87 lines
2.5 KiB
Python
87 lines
2.5 KiB
Python
# Copyright (C) 2018-2023 Intel Corporation
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# SPDX-License-Identifier: Apache-2.0
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#
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import tempfile
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import numpy as np
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from sys import platform
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import openvino as ov
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import openvino.runtime.opset12 as ops
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import ngraph as ng
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from ngraph.impl import Function
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import openvino.inference_engine as ie
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def get_dynamic_model():
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param = ops.parameter(ov.PartialShape([-1, -1]), name="input")
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return ov.Model(ops.relu(param), [param])
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def get_model(input_shape = None, input_dtype=np.float32) -> ov.Model:
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if input_shape is None:
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input_shape = [1, 3, 32, 32]
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param = ops.parameter(input_shape, input_dtype, name="input")
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relu = ops.relu(param, name="relu")
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relu.output(0).get_tensor().set_names({"result"})
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model = ov.Model([relu], [param], "test_model")
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assert model is not None
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return model
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def get_advanced_model():
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data = ops.parameter(ov.Shape([1, 3, 64, 64]), ov.Type.f32, name="input")
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data1 = ops.parameter(ov.Shape([1, 3, 64, 64]), ov.Type.f32, name="input2")
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axis_const = ops.constant(1, dtype=ov.Type.i64)
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split = ops.split(data, axis_const, 3)
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relu = ops.relu(split.output(1))
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relu.output(0).get_tensor().set_names({"result"})
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return ov.Model([split.output(0), relu.output(0), split.output(2)], [data, data1], "model")
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def get_ngraph_model(input_shape = None, input_dtype=np.float32):
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if input_shape is None:
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input_shape = [1, 3, 32, 32]
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param = ng.opset11.parameter(input_shape, input_dtype, name="data")
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relu = ng.opset11.relu(param, name="relu")
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func = Function([relu], [param], "test_model")
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caps = ng.Function.to_capsule(func)
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net = ie.IENetwork(caps)
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assert net is not None
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return net
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def get_image(shape = (1, 3, 32, 32), dtype = "float32"):
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np.random.seed(42)
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return np.random.rand(*shape).astype(dtype)
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def get_path_to_extension_library():
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library_path=""
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if platform == "win32":
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library_path="openvino_template_extension.dll"
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else:
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library_path="libopenvino_template_extension.so"
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return library_path
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def get_path_to_model(input_shape = None, is_old_api=False):
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if input_shape is None:
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input_shape = [1, 3, 32, 32]
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path_to_xml = tempfile.NamedTemporaryFile(suffix="_model.xml").name
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if is_old_api:
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net = get_ngraph_model(input_shape, input_dtype=np.int64)
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net.serialize(path_to_xml)
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else:
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model = get_model(input_shape)
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ov.serialize(model, path_to_xml)
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return path_to_xml
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def get_temp_dir():
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temp_dir = tempfile.TemporaryDirectory()
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return temp_dir
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