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[Python API] removal of deprecated python api
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@akuporos
akuporos committed Jul 12, 2021
1 parent 811f4c5 commit 6e5f112
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Showing 7 changed files with 9 additions and 265 deletions.
117 changes: 7 additions & 110 deletions inference-engine/ie_bridges/python/src/openvino/inference_engine/ie_api.pyx
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Original file line number Diff line number Diff line change
Expand Up @@ -923,25 +923,6 @@ cdef class ExecutableNetwork:
inputs[in_.first.decode()] = input_info_ptr
return inputs

## \note The property is deprecated. Please use the input_info property
# to get the map of inputs
#
## A dictionary that maps input layer names to DataPtr objects
@property
def inputs(self):
warnings.warn("'inputs' property of ExecutableNetwork class is deprecated. "
"To access DataPtrs user need to use 'input_data' property "
"of InputInfoCPtr objects which can be accessed by 'input_info' property.",
DeprecationWarning)
cdef map[string, C.DataPtr] c_inputs = deref(self.impl).getInputs()
inputs = {}
cdef DataPtr data_ptr
for in_ in c_inputs:
data_ptr = DataPtr()
data_ptr._ptr = in_.second
data_ptr._ptr_plugin = deref(self.impl).getPluginLink()
inputs[in_.first.decode()] = data_ptr
return inputs

## A dictionary that maps output layer names to CDataPtr objects
@property
Expand Down Expand Up @@ -1268,26 +1249,6 @@ cdef class InferRequest:
"cpu_time": info.cpu_time, "execution_index": info.execution_index}
return profile

## A dictionary that maps input layer names to `numpy.ndarray`
# objects of proper shape with input data for the layer
@property
def inputs(self):
warnings.warn("'inputs' property of InferRequest is deprecated. Please instead use 'input_blobs' property.",
DeprecationWarning)
inputs = {}
for input in self._inputs_list:
inputs[input] = self._get_blob_buffer(input.encode()).to_numpy()
return inputs

## A dictionary that maps output layer names to `numpy.ndarray` objects with output data of the layer
@property
def outputs(self):
warnings.warn("'outputs' property of InferRequest is deprecated. Please instead use 'output_blobs' property.",
DeprecationWarning)
outputs = {}
for output in self._outputs_list:
outputs[output] = self._get_blob_buffer(output.encode()).to_numpy()
return deepcopy(outputs)

## Current infer request inference time in milliseconds
@property
Expand Down Expand Up @@ -1333,68 +1294,23 @@ cdef class InferRequest:
cdef class IENetwork:
## Class constructor
#
# \note Reading networks using IENetwork constructor is deprecated.
# Please, use IECore.read_network() method instead.
# @param model: A PyCapsule containing smart pointer to nGraph function.
#
# @param model: A `.xml` file of the IR or PyCapsule containing smart pointer to nGraph function.
# In case of passing a `.xml` file attribute value can be a string path or bytes with file content
# depending on `init_from_buffer` attribute value
# .
# @param weights: A `.bin` file of the IR. Depending on `init_from_buffer` value, can be a string path or
# bytes with file content.
# @param init_from_buffer: Defines the way of how `model` and `weights` attributes are interpreted.
# If `False`, attributes are interpreted as strings with paths to .xml and .bin files
# of IR. If `True`, they are interpreted as Python `bytes` object with .xml and .bin files content.
# Ignored in case of `IENetwork` object initialization from nGraph function.
# @return Instance of IENetwork class
#
# Usage example:\n
# Initializing `IENetwork` object from IR files:
# ```python
# net = IENetwork(model=path_to_xml_file, weights=path_to_bin_file)
# ```
#
# Initializing `IENetwork` object bytes with content of IR files:
# ```python
# with open(path_to_bin_file, 'rb') as f:
# bin = f.read()
# with open(path_to_xml_file, 'rb') as f:
# xml = f.read()
# net = IENetwork(model=xml, weights=bin, init_from_buffer=True)
# func = Function([relu], [param], 'test')
# caps = Function.to_capsule(func)
# net = IENetwork(caps)
# ```

