:rotating_light: fix yapf and mypy error (d0b90f4f) · Commits · 钟慕尧 / deepchem

deepchem/data/datasets.py

+2 −14

Original line number	Diff line number	Diff line
		@@ -871,13 +871,7 @@ class NumpyDataset(Dataset):
		raise ValueError("This method requires PyTorch to be installed.")

		pytorch_ds = TorchNumpyDataset(
		X=self._X,
		y=self._y,
		w=self._w,
		ids=self._ids,
		n_samples=self._X.shape[0],
		epochs=epochs,
		deterministic=deterministic)
		numpy_dataset=self, epochs=epochs, deterministic=deterministic)
		return pytorch_ds

		@staticmethod
		@@ -2243,13 +2237,7 @@ class ImageDataset(Dataset):
		raise ValueError("This method requires PyTorch to be installed.")

		pytorch_ds = TorchImageDataset(
		X=self.X,
		y=self.y,
		w=self.w,
		ids=self._ids,
		n_samples=self._X_shape[0],
		epochs=epochs,
		deterministic=deterministic)
		image_dataset=self, epochs=epochs, deterministic=deterministic)
		return pytorch_ds

deepchem/data/pytorch_datasets.py

+15 −9

Original line number	Diff line number	Diff line
		@@ -8,7 +8,8 @@ from deepchem.data.datasets import NumpyDataset, DiskDataset, ImageDataset

		class TorchNumpyDataset(torch.utils.data.IterableDataset): # type: ignore

		def __init__(self, numpy_dataset: NumpyDataset, epochs: int, deterministic: bool):
		def __init__(self, numpy_dataset: NumpyDataset, epochs: int,
		deterministic: bool):
		"""
		Parameters
		----------
		@@ -39,12 +40,14 @@ class TorchNumpyDataset(torch.utils.data.IterableDataset): # type: ignore
		else:
		order = first_sample + np.random.permutation(last_sample - first_sample)
		for i in order:
		yield (self.numpy_dataset._X[i], self.numpy_dataset._y[i], self.numpy_dataset._w[i], self.numpy_dataset._ids[i])
		yield (self.numpy_dataset._X[i], self.numpy_dataset._y[i],
		self.numpy_dataset._w[i], self.numpy_dataset._ids[i])


		class TorchDiskDataset(torch.utils.data.IterableDataset): # type: ignore

		def __init__(self, disk_dataset: DiskDataset, epochs: int, deterministic: bool):
		def __init__(self, disk_dataset: DiskDataset, epochs: int,
		deterministic: bool):
		"""
		Parameters
		----------
		@@ -82,7 +85,8 @@ class TorchDiskDataset(torch.utils.data.IterableDataset): # type: ignore

		class TorchImageDataset(torch.utils.data.IterableDataset): # type: ignore

		def __init__(self, image_dataset: ImageDataset, epochs: int, deterministic: bool):
		def __init__(self, image_dataset: ImageDataset, epochs: int,
		deterministic: bool):
		"""
		Parameters
		----------
		@@ -99,7 +103,7 @@ class TorchImageDataset(torch.utils.data.IterableDataset): # type: ignore
		self.deterministic = deterministic

		def __iter__(self):
		n_samples = self.image_dataset._X.shape[0]
		n_samples = self.image_dataset._X_shape[0]
		worker_info = torch.utils.data.get_worker_info()
		if worker_info is None:
		first_sample = 0
		@@ -113,18 +117,20 @@ class TorchImageDataset(torch.utils.data.IterableDataset): # type: ignore
		else:
		order = first_sample + np.random.permutation(last_sample - first_sample)
		for i in order:
		yield (self._get_image(self.image_dataset._X, i), self._get_image(self.image_dataset._y, i),
		yield (self._get_image(self.image_dataset._X, i),
		self._get_image(self.image_dataset._y, i),
		self.image_dataset._w[i], self.image_dataset._ids[i])

		def _get_image(self, array: Union[np.ndarray, List[str]], index: int) -> np.ndarray:
		def _get_image(self, array: Union[np.ndarray, List[str]],
		index: int) -> np.ndarray:
		"""Function for loading an image

		Parameters
		----------
		array: Union[np.ndarray, List[str]]
		A numpy array which contains all images or List of image filenames
		A numpy array which contains images or List of image filenames
		index: int
		Index you want to get the images
		Index you want to get the image

		Returns
		-------

Admin message