remove all warnings (9112983a) · Commits · 钟慕尧 / deepchem

deepchem/feat/init.py

+3 −2

Original line number	Diff line number	Diff line
		@@ -75,13 +75,14 @@ except ModuleNotFoundError:

		try:
		from transformers import RobertaTokenizerFast
		from deepchem.feat.roberta_tokenizer import RobertaFeaturizer
		except ModuleNotFoundError:
		# raise ImportError('This class requires transformers.')
		raise ImportWarning(
		""" raise ImportWarning(
		'This class requires transformers. Please use "pip install transformers" to continue.'
		)
		"""
		pass
		from deepchem.feat.roberta_tokenizer import RobertaFeaturizer

		# support classes
		from deepchem.feat.molecule_featurizers import GraphMatrix

deepchem/feat/base_classes.py

+7 −15

Original line number	Diff line number	Diff line
		@@ -23,10 +23,8 @@ class Featurizer(object):
		new datatype.
		"""

		def featurize(self,
		datapoints: Iterable[Any],
		log_every_n: int = 1000,
		**kwargs) -> np.ndarray:
		def featurize(self, datapoints: Iterable[Any],
		log_every_n: int = 1000, **kwargs) -> np.ndarray:
		"""Calculate features for datapoints.

		Parameters
		@@ -159,8 +157,7 @@ class ComplexFeaturizer(Featurizer):

		def featurize(self,
		datapoints: Iterable[Tuple[str, str]] = None,
		log_every_n: int = 100,
		**kwargs) -> np.ndarray:
		log_every_n: int = 100, **kwargs) -> np.ndarray:
		"""
		Calculate features for mol/protein complexes.

		@@ -179,9 +176,7 @@ class ComplexFeaturizer(Featurizer):

		if 'complexes' in kwargs:
		datapoints = kwargs.get("complexes")
		raise DeprecationWarning(
		'Complexes is being phased out as a parameter, please pass "datapoints" instead.'
		)
		raise DeprecationWarning('Complexes is being phased out as a parameter, please pass "datapoints" instead.')
		if not isinstance(datapoints, Iterable):
		datapoints = [cast(Tuple[str, str], datapoints)]
		features, failures, successes = [], [], []
		@@ -324,8 +319,7 @@ class MaterialStructureFeaturizer(Featurizer):

		def featurize(self,
		structures: Iterable[Union[Dict[str, Any], PymatgenStructure]],
		log_every_n: int = 1000,
		**kwargs) -> np.ndarray:
		log_every_n: int = 1000, **kwargs) -> np.ndarray:
		"""Calculate features for crystal structures.

		Parameters
		@@ -388,10 +382,8 @@ class MaterialCompositionFeaturizer(Featurizer):
		installed.
		"""

		def featurize(self,
		compositions: Iterable[str],
		log_every_n: int = 1000,
		**kwargs) -> np.ndarray:
		def featurize(self, compositions: Iterable[str],
		log_every_n: int = 1000, **kwargs) -> np.ndarray:
		"""Calculate features for crystal compositions.

		Parameters

deepchem/feat/roberta_tokenizer.py

+1 −1

Original line number	Diff line number	Diff line
		@@ -3,7 +3,7 @@ from typing import Dict, List
		try:
		from transformers import RobertaTokenizerFast
		except ModuleNotFoundError:
		raise ImportError('This class requires transformers.')
		# raise ImportError('This class requires transformers.')
		pass

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