testing import parameterized

from datasets import config
from datasets.arrow_reader import HF_GCP_BASE_URL
from datasets.builder import DatasetBuilder
from datasets.dataset_dict import IterableDatasetDict
from datasets.iterable_dataset import IterableDataset
from datasets.load import dataset_module_factory, import_main_class
from datasets.utils.file_utils import cached_path


_lowercase							=				[
    {'''dataset''': '''wikipedia''', '''config_name''': '''20220301.de'''},
    {'''dataset''': '''wikipedia''', '''config_name''': '''20220301.en'''},
    {'''dataset''': '''wikipedia''', '''config_name''': '''20220301.fr'''},
    {'''dataset''': '''wikipedia''', '''config_name''': '''20220301.frr'''},
    {'''dataset''': '''wikipedia''', '''config_name''': '''20220301.it'''},
    {'''dataset''': '''wikipedia''', '''config_name''': '''20220301.simple'''},
    {'''dataset''': '''snli''', '''config_name''': '''plain_text'''},
    {'''dataset''': '''eli5''', '''config_name''': '''LFQA_reddit'''},
    {'''dataset''': '''wiki40b''', '''config_name''': '''en'''},
    {'''dataset''': '''wiki_dpr''', '''config_name''': '''psgs_w100.nq.compressed'''},
    {'''dataset''': '''wiki_dpr''', '''config_name''': '''psgs_w100.nq.no_index'''},
    {'''dataset''': '''wiki_dpr''', '''config_name''': '''psgs_w100.multiset.no_index'''},
    {'''dataset''': '''natural_questions''', '''config_name''': '''default'''},
]



def      lowerCAmelCase__			(		__magic_name__=True      )						->int:
			if with_config:
						return [
						    {
						        "testcase_name": d["dataset"] + "/" + d["config_name"],
						        "dataset": d["dataset"],
						        "config_name": d["config_name"],
						    }
						    for d in DATASETS_ON_HF_GCP
						]
			else:
						return [
						    {"testcase_name": dataset, "dataset": dataset} for dataset in {d["dataset"] for d in DATASETS_ON_HF_GCP}
						]

@parameterized.named_parameters(list_datasets_on_hf_gcp_parameters(with_config=__a       )       )
class 					__a     ( __a       ):



							'''simple docstring'''







							_lowerCamelCase					:			int          =   None
							_lowerCamelCase					:			int          =   None
							def   SCREAMING_SNAKE_CASE						(     self  ,    _lowerCamelCase  ,    _lowerCamelCase       )			->							Optional[Any]:




										'''simple docstring'''
										with TemporaryDirectory() as tmp_dir:
													__lowercase       =       dataset_module_factory(_lowerCamelCase  ,    cache_dir=_lowerCamelCase       )

													__lowercase       =       import_main_class(dataset_module.module_path  ,    dataset=_lowerCamelCase       )

													__lowercase       =       builder_cls(
													    cache_dir=_lowerCamelCase  ,    config_name=_lowerCamelCase  ,    hash=dataset_module.hash  ,    )

													__lowercase       =       "/".join(
													    [
													        HF_GCP_BASE_URL,
													        builder_instance._relative_data_dir(with_hash=_lowerCamelCase       ).replace(os.sep  ,    "/"       ),
													        config.DATASET_INFO_FILENAME,
													    ]       )
													__lowercase       =       cached_path(_lowerCamelCase  ,    cache_dir=_lowerCamelCase       )
													self.assertTrue(os.path.exists(_lowerCamelCase       )       )





@pytest.mark.integration
def      lowerCAmelCase__			(		__magic_name__      )						->str:
			__lowercase       =       tmp_path_factory.mktemp("test_hf_gcp"      ) / "test_wikipedia_simple"
			__lowercase       =       dataset_module_factory("wikipedia"			,   cache_dir=__magic_name__      )
			__lowercase       =       import_main_class(dataset_module.module_path      )
			__lowercase       =       builder_cls(
			    cache_dir=__magic_name__			,   config_name="20220301.frr"			,   hash=dataset_module.hash			,   )
			# use the HF cloud storage, not the original download_and_prepare that uses apache-beam
			__lowercase       =       None
			builder_instance.download_and_prepare()
			__lowercase       =       builder_instance.as_dataset()
			assert ds







@pytest.mark.integration
def      lowerCAmelCase__			(		__magic_name__      )						->Any:
			__lowercase       =       dataset_module_factory("wikipedia"			,   cache_dir=__magic_name__      )
			__lowercase       =       import_main_class(dataset_module.module_path			,   dataset=__magic_name__      )
			__lowercase       =       builder_cls(
			    cache_dir=__magic_name__			,   config_name="20220301.frr"			,   hash=dataset_module.hash			,   )
			__lowercase       =       builder_instance.as_streaming_dataset()
			assert ds
			assert isinstance(__magic_name__			,   __magic_name__      )
			assert "train" in ds
			assert isinstance(ds["train"]			,   __magic_name__      )
			assert next(iter(ds["train"]      )      )





