131 lines
4.4 KiB
Python
131 lines
4.4 KiB
Python
import warnings
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import numpy
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from openvino.inference_engine import DataPtr, IECore
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from conftest import model_path
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test_net_xml, test_net_bin = model_path()
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def test_name():
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ie = IECore()
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net = ie.read_network(model=test_net_xml, weights=test_net_bin)
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assert net.layers['27'].name == "27"
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def test_type():
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ie = IECore()
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net = ie.read_network(model=test_net_xml, weights=test_net_bin)
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assert net.layers['27'].type == "Pooling"
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def test_precision_getter(recwarn):
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warnings.simplefilter("always")
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ie = IECore()
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net = ie.read_network(model=test_net_xml, weights=test_net_bin)
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assert net.layers['27'].precision == "FP32"
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assert len(recwarn) == 1
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assert recwarn.pop(DeprecationWarning)
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def test_precision_setter(recwarn):
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warnings.simplefilter("always")
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ie = IECore()
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net = ie.read_network(model=test_net_xml, weights=test_net_bin)
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net.layers['27'].precision = "I8"
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assert net.layers['27'].precision == "I8"
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assert len(recwarn) == 1
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assert recwarn.pop(DeprecationWarning)
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def test_affinuty_getter():
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ie = IECore()
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net = ie.read_network(model=test_net_xml, weights=test_net_bin)
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assert net.layers['27'].affinity == ""
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def test_affinity_setter():
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ie = IECore()
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net = ie.read_network(model=test_net_xml, weights=test_net_bin)
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net.layers['27'].affinity = "CPU"
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assert net.layers['27'].affinity == "CPU"
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def test_blobs():
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ie = IECore()
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net = ie.read_network(model=test_net_xml, weights=test_net_bin)
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assert isinstance(net.layers['19/Fused_Add_'].blobs["biases"], numpy.ndarray)
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assert isinstance(net.layers['19/Fused_Add_'].blobs["weights"], numpy.ndarray)
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assert net.layers['19/Fused_Add_'].blobs["biases"].size != 0
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assert net.layers['19/Fused_Add_'].blobs["weights"].size != 0
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def test_weights(recwarn):
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warnings.simplefilter("always")
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ie = IECore()
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net = ie.read_network(model=test_net_xml, weights=test_net_bin)
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assert isinstance(net.layers['19/Fused_Add_'].weights["biases"], numpy.ndarray)
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assert isinstance(net.layers['19/Fused_Add_'].weights["weights"], numpy.ndarray)
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assert net.layers['19/Fused_Add_'].weights["biases"].size != 0
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assert net.layers['19/Fused_Add_'].weights["weights"].size != 0
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assert len(recwarn) == 4
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assert recwarn.pop(DeprecationWarning)
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def test_params_getter():
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ie = IECore()
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net = ie.read_network(model=test_net_xml, weights=test_net_bin)
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assert net.layers['27'].params == {"kernel" : "2,2", "pads_begin" : "0,0",
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"pads_end" : "0,0", "rounding_type" : "floor",
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"strides" : "2,2", "pool-method" : "max",
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"originalLayersNames" : "27"}
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def test_params_setter():
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ie = IECore()
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net = ie.read_network(model=test_net_xml, weights=test_net_bin)
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params = net.layers['27'].params
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params.update({'PrimitivesPriority': 'cpu:ref_any'})
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net.layers['27'].params = params
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assert net.layers['27'].params == {"kernel" : "2,2", "pads_begin" : "0,0",
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"pads_end" : "0,0", "rounding_type" : "floor",
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"strides" : "2,2", "pool-method" : "max",
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"originalLayersNames" : "27", 'PrimitivesPriority': 'cpu:ref_any'}
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def test_layer_parents():
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ie = IECore()
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net = ie.read_network(model=test_net_xml, weights=test_net_bin)
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assert net.layers['27'].parents == ['26']
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def test_layer_children():
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ie = IECore()
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net = ie.read_network(model=test_net_xml, weights=test_net_bin)
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assert net.layers['27'].children == ['29']
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def test_layout(recwarn):
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warnings.simplefilter("always")
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ie = IECore()
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net = ie.read_network(model=test_net_xml, weights=test_net_bin)
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assert net.layers['27'].layout == 'NCHW'
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assert len(recwarn) == 1
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assert recwarn.pop(DeprecationWarning)
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def test_shape(recwarn):
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warnings.simplefilter("always")
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ie = IECore()
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net = ie.read_network(model=test_net_xml, weights=test_net_bin)
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assert net.layers['27'].shape == [1, 64, 9, 9]
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assert len(recwarn) == 1
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def test_out_data():
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ie = IECore()
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net = ie.read_network(model=test_net_xml, weights=test_net_bin)
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assert isinstance(net.layers['27'].out_data[0], DataPtr)
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def test_in_data():
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ie = IECore()
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net = ie.read_network(model=test_net_xml, weights=test_net_bin)
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assert isinstance(net.layers['27'].in_data[0], DataPtr)
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