chainer_chemistry.models.RSGCN

class chainer_chemistry.models.RSGCN(out_dim, hidden_dim=32, n_layers=4, n_atom_types=117, use_batch_norm=False, readout=None, dropout_ratio=0.5)[source]

Renormalized Spectral Graph Convolutional Network (RSGCN)

See: Thomas N. Kipf and Max Welling, Semi-Supervised Classification with Graph Convolutional Networks. September 2016. arXiv:1609.02907

The name of this model “Renormalized Spectral Graph Convolutional Network (RSGCN)” is named by us rather than the authors of the paper above. The authors call this model just “Graph Convolution Network (GCN)”, but we think that “GCN” is bit too general and may cause namespace issue. That is why we did not name this model as GCN.

Parameters:
  • out_dim (int) – dimension of output feature vector
  • hidden_dim (int) – dimension of feature vector associated to each atom
  • n_atom_types (int) – number of types of atoms
  • n_layers (int) – number of layers
  • use_batch_norm (bool) – If True, batch normalization is applied after graph convolution.
  • readout (Callable) – readout function. If None, GeneralReadout(mode=’sum) is used. To the best of our knowledge, the paper of RSGCN model does not give any suggestion on readout.
  • dropout_ratio (float) – ratio used in dropout function. If 0 or negative value is set, dropout function is skipped.
__init__(out_dim, hidden_dim=32, n_layers=4, n_atom_types=117, use_batch_norm=False, readout=None, dropout_ratio=0.5)[source]

Initialize self. See help(type(self)) for accurate signature.

Methods

__init__(out_dim[, hidden_dim, n_layers, …]) Initialize self.
add_hook(hook[, name]) Registers a link hook.
add_link(name, link) Registers a child link to this chain.
add_param(name[, shape, dtype, initializer]) Registers a parameter to the link.
add_persistent(name, value) Registers a persistent value to the link.
addgrads(link) Accumulates gradient values from given link.
children() Returns a generator of all child links.
cleargrads() Clears all gradient arrays.
copy([mode]) Copies the link hierarchy to new one.
copyparams(link[, copy_persistent]) Copies all parameters from given link.
count_params() Counts the total number of parameters.
delete_hook(name) Unregisters the link hook.
disable_update() Disables update rules of all parameters under the link hierarchy.
enable_update() Enables update rules of all parameters under the link hierarchy.
init_scope() Creates an initialization scope.
links([skipself]) Returns a generator of all links under the hierarchy.
namedlinks([skipself]) Returns a generator of all (path, link) pairs under the hierarchy.
namedparams([include_uninit]) Returns a generator of all (path, param) pairs under the hierarchy.
params([include_uninit]) Returns a generator of all parameters under the link hierarchy.
register_persistent(name) Registers an attribute of a given name as a persistent value.
repeat(n_repeat[, mode]) Repeats this link multiple times to make a Sequential.
serialize(serializer) Serializes the link object.
to_cpu() Copies parameter variables and persistent values to CPU.
to_gpu([device]) Copies parameter variables and persistent values to GPU.
to_intel64() Copies parameter variables and persistent values to CPU.
zerograds() Initializes all gradient arrays by zero.

Attributes

local_link_hooks Ordered dictionary of registered link hooks.
update_enabled True if at least one parameter has an update rule enabled.
within_init_scope True if the current code is inside of an initialization scope.
xp Array module for this link.