yapfed (29a97407) · Commits · 钟慕尧 / deepchem

deepchem/data/datasets.py

+6 −3

Original line number	Diff line number	Diff line
		@@ -469,7 +469,8 @@ class NumpyDataset(Dataset):
		w = np.concatenate([w, dataset.w], axis=0)
		ids = np.concatenate(
		[ids, dataset.ids],
		axis=0,)
		axis=0,
		)

		return NumpyDataset(X, y, w, ids, n_tasks=y.shape[1])

		@@ -647,7 +648,8 @@ class DiskDataset(Dataset):
		if not len(self.metadata_df):
		raise ValueError("No data in dataset.")
		sample_X = load_from_disk(
		os.path.join(self.data_dir, next(self.metadata_df.iterrows())[1]['X']))
		os.path.join(self.data_dir,
		next(self.metadata_df.iterrows())[1]['X']))
		return np.shape(sample_X)[1:]

		def get_shard_size(self):
		@@ -655,7 +657,8 @@ class DiskDataset(Dataset):
		if not len(self.metadata_df):
		raise ValueError("No data in dataset.")
		sample_y = load_from_disk(
		os.path.join(self.data_dir, next(self.metadata_df.iterrows())[1]['y']))
		os.path.join(self.data_dir,
		next(self.metadata_df.iterrows())[1]['y']))
		return len(sample_y)

		def _get_metadata_filename(self):

deepchem/models/tensorgraph/layers.py

+18 −19

Original line number	Diff line number	Diff line
		@@ -735,7 +735,8 @@ class Squeeze(Layer):
		self._shape = [i for i in parent_shape if i != 1]
		else:
		self._shape = [
		parent_shape[i] for i in range(len(parent_shape))
		parent_shape[i]
		for i in range(len(parent_shape))
		if i not in squeeze_dims
		]
		except:
		@@ -2094,8 +2095,8 @@ class MaxPool1D(Layer):
		super(MaxPool1D, self).__init__(**kwargs)
		try:
		parent_shape = self.in_layers[0].shape
		self._shape = tuple(None if p is None else p // s
		for p, s in zip(parent_shape, strides))
		self._shape = tuple(
		None if p is None else p // s for p, s in zip(parent_shape, strides))
		except:
		pass

		@@ -2126,8 +2127,8 @@ class MaxPool2D(Layer):
		super(MaxPool2D, self).__init__(**kwargs)
		try:
		parent_shape = self.in_layers[0].shape
		self._shape = tuple(None if p is None else p // s
		for p, s in zip(parent_shape, strides))
		self._shape = tuple(
		None if p is None else p // s for p, s in zip(parent_shape, strides))
		except:
		pass

		@@ -2173,8 +2174,8 @@ class MaxPool3D(Layer):
		super(MaxPool3D, self).__init__(**kwargs)
		try:
		parent_shape = self.in_layers[0].shape
		self._shape = tuple(None if p is None else p // s
		for p, s in zip(parent_shape, strides))
		self._shape = tuple(
		None if p is None else p // s for p, s in zip(parent_shape, strides))
		except:
		pass

		@@ -2939,15 +2940,13 @@ class VinaFreeEnergy(Layer):

		def hydrophobic(self, d):
		"""Computes Autodock Vina's hydrophobic interaction term."""
		out_tensor = tf.where(d < 0.5,
		tf.ones_like(d),
		out_tensor = tf.where(d < 0.5, tf.ones_like(d),
		tf.where(d < 1.5, 1.5 - d, tf.zeros_like(d)))
		return out_tensor

		def hydrogen_bond(self, d):
		"""Computes Autodock Vina's hydrogen bond interaction term."""
		out_tensor = tf.where(d < -0.7,
		tf.ones_like(d),
		out_tensor = tf.where(d < -0.7, tf.ones_like(d),
		tf.where(d < 0, (1.0 / 0.7) * (0 - d),
		tf.zeros_like(d)))
		return out_tensor
		@@ -3324,8 +3323,8 @@ class NeighborList(Layer):
		mesh_args = [tf.range(start, stop, nbr_cutoff) for _ in range(self.ndim)]
		return tf.to_float(
		tf.reshape(
		tf.transpose(tf.stack(tf.meshgrid(*mesh_args))), (self.n_cells,
		self.ndim)))
		tf.transpose(tf.stack(tf.meshgrid(*mesh_args))),
		(self.n_cells, self.ndim)))


