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fix gpu build error

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cblas_new
qijun 8 years ago
parent 2ddef137fe
commit 358261f0bd
5 changed files with 47 additions and 33 deletions
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22
paddle/pybind/pybind.cc
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@ -64,23 +64,25 @@ PYBIND11_PLUGIN(core) {
self.Resize(pd::make_ddim(dim));
})
.def("alloc_float",
[](pd::Tensor& self, paddle::platform::Place& place) {
[](pd::Tensor& self, paddle::platform::GPUPlace& place) {
self.mutable_data<float>(place);
})
.def("alloc_float",
[](pd::Tensor& self) {
self.mutable_data<float>(paddle::platform::CPUPlace());
[](pd::Tensor& self, paddle::platform::CPUPlace& place) {
self.mutable_data<float>(place);
})
.def("alloc_int",
[](pd::Tensor& self, paddle::platform::Place& place) {
[](pd::Tensor& self, paddle::platform::CPUPlace& place) {
self.mutable_data<int>(place);
})
.def("alloc_int",
[](pd::Tensor& self) {
self.mutable_data<int>(paddle::platform::CPUPlace());
[](pd::Tensor& self, paddle::platform::GPUPlace& place) {
self.mutable_data<int>(place);
})
.def("set", paddle::pybind::PyTensorSetFromArray<float>)
.def("set", paddle::pybind::PyTensorSetFromArray<int>)
.def("set", paddle::pybind::PyCPUTensorSetFromArray<float>)
.def("set", paddle::pybind::PyCUDATensorSetFromArray<float>)
.def("set", paddle::pybind::PyCPUTensorSetFromArray<int>)
.def("set", paddle::pybind::PyCUDATensorSetFromArray<int>)
.def("shape",
[](pd::Tensor& self) { return pd::vectorize(self.dims()); });
@ -144,9 +146,9 @@ All parameter, weight, gradient are variables in Paddle.
})
#endif
; // NOLINT
py::class_<paddle::platform::Place>(m, "GPUPlace").def(py::init<int>());
py::class_<paddle::platform::GPUPlace>(m, "GPUPlace").def(py::init<int>());
py::class_<paddle::platform::Place>(m, "CPUPlace").def(py::init<>());
py::class_<paddle::platform::CPUPlace>(m, "CPUPlace").def(py::init<>());
py::class_<pd::OperatorBase, std::shared_ptr<pd::OperatorBase>> operator_base(
m, "Operator");

37
paddle/pybind/tensor_bind.h
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@ -61,7 +61,7 @@ struct CastToPyBufferImpl<true, I, ARGS...> {
framework::Tensor dst_tensor;
if (paddle::platform::is_gpu_place(tensor.holder_->place())) {
dst_tensor.CopyFrom<CUR_TYPE>(tensor, platform::CPUPlace());
} else if (paddle::platform::is_gpu_place(tensor.holder_->place())) {
} else if (paddle::platform::is_cpu_place(tensor.holder_->place())) {
dst_tensor = tensor;
}
return py::buffer_info(
@ -84,9 +84,10 @@ inline py::buffer_info CastToPyBuffer(framework::Tensor &tensor) {
}
template <typename T>
void PyTensorSetFromArray(
void PyCPUTensorSetFromArray(
framework::Tensor &self,
py::array_t<T, py::array::c_style | py::array::forcecast> array) {
py::array_t<T, py::array::c_style | py::array::forcecast> array,
paddle::platform::CPUPlace &place) {
std::vector<int> dims;
dims.reserve(array.ndim());
for (size_t i = 0; i < array.ndim(); ++i) {
@ -94,18 +95,26 @@ void PyTensorSetFromArray(
}
self.Resize(framework::make_ddim(dims));
auto *dst = self.mutable_data<T>(self.place());
if (paddle::platform::is_cpu_place(self.place())) {
std::memcpy(dst, array.data(), sizeof(T) * array.size());
} else if (paddle::platform::is_gpu_place(self.place())) {
#ifdef PADDLE_ONLY_CPU
PADDLE_THROW("'GPUPlace' is not supported in CPU only device.");
#else
platform::GpuMemcpySync(
dst, array.data(), sizeof(T) * array.size(), cudaMemcpyHostToDevice);
#endif
auto *dst = self.mutable_data<T>(place);
std::memcpy(dst, array.data(), sizeof(T) * array.size());
}
template <typename T>
void PyCUDATensorSetFromArray(
framework::Tensor &self,
py::array_t<T, py::array::c_style | py::array::forcecast> array,
paddle::platform::GPUPlace &place) {
std::vector<int> dims;
dims.reserve(array.ndim());
for (size_t i = 0; i < array.ndim(); ++i) {
dims.push_back((int)array.shape()[i]);
}
self.Resize(framework::make_ddim(dims));
auto *dst = self.mutable_data<T>(place);
std::memcpy(dst, array.data(), sizeof(T) * array.size());
paddle::platform::GpuMemcpySync(
dst, array.data(), sizeof(T) * array.size(), cudaMemcpyHostToDevice);
}
} // namespace pybind