def __cinit__(self, model: [str, bytes] = "", weights: [str, bytes] = "", init_from_buffer: bool = False):
def __cinit__(self, model = ""):
# Try to create Inference Engine network from capsule
if model.__class__.__name__ == 'PyCapsule' and weights == '' and init_from_buffer is False:
if model.__class__.__name__ == 'PyCapsule':
self.impl = C.IENetwork(model)
return
cdef char*xml_buffer = <char*> malloc(len(model)+1)
cdef uint8_t*bin_buffer = <uint8_t *> malloc(len(weights))
cdef string model_
cdef string weights_
if init_from_buffer:
warnings.warn("Reading network using constructor is deprecated. "
"Please, use IECore.read_network() method instead", DeprecationWarning)
memcpy(xml_buffer, <char*> model, len(model))
memcpy(bin_buffer, <uint8_t *> weights, len(weights))
xml_buffer[len(model)] = b'\0'
self.impl = C.IENetwork()
self.impl.load_from_buffer(xml_buffer, len(model), bin_buffer, len(weights))
else:
if model and weights:
warnings.warn("Reading network using constructor is deprecated. "
"Please, use IECore.read_network() method instead", DeprecationWarning)
if not os.path.isfile(model):
raise Exception(f"Path to the model {model} doesn't exist or it's a directory")
if not os.path.isfile(weights):
raise Exception(f"Path to the weights {weights} doesn't exist or it's a directory")
model_ = model.encode()
weights_ = weights.encode()
self.impl = C.IENetwork(model_, weights_)
else:
self.impl = C.IENetwork()
free(bin_buffer)
free(xml_buffer)
self.impl = C.IENetwork()

## Name of the loaded network
@property
Expand All @@ -1415,25 +1331,6 @@ cdef class IENetwork:
inputs[input.first.decode()] = input_info_ptr
return inputs

## \note The property is deprecated. Please use the input_info property
# to get the map of inputs
#
## A dictionary that maps input layer names to DataPtr objects
@property
def inputs(self):
warnings.warn("'inputs' property of IENetwork class is deprecated. "
"To access DataPtrs user need to use 'input_data' property "
"of InputInfoPtr objects which can be accessed by 'input_info' property.",
DeprecationWarning)
cdef map[string, C.DataPtr] c_inputs = self.impl.getInputs()
inputs = {}
cdef DataPtr data_ptr
for input in c_inputs:
data_ptr = DataPtr()
data_ptr._ptr_network = &self.impl
data_ptr._ptr = input.second
inputs[input.first.decode()] = data_ptr
return inputs

## A dictionary that maps output layer names to DataPtr objects
@property
Expand Down
36 changes: 0 additions & 36 deletions inference-engine/ie_bridges/python/src/openvino/inference_engine/ie_api_impl.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -200,14 +200,6 @@ InferenceEnginePython::IENetwork InferenceEnginePython::read_network(std::string
return InferenceEnginePython::IENetwork(std::make_shared<InferenceEngine::CNNNetwork>(net));
}

InferenceEnginePython::IENetwork::IENetwork(const std::string& model, const std::string& weights) {
InferenceEngine::Core reader;
auto net = reader.ReadNetwork(model, weights);
actual = std::make_shared<InferenceEngine::CNNNetwork>(net);
name = actual->getName();
batch_size = actual->getBatchSize();
}

InferenceEnginePython::IENetwork::IENetwork(const std::shared_ptr<InferenceEngine::CNNNetwork>& cnn_network): actual(cnn_network) {
if (actual == nullptr)
IE_THROW() << "IENetwork was not initialized.";
Expand All @@ -228,16 +220,6 @@ InferenceEnginePython::IENetwork::IENetwork(PyObject* network) {
batch_size = actual->getBatchSize();
}

void InferenceEnginePython::IENetwork::load_from_buffer(const char* xml, size_t xml_size, uint8_t* bin, size_t bin_size) {
InferenceEngine::Core reader;
InferenceEngine::TensorDesc tensorDesc(InferenceEngine::Precision::U8, {bin_size}, InferenceEngine::Layout::C);
auto weights_blob = InferenceEngine::make_shared_blob<uint8_t>(tensorDesc, bin, bin_size);
auto net = reader.ReadNetwork(std::string(xml, xml + xml_size), weights_blob);
name = net.getName();
actual = std::make_shared<InferenceEngine::CNNNetwork>(net);
batch_size = actual->getBatchSize();
}

void InferenceEnginePython::IENetwork::serialize(const std::string& path_to_xml, const std::string& path_to_bin) {
actual->serialize(path_to_xml, path_to_bin);
}
Expand Down Expand Up @@ -275,15 +257,6 @@ const std::map<std::string, InferenceEngine::InputInfo::Ptr> InferenceEnginePyth
return inputs;
}

const std::map<std::string, InferenceEngine::DataPtr> InferenceEnginePython::IENetwork::getInputs() {
std::map<std::string, InferenceEngine::DataPtr> inputs;
const InferenceEngine::InputsDataMap& inputsInfo = actual->getInputsInfo();
for (auto& in : inputsInfo) {
inputs[in.first] = in.second->getInputData();
}
return inputs;
}

