Improved test cases (885d0d5f) · Commits · 钟慕尧 / deepchem

deepchem/models/tensorgraph/tests/test_estimators.py

+6 −6

Original line number	Diff line number	Diff line
		@@ -14,7 +14,7 @@ class TestEstimators(unittest.TestCase):
		"""Test creating an Estimator from a MultiTaskClassifier."""
		n_samples = 10
		n_features = 3
		n_tasks = 1
		n_tasks = 2

		# Create a dataset and an input function for processing it.

		@@ -35,7 +35,7 @@ class TestEstimators(unittest.TestCase):
		# Create an estimator from it.

		x_col = tf.feature_column.numeric_column('x', shape=(n_features,))
		weight_col = tf.feature_column.numeric_column('weights')
		weight_col = tf.feature_column.numeric_column('weights', shape=(n_tasks,))

		def accuracy(labels, predictions, weights):
		return tf.metrics.accuracy(labels, tf.round(predictions), weights)
		@@ -46,7 +46,7 @@ class TestEstimators(unittest.TestCase):

		# Train the model.

		estimator.train(input_fn=lambda: input_fn(100), steps=100)
		estimator.train(input_fn=lambda: input_fn(100))

		# Evaluate the model.

		@@ -58,7 +58,7 @@ class TestEstimators(unittest.TestCase):
		"""Test creating an Estimator from a MultiTaskRegressor."""
		n_samples = 10
		n_features = 3
		n_tasks = 1
		n_tasks = 2

		# Create a dataset and an input function for processing it.

		@@ -79,14 +79,14 @@ class TestEstimators(unittest.TestCase):
		# Create an estimator from it.

		x_col = tf.feature_column.numeric_column('x', shape=(n_features,))
		weight_col = tf.feature_column.numeric_column('weights')
		weight_col = tf.feature_column.numeric_column('weights', shape=(n_tasks,))
		metrics = {'error': tf.metrics.mean_absolute_error}
		estimator = model.make_estimator(
		feature_columns=[x_col], weight_column=weight_col, metrics=metrics)

		# Train the model.

		estimator.train(input_fn=lambda: input_fn(100), steps=100)
		estimator.train(input_fn=lambda: input_fn(100))

		# Evaluate the model.

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