Merge pull request #567 from peastman/reshape (2612ceb8) · Commits · 钟慕尧 / deepchem

deepchem/models/tensorflow_models/fcnet.py

+2 −5

Original line number	Diff line number	Diff line
		@@ -98,9 +98,7 @@ class TensorGraphMultiTaskClassifier(TensorGraph):
		self.add_output(output)
		labels = Label(shape=(None, n_tasks, n_classes))
		weights = Weights(shape=(None, n_tasks))
		loss = Reshape(
		shape=(-1, n_tasks),
		in_layers=[SoftMaxCrossEntropy(in_layers=[labels, output])])
		loss = SoftMaxCrossEntropy(in_layers=[labels, output])
		weighted_loss = WeightedError(in_layers=[loss, weights])
		if weight_decay_penalty != 0.0:
		weighted_loss = WeightDecay(
		@@ -211,8 +209,7 @@ class TensorGraphMultiTaskRegressor(TensorGraph):
		self.add_output(output)
		labels = Label(shape=(None, n_tasks, 1))
		weights = Weights(shape=(None, n_tasks))
		loss = Reshape(
		shape=(-1, n_tasks), in_layers=[L2Loss(in_layers=[labels, output])])
		loss = L2Loss(in_layers=[labels, output])
		weighted_loss = WeightedError(in_layers=[loss, weights])
		if weight_decay_penalty != 0.0:
		weighted_loss = WeightDecay(

+155 −194

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Original line number	Diff line number	Diff line
		@@ -511,3 +511,13 @@ class TestLayers(test_util.TensorFlowTestCase):
		sess.run(tf.global_variables_initializer())
		out_tensor = out_tensor.eval()
		assert out_tensor.shape == (batch_size, n_features)

		def test_reshape_inputs(self):
		"""Test that layers can automatically reshape inconsistent inputs."""
		value1 = np.random.uniform(size=(2, 3)).astype(np.float32)
		value2 = np.random.uniform(size=(1, 6, 1)).astype(np.float32)
		with self.test_session() as sess:
		out_tensor = Add()(tf.constant(value1), tf.constant(value2))
		result = out_tensor.eval()
		assert result.shape == (1, 6, 1)
		assert np.array_equal(value1.reshape((1, 6, 1)) + value2, result)