147 lines
6.5 KiB
Python
147 lines
6.5 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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import numpy as np
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from extensions.ops.regionyolo import RegionYoloOp
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from mo.front.common.extractors.utils import layout_attrs
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from mo.graph.graph import Node
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from mo.utils.unittest.graph import build_graph
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nodes_attributes = {'node_1': {'type': 'Identity', 'kind': 'op'},
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'region': {'type': 'RegionYolo', 'kind': 'op'},
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'node_3': {'type': 'Identity', 'kind': 'op'},
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'op_output': { 'kind': 'op', 'op': 'Result'}
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}
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class TestRegionYOLOCaffe(unittest.TestCase):
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def test_region_infer(self):
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graph = build_graph(nodes_attributes,
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[('node_1', 'region'),
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('region', 'node_3'),
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('node_3', 'op_output')
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],
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{'node_3': {'shape': None},
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'node_1': {'shape': np.array([1, 3, 227, 227])},
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'region': {'axis': 1, 'end_axis': -1, 'do_softmax': 1, **layout_attrs()}
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})
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graph.graph['layout'] = 'NCHW'
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reorg_node = Node(graph, 'region')
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RegionYoloOp.regionyolo_infer(reorg_node)
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exp_shape = np.array([1, 3 * 227 * 227])
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res_shape = graph.node['node_3']['shape']
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for i in range(0, len(exp_shape)):
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self.assertEqual(exp_shape[i], res_shape[i])
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def test_region_infer_flatten(self):
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graph = build_graph(nodes_attributes,
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[('node_1', 'region'),
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('region', 'node_3'),
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('node_3', 'op_output')
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],
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{'node_3': {'shape': None},
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'node_1': {'shape': np.array([1, 3, 227, 227])},
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'region': {'end_axis': 1, 'axis': 0, 'do_softmax': 1, **layout_attrs()}
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})
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graph.graph['layout'] = 'NCHW'
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reorg_node = Node(graph, 'region')
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RegionYoloOp.regionyolo_infer(reorg_node)
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exp_shape = np.array([1 * 3, 227, 227])
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res_shape = graph.node['node_3']['shape']
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for i in range(0, len(exp_shape)):
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self.assertEqual(exp_shape[i], res_shape[i])
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def test_region_infer_flatten_again(self):
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graph = build_graph(nodes_attributes,
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[('node_1', 'region'),
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('region', 'node_3'),
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('node_3', 'op_output')
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],
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{'node_3': {'shape': None},
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'node_1': {'shape': np.array([1, 3, 227, 227])},
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'region': {'end_axis': 2, 'axis': 0, 'do_softmax': 1, **layout_attrs()}
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})
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graph.graph['layout'] = 'NCHW'
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reorg_node = Node(graph, 'region')
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RegionYoloOp.regionyolo_infer(reorg_node)
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exp_shape = np.array([1 * 3 * 227, 227])
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res_shape = graph.node['node_3']['shape']
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for i in range(0, len(exp_shape)):
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self.assertEqual(exp_shape[i], res_shape[i])
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def test_region_infer_do_softmax(self):
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graph = build_graph(nodes_attributes,
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[('node_1', 'region'),
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('region', 'node_3'),
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('node_3', 'op_output')
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],
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{'node_3': {'shape': None},
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'node_1': {'shape': np.array([1, 3, 227, 227])},
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'region': {'do_softmax': 0, 'end_axis': -1, 'axis': 1, 'classes': 80, 'coords': 4,
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'mask': np.array([6, 7, 8]), **layout_attrs()}
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})
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graph.graph['layout'] = 'NCHW'
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reorg_node = Node(graph, 'region')
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RegionYoloOp.regionyolo_infer(reorg_node)
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exp_shape = np.array([1, (80 + 4 + 1) * 3, 227, 227])
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res_shape = graph.node['node_3']['shape']
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for i in range(0, len(exp_shape)):
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self.assertEqual(exp_shape[i], res_shape[i])
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class TestRegionYOLOTF(unittest.TestCase):
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def test_region_infer(self):
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graph = build_graph(nodes_attributes,
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[('node_1', 'region'),
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('region', 'node_3'),
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('node_3', 'op_output')
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],
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{'node_3': {'shape': None},
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'node_1': {'shape': np.array([1, 227, 227, 3])},
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'region': {'axis': 1, 'end_axis': -1, 'do_softmax': 1, **layout_attrs()}
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})
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graph.graph['layout'] = 'NHWC'
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reorg_node = Node(graph, 'region')
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RegionYoloOp.regionyolo_infer(reorg_node)
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exp_shape = np.array([1, 3 * 227 * 227])
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res_shape = graph.node['node_3']['shape']
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for i in range(0, len(exp_shape)):
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self.assertEqual(exp_shape[i], res_shape[i])
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def test_region_infer_do_softmax(self):
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graph = build_graph(nodes_attributes,
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[('node_1', 'region'),
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('region', 'node_3'),
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('node_3', 'op_output')
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],
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{'node_3': {'shape': None},
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'node_1': {'shape': np.array([1, 227, 227, 3])},
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'region': {'do_softmax': 0, 'end_axis': -1, 'axis': 1, 'classes': 80, 'coords': 4,
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'mask': np.array([6, 7, 8]), **layout_attrs()}
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})
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graph.graph['layout'] = 'NHWC'
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reorg_node = Node(graph, 'region')
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RegionYoloOp.regionyolo_infer(reorg_node)
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exp_shape = np.array([1, 227, 227, (80 + 4 + 1) * 3])
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res_shape = graph.node['node_3']['shape']
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for i in range(0, len(exp_shape)):
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self.assertEqual(exp_shape[i], res_shape[i])
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