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https://github.com/zebrajr/pytorch.git
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aebf3b47ae
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/9939 Pull Request resolved: https://github.com/facebookresearch/weakly-supervised-action-detection/pull/13 Pull Request resolved: https://github.com/pytorch/translate/pull/166 Pull Request resolved: https://github.com/pytorch/pytorch/pull/9125 Closes https://github.com/pytorch/pytorch/pull/9125 Use inheritance for polymorphism, and remove template parameter This is to change the templating in call sites, the core implementations will change later Before Caffe2 Tensor class was compile-time fixed to bind to a particular device/context. With this change, we're making it a runtime property (stored inside the tensor), but preserve the same semantics. For example, one has to specify device type in order to create a Tensor - there are no uninitialized tensors. More specifically the changes are: 1. We added an extra argument *DeviceType* to most of the constructors of the tensor, e.g. (Tensor(DeviceType type)), 2. Semantics of constructor Tensor(const Tensor<SrcContext>& src, ContextForCopy* context); is changed, in this constructor, the second context is passed in to enable us to call the templated Copy function, it could be in a different context as source and target previously, now we'll enforce that the context should have same device type as src, if it is provided. 3. To preserve 'get-or-construct' semantics of Blob, we added specialized getter Blob::GetMutableTensor that verifies both that Blob contains a Tensor and that it's of a correct type 4. Specifically, Tensor type is not default-constructible any more (as we don't have unknown device tensors) and thus some of the code handling STL containers needs to change Note: Some changes are postponed just to keep this diff a bit smaller. Please see `TODO`s. Reviewed By: ezyang, houseroad Differential Revision: D9024330 fbshipit-source-id: e0b8295d2dc6ebe2963383ded5af799ad17164ba
91 lines
2.8 KiB
C++
91 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_hip.h"
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#include "caffe2/operators/hip/operator_fallback_hip.h"
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namespace caffe2 {
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namespace python {
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REGISTER_HIP_OPERATOR(Python, GPUFallbackOp<PythonOp<CPUContext, false>>);
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REGISTER_HIP_OPERATOR(
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PythonGradient,
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GPUFallbackOp<PythonGradientOp<CPUContext, false>>);
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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("set_default_gpu_id", &SetDefaultGPUID);
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m.def("get_default_gpu_id", &GetDefaultGPUID);
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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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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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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<TIndex> 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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}
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} // namespace python
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} // namespace caffe2
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