



'''simple docstring'''




import os
import tempfile
from pathlib import Path
from unittest import TestCase

import pyarrow as pa
import pytest

from datasets.arrow_dataset import Dataset
from datasets.arrow_reader import ArrowReader, BaseReader, FileInstructions, ReadInstruction, make_file_instructions
from datasets.info import DatasetInfo
from datasets.splits import NamedSplit, Split, SplitDict, SplitInfo

from .utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases






class 						_UpperCamelCase  (							lowerCamelCase__   ):


			'''simple docstring'''

			def UpperCamelCase__ (							self					:			str							,					lowerCAmelCase__					:			List[str]							,					lowerCAmelCase__					:			Tuple=False						):





					"""simple docstring"""






					__SCREAMING_SNAKE_CASE	,						__SCREAMING_SNAKE_CASE	,						__SCREAMING_SNAKE_CASE	:		Optional[int]   	=		(
					    filename_skip_take["""filename"""],
					    filename_skip_take["""skip"""] if """skip""" in filename_skip_take else None,
					    filename_skip_take["""take"""] if """take""" in filename_skip_take else None,
					)
					open(os.path.join(lowerCAmelCase__						)							,					"""wb"""						).close()
					__SCREAMING_SNAKE_CASE	:		Dict   	=		pa.Table.from_pydict({"""filename""": [Path(lowerCAmelCase__						).name] * 1_0_0}						)
					if take == -1:
							__SCREAMING_SNAKE_CASE	:		int   	=		len(lowerCAmelCase__						) - skip
					if skip is not None and take is not None:
							__SCREAMING_SNAKE_CASE	:		str   	=		pa_table.slice(lowerCAmelCase__							,					lowerCAmelCase__						)
					return pa_table






class 						_UpperCamelCase  (							lowerCamelCase__   ):


			'''simple docstring'''

			def UpperCamelCase__ (							self					:			Union[str, Any]						):





					"""simple docstring"""






					__SCREAMING_SNAKE_CASE	:		Any   	=		"""my_name"""
					__SCREAMING_SNAKE_CASE	:		Union[str, Any]   	=		SplitInfo(name="""train"""							,					num_examples=1_0_0						)
					__SCREAMING_SNAKE_CASE	:		int   	=		SplitInfo(name="""test"""							,					num_examples=1_0_0						)
					__SCREAMING_SNAKE_CASE	:		Union[str, Any]   	=		[train_info, test_info]
					__SCREAMING_SNAKE_CASE	:		str   	=		SplitDict()
					split_dict.add(lowerCAmelCase__						)
					split_dict.add(lowerCAmelCase__						)
					__SCREAMING_SNAKE_CASE	:		str   	=		DatasetInfo(splits=lowerCAmelCase__						)

					with tempfile.TemporaryDirectory() as tmp_dir:
							__SCREAMING_SNAKE_CASE	:		Tuple   	=		ReaderTest(lowerCAmelCase__							,					lowerCAmelCase__						)

							__SCREAMING_SNAKE_CASE	:		Dict   	=		"""test[:33%]"""
							__SCREAMING_SNAKE_CASE	:		Union[str, Any]   	=		Dataset(**reader.read(lowerCAmelCase__							,					lowerCAmelCase__							,					lowerCAmelCase__						)						)
							self.assertEqual(dset["""filename"""][0]							,					F"{name}-test"						)
							self.assertEqual(dset.num_rows							,					3_3						)
							self.assertEqual(dset.num_columns							,					1						)

							__SCREAMING_SNAKE_CASE	:		Optional[Any]   	=		["""train""", """test[:33%]"""]
							__SCREAMING_SNAKE_CASE	:		Tuple   	=		[Split.TRAIN, ReadInstruction.from_spec("""test[:33%]"""						)]
							for instructions in [instructionsa, instructionsa]:
									__SCREAMING_SNAKE_CASE	:		List[str]   	=		[reader.read(lowerCAmelCase__							,					lowerCAmelCase__							,					lowerCAmelCase__						) for instr in instructions]
									__SCREAMING_SNAKE_CASE	,						__SCREAMING_SNAKE_CASE	:		List[Any]   	=		(Dataset(**lowerCAmelCase__						) for dataset_kwargs in datasets_kwargs)
									self.assertEqual(train_dset["""filename"""][0]							,					F"{name}-train"						)
									self.assertEqual(train_dset.num_rows							,					1_0_0						)
									self.assertEqual(train_dset.num_columns							,					1						)
									self.assertIsInstance(train_dset.split							,					lowerCAmelCase__						)
									self.assertEqual(str(train_dset.split						)							,					"""train"""						)
									self.assertEqual(test_dset["""filename"""][0]							,					F"{name}-test"						)
									self.assertEqual(test_dset.num_rows							,					3_3						)
									self.assertEqual(test_dset.num_columns							,					1						)
									self.assertIsInstance(test_dset.split							,					lowerCAmelCase__						)
									self.assertEqual(str(test_dset.split						)							,					"""test[:33%]"""						)
									del train_dset, test_dset

			def UpperCamelCase__ (							self					:			Dict						):





