ANI debug (94600fb9) · Commits · 钟慕尧 / deepchem

deepchem/models/tensorgraph/symmetry_functions.py

+11 −11

Original line number	Diff line number	Diff line
		@@ -103,7 +103,7 @@ class RadialSymmetry(Layer):
		else:
		self.Rs_init = np.array(Rs_init)
		if ita_init is None:
		self.ita_init = np.array([1.5])
		self.ita_init = np.array([1.12])
		else:
		self.ita_init = np.array(ita_init)

		@@ -255,7 +255,7 @@ class AngularSymmetryMod(Layer):
		self.lambd_init = np.array(lambd_init)

		if ita_init is None:
		self.ita_init = np.array([1.5])
		self.ita_init = np.array([1.12])
		else:
		self.ita_init = np.array(ita_init)

		@@ -420,14 +420,14 @@ class AtomicDifferentiatedDense(Layer):
		inputs = in_layers[0].out_tensor
		atom_numbers = in_layers[1].out_tensor
		in_channels = inputs.get_shape().as_list()[-1]
		in_dimension = len(inputs.get_shape())
		self.W = self.init([max(self.atom_number_cases), in_channels, self.out_channels])
		self.b = model_ops.zeros((max(self.atom_number_cases), self.out_channels))
		W = tf.nn.embedding_lookup(self.W, atom_numbers)
		b = tf.nn.embedding_lookup(self.b, atom_numbers)
		outputs = tf.expand_dims(inputs, in_dimension) * W
		outputs = tf.reduce_sum(outputs, in_dimension-1) + b
		outputs = self.activation(outputs)
		self.out_tensor = outputs
		self.W = self.init([len(self.atom_number_cases), in_channels, self.out_channels])
		self.b = model_ops.zeros((len(self.atom_number_cases), self.out_channels))
		outputs = []
		for i, atom_case in enumerate(self.atom_number_cases):
		output = self.activation(tf.tensordot(inputs, self.W[i, :, :], [[2], [0]]) + self.b[i, :])
		mask = 1 - tf.to_float(tf.cast(atom_numbers-atom_case, tf.bool))
		output = tf.reshape(output * tf.expand_dims(mask, 2), (-1, self.max_atoms, self.out_channels))
		outputs.append(output)
		self.out_tensor = tf.add_n(outputs)

examples/qm7/qm7_ANI.py

+2 −2

Original line number	Diff line number	Diff line
		@@ -27,7 +27,7 @@ max_atoms = 23
		n_hidden = 40
		n_embedding = 0
		batch_size = 16
		atom_number_cases = [1, 6, 7, 8]
		atom_number_cases = [1, 6, 7, 8, 16]

		model = dc.models.ANIRegression(
		len(tasks),
		@@ -41,7 +41,7 @@ model = dc.models.ANIRegression(
		mode="regression")

		# Fit trained model
		model.fit(train_dataset, nb_epoch=20, checkpoint_interval=1000)
		model.fit(train_dataset, nb_epoch=20, checkpoint_interval=10)

		print("Evaluating model")
		train_scores = model.evaluate(train_dataset, metric, transformers)

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