37 lines
1.3 KiB
Python
37 lines
1.3 KiB
Python
# Copyright (C) 2018-2021 Intel Corporation
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# SPDX-License-Identifier: Apache-2.0
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import numpy as np
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import ngraph as ng
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from ngraph.impl import Shape, Type
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def test_proposal_props():
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float_dtype = np.float32
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batch_size = 1
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post_nms_topn = 20
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probs = ng.parameter(Shape([batch_size, 8, 255, 255]), dtype=float_dtype, name="probs")
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deltas = ng.parameter(Shape([batch_size, 16, 255, 255]), dtype=float_dtype, name="bbox_deltas")
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im_info = ng.parameter(Shape([4]), dtype=float_dtype, name="im_info")
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attrs = {
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"base_size": np.uint32(85),
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"pre_nms_topn": np.uint32(10),
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"post_nms_topn": np.uint32(post_nms_topn),
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"nms_thresh": np.float32(0.34),
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"feat_stride": np.uint32(16),
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"min_size": np.uint32(32),
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"ratio": np.array([0.1, 1.5, 2.0, 2.5], dtype=np.float32),
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"scale": np.array([2, 3, 3, 4], dtype=np.float32),
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}
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node = ng.proposal(probs, deltas, im_info, attrs)
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assert node.get_type_name() == "Proposal"
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assert node.get_output_size() == 2
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assert list(node.get_output_shape(0)) == [batch_size * post_nms_topn, 5]
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assert list(node.get_output_shape(1)) == [batch_size * post_nms_topn]
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assert node.get_output_element_type(0) == Type.f32
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assert node.get_output_element_type(1) == Type.f32
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