



import io
import json

import fsspec
import pytest

from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.json import JsonDatasetReader, JsonDatasetWriter

from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases







def     UpperCAmelCase_		(					snake_case__    ,			snake_case__					)	->     Optional[int]:



				"""simple docstring"""





				assert isinstance(snake_case__    ,			snake_case__					)
				assert dataset.num_rows == 4
				assert dataset.num_columns == 3
				assert dataset.column_names == ["col_1", "col_2", "col_3"]
				for feature, expected_dtype in expected_features.items():
								assert dataset.features[feature].dtype == expected_dtype







@pytest.mark.parametrize('keep_in_memory'    ,			[False, True]					)
def     UpperCAmelCase_		(					snake_case__    ,			snake_case__    ,			snake_case__					)	->     Tuple:



				"""simple docstring"""





				lowerCAmelCase__		  =  tmp_path / 'cache'
				lowerCAmelCase__		  =  {'col_1': 'string', 'col_2': 'int64', 'col_3': 'float64'}
				with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
								lowerCAmelCase__		  =  JsonDatasetReader(snake_case__    ,			cache_dir=snake_case__    ,			keep_in_memory=snake_case__					).read()
				_check_json_dataset(snake_case__    ,			snake_case__					)







@pytest.mark.parametrize(
    'features'    ,			[
        None,
        {'col_1': 'string', 'col_2': 'int64', 'col_3': 'float64'},
        {'col_1': 'string', 'col_2': 'string', 'col_3': 'string'},
        {'col_1': 'int32', 'col_2': 'int32', 'col_3': 'int32'},
        {'col_1': 'float32', 'col_2': 'float32', 'col_3': 'float32'},
    ]    ,			)
def     UpperCAmelCase_		(					snake_case__    ,			snake_case__    ,			snake_case__					)	->     Dict:



				"""simple docstring"""





				lowerCAmelCase__		  =  tmp_path / 'cache'
				lowerCAmelCase__		  =  {'col_1': 'string', 'col_2': 'int64', 'col_3': 'float64'}
				lowerCAmelCase__		  =  features.copy() if features else default_expected_features
				lowerCAmelCase__		  =  (
				    Features({feature: Value(snake_case__					) for feature, dtype in features.items()}					) if features is not None else None
				)
				lowerCAmelCase__		  =  JsonDatasetReader(snake_case__    ,			features=snake_case__    ,			cache_dir=snake_case__					).read()
				_check_json_dataset(snake_case__    ,			snake_case__					)







@pytest.mark.parametrize(
    'features'    ,			[
        None,
        {'col_3': 'float64', 'col_1': 'string', 'col_2': 'int64'},
    ]    ,			)
def     UpperCAmelCase_		(					snake_case__    ,			snake_case__    ,			snake_case__					)	->     Any:



				"""simple docstring"""





				lowerCAmelCase__		  =  tmp_path / 'cache'
				lowerCAmelCase__		  =  {'col_3': 'float64', 'col_1': 'string', 'col_2': 'int64'}
				lowerCAmelCase__		  =  features.copy() if features else default_expected_features
				lowerCAmelCase__		  =  (
				    Features({feature: Value(snake_case__					) for feature, dtype in features.items()}					) if features is not None else None
				)
				lowerCAmelCase__		  =  JsonDatasetReader(snake_case__    ,			features=snake_case__    ,			cache_dir=snake_case__					).read()
				assert isinstance(snake_case__    ,			snake_case__					)
				assert dataset.num_rows == 2
				assert dataset.num_columns == 3
				assert dataset.column_names == ["col_3", "col_1", "col_2"]
				for feature, expected_dtype in expected_features.items():
								assert dataset.features[feature].dtype == expected_dtype







def     UpperCAmelCase_		(					snake_case__    ,			snake_case__					)	->     int:



