pytorch/caffe2/python/pybind_state_hip.cc

#define NO_IMPORT_ARRAY

#include "pybind_state.h"

#include <pybind11/pybind11.h>
#include <pybind11/stl.h>

#include "caffe2/core/hip/common_miopen.h"
#include "caffe2/core/hip/context_gpu.h"
#include "caffe2/operators/hip/operator_fallback_gpu.h"
#include "caffe2/python/pybind_state_registry.h"
#include <c10/hip/HIPGuard.h>

namespace caffe2 {
namespace python {

REGISTER_HIP_OPERATOR(Python, GPUFallbackOp);
REGISTER_HIP_OPERATOR(
    PythonGradient,
    GPUFallbackOp);

REGISTER_HIP_OPERATOR(PythonDLPack, GPUFallbackOp);
REGISTER_HIP_OPERATOR(PythonDLPackGradient, GPUFallbackOp);

REGISTER_BLOB_FEEDER(HIP, TensorFeeder<HIPContext>);

namespace py = pybind11;

void addHIPGlobalMethods(py::module& m) {
  m.def("num_hip_devices", &NumHipDevices);
  m.def("get_hip_version", &HipVersion);
  m.def("get_miopen_version", &miopenCompiledVersion);
  m.def("get_gpu_memory_info", [](int device_id) {
    HIPGuard guard(device_id);
    size_t device_free, device_total;
    HIP_CHECK(hipMemGetInfo(&device_free, &device_total));
    return std::pair<size_t, size_t>{device_free, device_total};
  });
  m.def("get_hip_peer_access_pattern", []() {
    std::vector<std::vector<bool>> pattern;
    CAFFE_ENFORCE(caffe2::GetHipPeerAccessPattern(&pattern));
    return pattern;
  });
  m.def("get_device_properties", [](int deviceid) {
    auto& prop = GetDeviceProperty(deviceid);
    std::map<std::string, py::object> obj;
    obj["name"] = py::cast(prop.name);
    obj["major"] = py::cast(prop.major);
    obj["minor"] = py::cast(prop.minor);
    obj["totalGlobalMem"] = py::cast(prop.totalGlobalMem);
    return obj;
  });
};

void addHIPObjectMethods(py::module& m) {
  py::class_<DLPackWrapper<HIPContext>>(m, "DLPackTensorHIP")
      .def_property_readonly(
          "data",
          [](DLPackWrapper<HIPContext>* t) -> py::object {
            CAFFE_ENFORCE_EQ(
                t->device_option.device_type(),
                PROTO_HIP,
                "Expected HIP device option for HIP tensor");

            return t->data();
          },
          "Return DLPack tensor with tensor's data.")
      .def(
          "feed",
          [](DLPackWrapper<HIPContext>* t, py::object obj) {
            CAFFE_ENFORCE_EQ(
                t->device_option.device_type(),
                PROTO_HIP,
                "Expected HIP device option for HIP tensor");
            t->feed(obj);
          },
          "Copy data from given DLPack tensor into this tensor.")
      .def_property_readonly(
          "_shape",
          [](const DLPackWrapper<HIPContext>& t) { return t.tensor->sizes(); })
      .def(
          "_reshape",
          [](DLPackWrapper<HIPContext>* t, std::vector<int64_t> dims) {
            t->tensor->Resize(dims);
          });
}

PYBIND11_MODULE(caffe2_pybind11_state_hip, m) {
  m.doc() = "pybind11 stateful interface to Caffe2 workspaces - GPU edition";

  addGlobalMethods(m);
  addHIPGlobalMethods(m);
  addObjectMethods(m);
  addHIPObjectMethods(m);
  for (const auto& addition : PybindAdditionRegistry()->Keys()) {
    PybindAdditionRegistry()->Create(addition, m);
  }
}
} // namespace python
} // namespace caffe2