mirror of
https://github.com/zebrajr/pytorch.git
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0d7a986da1
Summary:
xw285cornell
- To make hip files to have unique filename extension we change hip files from _hip.cc to .hip (it's the only blessing option other than .cu in hipcc 3d51a1fb01/bin/hipcc (L552)).
- Change to use host compiler to compile .cc|.cpp files. Previously we use hcc to compile them which is unnecessary
- Change the hipify script to not replace "gpu" with "hip" in the filename of the generated hipified files. Previously we do this because hcc has a bug when linking files that have same filename. We have now changed to use host linker to do linking so this is unnecessary anymore.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/14036
Reviewed By: xw285cornell
Differential Revision: D13091813
Pulled By: bddppq
fbshipit-source-id: ea3d887751d8abb39d75f5d5104aa66ce66b9ee0
93 lines
2.8 KiB
C++
93 lines
2.8 KiB
C++
#define NO_IMPORT_ARRAY
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#include "pybind_state.h"
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#include <pybind11/pybind11.h>
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#include <pybind11/stl.h>
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#include "caffe2/core/hip/common_miopen.h"
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#include "caffe2/core/hip/context_gpu.h"
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#include "caffe2/operators/hip/operator_fallback_gpu.h"
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#include "caffe2/python/pybind_state_registry.h"
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namespace caffe2 {
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namespace python {
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REGISTER_HIP_OPERATOR(Python, GPUFallbackOp);
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REGISTER_HIP_OPERATOR(
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PythonGradient,
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GPUFallbackOp);
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REGISTER_HIP_OPERATOR(PythonDLPack, PythonOp<HIPContext, true>);
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REGISTER_HIP_OPERATOR(PythonDLPackGradient, PythonGradientOp<HIPContext, true>);
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REGISTER_BLOB_FEEDER(HIP, TensorFeeder<HIPContext>);
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namespace py = pybind11;
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void addHIPGlobalMethods(py::module& m) {
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m.def("num_hip_devices", &NumHipDevices);
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m.def("get_hip_version", &HipVersion);
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m.def("get_miopen_version", &miopenCompiledVersion);
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m.def("get_hip_peer_access_pattern", []() {
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std::vector<std::vector<bool>> pattern;
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CAFFE_ENFORCE(caffe2::GetHipPeerAccessPattern(&pattern));
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return pattern;
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});
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m.def("get_device_properties", [](int deviceid) {
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auto& prop = GetDeviceProperty(deviceid);
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std::map<std::string, py::object> obj;
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obj["name"] = py::cast(prop.name);
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obj["major"] = py::cast(prop.major);
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obj["minor"] = py::cast(prop.minor);
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return obj;
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});
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};
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void addHIPObjectMethods(py::module& m) {
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py::class_<DLPackWrapper<HIPContext>>(m, "DLPackTensorHIP")
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.def_property_readonly(
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"data",
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[](DLPackWrapper<HIPContext>* t) -> py::object {
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CAFFE_ENFORCE_EQ(
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t->device_option.device_type(),
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PROTO_HIP,
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"Expected HIP device option for HIP tensor");
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return t->data();
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},
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"Return DLPack tensor with tensor's data.")
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.def(
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"feed",
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[](DLPackWrapper<HIPContext>* t, py::object obj) {
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CAFFE_ENFORCE_EQ(
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t->device_option.device_type(),
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PROTO_HIP,
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"Expected HIP device option for HIP tensor");
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t->feed(obj);
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},
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"Copy data from given DLPack tensor into this tensor.")
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.def_property_readonly(
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"_shape",
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[](const DLPackWrapper<HIPContext>& t) { return t.tensor->dims(); })
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.def(
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"_reshape",
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[](DLPackWrapper<HIPContext>* t, std::vector<int64_t> dims) {
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t->tensor->Resize(dims);
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});
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}
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PYBIND11_MODULE(caffe2_pybind11_state_hip, m) {
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m.doc() = "pybind11 stateful interface to Caffe2 workspaces - GPU edition";
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addGlobalMethods(m);
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addHIPGlobalMethods(m);
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addObjectMethods(m);
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addHIPObjectMethods(m);
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for (const auto& addition : PybindAdditionRegistry()->Keys()) {
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PybindAdditionRegistry()->Create(addition, m);
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}
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}
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} // namespace python
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} // namespace caffe2
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