				"""simple docstring"""





				lowerCAmelCase__		  =  {'col_2': 'int64', 'col_3': 'float64', 'col_1': 'string'}
				lowerCAmelCase__		  =  features.copy()
				lowerCAmelCase__		  =  (
				    Features({feature: Value(snake_case__					) for feature, dtype in features.items()}					) if features is not None else None
				)
				lowerCAmelCase__		  =  tmp_path / 'cache'
				lowerCAmelCase__		  =  JsonDatasetReader(snake_case__    ,			features=snake_case__    ,			cache_dir=snake_case__					).read()
				assert isinstance(snake_case__    ,			snake_case__					)
				assert dataset.num_rows == 2
				assert dataset.num_columns == 3
				assert dataset.column_names == ["col_2", "col_3", "col_1"]
				for feature, expected_dtype in expected_features.items():
								assert dataset.features[feature].dtype == expected_dtype







@pytest.mark.parametrize('split'    ,			[None, NamedSplit('train'					), 'train', 'test']					)
def     UpperCAmelCase_		(					snake_case__    ,			snake_case__    ,			snake_case__					)	->     Union[str, Any]:



				"""simple docstring"""





				lowerCAmelCase__		  =  tmp_path / 'cache'
				lowerCAmelCase__		  =  {'col_1': 'string', 'col_2': 'int64', 'col_3': 'float64'}
				lowerCAmelCase__		  =  JsonDatasetReader(snake_case__    ,			cache_dir=snake_case__    ,			split=snake_case__					).read()
				_check_json_dataset(snake_case__    ,			snake_case__					)
				assert dataset.split == split if split else "train"







@pytest.mark.parametrize('path_type'    ,			[str, list]					)
def     UpperCAmelCase_		(					snake_case__    ,			snake_case__    ,			snake_case__					)	->     int:



				"""simple docstring"""





				if issubclass(snake_case__    ,			snake_case__					):
								lowerCAmelCase__		  =  jsonl_path
				elif issubclass(snake_case__    ,			snake_case__					):
								lowerCAmelCase__		  =  [jsonl_path]
				lowerCAmelCase__		  =  tmp_path / 'cache'
				lowerCAmelCase__		  =  {'col_1': 'string', 'col_2': 'int64', 'col_3': 'float64'}
				lowerCAmelCase__		  =  JsonDatasetReader(snake_case__    ,			cache_dir=snake_case__					).read()
				_check_json_dataset(snake_case__    ,			snake_case__					)







def     UpperCAmelCase_		(					snake_case__    ,			snake_case__    ,			snake_case__=("train",)					)	->     Any:



				"""simple docstring"""





				assert isinstance(snake_case__    ,			snake_case__					)
				for split in splits:
								lowerCAmelCase__		  =  dataset_dict[split]
								assert dataset.num_rows == 4
								assert dataset.num_columns == 3
								assert dataset.column_names == ["col_1", "col_2", "col_3"]
								for feature, expected_dtype in expected_features.items():
												assert dataset.features[feature].dtype == expected_dtype







@pytest.mark.parametrize('keep_in_memory'    ,			[False, True]					)
def     UpperCAmelCase_		(					snake_case__    ,			snake_case__    ,			snake_case__					)	->     List[str]:



				"""simple docstring"""





				lowerCAmelCase__		  =  tmp_path / 'cache'
				lowerCAmelCase__		  =  {'col_1': 'string', 'col_2': 'int64', 'col_3': 'float64'}
				with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
								lowerCAmelCase__		  =  JsonDatasetReader({'train': jsonl_path}    ,			cache_dir=snake_case__    ,			keep_in_memory=snake_case__					).read()
				_check_json_datasetdict(snake_case__    ,			snake_case__					)







@pytest.mark.parametrize(
    'features'    ,			[
        None,
        {'col_1': 'string', 'col_2': 'int64', 'col_3': 'float64'},
        {'col_1': 'string', 'col_2': 'string', 'col_3': 'string'},
        {'col_1': 'int32', 'col_2': 'int32', 'col_3': 'int32'},
        {'col_1': 'float32', 'col_2': 'float32', 'col_3': 'float32'},
    ]    ,			)
def     UpperCAmelCase_		(					snake_case__    ,			snake_case__    ,			snake_case__					)	->     int:



