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)