					"""simple docstring"""






					__SCREAMING_SNAKE_CASE	:		Optional[int]   	=		"""my_name"""
					__SCREAMING_SNAKE_CASE	:		int   	=		SplitInfo(name="""train"""							,					num_examples=1_0_0_0							,					shard_lengths=[1_0_0] * 1_0						)
					__SCREAMING_SNAKE_CASE	:		int   	=		[train_info]
					__SCREAMING_SNAKE_CASE	:		Optional[int]   	=		SplitDict()
					split_dict.add(lowerCAmelCase__						)
					__SCREAMING_SNAKE_CASE	:		Union[str, Any]   	=		DatasetInfo(splits=lowerCAmelCase__						)

					with tempfile.TemporaryDirectory() as tmp_dir:
							__SCREAMING_SNAKE_CASE	:		List[str]   	=		ReaderTest(lowerCAmelCase__							,					lowerCAmelCase__						)

							__SCREAMING_SNAKE_CASE	:		Any   	=		"""train[:33%]"""
							__SCREAMING_SNAKE_CASE	:		str   	=		Dataset(**reader.read(lowerCAmelCase__							,					lowerCAmelCase__							,					lowerCAmelCase__						)						)
							self.assertEqual(dset["""filename"""][0]							,					F"{name}-train-00000-of-00010"						)
							self.assertEqual(dset["""filename"""][-1]							,					F"{name}-train-00003-of-00010"						)
							self.assertEqual(dset.num_rows							,					3_3_0						)
							self.assertEqual(dset.num_columns							,					1						)



			def UpperCamelCase__ (							self					:			Optional[int]						):





					"""simple docstring"""






					__SCREAMING_SNAKE_CASE	:		List[str]   	=		SplitInfo(name="""train"""							,					num_examples=1_0_0						)
					__SCREAMING_SNAKE_CASE	:		Optional[int]   	=		SplitInfo(name="""test"""							,					num_examples=1_0_0						)
					__SCREAMING_SNAKE_CASE	:		Optional[int]   	=		SplitDict()
					split_dict.add(lowerCAmelCase__						)
					split_dict.add(lowerCAmelCase__						)
					__SCREAMING_SNAKE_CASE	:		Any   	=		DatasetInfo(splits=lowerCAmelCase__						)

					with tempfile.TemporaryDirectory() as tmp_dir:
							__SCREAMING_SNAKE_CASE	:		List[str]   	=		ReaderTest(lowerCAmelCase__							,					lowerCAmelCase__						)

							__SCREAMING_SNAKE_CASE	:		Tuple   	=		[
							    {"""filename""": os.path.join(lowerCAmelCase__							,					"""train"""						)},
							    {"""filename""": os.path.join(lowerCAmelCase__							,					"""test"""						), """skip""": 1_0, """take""": 1_0},
							]
							__SCREAMING_SNAKE_CASE	:		str   	=		Dataset(**reader.read_files(lowerCAmelCase__							,					original_instructions="""train+test[10:20]"""						)						)
							self.assertEqual(dset.num_rows							,					1_1_0						)
							self.assertEqual(dset.num_columns							,					1						)
							del dset


@pytest.mark.parametrize("""in_memory"""	,				[False, True] )
def     lowerCAmelCase_       (     _lowerCamelCase:       Tuple	,				_lowerCamelCase:       int	,				_lowerCamelCase:       Tuple ):
		__SCREAMING_SNAKE_CASE	:		int   	=		arrow_file
		with assert_arrow_memory_increases() if in_memory else assert_arrow_memory_doesnt_increase():
				__SCREAMING_SNAKE_CASE	:		List[str]   	=		ArrowReader.read_table(_lowerCamelCase	,				in_memory=_lowerCamelCase )
		assert table.shape == dataset.data.shape
		assert set(table.column_names ) == set(dataset.data.column_names )
		assert dict(table.to_pydict() ) == dict(dataset.data.to_pydict() )  # to_pydict returns OrderedDict


