def __init__(self, max_atoms=50, n_atom_feat=75, n_pair_feat=14): """ Parameters ---------- max_atoms: int, optional Maximum number of atoms in a molecule, should be defined based on dataset n_atom_feat: int, optional Number of features per atom. n_pair_feat: int, optional Number of features per pair of atoms. """ warnings.warn( "SequentialWeaveGraph is deprecated. " "Will be removed in DeepChem 1.4.", DeprecationWarning) self.graph = tf.Graph() self.max_atoms = max_atoms self.n_atom_feat = n_atom_feat self.n_pair_feat = n_pair_feat with self.graph.as_default(): self.graph_topology = WeaveGraphTopology(self.max_atoms, self.n_atom_feat, self.n_pair_feat) self.output = self.graph_topology.get_atom_features_placeholder() self.output_P = self.graph_topology.get_pair_features_placeholder() self.layers = []
def __init__(self, max_atoms=50, n_atom_feat=75, n_pair_feat=14): self.graph = tf.Graph() self.max_atoms = max_atoms self.n_atom_feat = n_atom_feat self.n_pair_feat = n_pair_feat with self.graph.as_default(): self.graph_topology = WeaveGraphTopology(self.max_atoms, self.n_atom_feat, self.n_pair_feat) self.output = self.graph_topology.get_atom_features_placeholder() self.output_P = self.graph_topology.get_pair_features_placeholder() self.layers = []
def __init__(self, max_atoms=50, n_atom_feat=75, n_pair_feat=14): """ Parameters ---------- max_atoms: int, optional Maximum number of atoms in a molecule, should be defined based on dataset n_atom_feat: int, optional Number of features per atom. n_pair_feat: int, optional Number of features per pair of atoms. """ self.graph = tf.Graph() self.max_atoms = max_atoms self.n_atom_feat = n_atom_feat self.n_pair_feat = n_pair_feat with self.graph.as_default(): self.graph_topology = WeaveGraphTopology(self.max_atoms, self.n_atom_feat, self.n_pair_feat) self.output = self.graph_topology.get_atom_features_placeholder() self.output_P = self.graph_topology.get_pair_features_placeholder() self.layers = []