Fix most broken tests. One last broken test remains. (eb8c46f0) · Commits · 钟慕尧 / deepchem

deepchem/hyperparameters/tests/test_hyperparam_opt.py

+1 −3

Original line number	Diff line number	Diff line
		@@ -74,8 +74,7 @@ class TestHyperparamOptAPI(TestAPI):
		splittype = "scaffold"
		compound_featurizers = [CircularFingerprint(size=1024)]
		complex_featurizers = []
		output_transformer_classes = []
		input_transformer_classes = []
		output_transformers = []
		tasks = ["task0", "task1", "task2", "task3", "task4", "task5", "task6",
		"task7", "task8", "task9", "task10", "task11", "task12",
		"task13", "task14", "task15", "task16"]
		@@ -114,7 +113,6 @@ class TestHyperparamOptAPI(TestAPI):
		verbosity=None):
		return SingletaskToMultitask(tasks, task_types, params_dict,
		self.model_dir, model_builder)
		output_transformers = []
		self._hyperparam_opt(multitask_model_builder, params_dict, train_dataset,
		valid_dataset, output_transformers, tasks, task_types,
		classification_metric)

deepchem/metrics/init.py

+3 −0

Original line number	Diff line number	Diff line
		@@ -165,6 +165,9 @@ class Metric(object):
		"""
		y_true = y_true[w != 0]
		y_pred = y_pred[w != 0]
		# If there are no nonzero examples, metric is ill-defined.
		if not len(y_true):
		return np.nan
		if self.mode == "classification":
		y_true = to_one_hot(y_true).astype(int)
		y_pred = y_pred[:, np.newaxis]

deepchem/models/test/test_singletask_to_multitask.py

+24 −7

Original line number	Diff line number	Diff line
		@@ -9,9 +9,11 @@ __author__ = "Bharath Ramsundar"
		__copyright__ = "Copyright 2016, Stanford University"
		__license__ = "LGPL"

		import numpy as np
		from deepchem.models.test import TestAPI
		from deepchem import metrics
		from deepchem.metrics import Metric
		from deepchem.datasets import Dataset
		from deepchem.featurizers.fingerprints import CircularFingerprint
		from deepchem.models.multitask import SingletaskToMultitask
		from deepchem.models.sklearn_models import SklearnModel
		@@ -25,18 +27,33 @@ class TestSingletasktoMultitaskAPI(TestAPI):
		splittype = "scaffold"
		compound_featurizers = [CircularFingerprint(size=1024)]
		complex_featurizers = []
		output_transformer_classes = []
		input_transformer_classes = []
		output_transformers = []
		tasks = ["task0", "task1", "task2", "task3", "task4", "task5", "task6",
		"task7", "task8", "task9", "task10", "task11", "task12",
		"task13", "task14", "task15", "task16"]
		task_types = {task: "classification" for task in tasks}
		input_file = "multitask_example.csv"
		train_dataset, test_dataset, _, output_transformers, = \
		self._featurize_train_test_split(
		splittype, compound_featurizers,
		complex_featurizers, input_transformer_classes,
		output_transformer_classes, input_file, tasks)

		n_features = 10
		n_tasks = len(tasks)
		# Define train dataset
		n_train = 100
		X_train = np.random.rand(n_train, n_features)
		y_train = np.random.randint(2, size=(n_train, n_tasks))
		w_train = np.ones_like(y_train)
		ids_train = ["C"] * n_train
		train_dataset = Dataset.from_numpy(self.train_dir, tasks,
		X_train, y_train, w_train, ids_train)

		# Define test dataset
		n_test = 10
		X_test = np.random.rand(n_test, n_features)
		y_test = np.random.randint(2, size=(n_test, n_tasks))
		w_test = np.ones_like(y_test)
		ids_test = ["C"] * n_test
		test_dataset = Dataset.from_numpy(self.test_dir, tasks,
		X_test, y_test, w_test, ids_test)

		params_dict = {
		"batch_size": 32,
		"data_shape": train_dataset.get_data_shape()

deepchem/utils/evaluate.py

+2 −0

Original line number	Diff line number	Diff line
		@@ -47,6 +47,8 @@ class Evaluator(object):
		y_pred = self.model.predict(self.dataset, self.transformers)
		multitask_scores = {}

		print("y.shape, y_pred.shape")
		print(y.shape, y_pred.shape)
		# Compute multitask metrics
		for metric in metrics:
		multitask_scores[metric.name] = metric.compute_metric(y, y_pred, w)

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