:ok_hand: fix for review (a3f1fd67) · Commits · 钟慕尧 / deepchem

deepchem/data/datasets.py

+4 −3

Original line number	Diff line number	Diff line
		@@ -420,7 +420,7 @@ class Dataset(object):
		"""
		raise NotImplementedError()

		def select(self, indices: Sequence[int], select_dir: Optional[str] = None):
		def select(self, indices: Sequence[int], select_dir: Optional[str] = None) -> "Dataset":
		"""Creates a new dataset from a selection of indices from self.

		Parameters
		@@ -2294,8 +2294,9 @@ class DiskDataset(Dataset):

		Returns
		-------
		DiskDataset
		A Dataset containing the selected samples
		Dataset
		A dataset containing the selected samples. The default dataset is `DiskDataset`.
		If `output_numpy_dataset` is True, the datset is `NumpyDataset`.
		"""
		if output_numpy_dataset and (select_dir is not None or
		select_shard_size is not None):

+14 −13

Original line number	Diff line number	Diff line
		@@ -103,7 +103,8 @@ class Splitter(object):
		train_ds_base = DiskDataset.merge(update_train_base_merge)
		return list(zip(train_datasets, cv_datasets))

		def train_valid_test_split(self,
		def train_valid_test_split(
		self,
		dataset: Dataset,
		train_dir: Optional[str] = None,
		valid_dir: Optional[str] = None,
		@@ -113,7 +114,7 @@ class Splitter(object):
		frac_test: float = 0.1,
		seed: Optional[int] = None,
		log_every_n: int = 1000,
		**kwargs) -> Tuple[Dataset, Dataset, Dataset]:
		**kwargs) -> Tuple[Dataset, Optional[Dataset], Dataset]:
		""" Splits self into train/validation/test sets.

		Returns Dataset objects for train, valid, test.
		@@ -150,7 +151,7 @@ class Splitter(object):

		Returns
		-------
		Tuple[Dataset, Dataset, Dataset]
		Tuple[Dataset, Optional[Dataset], Dataset]
		A tuple of train, valid and test datasets as dc.data.Dataset objects.
		"""
		logger.info("Computing train/valid/test indices")
		@@ -169,7 +170,7 @@ class Splitter(object):
		test_dir = tempfile.mkdtemp()
		train_dataset = dataset.select(train_inds, train_dir)
		if frac_valid != 0:
		valid_dataset = dataset.select(valid_inds, valid_dir)
		valid_dataset: Optional[Dataset] = dataset.select(valid_inds, valid_dir)
		else:
		valid_dataset = None
		test_dataset = dataset.select(test_inds, test_dir)