未验证 提交 59fec5d6 编写于 作者: S Siming Dai 提交者: GitHub

[cherry-pick 2.4] Fix to_dlpack (#50138) (#50250)

* Fix to_dlpack (#50138)

* fix to_dlpack for loop

* fix reference count

* fix conflicts
上级 b50f04ab
......@@ -134,7 +134,59 @@ struct DLDeviceVisitor
};
} // namespace internal
DLPackTensor::DLPackTensor(const Tensor &tensor, LaneType lanes) {
struct PaddleDLMTensor {
phi::DenseTensor handle;
DLManagedTensor tensor;
};
void deleter(DLManagedTensor *arg) {
delete[] arg->dl_tensor.shape;
delete[] arg->dl_tensor.strides;
delete static_cast<PaddleDLMTensor *>(arg->manager_ctx);
}
DLManagedTensor *toDLPack(const phi::DenseTensor &src) {
PaddleDLMTensor *pdDLMTensor(new PaddleDLMTensor);
pdDLMTensor->handle = const_cast<phi::DenseTensor &>(src);
pdDLMTensor->tensor.manager_ctx = pdDLMTensor;
pdDLMTensor->tensor.deleter = &deleter;
pdDLMTensor->tensor.dl_tensor.data = const_cast<void *>(src.data());
// init ndim
using DimType = decltype(pdDLMTensor->tensor.dl_tensor.ndim); // int
pdDLMTensor->tensor.dl_tensor.ndim = static_cast<DimType>(src.dims().size());
DimType ndim = pdDLMTensor->tensor.dl_tensor.ndim;
// init shape
auto shape = new int64_t[ndim];
for (DimType i = 0; i < ndim; ++i) {
shape[i] = src.dims()[i];
}
pdDLMTensor->tensor.dl_tensor.shape = shape;
// init stride
auto strides = new int64_t[ndim];
for (DimType i = 0; i < ndim; ++i) {
strides[i] = 1;
}
for (DimType i = ndim - 2; i >= 0; --i) {
strides[i] = shape[i + 1] * strides[i + 1];
}
pdDLMTensor->tensor.dl_tensor.strides = strides;
// init device, DLDevice type with device_type and device_id
auto place = src.place();
pdDLMTensor->tensor.dl_tensor.device =
paddle::platform::VisitPlace(place, internal::DLDeviceVisitor());
pdDLMTensor->tensor.dl_tensor.dtype = internal::GetDLDataTypeFromTypeIndex(
framework::TransToProtoVarType(src.dtype()));
pdDLMTensor->tensor.dl_tensor.byte_offset = 0;
return &(pdDLMTensor->tensor);
}
DLPackTensor::DLPackTensor(const phi::DenseTensor &tensor, LaneType lanes) {
// init data, data buffer
t_.data = const_cast<void *>(tensor.data());
......
......@@ -28,7 +28,7 @@ class DLPackTensor {
std::remove_reference<decltype(::DLTensor::shape[0])>::type; // int64_t
// lanes is only used in CPU to enable vectorization
explicit DLPackTensor(const Tensor& tensor, LaneType lanes = 1);
explicit DLPackTensor(const phi::DenseTensor& tensor, LaneType lanes = 1);
inline operator const ::DLTensor&() const { return t_; }
......@@ -44,5 +44,7 @@ class DLPackTensor {
ShapeType shape_[DDim::kMaxRank];
};
DLManagedTensor* toDLPack(const phi::DenseTensor& src);
} // namespace framework
} // namespace paddle
......@@ -472,23 +472,16 @@ void BindTensor(pybind11::module &m) { // NOLINT
print(t.shape()) # [5, 30]
)DOC")
.def("_to_dlpack",
[](framework::Tensor &self) {
DLPackTensor dlpack_tensor(self, 1);
DLManagedTensor *dmt = dlpack_tensor.ToDLManagedTensor();
auto capsule = py::capsule(
[](phi::DenseTensor &self) {
DLManagedTensor *dmt = framework::toDLPack(self);
auto capsule = pybind11::capsule(
static_cast<void *>(dmt), "dltensor", [](PyObject *ptr) {
if (ptr) {
auto dltensor = new DLManagedTensor;
try {
dltensor = reinterpret_cast<DLManagedTensor *>(
PyCapsule_GetPointer(ptr, "used_dltensor"));
return;
} catch (...) {
dltensor = reinterpret_cast<DLManagedTensor *>(
PyCapsule_GetPointer(ptr, "dltensor"));
}
dltensor->deleter(dltensor);
