1 files changed, 56 insertions, 0 deletions

diff --git a/lib/oeqa/runtime/miutils/tests/dldt_inference_engine_test.py b/lib/oeqa/runtime/miutils/tests/dldt_inference_engine_test.py
new file mode 100644
index 00000000..31bfb539
--- /dev/null
+++ b/lib/oeqa/runtime/miutils/tests/dldt_inference_engine_test.py
@@ -0,0 +1,56 @@
+import os
+script_path = os.path.dirname(os.path.realpath(__file__))
+files_path = os.path.join(script_path, '../../files/')
+
+class DldtInferenceEngineTest(object):
+    ie_input_files = {'ie_python_sample': 'classification_sample.py',
+                      'input': 'chicky_512.png',
+                      'input_download': 'https://raw.githubusercontent.com/opencv/opencv/master/samples/data/chicky_512.png',
+                      'model': 'squeezenet_v1.1.xml'}
+
+    def __init__(self, target, work_dir):
+        self.target = target
+        self.work_dir = work_dir
+
+    def setup(self):
+        self.target.run('mkdir -p %s' % self.work_dir)
+        self.target.copy_to(os.path.join(files_path, 'dldt-inference-engine', self.ie_input_files['ie_python_sample']),
+                            self.work_dir)
+        python_cmd = 'from openvino.inference_engine import IENetwork, IECore; ie = IECore(); print(ie.available_devices)'
+        __, output = self.target.run('python3 -c "%s"' % python_cmd)
+        self.available_devices = output
+
+    def tear_down(self):
+        self.target.run('rm -rf %s' % self.work_dir)
+
+    def test_check_if_openvino_device_available(self, device):
+        if device not in self.available_devices:
+            return False, self.available_devices
+        return True, self.available_devices
+
+    def test_can_download_input_file(self, proxy_port):
+        return self.target.run('cd %s; wget %s -e https_proxy=%s' %
+                               (self.work_dir,
+                                self.ie_input_files['input_download'],
+                                proxy_port))
+
+    def test_dldt_ie_classification_with_device(self, device, ir_files_dir):
+        return self.target.run('classification_sample_async -d %s -i %s -m %s' %
+                               (device,
+                                os.path.join(self.work_dir, self.ie_input_files['input']),
+                                os.path.join(ir_files_dir, self.ie_input_files['model'])))
+
+    def test_dldt_ie_classification_python_api_with_device(self, device, ir_files_dir, extension=''):
+        if extension:
+            return self.target.run('python3 %s -d %s -i %s -m %s -l %s' %
+                                   (os.path.join(self.work_dir, self.ie_input_files['ie_python_sample']),
+                                    device,
+                                    os.path.join(self.work_dir, self.ie_input_files['input']),
+                                    os.path.join(ir_files_dir, self.ie_input_files['model']),
+                                    extension))
+        else:
+            return self.target.run('python3 %s -d %s -i %s -m %s' %
+                                   (os.path.join(self.work_dir, self.ie_input_files['ie_python_sample']),
+                                    device,
+                                    os.path.join(self.work_dir, self.ie_input_files['input']),
+                                    os.path.join(ir_files_dir, self.ie_input_files['model'])))