85 lines
2.8 KiB
Python
85 lines
2.8 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 onnx
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from extensions.front.onnx.upsample_ext import UpsampleFrontExtractor
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from mo.graph.graph import Node
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from mo.utils.error import Error
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from mo.utils.unittest.extractors import BaseExtractorsTestingClass
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from mo.utils.unittest.graph import build_graph
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class UpsampleONNXExtractorTest(BaseExtractorsTestingClass):
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@staticmethod
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def _create_node(attrs: dict):
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pb = onnx.helper.make_node("Upsample", ["X"], ["Y"], **attrs)
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graph = build_graph({'node_0': {'pb': pb}}, [])
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return Node(graph, 'node_0')
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@staticmethod
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def _base_attrs():
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# Commonly used attributes in the tests
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# Each test takes these ones and then adds/modifies/deletes particular fields
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return (
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# test input ONNX attributes
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dict(
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mode='nearest',
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scales=[1., 1., 2., 2.],
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),
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# reference output Node attributes
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dict(
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width_scale=2.0,
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height_scale=2.0,
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mode='nearest',
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)
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)
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@staticmethod
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def _extract(inp):
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node = __class__._create_node(inp)
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UpsampleFrontExtractor.extract(node)
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return node
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def _match(self, out, ref):
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self.res = out
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self.expected = ref
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self.compare()
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def test_all_valid_default(self):
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inp, ref = self._base_attrs()
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out = self._extract(inp)
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self._match(out, ref)
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def test_invalid_mode(self):
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inp, ref = self._base_attrs()
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inp['mode'] = 'invalid_mode'
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with self.assertRaisesRegex(Error, '.*decoding Upsample.*supported modes.*'):
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out = self._extract(inp)
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def test_invalid_scales(self):
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inp, ref = self._base_attrs()
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inp['scales'] = [1.5, 1.5, 2.0, 2.0]
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with self.assertRaisesRegex(Error, '.*Upsampling of batch and feature dimensions is not supported for node.*'):
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out = self._extract(inp)
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def test_invalid_2D_scales(self):
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inp, ref = self._base_attrs()
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inp['scales'] = [2.0, 2.0]
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with self.assertRaisesRegex(Error,
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'.*Upsample scales attribute is wrong for node.*. Only 4D scales are supported.'):
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out = self._extract(inp)
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