@pytest.mark.parametrize("""in_memory"""	,				[False, True] )
def     lowerCAmelCase_       (     _lowerCamelCase:       Tuple	,				_lowerCamelCase:       Optional[Any]	,				_lowerCamelCase:       int ):
		__SCREAMING_SNAKE_CASE	:		Tuple   	=		arrow_file
		__SCREAMING_SNAKE_CASE	:		Dict   	=		ArrowReader(""""""	,				_lowerCamelCase )
		with assert_arrow_memory_increases() if in_memory else assert_arrow_memory_doesnt_increase():
				__SCREAMING_SNAKE_CASE	:		Dict   	=		reader.read_files([{"""filename""": filename}]	,				in_memory=_lowerCamelCase )
		assert dataset_kwargs.keys() == {"arrow_table", "info", "split"}
		__SCREAMING_SNAKE_CASE	:		int   	=		dataset_kwargs["""arrow_table"""]
		assert table.shape == dataset.data.shape
		assert set(table.column_names ) == set(dataset.data.column_names )
		assert dict(table.to_pydict() ) == dict(dataset.data.to_pydict() )  # to_pydict returns OrderedDict


def     lowerCAmelCase_       (     ):
		assert ReadInstruction("""train"""	,				to=10	,				unit="""abs""" ).to_spec() == "train[:10]"
		assert ReadInstruction("""train"""	,				from_=-80	,				to=10	,				unit="""%""" ).to_spec() == "train[-80%:10%]"

		__SCREAMING_SNAKE_CASE	:		Dict   	=		"""train+test"""
		assert ReadInstruction.from_spec(_lowerCamelCase ).to_spec() == spec_train_test

		__SCREAMING_SNAKE_CASE	:		Optional[int]   	=		"""train[2:10]"""
		assert ReadInstruction.from_spec(_lowerCamelCase ).to_spec() == spec_train_abs

		__SCREAMING_SNAKE_CASE	:		Tuple   	=		"""train[15%:-20%]"""
		assert ReadInstruction.from_spec(_lowerCamelCase ).to_spec() == spec_train_pct

		__SCREAMING_SNAKE_CASE	:		Tuple   	=		"""train[:10%](closest)"""
		assert ReadInstruction.from_spec(_lowerCamelCase ).to_spec() == "train[:10%]"

		__SCREAMING_SNAKE_CASE	:		Optional[Any]   	=		"""train[:10%](pct1_dropremainder)"""
		assert ReadInstruction.from_spec(_lowerCamelCase ).to_spec() == spec_train_pct_rounding

		__SCREAMING_SNAKE_CASE	:		List[str]   	=		"""train[:10%](pct1_dropremainder)+test[-10%:](pct1_dropremainder)"""
		assert ReadInstruction.from_spec(_lowerCamelCase ).to_spec() == spec_train_test_pct_rounding


def     lowerCAmelCase_       (     ):
		__SCREAMING_SNAKE_CASE	:		Optional[int]   	=		"""dummy"""
		__SCREAMING_SNAKE_CASE	:		Tuple   	=		[SplitInfo(name="""train"""	,				num_examples=1_00 )]
		__SCREAMING_SNAKE_CASE	:		Tuple   	=		"""train[:33%]"""
		__SCREAMING_SNAKE_CASE	:		Dict   	=		"""arrow"""
		__SCREAMING_SNAKE_CASE	:		Optional[int]   	=		"""prefix"""

		__SCREAMING_SNAKE_CASE	:		List[Any]   	=		make_file_instructions(_lowerCamelCase	,				_lowerCamelCase	,				_lowerCamelCase	,				_lowerCamelCase	,				_lowerCamelCase )
		assert isinstance(_lowerCamelCase	,				_lowerCamelCase )
		assert file_instructions.num_examples == 33
		assert file_instructions.file_instructions == [
		    {"filename": os.path.join(_lowerCamelCase	,				F"{name}-train.arrow" ), "skip": 0, "take": 33}
		]

