116 lines
3.7 KiB
Python
116 lines
3.7 KiB
Python
"""
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Copyright (C) 2018-2020 Intel Corporation
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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"""
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import unittest
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from extensions.front.caffe.proposal_python_ext import ProposalPythonFrontExtractor
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from extensions.ops.proposal import ProposalOp
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from mo.ops.op import Op
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from mo.utils.unittest.extractors import FakeMultiParam
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from mo.utils.unittest.graph import FakeNode, FakeAttr
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class FakeProposalPythonProtoLayer:
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def __init__(self, val):
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self.python_param = val
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class TestProposalPythonExt(unittest.TestCase):
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@classmethod
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def setUpClass(cls):
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Op.registered_ops['Proposal'] = ProposalOp
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def test_proposal_no_pb_no_ml(self):
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self.assertRaises(AttributeError, ProposalPythonFrontExtractor.extract, None)
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def test_proposal_ext_ideal_numbers(self):
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params = {
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'param_str': "'feat_stride': 16"
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}
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fake_pl = FakeProposalPythonProtoLayer(FakeMultiParam(params))
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fake_node = FakeNode(fake_pl, None)
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fake_node.graph.graph['cmd_params'] = FakeAttr(generate_experimental_IR_V10=False)
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ProposalPythonFrontExtractor.extract(fake_node)
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exp_res = {
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'type': "Proposal",
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'feat_stride': 16,
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'base_size': 16,
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'min_size': 16,
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'ratio': [0.5, 1, 2],
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'scale': [8, 16, 32],
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'pre_nms_topn': 6000,
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'post_nms_topn': 300,
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'nms_thresh': 0.7,
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'infer': ProposalOp.proposal_infer
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}
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for key in exp_res.keys():
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self.assertEqual(fake_node[key], exp_res[key])
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def test_proposal_ext_scales(self):
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params = {
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'param_str': "'feat_stride': 16, 'scales': [1,2,3], 'ratios':[5, 6,7]"
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}
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fake_pl = FakeProposalPythonProtoLayer(FakeMultiParam(params))
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fake_node = FakeNode(fake_pl, None)
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fake_node.graph.graph['cmd_params'] = FakeAttr(generate_experimental_IR_V10=False)
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ProposalPythonFrontExtractor.extract(fake_node)
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exp_res = {
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'type': "Proposal",
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'feat_stride': 16,
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'base_size': 16,
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'min_size': 16,
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'ratio': [5, 6, 7],
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'scale': [1, 2, 3],
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'pre_nms_topn': 6000,
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'post_nms_topn': 300,
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'nms_thresh': 0.7,
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'infer': ProposalOp.proposal_infer
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}
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for key in exp_res.keys():
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self.assertEqual(fake_node[key], exp_res[key])
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def test_proposal_ext_scale(self):
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params = {
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'param_str': "'feat_stride': 16, 'scale': [1,2,3], 'ratio':[5, 6,7]"
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}
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fake_pl = FakeProposalPythonProtoLayer(FakeMultiParam(params))
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fake_node = FakeNode(fake_pl, None)
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fake_node.graph.graph['cmd_params'] = FakeAttr(generate_experimental_IR_V10=False)
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ProposalPythonFrontExtractor.extract(fake_node)
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exp_res = {
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'type': "Proposal",
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'feat_stride': 16,
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'base_size': 16,
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'min_size': 16,
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'ratio': [5, 6, 7],
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'scale': [1, 2, 3],
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'pre_nms_topn': 6000,
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'post_nms_topn': 300,
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'nms_thresh': 0.7,
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'infer': ProposalOp.proposal_infer
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}
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for key in exp_res.keys():
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self.assertEqual(fake_node[key], exp_res[key])
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