Commit 31dd8d58 authored by peastman's avatar peastman
Browse files

Fixed errors

parent 82f7b8b8

deepchem/models/tests/test_chemnet_models.py

+2 −2
Original line number Diff line number Diff line
@@ -7,7 +7,7 @@ import pytest 
import deepchem as dc

from deepchem.models import Smiles2Vec, ChemCeption

from deepchem.feat import create_char_to_idx, SmilesToSeq, SmilesToImage

from deepchem.molnet.load_function.chembl25_datasets import chembl25_tasks

from deepchem.molnet.load_function.chembl25_datasets import CHEMBL25_TASKS





def get_dataset(mode="classification",
@@ -32,7 +32,7 @@ def get_dataset(mode="classification", 
    feat = SmilesToImage(img_size=img_size, img_spec=img_spec, res=res)



  loader = dc.data.CSVLoader(

      tasks=chembl25_tasks, smiles_field='smiles', featurizer=feat)

      tasks=CHEMBL25_TASKS, smiles_field='smiles', featurizer=feat)

  dataset = loader.create_dataset(

      inputs=[dataset_file], shard_size=10000, data_dir=tempfile.mkdtemp())

deepchem/models/tests/test_reload.py

+2 −2
Original line number Diff line number Diff line
@@ -11,7 +11,7 @@ import tensorflow as tf 
import scipy

from flaky import flaky

from sklearn.ensemble import RandomForestClassifier

from deepchem.molnet.load_function.chembl25_datasets import chembl25_tasks

from deepchem.molnet.load_function.chembl25_datasets import CHEMBL25_TASKS

from deepchem.feat import create_char_to_idx
@@ -1000,7 +1000,7 @@ def test_smiles2vec_reload(): 
  data_points = 10



  loader = dc.data.CSVLoader(

      tasks=chembl25_tasks, smiles_field='smiles', featurizer=feat)

      tasks=CHEMBL25_TASKS, smiles_field='smiles', featurizer=feat)

  dataset = loader.create_dataset(

      inputs=[dataset_file], shard_size=10000, data_dir=tempfile.mkdtemp())

  y = np.random.randint(0, 2, size=(data_points, n_tasks))

deepchem/molnet/load_function/chembl_datasets.py

+1 −1
Original line number Diff line number Diff line
@@ -32,7 +32,7 @@ def load_chembl( 
    featurizer: Union[dc.feat.Featurizer, str] = 'ECFP',

    splitter: Union[dc.splits.Splitter, str, None] = 'scaffold',

    transformers: List[Union[TransformerGenerator, str]] = ['normalization'],

    set: bool = "5thresh",

    set: str = "5thresh",

    reload: bool = True,

    data_dir: Optional[str] = None,

    save_dir: Optional[str] = None,

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