102 lines
5.1 KiB
Python
102 lines
5.1 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.sparse_segment_sum import SparseSegmentSum
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from mo.front.common.partial_infer.utils import int64_array
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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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# graph 1
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nodes_attributes1 = {'input_data': {'shape': None, 'value': None, 'kind': 'data'},
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'input_indices': {'shape': None, 'value': None, 'kind': 'data'},
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'input_segment_ids': {'shape': None, 'value': None, 'kind': 'data'},
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'sparse_segment_sum_node': {'op': 'SparseSegmentSum', 'kind': 'op'},
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'output_segments': {'shape': None, 'value': None, 'kind': 'data'},
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}
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edges1 = [('input_data', 'sparse_segment_sum_node', {'in': 0}),
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('input_indices', 'sparse_segment_sum_node', {'in': 1}),
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('input_segment_ids', 'sparse_segment_sum_node', {'in': 2}),
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('sparse_segment_sum_node', 'output_segments', {'out': 0})]
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inputs1 = {'input_data': {'shape': int64_array([20, 4, 5]), 'value': None},
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'input_indices': {'shape': int64_array([40]), 'value': None},
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'input_segment_ids': {'shape': int64_array([40]), 'value': None}}
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# graph 2 with constant input, sum
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nodes_attributes2 = {'input_data': {'shape': None, 'value': None, 'kind': 'data'},
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'input_indices': {'shape': None, 'value': None, 'kind': 'data'},
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'input_segment_ids': {'shape': None, 'value': None, 'kind': 'data'},
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'sparse_segment_sum_node': {'op': 'SparseSegmentSum', 'kind': 'op'},
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'output_segments': {'shape': None, 'value': None, 'kind': 'data'},
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}
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edges2 = [('input_data', 'sparse_segment_sum_node', {'in': 0}),
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('input_indices', 'sparse_segment_sum_node', {'in': 1}),
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('input_segment_ids', 'sparse_segment_sum_node', {'in': 2}),
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('sparse_segment_sum_node', 'output_segments', {'out': 0})]
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inputs2 = {'input_data': {'shape': int64_array([3, 4]), 'value': np.array([[1, 2, 3, 4], [-1, -2, -3, -4], [5, 6, 7, 8]], dtype=np.float)},
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'input_indices': {'shape': int64_array([3]), 'value': np.array([0, 1, 2], dtype=np.float)},
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'input_segment_ids': {'shape': int64_array([3]), 'value': np.array([0, 0, 1], dtype=np.float)}}
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class TestSparseSegmentSum(unittest.TestCase):
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def test_partial_infer(self):
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graph = build_graph(nodes_attributes1, edges1, inputs1)
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sparse_segment_sum_node = Node(graph, 'sparse_segment_sum_node')
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SparseSegmentSum.infer(sparse_segment_sum_node)
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# prepare reference results
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ref_output_segments_shape = int64_array([40, 4, 5])
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# get resulted shapes
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res_output_segments_shape = graph.node['output_segments']['shape']
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self.assertTrue(np.array_equal(ref_output_segments_shape, res_output_segments_shape),
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'Shapes do not match expected: {} and given: {}'.format(ref_output_segments_shape, res_output_segments_shape))
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def test_incorrect_shapes(self):
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inputs = {'input_data': {'shape': int64_array([20, 4, 5]), 'value': None},
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'input_indices': {'shape': int64_array([39]), 'value': None},
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'input_segment_ids': {'shape': int64_array([40]), 'value': None}}
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graph = build_graph(nodes_attributes1, edges1, inputs)
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sparse_segment_sum_node = Node(graph, 'sparse_segment_sum_node')
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self.assertRaises(AssertionError, SparseSegmentSum.infer, sparse_segment_sum_node)
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def test_infer_constant_input_sum(self):
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graph = build_graph(nodes_attributes2, edges2, inputs2)
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sparse_segment_sum_node = Node(graph, 'sparse_segment_sum_node')
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SparseSegmentSum.infer(sparse_segment_sum_node)
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# prepare reference results
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ref_output_segments_shape = int64_array([2, 4])
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ref_output_segments_value = np.array([[0, 0, 0, 0], [5, 6, 7, 8]], dtype=np.float)
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# get resulted shapes
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res_output_segments_shape = graph.node['output_segments']['shape']
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res_output_segments_value = graph.node['output_segments']['value']
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self.assertTrue(np.array_equal(ref_output_segments_shape, res_output_segments_shape),
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'Shapes do not match expected: {} and given: {}'.format(ref_output_segments_shape, res_output_segments_shape))
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self.assertTrue(np.array_equal(ref_output_segments_value, res_output_segments_value),
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'Shapes do not match expected: {} and given: {}'.format(ref_output_segments_value, res_output_segments_value))
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