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Fix set_tensor with remote tensor in python #26724

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Sep 23, 2024
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20 changes: 19 additions & 1 deletion src/bindings/python/src/pyopenvino/core/infer_request.cpp
Original file line number Diff line number Diff line change
Expand Up @@ -10,6 +10,7 @@
#include <string>

#include "pyopenvino/core/common.hpp"
#include "pyopenvino/core/remote_tensor.hpp"
#include "pyopenvino/utils/utils.hpp"

namespace py = pybind11;
Expand Down Expand Up @@ -464,12 +465,29 @@ void regclass_InferRequest(py::module m) {
},
R"(
Gets output tensor of InferRequest.
:return: An output Tensor for the model.
If model has several outputs, an exception is thrown.
:rtype: openvino.runtime.Tensor
)");

cls.def(
"set_tensor",
[](InferRequestWrapper& self, const std::string& name, const RemoteTensorWrapper& tensor) {
self.m_request->set_tensor(name, tensor.tensor);
},
py::arg("name"),
py::arg("tensor"),
R"(
Sets input/output tensor of InferRequest.
:param name: Name of input/output tensor.
:type name: str
:param tensor: Tensor object. The element_type and shape of a tensor
must match the model's input/output element_type and shape.
:type tensor: openvino.runtime.Tensor
)");

cls.def(
"set_tensor",
[](InferRequestWrapper& self, const std::string& name, const ov::Tensor& tensor) {
Expand Down
2 changes: 1 addition & 1 deletion src/plugins/intel_gpu/src/graph/program_node.cpp
Original file line number Diff line number Diff line change
Expand Up @@ -528,7 +528,7 @@ bool program_node::is_fused_dep(size_t dep_idx) const {
std::set<size_t> program_node::get_lockable_input_ids() const {
const auto impl = get_selected_impl();
const bool has_cpu_impl = get_preferred_impl_type() == impl_types::cpu || (impl && impl->is_cpu());
if (has_cpu_impl) {
if (has_cpu_impl && !is_type<shape_of>()) {
std::set<size_t> dependencies_indexes;
for (size_t i = 0; i < get_dependencies().size(); i++)
dependencies_indexes.insert(i);
Expand Down
Original file line number Diff line number Diff line change
Expand Up @@ -3,6 +3,10 @@
//

#include "openvino/core/preprocess/pre_post_process.hpp"
#include "openvino/op/add.hpp"
#include "openvino/op/constant.hpp"
#include "openvino/op/parameter.hpp"
#include "openvino/op/shape_of.hpp"
#include "openvino/runtime/intel_gpu/ocl/ocl.hpp"
#include "openvino/runtime/intel_gpu/properties.hpp"
#include "openvino/runtime/remote_tensor.hpp"
Expand Down Expand Up @@ -2616,6 +2620,45 @@ ov::RemoteTensor create_tensor(ov::intel_gpu::ocl::ClContext context,
}
} // namespace

TEST(RemoteTensor, smoke_LockableHandling) {
#if defined(ANDROID)
GTEST_SKIP();
#endif

auto core = ov::Core();
auto remote_context = core.get_default_context(ov::test::utils::DEVICE_GPU);
auto gpu_context = remote_context.as<ov::intel_gpu::ocl::ClContext>();
auto type = ov::element::f32;
ov::Shape shape = {4};

auto remote_tensor = gpu_context.create_tensor(type, shape);

auto host_tensor_in = ov::Tensor(type, shape);
init_tensor(host_tensor_in);
remote_tensor.copy_from(host_tensor_in);

auto param_node = std::make_shared<ov::op::v0::Parameter>(type, ov::PartialShape{-1});
auto const_node = std::make_shared<ov::op::v0::Constant>(host_tensor_in);
auto add_node = std::make_shared<ov::op::v1::Add>(param_node, const_node);
auto shape_of_node = std::make_shared<ov::op::v3::ShapeOf>(param_node);
auto res1 = std::make_shared<ov::op::v0::Result>(add_node);
auto res2 = std::make_shared<ov::op::v0::Result>(shape_of_node);
auto model = std::make_shared<ov::Model>(ov::ResultVector{res1, res2}, ov::ParameterVector{param_node});

auto compiled_model = core.compile_model(model, ov::test::utils::DEVICE_GPU, ov::hint::inference_precision(ov::element::f32));
auto request = compiled_model.create_infer_request();
request.set_input_tensor(remote_tensor);

request.infer();
auto res = request.get_output_tensor(0);
auto host_res = ov::Tensor(type, shape);
res.copy_to(host_res);

for (size_t i = 0; i < ov::shape_size(host_tensor_in.get_shape()); i++) {
ASSERT_EQ(host_res.data<float>()[i], host_tensor_in.data<float>()[i] * 2);
}
}

TEST_P(RemoteTensor, smoke_CopyFrom) {
#if defined(ANDROID)
GTEST_SKIP();
Expand Down
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