				"""simple docstring"""





				lowerCAmelCase__		  =  tmp_path / 'cache'
				lowerCAmelCase__		  =  {'col_1': 'string', 'col_2': 'int64', 'col_3': 'float64'}
				lowerCAmelCase__		  =  features.copy() if features else default_expected_features
				lowerCAmelCase__		  =  (
				    Features({feature: Value(snake_case__					) for feature, dtype in features.items()}					) if features is not None else None
				)
				lowerCAmelCase__		  =  JsonDatasetReader({'train': jsonl_path}    ,			features=snake_case__    ,			cache_dir=snake_case__					).read()
				_check_json_datasetdict(snake_case__    ,			snake_case__					)







@pytest.mark.parametrize('split'    ,			[None, NamedSplit('train'					), 'train', 'test']					)
def     UpperCAmelCase_		(					snake_case__    ,			snake_case__    ,			snake_case__					)	->     Optional[int]:



				"""simple docstring"""





				if split:
								lowerCAmelCase__		  =  {split: jsonl_path}
				else:
								lowerCAmelCase__		  =  'train'
								lowerCAmelCase__		  =  {'train': jsonl_path, 'test': jsonl_path}
				lowerCAmelCase__		  =  tmp_path / 'cache'
				lowerCAmelCase__		  =  {'col_1': 'string', 'col_2': 'int64', 'col_3': 'float64'}
				lowerCAmelCase__		  =  JsonDatasetReader(snake_case__    ,			cache_dir=snake_case__					).read()
				_check_json_datasetdict(snake_case__    ,			snake_case__    ,			splits=list(path.keys()					)					)
				assert all(dataset[split].split == split for split in path.keys()					)







def     UpperCAmelCase_		(					snake_case__					)	->     List[str]:



				"""simple docstring"""





				return json.load(snake_case__					)







def     UpperCAmelCase_		(					snake_case__					)	->     Optional[Any]:



				"""simple docstring"""





				return [json.loads(snake_case__					) for line in buffer]


class 	__snake_case   :
		@pytest.mark.parametrize('lines, load_json_function'    ,[(True, load_json_lines), (False, load_json)]						)
		def 						SCREAMING_SNAKE_CASE_					(							self    ,a_    ,a_    ,a_						):







						"""simple docstring"""
						with io.BytesIO() as buffer:
										JsonDatasetWriter(a_    ,a_    ,lines=a_						).write()
										buffer.seek(0						)
										lowerCAmelCase__		  =  load_json_function(a_						)
						assert isinstance(a_    ,a_						)
						assert isinstance(exported_content[0]    ,a_						)
						assert len(a_						) == 10
		@pytest.mark.parametrize(
		    'orient, container, keys, len_at'    ,[
		        ('records', list, {'tokens', 'labels', 'answers', 'id'}, None),
		        ('split', dict, {'columns', 'data'}, 'data'),
		        ('index', dict, set('0123456789'						), None),
		        ('columns', dict, {'tokens', 'labels', 'answers', 'id'}, 'tokens'),
		        ('values', list, None, None),
		        ('table', dict, {'schema', 'data'}, 'data'),
		    ]    ,)
		def 						SCREAMING_SNAKE_CASE_					(							self    ,a_    ,a_    ,a_    ,a_    ,a_						):







						"""simple docstring"""
						with io.BytesIO() as buffer:
										JsonDatasetWriter(a_    ,a_    ,lines=a_    ,orient=a_						).write()
										buffer.seek(0						)
										lowerCAmelCase__		  =  load_json(a_						)
						assert isinstance(a_    ,a_						)
						if keys:
										if container is dict:
														assert exported_content.keys() == keys
										else:
														assert exported_content[0].keys() == keys
						else:
										assert not hasattr(a_    ,'keys'						) and not hasattr(exported_content[0]    ,'keys'						)
						if len_at:
										assert len(exported_content[len_at]						) == 10
						else:
										assert len(a_						) == 10
		@pytest.mark.parametrize('lines, load_json_function'    ,[(True, load_json_lines), (False, load_json)]						)
		def 						SCREAMING_SNAKE_CASE_					(							self    ,a_    ,a_    ,a_						):







