def test_list_backends(self):
if not len(openvino_tensorflow.list_backends()):
raise AssertionError
input_mean = args.input_mean
if args.input_std:
input_std = args.input_std
if args.backend:
backend_name = args.backend
if model_file == "":
model = hub.load(
"https://tfhub.dev/google/imagenet/inception_v3/classification/4")
else:
model = tf.saved_model.load(model_file)
if not args.disable_ovtf:
#Print list of available backends
print('Available Backends:')
backends_list = ovtf.list_backends()
for backend in backends_list:
print(backend)
ovtf.set_backend(backend_name)
else:
ovtf.disable()
#Load the labels
cap = None
images = []
if label_file:
labels = load_labels(label_file)
input_mode = get_input_mode(input_file)
if input_mode == "video":
cap = cv2.VideoCapture(input_file)
elif input_mode == "camera":
def test_set_backend(self):
# store env variables
# when testing on backends like GPU the tests are run with OPENVINO_TF_BACKEND
# by storing and restoring the env_variables we run the tests independent of the backend set
# currently we store and restore only the OPENVINO_TF_BACKEND
env_var_map = self.store_env_variables(["OPENVINO_TF_BACKEND"])
self.unset_env_variable("OPENVINO_TF_BACKEND")
# test
openvino_tensorflow.enable()
backend_cpu = 'CPU'
backend_interpreter = 'INTERPRETER'
found_cpu = False
found_interpreter = False
# These will only print when running pytest with flag "-s"
supported_backends = openvino_tensorflow.list_backends()
print("Number of supported backends ", len(supported_backends))
print(" ****** Supported Backends ****** ")
for backend_name in supported_backends:
print(backend_name)
if backend_name == backend_cpu:
found_cpu = True
if backend_name == backend_interpreter:
found_interpreter = True
print(" ******************************** ")
if not (found_cpu and found_interpreter) == True:
raise AssertionError
# Create Graph
val = tf.compat.v1.placeholder(tf.float32)
out1 = tf.abs(val)
out2 = tf.abs(out1)
# set INTERPRETER backend
openvino_tensorflow.set_backend(backend_interpreter)
current_backend = openvino_tensorflow.get_backend()
if not current_backend == backend_interpreter:
raise AssertionError
# create new session to execute graph
# If you want to re-confirm which backend the graph was executed
# currently the only way is to enable OPENVINO_TF_VLOG_LEVEL=5
with tf.compat.v1.Session() as sess:
sess.run((out2, ), feed_dict={val: ((1.4, -0.5, -1))})
current_backend = openvino_tensorflow.get_backend()
if not current_backend == backend_interpreter:
raise AssertionError
# set CPU backend
openvino_tensorflow.set_backend(backend_cpu)
current_backend = openvino_tensorflow.get_backend()
if not current_backend == backend_cpu:
raise AssertionError
# create new session to execute graph
with tf.compat.v1.Session() as sess:
sess.run((out2, ), feed_dict={val: ((1.4, -0.5, -1))})
current_backend = openvino_tensorflow.get_backend()
if not current_backend == backend_cpu:
raise AssertionError
# restore env_variables
self.restore_env_variables(env_var_map)