def test_infer_dynamic_network_with_set_blob_twice():
from conftest import create_ngraph_function
import ngraph as ng
shape, p_shape = [1, 4, 20, 20], [(0, 5), 4, 20, 20]
ref_shape1, ref_shape2 = [2, 4, 20, 20], [3, 4, 20, 20]
function = create_ngraph_function(shape)
net = ng.function_to_cnn(function)
net.reshape({"data": p_shape})
ie_core = ie.IECore()
ie_core.register_plugin("templatePlugin", "TEMPLATE")
exec_net = ie_core.load_network(net, "TEMPLATE")
request = exec_net.requests[0]
td = request.input_blobs['data'].tensor_desc
td.dims = ref_shape1
blob = ie.Blob(td)
request.set_blob("data", blob)
request.infer({"data": np.ones(ref_shape1)})
assert exec_net.requests[0].input_blobs[
"data"].tensor_desc.dims == ref_shape1
assert request.output_blobs['out'].tensor_desc.dims == ref_shape1
td = request.input_blobs['data'].tensor_desc
td.dims = ref_shape2
blob = ie.Blob(td)
request.set_blob("data", blob)
request.infer({"data": np.ones(ref_shape2)})
assert exec_net.requests[0].input_blobs[
"data"].tensor_desc.dims == ref_shape2
assert request.output_blobs['out'].tensor_desc.dims == ref_shape2
def test_get_IENetwork_from_nGraph():
func = create_ngraph_function([1, 3, 22, 22])
caps = Function.to_capsule(func)
cnnNetwork = IENetwork(caps)
assert cnnNetwork != None
assert ng.function_from_cnn(cnnNetwork) != None
func2 = ng.function_from_cnn(cnnNetwork)
assert func2 != None
def test_incorrect_reshape(device):
from conftest import create_ngraph_function
import ngraph as ng
function = create_ngraph_function([1, 3, 22, 22])
net = ng.function_to_cnn(function)
with pytest.raises(ValueError) as e:
net.reshape({"data": [(2, 4, 6), 3, 22, 22]})
assert "Incorrect PartialShape dimension definition '(2, 4, 6)' " \
"in shape '[(2, 4, 6), 3, 22, 22]', expected one or two values for a dimension! " in str(e.value)
def test_is_dynamic():
from conftest import create_ngraph_function
import ngraph as ng
function = create_ngraph_function([-1, 3, 20, 20])
net = ng.function_to_cnn(function)
ie = IECore()
ie.register_plugin("templatePlugin", "TEMPLATE")
exec_net = ie.load_network(net, "TEMPLATE")
assert exec_net.outputs["out"].is_dynamic
p_shape = ng.partial_shape_from_data(exec_net.outputs["out"])
assert isinstance(p_shape, ng.impl.PartialShape)
with pytest.raises(RuntimeError) as e:
exec_net.outputs["out"].shape
assert "Cannot return dims for Data with dynamic shapes!" in str(e.value)
def test_set_blob_with_incorrect_name():
from conftest import create_ngraph_function
import ngraph as ng
function = create_ngraph_function([4, 4, 20, 20])
net = ng.function_to_cnn(function)
ie_core = ie.IECore()
ie_core.register_plugin("templatePlugin", "TEMPLATE")
exec_net = ie_core.load_network(net, "TEMPLATE")
tensor_desc = exec_net.requests[0].input_blobs["data"].tensor_desc
tensor_desc.dims = [4, 4, 20, 20]
blob = ie.Blob(tensor_desc)
with pytest.raises(RuntimeError) as e:
exec_net.requests[0].set_blob("incorrect_name", blob)
assert f"Failed to find input or output with name: 'incorrect_name'" in str(e.value)
def test_async_infer_dynamic_network_3_requests(shapes):
from conftest import create_ngraph_function
import ngraph as ng
function = create_ngraph_function([3, 4, 20, 20])
net = ng.function_to_cnn(function)
net.reshape({"data": [3, (2, 10), 20, 20]})
ie_core = ie.IECore()
ie_core.register_plugin("templatePlugin", "TEMPLATE")
exec_net = ie_core.load_network(net, "TEMPLATE", num_requests=3)
for i, request in enumerate(exec_net.requests):
request.async_infer({"data": np.ones(shapes[i])})
for i, request in enumerate(exec_net.requests):
status = request.wait(ie.WaitMode.RESULT_READY)
assert status == ie.StatusCode.OK