						"""simple docstring"""
						with io.BytesIO() as buffer:
										JsonDatasetWriter(a_    ,a_    ,lines=a_    ,num_proc=2						).write()
										buffer.seek(0						)
										lowerCAmelCase__		  =  load_json_function(a_						)
						assert isinstance(a_    ,a_						)
						assert isinstance(exported_content[0]    ,a_						)
						assert len(a_						) == 10
		@pytest.mark.parametrize(
		    'orient, container, keys, len_at'    ,[
		        ('records', list, {'tokens', 'labels', 'answers', 'id'}, None),
		        ('split', dict, {'columns', 'data'}, 'data'),
		        ('index', dict, set('0123456789'						), None),
		        ('columns', dict, {'tokens', 'labels', 'answers', 'id'}, 'tokens'),
		        ('values', list, None, None),
		        ('table', dict, {'schema', 'data'}, 'data'),
		    ]    ,)
		def 						SCREAMING_SNAKE_CASE_					(							self    ,a_    ,a_    ,a_    ,a_    ,a_						):







						"""simple docstring"""
						with io.BytesIO() as buffer:
										JsonDatasetWriter(a_    ,a_    ,lines=a_    ,orient=a_    ,num_proc=2						).write()
										buffer.seek(0						)
										lowerCAmelCase__		  =  load_json(a_						)
						assert isinstance(a_    ,a_						)
						if keys:
										if container is dict:
														assert exported_content.keys() == keys
										else:
														assert exported_content[0].keys() == keys
						else:
										assert not hasattr(a_    ,'keys'						) and not hasattr(exported_content[0]    ,'keys'						)
						if len_at:
										assert len(exported_content[len_at]						) == 10
						else:
										assert len(a_						) == 10
		def 						SCREAMING_SNAKE_CASE_					(							self    ,a_						):







						"""simple docstring"""
						with pytest.raises(a_						):
										with io.BytesIO() as buffer:
														JsonDatasetWriter(a_    ,a_    ,num_proc=0						)



		@pytest.mark.parametrize('compression, extension'    ,[('gzip', 'gz'), ('bz2', 'bz2'), ('xz', 'xz')]						)
		def 						SCREAMING_SNAKE_CASE_					(							self    ,a_    ,a_    ,a_    ,a_    ,a_						):







						"""simple docstring"""
						lowerCAmelCase__		  =  tmp_path_factory.mktemp('data'						) / f'test.json.{extension}'
						lowerCAmelCase__		  =  str(shared_datadir / f'test_file.json.{extension}'						)
						JsonDatasetWriter(a_    ,a_    ,compression=a_						).write()

						with fsspec.open(a_    ,'rb'    ,compression='infer'						) as f:
										lowerCAmelCase__		  =  f.read()
						with fsspec.open(a_    ,'rb'    ,compression='infer'						) as f:
										lowerCAmelCase__		  =  f.read()
						assert exported_content == original_content





import gc
import tempfile
import unittest

import numpy as np
import torch

from diffusers import VersatileDiffusionPipeline
from diffusers.utils.testing_utils import load_image, nightly, require_torch_gpu, torch_device


_lowerCAmelCase	:   Any    =   False


class 	__snake_case   ( unittest.TestCase ):
		pass



@nightly
@require_torch_gpu
class 	__snake_case   ( unittest.TestCase ):
		def 						SCREAMING_SNAKE_CASE_					(							self						):







						"""simple docstring"""
						# clean up the VRAM after each test
						super().tearDown()
						gc.collect()
						torch.cuda.empty_cache()
		def 						SCREAMING_SNAKE_CASE_					(							self						):







