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#include <utility>
#include <vector>
#include "pybind11/pybind11.h"
#include "pybind11/cast.h"
#include "pybind11/stl.h"
#include "cudnn_frontend.h"
#include "pygraph.h"
namespace py = pybind11;
using namespace pybind11::literals;
namespace cudnn_frontend {
namespace python_bindings {
std::vector<std::shared_ptr<cudnn_frontend::graph::Tensor_attributes>>
PyGraph::batchnorm(std::shared_ptr<cudnn_frontend::graph::Tensor_attributes>& x,
std::shared_ptr<cudnn_frontend::graph::Tensor_attributes>& scale,
std::shared_ptr<cudnn_frontend::graph::Tensor_attributes>& bias,
std::shared_ptr<cudnn_frontend::graph::Tensor_attributes>& in_running_mean,
std::shared_ptr<cudnn_frontend::graph::Tensor_attributes>& in_running_var,
std::shared_ptr<cudnn_frontend::graph::Tensor_attributes>& epsilon,
std::shared_ptr<cudnn_frontend::graph::Tensor_attributes>& momentum,
std::vector<std::shared_ptr<cudnn_frontend::graph::Tensor_attributes>>& peer_stats,
cudnn_frontend::DataType_t const& compute_data_type,
std::string const& name) {
auto attributes = cudnn_frontend::graph::Batchnorm_attributes()
.set_compute_data_type(compute_data_type)
.set_epsilon(epsilon)
.set_previous_running_stats(in_running_mean, in_running_var, momentum)
.set_peer_stats(peer_stats)
.set_name(name);
auto [Y, mean, inv_var, next_running_mean, next_running_var] = graph.batchnorm(x, scale, bias, attributes);
return {Y, mean, inv_var, next_running_mean, next_running_var};
}
std::vector<std::shared_ptr<cudnn_frontend::graph::Tensor_attributes>>
PyGraph::layernorm(cudnn_frontend::NormFwdPhase_t const forward_phase,
std::shared_ptr<cudnn_frontend::graph::Tensor_attributes>& x,
std::shared_ptr<cudnn_frontend::graph::Tensor_attributes>& scale,
std::shared_ptr<cudnn_frontend::graph::Tensor_attributes>& bias,
std::shared_ptr<cudnn_frontend::graph::Tensor_attributes>& epsilon,
cudnn_frontend::DataType_t const& compute_data_type,
std::string const& name) {
auto attributes = cudnn_frontend::graph::Layernorm_attributes()
.set_forward_phase(forward_phase)
.set_compute_data_type(compute_data_type)
.set_epsilon(epsilon)
.set_name(name);
auto [Y, mean, inv_var] = graph.layernorm(x, scale, bias, attributes);
return {Y, mean, inv_var};
}
std::shared_ptr<cudnn_frontend::graph::Tensor_attributes>
PyGraph::batchnorm_inference(std::shared_ptr<cudnn_frontend::graph::Tensor_attributes>& x,
std::shared_ptr<cudnn_frontend::graph::Tensor_attributes>& mean,
std::shared_ptr<cudnn_frontend::graph::Tensor_attributes>& inv_variance,
std::shared_ptr<cudnn_frontend::graph::Tensor_attributes>& scale,
std::shared_ptr<cudnn_frontend::graph::Tensor_attributes>& bias,
cudnn_frontend::DataType_t const& compute_data_type,
std::string const& name) {
auto attributes =
cudnn_frontend::graph::Batchnorm_inference_attributes().set_compute_data_type(compute_data_type).set_name(name);
return graph.batchnorm_inference(x, mean, inv_variance, scale, bias, attributes);
}
std::vector<std::shared_ptr<cudnn_frontend::graph::Tensor_attributes>>
PyGraph::layernorm_backward(std::shared_ptr<cudnn_frontend::graph::Tensor_attributes> const& dy,
std::shared_ptr<cudnn_frontend::graph::Tensor_attributes> const& x,
std::shared_ptr<cudnn_frontend::graph::Tensor_attributes> const& scale,
std::shared_ptr<cudnn_frontend::graph::Tensor_attributes> const& mean,
std::shared_ptr<cudnn_frontend::graph::Tensor_attributes> const& inv_variance,
cudnn_frontend::DataType_t const& compute_data_type,
std::string const& name) {