const std::map<std::string, InferenceEngine::DataPtr> InferenceEnginePython::IENetwork::getOutputs() {
std::map<std::string, InferenceEngine::DataPtr> outputs;
const InferenceEngine::OutputsDataMap& outputsInfo = actual->getOutputsInfo();
Expand Down Expand Up @@ -338,15 +311,6 @@ void InferenceEnginePython::IEExecNetwork::exportNetwork(const std::string& mode
actual->Export(model_file);
}

std::map<std::string, InferenceEngine::DataPtr> InferenceEnginePython::IEExecNetwork::getInputs() {
InferenceEngine::ConstInputsDataMap inputsDataMap = actual->GetInputsInfo();
std::map<std::string, InferenceEngine::DataPtr> pyInputs;
for (const auto& item : inputsDataMap) {
pyInputs[item.first] = item.second->getInputData();
}
return pyInputs;
}

std::map<std::string, InferenceEngine::InputInfo::CPtr> InferenceEnginePython::IEExecNetwork::getInputsInfo() {
InferenceEngine::ConstInputsDataMap inputsDataMap = actual->GetInputsInfo();
std::map<std::string, InferenceEngine::InputInfo::CPtr> pyInputs;
Expand Down
7 changes: 0 additions & 7 deletions inference-engine/ie_bridges/python/src/openvino/inference_engine/ie_api_impl.hpp
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Original file line number Diff line number Diff line change
Expand Up @@ -60,18 +60,12 @@ struct IENetwork {

const std::map<std::string, InferenceEngine::InputInfo::Ptr> getInputsInfo();

const std::map<std::string, InferenceEngine::DataPtr> getInputs();

const std::map<std::string, InferenceEngine::DataPtr> getOutputs();

void reshape(const std::map<std::string, std::vector<size_t>>& input_shapes);

void serialize(const std::string& path_to_xml, const std::string& path_to_bin);

void load_from_buffer(const char* xml, size_t xml_size, uint8_t* bin, size_t bin_size);

IENetwork(const std::string& model, const std::string& weights);

IENetwork(const std::shared_ptr<InferenceEngine::CNNNetwork>& cnn_network);

IENetwork(PyObject* network);
Expand Down Expand Up @@ -146,7 +140,6 @@ struct IEExecNetwork {
void exportNetwork(const std::string& model_file);

std::map<std::string, InferenceEngine::InputInfo::CPtr> getInputsInfo();
std::map<std::string, InferenceEngine::DataPtr> getInputs();
std::map<std::string, InferenceEngine::CDataPtr> getOutputs();

PyObject* getMetric(const std::string& metric_name);
Expand Down
6 changes: 1 addition & 5 deletions inference-engine/ie_bridges/python/src/openvino/inference_engine/ie_api_impl_defs.pxd
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Original file line number Diff line number Diff line change
Expand Up @@ -14,7 +14,7 @@ cdef extern from "<inference_engine.hpp>" namespace "InferenceEngine":
ctypedef vector[size_t] SizeVector

cdef cppclass CExecutableNetwork "InferenceEngine::ExecutableNetwork"

cdef cppclass TBlob[T]:
ctypedef shared_ptr[TBlob[T]] Ptr

Expand Down Expand Up @@ -154,7 +154,6 @@ cdef extern from "ie_api_impl.hpp" namespace "InferenceEnginePython":
cdef cppclass IEExecNetwork:
vector[InferRequestWrap] infer_requests
IENetwork GetExecGraphInfo() except +
map[string, DataPtr] getInputs() except +
map[string, CDataPtr] getOutputs() except +
map[string, InputInfo.CPtr] getInputsInfo()
void exportNetwork(const string & model_file) except +
Expand All @@ -167,13 +166,11 @@ cdef extern from "ie_api_impl.hpp" namespace "InferenceEnginePython":
cdef cppclass IENetwork:
IENetwork() except +
IENetwork(object) except +
IENetwork(const string &, const string &) except +
string name
size_t batch_size
string precision
map[string, vector[size_t]] inputs
const map[string, InputInfo.Ptr] getInputsInfo() except +
const map[string, DataPtr] getInputs() except +
map[string, DataPtr] getOutputs() except +
void addOutput(string &, size_t) except +
void setAffinity(map[string, string] & types_affinity_map, map[string, string] & layers_affinity_map) except +
Expand All @@ -182,7 +179,6 @@ cdef extern from "ie_api_impl.hpp" namespace "InferenceEnginePython":
void setLayerParams(map[string, map[string, string]] params_map) except +
void serialize(const string& path_to_xml, const string& path_to_bin) except +
void reshape(map[string, vector[size_t]] input_shapes) except +
void load_from_buffer(const char*xml, size_t xml_size, uint8_t*bin, size_t bin_size) except +
object getFunction() except +
void convertToOldRepresentation() except +
string getOVNameForTensor(const string &) except +
Expand Down
18 changes: 0 additions & 18 deletions inference-engine/ie_bridges/python/tests/test_ExecutableNetwork.py
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Original file line number Diff line number Diff line change
Expand Up @@ -82,24 +82,6 @@ def test_input_info(device):
del ie_core


