Files
openvino/model-optimizer/extensions/front/caffe/proposal_python_ext_test.py
Evgeny Lazarev 970b1301b5 Cleanup IR v7 from the MO (#1008)
* Removed back phase transformations related to IRv7

* Fixed setting value for the input port using the 'set_value' method

* Removed front and middle phase transformations related to IRv7

* Cleanup the rest of the Model Optimizer transformations from IRv7 specific transformations

* Final cleanup of the deprecated IR v7 related code

* Removed 'blobs_as_input' usage in the Model Optimizer.

* Removed function '_fuse_add' from the Model Optimizer since it is not used anymore.

* Removed 'keep_in_IR' node attribute for FakeQuantize ops in the MO

* Disabled failing gpu_engine.user_context test
2020-06-22 11:52:00 +03:00

113 lines
3.5 KiB
Python

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