3
python/paddle/v2/framework/tests/op_test_util.py
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@ -25,6 +25,7 @@ class OpTestMeta(type):
self.assertIsNotNone(func)
scope = core.Scope(None)
place = core.CPUPlace()
kwargs = dict()
for in_name in func.all_input_args:
@ -33,7 +34,7 @@ class OpTestMeta(type):
var = scope.create_var(in_name).get_tensor()
arr = getattr(self, in_name)
var.set_dims(arr.shape)
var.set(arr)
var.set(arr, place)
else:
kwargs[in_name] = "@EMPTY@"

7
python/paddle/v2/framework/tests/test_fc_op.py
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@ -7,17 +7,18 @@ import paddle.v2.framework.create_op_creation_methods as creation
class TestFc(unittest.TestCase):
def test_fc(self):
scope = core.Scope(None)
place = core.CPUPlace()
x = scope.create_var("X")
x_tensor = x.get_tensor()
x_tensor.set_dims([1000, 784])
x_tensor.alloc_float()
x_tensor.alloc_float(place)
w = scope.create_var("W")
w_tensor = w.get_tensor()
w_tensor.set_dims([784, 100])
w_tensor.alloc_float()
w_tensor.alloc_float(place)
w_tensor.set(numpy.random.random((784, 100)).astype("float32"))
w_tensor.set(numpy.random.random((784, 100)).astype("float32"), place)
# Set a real numpy array here.
# x_tensor.set(numpy.array([]))

11
python/paddle/v2/framework/tests/test_tensor.py
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@ -7,16 +7,16 @@ class TestScope(unittest.TestCase):
def test_int_tensor(self):
scope = core.Scope(None)
var = scope.create_var("test_tensor")
place = core.CPUPlace()
tensor = var.get_tensor()
tensor.set_dims([1000, 784])
tensor.alloc_int()
tensor.alloc_int(place)
tensor_array = numpy.array(tensor)
self.assertEqual((1000, 784), tensor_array.shape)
tensor_array[3, 9] = 1
tensor_array[19, 11] = 2
tensor.set(tensor_array)
tensor.set(tensor_array, place)
tensor_array_2 = numpy.array(tensor)
self.assertEqual(1.0, tensor_array_2[3, 9])
@ -25,16 +25,17 @@ class TestScope(unittest.TestCase):
def test_float_tensor(self):
scope = core.Scope(None)
var = scope.create_var("test_tensor")
place = core.CPUPlace()
tensor = var.get_tensor()
tensor.set_dims([1000, 784])
tensor.alloc_float()
tensor.alloc_float(place)
tensor_array = numpy.array(tensor)
self.assertEqual((1000, 784), tensor_array.shape)
tensor_array[3, 9] = 1.0
tensor_array[19, 11] = 2.0
tensor.set(tensor_array)
tensor.set(tensor_array, place)
tensor_array_2 = numpy.array(tensor)
self.assertAlmostEqual(1.0, tensor_array_2[3, 9])

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