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add read_model from buffer (#8593)

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* add read_model from buffer

* add new line

* remove bad quotes

* rename functin args

* fix read_model from buffer, add tests with empty weights

* remove redundant include

* add blank line

* fix indentation

Co-authored-by: Anastasia Kuporosova <anastasia.kuporosova@intel.com>
This commit is contained in:
Bartek Szmelczynski 2021-11-17 14:45:01 +01:00 committed by GitHub
parent c81e1aef05
commit 099d451d35
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GPG Key ID: 4AEE18F83AFDEB23
3 changed files with 126 additions and 21 deletions
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20
runtime/bindings/python/src/pyopenvino/core/core.cpp
View File

@ -50,6 +50,26 @@ void regclass_Core(py::module m) {
cls.def("get_versions", &ov::runtime::Core::get_versions);
cls.def(
"read_model",
[](ov::runtime::Core& self, py::bytes model, py::bytes weights) {
// works on view in order to omit copying bytes into string
py::buffer_info info(py::buffer(weights).request());
size_t bin_size = static_cast<size_t>(info.size);
// if weights are not empty
if (bin_size) {
const uint8_t* bin = reinterpret_cast<const uint8_t*>(info.ptr);
ov::runtime::Tensor tensor(ov::element::Type_t::u8, {bin_size});
std::memcpy(tensor.data(), bin, bin_size);
return self.read_model(model, tensor);
}
// create empty tensor of type u8
ov::runtime::Tensor tensor(ov::element::Type_t::u8, {});
return self.read_model(model, tensor);
},
py::arg("model"),
py::arg("weights") = py::bytes());
cls.def("read_model",
(std::shared_ptr<ov::Function>(ov::runtime::Core::*)(const std::string&, const std::string&) const) &
ov::runtime::Core::read_model,

100
runtime/bindings/python/tests/test_inference_engine/test_core.py
View File

@ -105,18 +105,16 @@ def test_read_model_from_onnx_as_path():
assert isinstance(func, Function)
# @pytest.mark.xfail("68212")
# def test_read_net_from_buffer():
# core = Core()
# with open(test_net_bin, "rb") as f:
# bin = f.read()
# with open(model_path()[0], "rb") as f:
# xml = f.read()
# func = core.read_model(model=xml, weights=bin)
# assert isinstance(func, IENetwork)
def test_read_net_from_buffer():
core = Core()
with open(test_net_bin, "rb") as f:
bin = f.read()
with open(model_path()[0], "rb") as f:
xml = f.read()
func = core.read_model(model=xml, weights=bin)
assert isinstance(func, Function)
@pytest.mark.xfail("68212")
def test_net_from_buffer_valid():
core = Core()
with open(test_net_bin, "rb") as f:
@ -125,14 +123,9 @@ def test_net_from_buffer_valid():
xml = f.read()
func = core.read_model(model=xml, weights=bin)
ref_func = core.read_model(model=test_net_xml, weights=test_net_bin)
assert func.name == func.name
assert func.batch_size == ref_func.batch_size
ii_func = func.input_info
ii_func2 = ref_func.input_info
o_func = func.outputs
o_func2 = ref_func.outputs
assert ii_func.keys() == ii_func2.keys()
assert o_func.keys() == o_func2.keys()
assert func.get_parameters() == ref_func.get_parameters()
assert func.get_results() == ref_func.get_results()
assert func.get_ordered_ops() == ref_func.get_ordered_ops()
def test_get_version(device):
@ -252,7 +245,7 @@ def test_unregister_plugin(device):
assert f"Device with '{device}' name is not registered in the InferenceEngine" in str(e.value)
@pytest.mark.xfail("68212")
@pytest.mark.skip(reason="dlSym cannot locate method 'create_extensions': libtemplate_extension.so")
@pytest.mark.template_extension
def test_add_extension(device):
model = bytes(b"""<net name="Network" version="10">
@ -306,9 +299,9 @@ def test_add_extension(device):
core = Core()
if platform == "win32":
core.add_extension(extension_path="template_extension.dll")
core.add_extension(library_path="template_extension.dll")
else:
core.add_extension(extension_path="libtemplate_extension.so")
core.add_extension(library_path="libtemplate_extension.so")
func = core.read_model(model=model, init_from_buffer=True)
assert isinstance(func, Function)
@ -323,3 +316,68 @@ def test_add_extension(device):
# computed = exec_network.infer_new_request(inputs={input_blob : input_values})
# output_blob = next(iter(network.outputs))
# assert np.allclose(expected, computed[output_blob], atol=1e-2, rtol=1e-2)
def test_read_model_from_buffer_no_weights(device):
model = bytes(b"""<net name="add_model" version="10">
<layers>
<layer id="0" name="x" type="Parameter" version="opset1">
<data element_type="f32" shape="3,4,5"/>
<output>
<port id="0" precision="FP32">
<dim>3</dim>
<dim>4</dim>
<dim>5</dim>
</port>
</output>
</layer>
<layer id="1" name="y" type="Parameter" version="opset1">
<data element_type="f32" shape="3,4,5"/>
<output>
<port id="0" precision="FP32">
<dim>3</dim>
<dim>4</dim>
<dim>5</dim>
</port>
</output>
</layer>
<layer id="2" name="sum" type="Add" version="opset1">
<input>
<port id="0">
<dim>3</dim>
<dim>4</dim>
<dim>5</dim>
</port>
<port id="1">
<dim>3</dim>
<dim>4</dim>
<dim>5</dim>
</port>
</input>
<output>
<port id="2" precision="FP32">
<dim>3</dim>
<dim>4</dim>
<dim>5</dim>
</port>
</output>
</layer>
<layer id="3" name="sum/sink_port_0" type="Result" version="opset1">
<input>
<port id="0">
<dim>3</dim>
<dim>4</dim>
<dim>5</dim>
</port>
</input>
</layer>
</layers>
<edges>
<edge from-layer="0" from-port="0" to-layer="2" to-port="0"/>
<edge from-layer="1" from-port="0" to-layer="2" to-port="1"/>
<edge from-layer="2" from-port="2" to-layer="3" to-port="0"/>
</edges>
</net>""")
core = Core()
func = core.read_model(model=model)
assert isinstance(func, Function)

27
runtime/bindings/python/tests/test_inference_engine/test_executable_network.py
View File

@ -280,3 +280,30 @@ def test_infer_tensor_wrong_input_data(device):
with pytest.raises(TypeError) as e:
exec_net.infer_new_request({0.: tensor})
assert "Incompatible key type for tensor named: 0." in str(e.value)
def test_infer_numpy_model_from_buffer(device):
core = Core()
with open(test_net_bin, "rb") as f:
bin = f.read()
with open(test_net_xml, "rb") as f:
xml = f.read()
func = core.read_model(model=xml, weights=bin)
img = read_image()
exec_net = core.compile_model(func, device)
res = exec_net.infer_new_request({"data": img})
assert np.argmax(res) == 2
def test_infer_tensor_model_from_buffer(device):
core = Core()
with open(test_net_bin, "rb") as f:
bin = f.read()
with open(test_net_xml, "rb") as f:
xml = f.read()
func = core.read_model(model=xml, weights=bin)
img = read_image()
tensor = Tensor(img)
exec_net = core.compile_model(func, device)
res = exec_net.infer_new_request({"data": tensor})
assert np.argmax(res) == 2