assert request.output_blobs['out'].tensor_desc.dims == shapes[i]
def test_create_two_exec_net():
from conftest import create_ngraph_function
import ngraph as ng
function = create_ngraph_function([
ng.Dimension(0, 5),
ng.Dimension(4),
ng.Dimension(20),
ng.Dimension(20)
])
net = ng.function_to_cnn(function)
ie_core = IECore()
ie_core.register_plugin("templatePlugin", "TEMPLATE")
exec_net1 = ie_core.load_network(net, "TEMPLATE", num_requests=2)
assert ng.function_from_cnn(net) != None
exec_net2 = ie_core.load_network(net, "TEMPLATE", num_requests=2)
assert ng.function_from_cnn(net) != None
def test_set_blob_after_async_infer():
from conftest import create_ngraph_function
import ngraph as ng
function = create_ngraph_function([ng.Dimension(0,5), ng.Dimension(4), ng.Dimension(20), ng.Dimension(20)])
net = ng.function_to_cnn(function)
ie_core = ie.IECore()
ie_core.register_plugin("templatePlugin", "TEMPLATE")
exec_net = ie_core.load_network(net, "TEMPLATE")
request = exec_net.requests[0]
tensor_desc = request.input_blobs['data'].tensor_desc
tensor_desc.dims = [2, 4, 20, 20]
blob = ie.Blob(tensor_desc)
request.async_infer({"data": np.ones([4, 4, 20, 20])})
with pytest.raises(RuntimeError) as e:
request.set_blob("data", blob)
assert "REQUEST_BUSY" in str(e.value)
def test_infer_dynamic_network_without_set_shape(shape, p_shape, ref_shape):
from conftest import create_ngraph_function
import ngraph as ng
function = create_ngraph_function(shape)
net = ng.function_to_cnn(function)
net.reshape({"data": p_shape})
ie_core = ie.IECore()
ie_core.register_plugin("templatePlugin", "TEMPLATE")
exec_net = ie_core.load_network(net, "TEMPLATE")
exec_net.infer({"data": np.ones(ref_shape)})
assert exec_net.requests[0].input_blobs["data"].tensor_desc.dims == ref_shape
request = exec_net.requests[0]
request.async_infer({"data": np.ones(ref_shape)})
status = request.wait(ie.WaitMode.RESULT_READY)
assert status == ie.StatusCode.OK
assert request.output_blobs['out'].tensor_desc.dims == ref_shape
def test_set_blob_with_incorrect_size():
from conftest import create_ngraph_function
import ngraph as ng
function = create_ngraph_function([4, 4, 20, 20])
net = ng.function_to_cnn(function)
ie_core = ie.IECore()
ie_core.register_plugin("templatePlugin", "TEMPLATE")
exec_net = ie_core.load_network(net, "TEMPLATE")
tensor_desc = exec_net.requests[0].input_blobs["data"].tensor_desc
tensor_desc.dims = [tensor_desc.dims[0] * 2, 4, 20, 20]
blob = ie.Blob(tensor_desc)
with pytest.raises(RuntimeError) as e:
exec_net.requests[0].set_blob("data", blob)
assert f"Input blob size is not equal network input size" in str(e.value)
with pytest.raises(RuntimeError) as e:
exec_net.requests[0].set_blob("out", blob)
assert f"Output blob size is not equal network output size" in str(e.value)
def test_reshape_with_partial_shape(device, shape, p_shape):
from conftest import create_ngraph_function
import ngraph as ng
function = create_ngraph_function(shape)
net = ng.function_to_cnn(function)
net.reshape({"data": p_shape})
changedFunction = ng.function_from_cnn(net)
p_shape = ng.impl.PartialShape(p_shape)
assert changedFunction.get_parameters()[0].get_partial_shape().is_dynamic
assert changedFunction.get_results()[0].get_output_partial_shape(
0).is_dynamic
assert function.get_parameters()[0].get_partial_shape().is_dynamic
assert function.get_results()[0].get_output_partial_shape(0).is_dynamic
assert changedFunction.get_parameters()[0].get_partial_shape() == p_shape
assert changedFunction.get_results()[0].get_output_partial_shape(
0) == p_shape
assert function.get_parameters()[0].get_partial_shape() == p_shape
assert function.get_results()[0].get_output_partial_shape(0) == p_shape