def test_inputs_deprecated(device):
ie_core = ie.IECore()
net = ie_core.read_network(model=test_net_xml, weights=test_net_bin)
exec_net = ie_core.load_network(net, device, num_requests=5)
with warnings.catch_warnings(record=True) as w:
assert len(exec_net.inputs) == 1
assert "data" in exec_net.inputs
assert isinstance(exec_net.inputs['data'], ie.DataPtr)
assert len(w) == 3
for i in range (len(w)):
assert "'inputs' property of ExecutableNetwork class is deprecated. " \
"To access DataPtrs user need to use 'input_data' property " \
"of InputInfoCPtr objects which " \
"can be accessed by 'input_info' property." in str(w[i].message)
del exec_net
del ie_core


def test_outputs(device):
ie_core = ie.IECore()
net = ie_core.read_network(model=test_net_xml, weights=test_net_bin)
Expand Down
64 changes: 1 addition & 63 deletions inference-engine/ie_bridges/python/tests/test_IENetwork.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -12,60 +12,12 @@
test_net_xml, test_net_bin = model_path()


def test_create_ie_network_deprecated():
with warnings.catch_warnings(record=True) as w:
net = IENetwork(model=test_net_xml, weights=test_net_bin)
assert isinstance(net, IENetwork)
assert len(w) == 1
assert issubclass(w[-1].category, DeprecationWarning)
assert "Reading network using constructor is deprecated. " \
"Please, use IECore.read_network() method instead" in str(w[0].message)


def test_incorrect_xml_deprecated():
with warnings.catch_warnings(record=True) as w:
with pytest.raises(Exception) as e:
IENetwork(model="./model.xml", weights=test_net_bin)
assert "Path to the model ./model.xml doesn't exist or it's a directory" in str(e.value)
assert len(w) == 1
assert issubclass(w[-1].category, DeprecationWarning)
assert "Reading network using constructor is deprecated. " \
"Please, use IECore.read_network() method instead" in str(w[0].message)


def test_incorrect_bin_deprecated():
with warnings.catch_warnings(record=True) as w:
with pytest.raises(Exception) as e:
IENetwork(model=test_net_xml, weights="./model.bin")
assert "Path to the weights ./model.bin doesn't exist or it's a directory" in str(e.value)
assert len(w) == 1
assert issubclass(w[-1].category, DeprecationWarning)
assert "Reading network using constructor is deprecated. " \
"Please, use IECore.read_network() method instead" in str(w[0].message)


def test_name():
ie = IECore()
net = ie.read_network(model=test_net_xml, weights=test_net_bin)
assert net.name == "test_model"


def test_inputs_deprecated():
ie = IECore()
net = ie.read_network(model=test_net_xml, weights=test_net_bin)
with warnings.catch_warnings(record=True) as w:
inp = net.inputs
assert isinstance(inp['data'], DataPtr)
assert inp['data'].layout == "NCHW"
assert inp['data'].precision == "FP32"
assert inp['data'].shape == [1, 3, 32, 32]
assert len(w) == 1
assert "'inputs' property of IENetwork class is deprecated. " \
"To access DataPtrs user need to use 'input_data' property " \
"of InputInfoPtr objects which " \
"can be accessed by 'input_info' property." in str(w[-1].message)


def test_input_info():
ie = IECore()
net = ie.read_network(model=test_net_xml, weights=test_net_bin)
Expand Down Expand Up @@ -208,21 +160,7 @@ def test_reshape():
net.reshape({"data": (2, 3, 32, 32)})


def test_read_net_from_buffer_deprecated():
with warnings.catch_warnings(record=True) as w:
with open(test_net_bin, 'rb') as f:
bin = f.read()
with open(test_net_xml, 'rb') as f:
xml = f.read()
net = IENetwork(model=xml, weights=bin, init_from_buffer=True)
assert isinstance(net, IENetwork)
assert len(w) == 1
assert issubclass(w[-1].category, DeprecationWarning)
assert "Reading network using constructor is deprecated. " \
"Please, use IECore.read_network() method instead" in str(w[0].message)


def test_net_from_buffer_valid_deprecated():
def test_net_from_buffer_valid():
ie = IECore()
with open(test_net_bin, 'rb') as f:
bin = f.read()
Expand Down
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