auto attributes = cudnn_frontend::graph::Layernorm_backward_attributes()
.set_saved_mean_and_inv_variance(mean, inv_variance)
.set_compute_data_type(compute_data_type)
.set_name(name);
auto [DX, DScale, DBias] = graph.layernorm_backward(dy, x, scale, attributes);
return {DX, DScale, DBias};
}
std::vector<std::shared_ptr<cudnn_frontend::graph::Tensor_attributes>>
PyGraph::batchnorm_backward(std::shared_ptr<cudnn_frontend::graph::Tensor_attributes> const& dy,
std::shared_ptr<cudnn_frontend::graph::Tensor_attributes> const& x,
std::shared_ptr<cudnn_frontend::graph::Tensor_attributes> const& scale,
std::shared_ptr<cudnn_frontend::graph::Tensor_attributes> const& mean,
std::shared_ptr<cudnn_frontend::graph::Tensor_attributes> const& inv_variance,
std::vector<std::shared_ptr<cudnn_frontend::graph::Tensor_attributes>>& peer_stats,
cudnn_frontend::DataType_t const& compute_data_type,
std::string const& name) {
auto attributes = cudnn_frontend::graph::Batchnorm_backward_attributes()
.set_saved_mean_and_inv_variance(mean, inv_variance)
.set_peer_stats(peer_stats)
.set_compute_data_type(compute_data_type)
.set_name(name);
auto [DX, DScale, DBias] = graph.batchnorm_backward(dy, x, scale, attributes);
return {DX, DScale, DBias};
}
std::vector<std::shared_ptr<cudnn_frontend::graph::Tensor_attributes>>
PyGraph::rmsnorm(cudnn_frontend::NormFwdPhase_t const forward_phase,
std::shared_ptr<cudnn_frontend::graph::Tensor_attributes>& x,
std::shared_ptr<cudnn_frontend::graph::Tensor_attributes>& scale,
std::shared_ptr<cudnn_frontend::graph::Tensor_attributes>& bias,
std::shared_ptr<cudnn_frontend::graph::Tensor_attributes>& epsilon,
cudnn_frontend::DataType_t const& compute_data_type,
std::string const& name) {
auto attributes = cudnn_frontend::graph::Rmsnorm_attributes()
.set_forward_phase(forward_phase)
.set_compute_data_type(compute_data_type)
.set_bias(bias)
.set_epsilon(epsilon)
.set_name(name);
auto [Y, inv_var] = graph.rmsnorm(x, scale, attributes);
return {Y, inv_var};
}
std::vector<std::shared_ptr<cudnn_frontend::graph::Tensor_attributes>>
PyGraph::rmsnorm_backward(std::shared_ptr<cudnn_frontend::graph::Tensor_attributes> const& dy,
std::shared_ptr<cudnn_frontend::graph::Tensor_attributes> const& x,
std::shared_ptr<cudnn_frontend::graph::Tensor_attributes> const& scale,
std::shared_ptr<cudnn_frontend::graph::Tensor_attributes> const& inv_variance,
bool const has_dbias,
cudnn_frontend::DataType_t const& compute_data_type,
std::string const& name) {
auto attributes = cudnn_frontend::graph::Rmsnorm_backward_attributes()
.has_dbias(has_dbias)
.set_compute_data_type(compute_data_type)
.set_name(name);
auto [DX, DScale, DBias] = graph.rmsnorm_backward(dy, x, scale, inv_variance, attributes);
return {DX, DScale, DBias};
}
std::vector<std::shared_ptr<cudnn_frontend::graph::Tensor_attributes>>
PyGraph::instancenorm(cudnn_frontend::NormFwdPhase_t const forward_phase,
std::shared_ptr<cudnn_frontend::graph::Tensor_attributes>& x,
std::shared_ptr<cudnn_frontend::graph::Tensor_attributes>& scale,
std::shared_ptr<cudnn_frontend::graph::Tensor_attributes>& bias,
std::shared_ptr<cudnn_frontend::graph::Tensor_attributes>& epsilon,
cudnn_frontend::DataType_t const& compute_data_type,
std::string const& name) {
auto attributes = cudnn_frontend::graph::Instancenorm_attributes()
.set_forward_phase(forward_phase)
.set_compute_data_type(compute_data_type)
.set_epsilon(epsilon)
.set_name(name);
auto [Y, mean, inv_var] = graph.instancenorm(x, scale, bias, attributes);