		class Dropout(Layer):
		@@ -3612,8 +3611,8 @@ class AtomicConvolution(Layer):
		example_tensors = tf.unstack(X, axis=0)
		example_nbrs = tf.unstack(nbr_indices, axis=0)
		all_nbr_coords = []
		for example, (example_tensor,
		example_nbr) in enumerate(zip(example_tensors, example_nbrs)):
		for example, (example_tensor, example_nbr) in enumerate(
		zip(example_tensors, example_nbrs)):
		nbr_coords = tf.gather(example_tensor, example_nbr)
		all_nbr_coords.append(nbr_coords)
		neighbors = tf.stack(all_nbr_coords)
		@@ -4179,13 +4178,13 @@ class GraphCNN(Layer):
		no_features = V.get_shape()[2].value
		W = tf.get_variable(
		'%s_weights' % self.name, [no_features * no_A, self.num_filters],
		initializer=tf.truncated_normal_initializer(stddev=math.sqrt(
		1.0 / (no_features * (no_A + 1) * 1.0))),
		initializer=tf.truncated_normal_initializer(
		stddev=math.sqrt(1.0 / (no_features * (no_A + 1) * 1.0))),
		dtype=tf.float32)
		W_I = tf.get_variable(
		'%s_weights_I' % self.name, [no_features, self.num_filters],
		initializer=tf.truncated_normal_initializer(stddev=math.sqrt(
		1.0 / (no_features * (no_A + 1) * 1.0))),
		initializer=tf.truncated_normal_initializer(
		stddev=math.sqrt(1.0 / (no_features * (no_A + 1) * 1.0))),
		dtype=tf.float32)

		b = tf.get_variable(

deepchem/models/tensorgraph/models/graph_models.py

+6 −6

Original line number	Diff line number	Diff line
		@@ -172,8 +172,8 @@ class WeaveTensorGraph(TensorGraph):
		atom_feat.append(mol.get_atom_features())
		# pair features
		pair_feat.append(
		np.reshape(mol.get_pair_features(), (n_atoms * n_atoms,
		self.n_pair_feat)))
		np.reshape(mol.get_pair_features(),
		(n_atoms * n_atoms, self.n_pair_feat)))

		feed_dict[self.atom_features] = np.concatenate(atom_feat, axis=0)
		feed_dict[self.pair_features] = np.concatenate(pair_feat, axis=0)
		@@ -317,8 +317,8 @@ class DTNNTensorGraph(TensorGraph):
		num_atoms = list(map(sum, X_b.astype(bool)[:, :, 0]))
		atom_number = [
		np.round(
		np.power(2 * np.diag(X_b[i, :num_atoms[i], :num_atoms[i]]), 1 /
		2.4)).astype(int) for i in range(len(num_atoms))
		np.power(2 * np.diag(X_b[i, :num_atoms[i], :num_atoms[i]]),
		1 / 2.4)).astype(int) for i in range(len(num_atoms))
		]
		start = 0
		for im, molecule in enumerate(atom_number):
		@@ -1090,8 +1090,8 @@ class MPNNTensorGraph(TensorGraph):
		atom_feat.append(mol.get_atom_features())
		# pair features
		pair_feat.append(
		np.reshape(mol.get_pair_features(), (n_atoms * n_atoms,
		self.n_pair_feat)))
		np.reshape(mol.get_pair_features(),
		(n_atoms * n_atoms, self.n_pair_feat)))

		feed_dict[self.atom_features] = np.concatenate(atom_feat, axis=0)
		feed_dict[self.pair_features] = np.concatenate(pair_feat, axis=0)

devtools/jenkins/generate_graph.py

+2 −2

Original line number	Diff line number	Diff line
		@@ -164,5 +164,5 @@ if __name__ == '__main__':
		os.mkdir(save_dir)
		for pair in TODO.keys():
		plot(pair[0], pair[1], FILE, save_dir)
		os.system('aws s3 sync ' + save_dir +
		' s3://deepchem.io/trained_models/MolNet_pic')
		os.system(
		'aws s3 sync ' + save_dir + ' s3://deepchem.io/trained_models/MolNet_pic')

Admin message