		__SCREAMING_SNAKE_CASE	:		Any   	=		[SplitInfo(name="""train"""	,				num_examples=1_00	,				shard_lengths=[10] * 10 )]
		__SCREAMING_SNAKE_CASE	:		List[str]   	=		make_file_instructions(_lowerCamelCase	,				_lowerCamelCase	,				_lowerCamelCase	,				_lowerCamelCase	,				_lowerCamelCase )
		assert isinstance(_lowerCamelCase	,				_lowerCamelCase )
		assert file_instructions.num_examples == 33
		assert file_instructions.file_instructions == [
		    {"filename": os.path.join(_lowerCamelCase	,				F"{name}-train-00000-of-00010.arrow" ), "skip": 0, "take": -1},
		    {"filename": os.path.join(_lowerCamelCase	,				F"{name}-train-00001-of-00010.arrow" ), "skip": 0, "take": -1},
		    {"filename": os.path.join(_lowerCamelCase	,				F"{name}-train-00002-of-00010.arrow" ), "skip": 0, "take": -1},
		    {"filename": os.path.join(_lowerCamelCase	,				F"{name}-train-00003-of-00010.arrow" ), "skip": 0, "take": 3},
		]


@pytest.mark.parametrize("""name, expected_exception"""	,				[(None, TypeError), ("""""", ValueError)] )
def     lowerCAmelCase_       (     _lowerCamelCase:       Tuple	,				_lowerCamelCase:       Union[str, Any] ):
		__SCREAMING_SNAKE_CASE	:		Union[str, Any]   	=		[SplitInfo(name="""train"""	,				num_examples=1_00 )]
		__SCREAMING_SNAKE_CASE	:		Optional[Any]   	=		"""train"""
		__SCREAMING_SNAKE_CASE	:		List[str]   	=		"""arrow"""
		__SCREAMING_SNAKE_CASE	:		Tuple   	=		"""prefix_path"""
		with pytest.raises(_lowerCamelCase ):
				__SCREAMING_SNAKE_CASE	:		Optional[Any]   	=		make_file_instructions(_lowerCamelCase	,				_lowerCamelCase	,				_lowerCamelCase	,				_lowerCamelCase	,				_lowerCamelCase )




'''simple docstring'''




import torch
import torch.nn.functional as F

from diffusers import VQDiffusionScheduler

from .test_schedulers import SchedulerCommonTest






class 						_UpperCamelCase  (							lowerCamelCase__   ):


			'''simple docstring'''

			_A				:		int         =		(VQDiffusionScheduler,)

			def UpperCamelCase__ (							self					:			List[str]							,					**lowerCAmelCase__					:			Dict						):





					"""simple docstring"""






					__SCREAMING_SNAKE_CASE	:		int   	=		{
					    """num_vec_classes""": 4_0_9_7,
					    """num_train_timesteps""": 1_0_0,
					}

					config.update(**lowerCAmelCase__						)
					return config

			def UpperCamelCase__ (							self					:			Dict							,					lowerCAmelCase__					:			int						):





					"""simple docstring"""






					__SCREAMING_SNAKE_CASE	:		Dict   	=		4
					__SCREAMING_SNAKE_CASE	:		Tuple   	=		8
					__SCREAMING_SNAKE_CASE	:		int   	=		8

					__SCREAMING_SNAKE_CASE	:		Dict   	=		torch.randint(0							,					lowerCAmelCase__							,					(batch_size, height * width)						)

					return sample

			@property
			def UpperCamelCase__ (							self					:			str						):





					"""simple docstring"""






					assert False

			def UpperCamelCase__ (							self					:			Dict							,					lowerCAmelCase__					:			str						):





					"""simple docstring"""






					def model(lowerCAmelCase__					:			Optional[Any]							,					lowerCAmelCase__					:			Any							,					*lowerCAmelCase__					:			Optional[int]						):
							__SCREAMING_SNAKE_CASE	,						__SCREAMING_SNAKE_CASE	:		Optional[int]   	=		sample.shape
							__SCREAMING_SNAKE_CASE	:		Optional[Any]   	=		torch.rand((batch_size, num_vec_classes - 1, num_latent_pixels)						)
							__SCREAMING_SNAKE_CASE	:		str   	=		F.log_softmax(logits.double()							,					dim=1						).float()
							return return_value

					return model

			def UpperCamelCase__ (							self					:			Optional[int]						):





					"""simple docstring"""






					for timesteps in [2, 5, 1_0_0, 1_0_0_0]:
							self.check_over_configs(num_train_timesteps=lowerCAmelCase__						)

			def UpperCamelCase__ (							self					:			int						):





					"""simple docstring"""






					for num_vec_classes in [5, 1_0_0, 1_0_0_0, 4_0_0_0]:
							self.check_over_configs(num_vec_classes=lowerCAmelCase__						)

			def UpperCamelCase__ (							self					:			Any						):





					"""simple docstring"""






					for t in [0, 5_0, 9_9]:
							self.check_over_forward(time_step=lowerCAmelCase__						)



			def UpperCamelCase__ (							self					:			List[Any]						):





					"""simple docstring"""






					pass