shared_ptr<Node> op::Divide::copy_with_new_args(const NodeVector& new_args) const
{
if (new_args.size() != 2)
{
throw ngraph_error("Incorrect number of new arguments");
}
return make_shared<Divide>(new_args.at(0), new_args.at(1));
}
void op::Softmax::generate_adjoints(autodiff::Adjoints& adjoints, const NodeVector& deltas)
{
auto delta = deltas.at(0);
auto z = delta * shared_from_this();
auto zsum = make_shared<op::Sum>(z, m_axes);
Shape shape;
for (size_t i = 0; i < get_shape().size(); ++i)
{
if (m_axes.find(i) == m_axes.end())
{
shape.push_back(get_shape()[i]);
}
else
{
shape.push_back(1);
}
}
AxisVector order(zsum->get_shape().size());
iota(order.begin(), order.end(), 0);
auto zreshape = make_shared<op::Reshape>(zsum, order, shape);
auto adjoint =
z - builder::make_with_numpy_broadcast<op::Multiply>(shared_from_this(), zreshape);
auto x = get_argument(0);
adjoints.add_delta(x, adjoint);
}
shared_ptr<Node> op::ConvolutionBias::copy_with_new_args(const NodeVector& new_args) const
{
if (new_args.size() != 3)
{
throw ngraph_error("Incorrect number of new arguments");
}
return shared_ptr<Node>(new ConvolutionBias(new_args.at(0),
new_args.at(1),
new_args.at(2),
get_window_movement_strides(),
get_window_dilation_strides(),
get_padding_below(),
get_padding_above(),
get_data_dilation_strides()));
}
template<class NodeVector> void FileSystem::debugPrintNodes(NodeVector nodes) {
if( debug) {
unsigned int ix;
NodeInfo* node;
for (ix = 0; ix < nodes.size(); ++ix) {
node = nodes.at(ix);
cout << "Node: " << node->getName()
<< "\t\tSize: " << node->getSize()
<< "\tModify: " << node->getModifyTime()
<< "\tPath: " << node->getPath()
<< "\tSimilars: ";
vector<NodeInfo*>::iterator it;
vector<NodeInfo*> nodes = node->getSimilar();
for(it=nodes.begin(); it != nodes.end(); ++it) {
cout << (*it)->getPath() << ", ";
}
cout << endl;
}
}
}
void op::Cos::generate_adjoints(autodiff::Adjoints& adjoints, const NodeVector& deltas)
{
auto delta = deltas.at(0);
auto x = get_argument(0);
adjoints.add_delta(x, -delta * (make_shared<op::Sin>(x)));
}
shared_ptr<Node> op::Softmax::copy_with_new_args(const NodeVector& new_args) const
{
if (new_args.size() != 1)
{
throw ngraph_error("Incorrect number of new arguments");
}
return make_shared<Softmax>(new_args.at(0), m_axes);
}
shared_ptr<Node> op::Result::copy_with_new_args(const NodeVector& new_args) const
{
if (new_args.size() != 1)
{
throw ngraph_error("Incorrect number of new arguments");
}
if (new_args.at(0)->get_outputs().size() != 1)
{
throw ngraph_error("Expected a single-output argument");
}
auto res = make_shared<Result>(new_args.at(0));
res->set_needs_copy(m_needs_copy);
res->set_needs_default_layout(m_needs_default_layout);
return res;
}
shared_ptr<Node> op::GetOutputElement::copy_with_new_args(const NodeVector& new_args) const
{
if (new_args.size() != 1)
{
throw ngraph_error("Incorrect number of new arguments");
}
return make_shared<GetOutputElement>(new_args.at(0), m_n);
}
shared_ptr<Node>
op::ConvolutionBiasBackpropFiltersBias::copy_with_new_args(const NodeVector& new_args) const
{
if (new_args.size() != 2)
{
throw ngraph_error("Incorrect number of new arguments");
}
return make_shared<ConvolutionBiasBackpropFiltersBias>(new_args.at(0),
m_filters_shape,
m_bias_shape,
new_args.at(1),
m_window_movement_strides_forward,
m_window_dilation_strides_forward,
m_padding_below_forward,
m_padding_above_forward,
m_data_dilation_strides_forward);
}
shared_ptr<Node> op::OneHot::copy_with_new_args(const NodeVector& new_args) const
{
if (new_args.size() != 1)
{
throw ngraph_error("Incorrect number of new arguments");
}
return make_shared<OneHot>(new_args.at(0), m_shape, m_one_hot_axis);
}
void op::Divide::generate_adjoints(autodiff::Adjoints& adjoints, const NodeVector& deltas)
{
auto delta = deltas.at(0);
auto x = get_argument(0);
auto y = get_argument(1);
adjoints.add_delta(x, delta / y);
adjoints.add_delta(y, -delta * shared_from_this() / y);
}
shared_ptr<Node> op::ReduceWindow::copy_with_new_args(const NodeVector& new_args) const
{
if (new_args.size() != 2)
{
throw ngraph_error("Incorrect number of new arguments");
}
auto node = make_shared<ReduceWindow>(new_args.at(0),
new_args.at(1),
m_reduction_function,
m_window_shape,
m_window_movement_strides);
node->m_reduction_function = clone_function(*m_reduction_function);
return node;
}
void op::ConvolutionBias::generate_adjoints(autodiff::Adjoints& adjoints, const NodeVector& deltas)
{
auto delta = deltas.at(0);
auto data = get_argument(0);
const auto data_shape = data->get_shape();
auto filter = get_argument(1);
const auto filter_shape = filter->get_shape();
auto bias = get_argument(2);
const auto bias_shape = bias->get_shape();
// using regular convolution backprop for data
adjoints.add_delta(data,
make_shared<op::ConvolutionBackpropData>(data_shape,
filter,
delta,
m_window_movement_strides,
m_window_dilation_strides,
m_padding_below,
m_padding_above,
m_data_dilation_strides));
auto filter_bias_backprop =
make_shared<op::ConvolutionBiasBackpropFiltersBias>(data,
filter_shape,
bias_shape,
delta,
m_window_movement_strides,
m_window_dilation_strides,
m_padding_below,
m_padding_above,
m_data_dilation_strides);
auto filter_delta = make_shared<op::GetOutputElement>(filter_bias_backprop, 0);
auto bias_delta = make_shared<op::GetOutputElement>(filter_bias_backprop, 1);
adjoints.add_delta(filter, filter_delta);
adjoints.add_delta(bias, bias_delta);
}
void op::Result::generate_adjoints(autodiff::Adjoints& adjoints, const NodeVector& deltas)
{
auto delta = deltas.at(0);
adjoints.add_delta(get_argument(0), delta);
}
void op::GetOutputElement::generate_adjoints(autodiff::Adjoints& adjoints, const NodeVector& deltas)
{
auto delta = deltas.at(0);
adjoints.add_delta(get_inputs().at(0).get_output().get_node(), delta, get_n());
}
