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1172b152ab
These files don't follow the usual pattern: In general the files torch/csrc/X torch/csrc/cuda/X both include the generic file torch/csrc/generic/X, where torch/csrc/X includes the cpu implementations and torch/csrc/cuda/X includes the cuda implementations. (Aside: this is probably not the best structure, the torch/csrc/X fiels should probably be moved to torch/csrc/cpu/X). utils.cpp combines these so that torch/csrc/utils.cpp has cuda specific code. This makes it impossible to declare a single THTensor and THCTensor template type (i.e. THPPointer<_THTensor>, THPointer<_THCTensor>).
37 lines
1.1 KiB
C++
37 lines
1.1 KiB
C++
#include "torch/csrc/python_headers.h"
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#include <stdarg.h>
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#include <string>
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#include "THCP.h"
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#include "override_macros.h"
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#define THC_GENERIC_FILE "torch/csrc/generic/utils.cpp"
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#include <THC/THCGenerateAllTypes.h>
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#ifdef WITH_CUDA
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std::vector <THCStream*> THPUtils_PySequence_to_THCStreamList(PyObject *obj) {
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if (!PySequence_Check(obj)) {
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throw std::runtime_error("Expected a sequence in THPUtils_PySequence_to_THCStreamList");
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}
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THPObjectPtr seq = THPObjectPtr(PySequence_Fast(obj, NULL));
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if (seq.get() == NULL) {
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throw std::runtime_error("expected PySequence, but got " + std::string(THPUtils_typename(obj)));
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}
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std::vector<THCStream*> streams;
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Py_ssize_t length = PySequence_Fast_GET_SIZE(seq.get());
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for (Py_ssize_t i = 0; i < length; i++) {
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PyObject *stream = PySequence_Fast_GET_ITEM(seq.get(), i);
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if (PyObject_IsInstance(stream, THCPStreamClass)) {
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streams.push_back( ((THCPStream *)stream)->cdata);
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} else if (stream == Py_None) {
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streams.push_back(NULL);
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} else {
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std::runtime_error("Unknown data type found in stream list. Need THCStream or None");
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}
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}
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return streams;
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}
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#endif
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