def load_ov_model(path, device="CPU"):
"""
Load an OpenVINO IR model from an .xml file.
Args:
path (str): The path to the OpenVINO .xml file.
device (str): The device to run inference, can be "CPU", "GPU" or "MULTI:CPU,GPU". Default to be "CPU".
Returns:
exec_net (OpenVINO executable net): executable OpenVINO model.
input_blob (str): Input name.
output_blob (str): Output name.
"""
try:
from openvino import runtime as ov
except ImportError:
raise ImportError(
"OpenVINO inference engine is not configured correctly.")
core = ov.Core()
if device.lower() == "cuda":
device = "GPU"
if device == "GPU":
core.set_property(
{"CACHE_DIR": os.path.dirname(os.path.abspath(path))})
model = core.read_model(model=path, weights=path.replace("xml", "bin"))
compiled_model = core.compile_model(model=model,
device_name=device.upper())
input_layer = compiled_model.inputs
output_layer = compiled_model.outputs
return compiled_model, input_layer, output_layer
# Copyright (C) 2018-2022 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
import numpy as np
#! [import]
import openvino.runtime as ov
#! [import]
#! [reshape_undefined]
core = ov.Core()
model = core.read_model("model.xml")
# Set one static dimension (= 1) and another dynamic dimension (= Dimension())
model.reshape([1, ov.Dimension()])
# The same as above
model.reshape([1, -1])
# The same as above
model.reshape("1, ?")
# Or set both dimensions as dynamic if both are going to be changed dynamically
model.reshape([ov.Dimension(), ov.Dimension()])
# The same as above
model.reshape([-1, -1])
# The same as above
model.reshape("?, ?")
#! [reshape_undefined]
