Small bugfixes for atomic convs (81593ded) · Commits · 钟慕尧 / deepchem

contrib/atomicconv/acnn/core/opt_scaffold.py

+1 −2

Original line number	Diff line number	Diff line
		@@ -40,7 +40,6 @@ transformers = [
		]
		for transformer in transformers:
		train_dataset = transformer.transform(train_dataset)
		test_dataset = transformer.transform(test_dataset)

		at = [1., 6, 7., 8., 9., 11., 12., 15., 16., 17., 20., 25., 30., 35., 53.]
		radial = [[12.0], [0.0, 4.0, 8.0], [4.0]]

+1 −1

Original line number	Diff line number	Diff line
		@@ -282,7 +282,7 @@ def AtomicConvolutionLayer(X, Nbrs, Nbrs_Z, atom_types, radial_params, boxsize,
		"""Atomic convoluation layer

		N = max_num_atoms, M = max_num_neighbors, B = batch_size, d = num_features
		l = num_radial_filters
		l = num_radial_filters * num_atom_types

		Parameters
		----------

+3 −3

Original line number	Diff line number	Diff line
		@@ -604,8 +604,8 @@ class TensorflowClassifier(TensorflowGraphModel):
		A tensor with shape batch_size containing the weighted cost for each
		example.
		"""
		return tf.mul(
		tf.nn.softmax_cross_entropy_with_logits(logits, labels), weights)
		return tf.multiply(
		tf.nn.softmax_cross_entropy_with_logits(logits=logits, labels=labels), weights)

		def add_label_placeholders(self, graph, name_scopes):
		"""Add Placeholders for labels for each task.
		@@ -758,7 +758,7 @@ class TensorflowRegressor(TensorflowGraphModel):
		A tensor with shape batch_size containing the weighted cost for each
		example.
		"""
		return tf.mul(0.5 * tf.square(output - labels), weights)
		return tf.multiply(0.5 * tf.square(output - labels), weights)

		def add_label_placeholders(self, graph, name_scopes):
		"""Add Placeholders for labels for each task.