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Fix API bug of Tensor cuda #34416

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Aug 4, 2021
Merged

Fix API bug of Tensor cuda #34416

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24 changes: 17 additions & 7 deletions paddle/fluid/pybind/imperative.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -1400,20 +1400,26 @@ void BindImperative(py::module *m_ptr) {

)DOC")
.def("cuda",
[](const std::shared_ptr<imperative::VarBase> &self, int device_id,
bool blocking) {
[](const std::shared_ptr<imperative::VarBase> &self,
py::handle &handle, bool blocking) {
#if !defined(PADDLE_WITH_CUDA) && !defined(PADDLE_WITH_HIP)
PADDLE_THROW(platform::errors::PermissionDenied(
"Cannot copy this Tensor to GPU in CPU version Paddle, "
"Please recompile or reinstall Paddle with CUDA support."));
#else
int device_count = platform::GetCUDADeviceCount();
if (device_id == -1) {
int device_id = 0;
if (handle == py::none()) {
if (platform::is_gpu_place(self->Place())) {
return self;
} else {
device_id = 0;
}
} else {
PyObject *py_obj = handle.ptr();
PADDLE_ENFORCE_EQ(
PyCheckInteger(py_obj), true,
platform::errors::InvalidArgument(
" 'device_id' must be a positive integer"));
device_id = py::cast<int>(handle);
}
PADDLE_ENFORCE_GE(
device_id, 0,
Expand All @@ -1437,26 +1443,30 @@ void BindImperative(py::module *m_ptr) {
}
#endif
},
py::arg("device_id") = -1, py::arg("blocking") = true, R"DOC(
py::arg("device_id") = py::none(), py::arg("blocking") = true, R"DOC(
Returns a copy of this Tensor in GPU memory.

If this Tensor is already in GPU memory and device_id is default,
then no copy is performed and the original Tensor is returned.

Args:
device_id(int, optional): The destination GPU device id. Defaults to the current device.
device_id(int, optional): The destination GPU device id. Default: None, means current device.
blocking(bool, optional): If False and the source is in pinned memory, the copy will be
asynchronous with respect to the host. Otherwise, the argument has no effect. Default: False.

Examples:
.. code-block:: python

# required: gpu
import paddle
x = paddle.to_tensor(1.0, place=paddle.CPUPlace())
print(x.place) # CPUPlace

y = x.cuda()
print(y.place) # CUDAPlace(0)

y = x.cuda(None)
print(y.place) # CUDAPlace(0)

y = x.cuda(1)
print(y.place) # CUDAPlace(1)
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7 changes: 7 additions & 0 deletions python/paddle/fluid/tests/unittests/test_var_base.py
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Original file line number Diff line number Diff line change
Expand Up @@ -72,10 +72,17 @@ def _test_place(place):
if core.is_compiled_with_cuda():
y = x.pin_memory()
self.assertEqual(y.place.__repr__(), "CUDAPinnedPlace")
y = x.cuda()
y = x.cuda(None)
self.assertEqual(y.place.__repr__(), "CUDAPlace(0)")
y = x.cuda(device_id=0)
self.assertEqual(y.place.__repr__(), "CUDAPlace(0)")
y = x.cuda(blocking=False)
self.assertEqual(y.place.__repr__(), "CUDAPlace(0)")
y = x.cuda(blocking=True)
self.assertEqual(y.place.__repr__(), "CUDAPlace(0)")
with self.assertRaises(ValueError):
y = x.cuda("test")

# support 'dtype' is core.VarType
x = paddle.rand((2, 2))
Expand Down