Merge pull request #2089 from nd-02110114/cgcnn-impl (e0537202) · Commits · 钟慕尧 / deepchem

deepchem/data/data_loader.py

+2 −1

Original line number	Diff line number	Diff line
		@@ -8,6 +8,7 @@ import time
		import logging
		import warnings
		from typing import List, Optional, Tuple, Any, Sequence, Union, Iterator

		import pandas as pd
		import numpy as np

		@@ -628,7 +629,7 @@ class JsonLoader(DataLoader):
		(shard_num, time2 - time1))
		yield X, y, w, ids

		return DiskDataset.create_dataset(shard_generator(), data_dir)
		return DiskDataset.create_dataset(shard_generator(), data_dir, self.tasks)

		def _get_shards(self, input_files: List[str],
		shard_size: Optional[int]) -> Iterator[pd.DataFrame]:

deepchem/feat/base_classes.py

+11 −8

Original line number	Diff line number	Diff line
		@@ -4,7 +4,9 @@ Feature calculations.
		import logging
		import numpy as np
		import multiprocessing
		from typing import Any, Dict, List, Iterable, Sequence, Tuple
		from typing import Any, Dict, List, Iterable, Sequence, Tuple, Union

		from deepchem.utils.typing import PymatgenStructure

		logger = logging.getLogger(__name__)

		@@ -233,16 +235,16 @@ class MaterialStructureFeaturizer(Featurizer):
		"""

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

		Parameters
		----------
		structures: Iterable[Dict[str, Any]]
		Iterable sequence of pymatgen structure dictionaries.
		Dictionary representations of pymatgen.Structure
		https://pymatgen.org/pymatgen.core.structure.html
		structures: Iterable[Union[Dict, pymatgen.Structure]]
		Iterable sequence of pymatgen structure dictionaries
		or pymatgen.Structure. Please confirm the dictionary representations
		of pymatgen.Structure from https://pymatgen.org/pymatgen.core.structure.html.
		log_every_n: int, default 1000
		Logging messages reported every `log_every_n` samples.

		@@ -263,8 +265,9 @@ class MaterialStructureFeaturizer(Featurizer):
		if idx % log_every_n == 0:
		logger.info("Featurizing datapoint %i" % idx)
		try:
		s = Structure.from_dict(structure)
		features.append(self._featurize(s))
		if isinstance(structure, Dict):
		structure = Structure.from_dict(structure)
		features.append(self._featurize(structure))
		except:
		logger.warning(
		"Failed to featurize datapoint %i. Appending empty array" % idx)

deepchem/feat/material_featurizers/cgcnn_featurizer.py

+3 −0

Original line number	Diff line number	Diff line
		@@ -39,6 +39,9 @@ class CGCNNFeaturizer(MaterialStructureFeaturizer):
		>>> structure = mg.Structure(lattice, ["Cs", "Cl"], [[0, 0, 0], [0.5, 0.5, 0.5]])
		>>> featurizer = CGCNNFeaturizer()
		>>> features = featurizer.featurize([structure])
		>>> feature = features[0]
		>>> print(type(feature))
		<class 'deepchem.feat.graph_data.GraphData'>

		Notes
		-----

deepchem/models/init.py

+5 −1

Original line number	Diff line number	Diff line
		"""
		Gathers all models in one place for convenient imports
		"""
		# flake8:noqa

		from deepchem.models.models import Model
		from deepchem.models.keras_model import KerasModel
		from deepchem.models.sklearn_models import SklearnModel
		@@ -25,8 +27,10 @@ from deepchem.models.text_cnn import TextCNNModel
		from deepchem.models.atomic_conv import AtomicConvModel
		from deepchem.models.chemnet_models import Smiles2Vec, ChemCeption

		# PyTorch models
		try:
		from deepchem.models.torch_model import TorchModel
		from deepchem.models.torch_models import TorchModel
		from deepchem.models.torch_models import CGCNN, CGCNNModel
		except ModuleNotFoundError:
		pass

deepchem/models/tests/perovskite.tar.gz

0 → 100644

+16.5 KiB

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