return {Y, mean, inv_var};
}
std::vector<std::shared_ptr<cudnn_frontend::graph::Tensor_attributes>>
PyGraph::instancenorm_backward(std::shared_ptr<cudnn_frontend::graph::Tensor_attributes> const& dy,
std::shared_ptr<cudnn_frontend::graph::Tensor_attributes> const& x,
std::shared_ptr<cudnn_frontend::graph::Tensor_attributes> const& scale,
std::shared_ptr<cudnn_frontend::graph::Tensor_attributes> const& mean,
std::shared_ptr<cudnn_frontend::graph::Tensor_attributes> const& inv_variance,
cudnn_frontend::DataType_t const& compute_data_type,
std::string const& name) {
auto attributes = cudnn_frontend::graph::Instancenorm_backward_attributes()
.set_saved_mean_and_inv_variance(mean, inv_variance)
.set_compute_data_type(compute_data_type)
.set_name(name);
auto [DX, DScale, DBias] = graph.instancenorm_backward(dy, x, scale, attributes);
return {DX, DScale, DBias};
}
void
init_pygraph_norm_submodule(py::class_<PyGraph>& m) {
m.def("batchnorm",
&PyGraph::batchnorm,
py::arg("input"),
py::arg("scale"),
py::arg("bias"),
py::arg("in_running_mean"),
py::arg("in_running_var"),
py::arg("epsilon"),
py::arg("momentum"),
py::arg_v("peer_stats", std::vector<std::shared_ptr<cudnn_frontend::graph::Tensor_attributes>>()),
py::arg_v("compute_data_type", cudnn_frontend::DataType_t::NOT_SET),
py::arg_v("name", ""))
.def("layernorm",
&PyGraph::layernorm,
py::arg("norm_forward_phase"),
py::arg("input"),
py::arg("scale"),
py::arg("bias"),
py::arg("epsilon"),
py::arg_v("compute_data_type", cudnn_frontend::DataType_t::NOT_SET),
py::arg_v("name", ""))
.def("batchnorm_inference",
&PyGraph::batchnorm_inference,
py::arg("input"),
py::arg("mean"),
py::arg("inv_variance"),
py::arg("scale"),
py::arg("bias"),
py::arg_v("compute_data_type", cudnn_frontend::DataType_t::NOT_SET),
py::arg_v("name", ""))
.def("batchnorm_backward",
&PyGraph::batchnorm_backward,
py::arg("grad"),
py::arg("input"),
py::arg("scale"),
py::arg("mean"),
py::arg("inv_variance"),
py::arg_v("peer_stats", std::vector<std::shared_ptr<cudnn_frontend::graph::Tensor_attributes>>()),
py::arg_v("compute_data_type", cudnn_frontend::DataType_t::NOT_SET),
py::arg_v("name", ""))
.def("layernorm_backward",
&PyGraph::layernorm_backward,
py::arg("grad"),
py::arg("input"),
py::arg("scale"),
py::arg("mean"),
py::arg("inv_variance"),
py::arg_v("compute_data_type", cudnn_frontend::DataType_t::NOT_SET),
py::arg_v("name", ""))
.def("rmsnorm",
&PyGraph::rmsnorm,
py::arg("norm_forward_phase"),
py::arg("input"),
py::arg("scale"),
py::arg_v("bias", nullptr),
py::arg("epsilon"),
py::arg_v("compute_data_type", cudnn_frontend::DataType_t::NOT_SET),
py::arg_v("name", ""))
.def("rmsnorm_backward",
&PyGraph::rmsnorm_backward,
py::arg("grad"),
py::arg("input"),
py::arg("scale"),
py::arg("inv_variance"),
py::arg("has_dbias"),
py::arg_v("compute_data_type", cudnn_frontend::DataType_t::NOT_SET),
py::arg_v("name", ""))
.def("instancenorm",
&PyGraph::instancenorm,
py::arg("norm_forward_phase"),
py::arg("input"),
py::arg("scale"),
py::arg("bias"),
py::arg("epsilon"),
py::arg_v("compute_data_type", cudnn_frontend::DataType_t::NOT_SET),
py::arg_v("name", ""))
.def("instancenorm_backward",
&PyGraph::instancenorm_backward,
py::arg("grad"),
py::arg("input"),
py::arg("scale"),
py::arg_v("mean", nullptr),
py::arg_v("inv_variance", nullptr),
py::arg_v("compute_data_type", cudnn_frontend::DataType_t::NOT_SET),
py::arg_v("name", ""));
}
} // namespace python_bindings
} // namespace cudnn_frontend
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