						"""simple docstring"""
						lowerCAmelCase__		  =  VersatileDiffusionPipeline.from_pretrained('shi-labs/versatile-diffusion'    ,torch_dtype=torch.floataa						)
						pipe.to(a_						)
						pipe.set_progress_bar_config(disable=a_						)

						lowerCAmelCase__		  =  load_image(
						    'https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/versatile_diffusion/benz.jpg'						)

						lowerCAmelCase__		  =  torch.manual_seed(0						)
						lowerCAmelCase__		  =  pipe.dual_guided(
						    prompt='first prompt'    ,image=a_    ,text_to_image_strength=0.75    ,generator=a_    ,guidance_scale=7.5    ,num_inference_steps=2    ,output_type='numpy'    ,).images

						with tempfile.TemporaryDirectory() as tmpdirname:
										pipe.save_pretrained(a_						)
										lowerCAmelCase__		  =  VersatileDiffusionPipeline.from_pretrained(a_    ,torch_dtype=torch.floataa						)
						pipe.to(a_						)
						pipe.set_progress_bar_config(disable=a_						)

						lowerCAmelCase__		  =  generator.manual_seed(0						)
						lowerCAmelCase__		  =  pipe.dual_guided(
						    prompt='first prompt'    ,image=a_    ,text_to_image_strength=0.75    ,generator=a_    ,guidance_scale=7.5    ,num_inference_steps=2    ,output_type='numpy'    ,).images

						assert np.abs(image - new_image						).sum() < 1e-5, "Models don't have the same forward pass"



		def 						SCREAMING_SNAKE_CASE_					(							self						):







						"""simple docstring"""
						lowerCAmelCase__		  =  VersatileDiffusionPipeline.from_pretrained('shi-labs/versatile-diffusion'    ,torch_dtype=torch.floataa						)
						pipe.to(a_						)
						pipe.set_progress_bar_config(disable=a_						)

						lowerCAmelCase__		  =  'cyberpunk 2077'
						lowerCAmelCase__		  =  load_image(
						    'https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/versatile_diffusion/benz.jpg'						)
						lowerCAmelCase__		  =  torch.manual_seed(0						)
						lowerCAmelCase__		  =  pipe.dual_guided(
						    prompt=a_    ,image=a_    ,text_to_image_strength=0.75    ,generator=a_    ,guidance_scale=7.5    ,num_inference_steps=50    ,output_type='numpy'    ,).images

						lowerCAmelCase__		  =  image[0, 253:256, 253:256, -1]

						assert image.shape == (1, 512, 512, 3)
						lowerCAmelCase__		  =  np.array([0.1448, 0.1619, 0.1741, 0.1086, 0.1147, 0.1128, 0.1199, 0.1165, 0.1001]						)

						assert np.abs(image_slice.flatten() - expected_slice						).max() < 1e-1

						lowerCAmelCase__		  =  'A painting of a squirrel eating a burger '
						lowerCAmelCase__		  =  torch.manual_seed(0						)
						lowerCAmelCase__		  =  pipe.text_to_image(
						    prompt=a_    ,generator=a_    ,guidance_scale=7.5    ,num_inference_steps=50    ,output_type='numpy'						).images

						lowerCAmelCase__		  =  image[0, 253:256, 253:256, -1]

						assert image.shape == (1, 512, 512, 3)
						lowerCAmelCase__		  =  np.array([0.3367, 0.3169, 0.2656, 0.3870, 0.4790, 0.3796, 0.4009, 0.4878, 0.4778]						)

						assert np.abs(image_slice.flatten() - expected_slice						).max() < 1e-1

						lowerCAmelCase__		  =  pipe.image_variation(a_    ,generator=a_    ,output_type='numpy'						).images

						lowerCAmelCase__		  =  image[0, 253:256, 253:256, -1]

						assert image.shape == (1, 512, 512, 3)
						lowerCAmelCase__		  =  np.array([0.3076, 0.3123, 0.3284, 0.3782, 0.3770, 0.3894, 0.4297, 0.4331, 0.4456]						)

						assert np.abs(image_slice.flatten() - expected_slice						).max() < 1e-1
