def test_read_net_from_buffer():
ie = IECore()
with open(test_net_bin, 'rb') as f:
bin = f.read()
with open(model_path()[0], 'rb') as f:
xml = f.read()
net = ie.read_network(model=xml, weights=bin, init_from_buffer=True)
assert isinstance(net, IENetwork)
def test_net_from_buffer_valid():
ie = IECore()
with open(test_net_bin, 'rb') as f:
bin = f.read()
with open(model_path()[0], 'rb') as f:
xml = f.read()
net = ie.read_network(model=xml, weights=bin, init_from_buffer=True)
ref_net = ie.read_network(model=test_net_xml, weights=test_net_bin)
assert net.name == ref_net.name
assert net.batch_size == ref_net.batch_size
ii_net = net.input_info
ii_net2 = ref_net.input_info
o_net = net.outputs
o_net2 = ref_net.outputs
assert ii_net.keys() == ii_net2.keys()
assert o_net.keys() == o_net2.keys()
# SPDX-License-Identifier: Apache-2.0
import numpy as np
import os
import pytest
import threading
from datetime import datetime
import time
from openvino.inference_engine import ie_api as ie
from tests_compatibility.conftest import model_path, image_path, create_encoder
import ngraph as ng
from ngraph.impl import Function, Type
is_myriad = os.environ.get("TEST_DEVICE") == "MYRIAD"
test_net_xml, test_net_bin = model_path(is_myriad)
path_to_img = image_path()
def create_function_with_memory(input_shape, data_type):
input_data = ng.parameter(input_shape, name="input_data", dtype=data_type)
rv = ng.read_value(input_data, "var_id_667")
add = ng.add(rv, input_data, name="MemoryAdd")
node = ng.assign(add, "var_id_667")
res = ng.result(add, "res")
func = Function(results=[res], sinks=[node], parameters=[input_data], name="name")
caps = Function.to_capsule(func)
return caps
def read_image():
# Copyright (C) 2018-2022 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
import pytest
from openvino.inference_engine import IECore, DataPtr
from tests_compatibility.conftest import model_path, create_relu
import ngraph as ng
test_net_xml, test_net_bin = model_path()
def layer_out_data():
ie = IECore()
net = ie.read_network(model=test_net_xml, weights=test_net_bin)
return net.outputs['fc_out']
def test_name():
assert layer_out_data(
).name == 'fc_out', "Incorrect name for layer 'fc_out'"
def test_precision():
assert layer_out_data(
).precision == "FP32", "Incorrect precision for layer 'fc_out'"
def test_precision_setter():
ie = IECore()
net = ie.read_network(model=test_net_xml, weights=test_net_bin)
