73 lines
3.3 KiB
Python
73 lines
3.3 KiB
Python
# Copyright (C) 2018-2021 Intel Corporation
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# SPDX-License-Identifier: Apache-2.0
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import unittest
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import numpy as np
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from generator import generator, generate
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from extensions.ops.upsample import UpsampleOp
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from mo.graph.graph import Node
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from unit_tests.utils.graph import build_graph
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nodes_attributes = {'node_1': {'type': 'Identity', 'kind': 'op'},
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'upsample': {'type': 'Upsample', '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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@generator
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class TestUpsampleOp(unittest.TestCase):
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@generate(*[
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(np.array([1., 1., 2., 2.]), np.array([1, 3, 227, 227]), np.array([1, 3, 454, 454], dtype=np.int64)),
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(np.array([1., 1., 2.5, 1.5]), np.array([1, 5, 227, 227]), np.array([1, 5, 567, 340], dtype=np.int64)),
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(np.array([1., 1., 1.3, 0.7]), np.array([1, 14, 1023, 713]), np.array([1, 14, 1329, 499], dtype=np.int64)),
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])
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def test_upsample_with_scales_infer(self, scales, input_shape, expected_shape):
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graph = build_graph(nodes_attributes,
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[('node_1', 'upsample'),
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('upsample', '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': input_shape},
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'upsample': {'mode': 'linear',
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'height_scale': scales[2],
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'width_scale': scales[3]}
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})
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graph.graph['layout'] = 'NCHW'
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upsample_node = Node(graph, 'upsample')
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UpsampleOp.upsample_infer(upsample_node)
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res_shape = graph.node['node_3']['shape']
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for i in range(0, len(expected_shape)):
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self.assertEqual(expected_shape[i], res_shape[i])
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@generate(*[
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(np.array([1., 1., 2., 2.]), np.array([1, 3, 227, 227]), np.array([1, 3, 454, 454], dtype=np.int64)),
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(np.array([1., 1., 2.5, 1.5]), np.array([1, 5, 227, 227]), np.array([1, 5, 567, 340], dtype=np.int64)),
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(np.array([1., 1., 1.3, 0.7]), np.array([1, 14, 1023, 713]), np.array([1, 14, 1329, 499], dtype=np.int64)),
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])
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def test_upsample_with_second_input_infer(self, scales, input_shape, expected_shape):
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nodes_attributes['scales'] = {'kind': 'data', 'value': scales}
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graph = build_graph(nodes_attributes,
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[('node_1', 'upsample'),
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('scales', 'upsample'),
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('upsample', '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': input_shape},
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'upsample': {'mode': 'linear',
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'height_scale': None,
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'width_scale': None}
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})
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graph.graph['layout'] = 'NCHW'
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upsample_node = Node(graph, 'upsample')
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UpsampleOp.upsample_infer(upsample_node)
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res_shape = graph.node['node_3']['shape']
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for i in range(0, len(expected_shape)):
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self.assertEqual(expected_shape[i], res_shape[i])
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