if (!PyCapsule_IsValid(ptr, "dltensor")) {
return;
}
DLManagedTensor *dmt = static_cast<DLManagedTensor *>(
PyCapsule_GetPointer(ptr, "dltensor"));
dmt->deleter(dmt);
});
return capsule;
})
......
......@@ -22,7 +22,6 @@ from paddle.fluid.framework import _test_eager_guard, in_dygraph_mode
class TestDLPack(unittest.TestCase):
def func_test_dlpack_dygraph(self):
paddle.disable_static()
tensor = paddle.to_tensor(np.array([1, 2, 3, 4]).astype('int'))
......@@ -30,11 +29,13 @@ class TestDLPack(unittest.TestCase):
out_from_dlpack = paddle.utils.dlpack.from_dlpack(dlpack)
if paddle.fluid.framework.in_dygraph_mode():
self.assertTrue(
isinstance(out_from_dlpack, paddle.fluid.core.eager.Tensor))
isinstance(out_from_dlpack, paddle.fluid.core.eager.Tensor)
)
else:
self.assertTrue(isinstance(out_from_dlpack, paddle.Tensor))
np.testing.assert_array_equal(np.array(out_from_dlpack),
np.array([1, 2, 3, 4]).astype('int'))
np.testing.assert_array_equal(
np.array(out_from_dlpack), np.array([1, 2, 3, 4]).astype('int')
)
def test_dlpack_dygraph(self):
with _test_eager_guard():
......@@ -58,26 +59,32 @@ class TestDLPack(unittest.TestCase):
def test_dlpack_static(self):
paddle.enable_static()
tensor = fluid.create_lod_tensor(
np.array([[1], [2], [3], [4]]).astype('int'), [[1, 3]],
fluid.CPUPlace())
np.array([[1], [2], [3], [4]]).astype('int'),
[[1, 3]],
fluid.CPUPlace(),
)
dlpack = paddle.utils.dlpack.to_dlpack(tensor)
out_from_dlpack = paddle.utils.dlpack.from_dlpack(dlpack)
self.assertTrue(isinstance(out_from_dlpack, fluid.core.Tensor))
np.testing.assert_array_equal(
np.array(out_from_dlpack),
np.array([[1], [2], [3], [4]]).astype('int'))
np.array([[1], [2], [3], [4]]).astype('int'),
)
# when build with cuda
if core.is_compiled_with_cuda():
gtensor = fluid.create_lod_tensor(
np.array([[1], [2], [3], [4]]).astype('int'), [[1, 3]],
fluid.CUDAPlace(0))
np.array([[1], [2], [3], [4]]).astype('int'),
[[1, 3]],
fluid.CUDAPlace(0),
)
gdlpack = paddle.utils.dlpack.to_dlpack(gtensor)
gout_from_dlpack = paddle.utils.dlpack.from_dlpack(gdlpack)
self.assertTrue(isinstance(gout_from_dlpack, fluid.core.Tensor))
np.testing.assert_array_equal(
np.array(gout_from_dlpack),
np.array([[1], [2], [3], [4]]).astype('int'))
np.array([[1], [2], [3], [4]]).astype('int'),
)
def func_test_dlpack_dtype_conversion(self):
paddle.disable_static()
......@@ -104,7 +111,8 @@ class TestDLPack(unittest.TestCase):
for dtype in complex_dtypes:
x = paddle.to_tensor(
[[1 + 6j, 2 + 5j, 3 + 4j], [4 + 3j, 5 + 2j, 6 + 1j]],
dtype=dtype)
dtype=dtype,
)
dlpack = paddle.utils.dlpack.to_dlpack(x)
o = paddle.utils.dlpack.from_dlpack(dlpack)
self.assertEqual(x.dtype, o.dtype)
......@@ -115,12 +123,18 @@ class TestDLPack(unittest.TestCase):
self.func_test_dlpack_dtype_conversion()
self.func_test_dlpack_dtype_conversion()
def test_to_dlpack_for_loop(self):
# See Paddle issue 50120
for i in range(10):
x = paddle.rand([3, 5])
dlpack = paddle.utils.dlpack.to_dlpack(x)
class TestRaiseError(unittest.TestCase):
class TestRaiseError(unittest.TestCase):
def func_test_from_dlpack_raise_type_error(self):
self.assertRaises(TypeError, paddle.utils.dlpack.from_dlpack,
np.zeros(5))
self.assertRaises(
TypeError, paddle.utils.dlpack.from_dlpack, np.zeros(5)
)
def test_from_dlpack_raise_type_error(self):
with _test_eager_guard():
......
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