64 lines
2.9 KiB
Python
64 lines
2.9 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_reshape import SparseReshape
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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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nodes_attributes = {'input_indices': {'shape': None, 'value': None, 'kind': 'data'},
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'input_shape': {'shape': None, 'value': None, 'kind': 'data'},
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'new_shape': {'shape': None, 'value': None, 'kind': 'data'},
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'sparse_reshape_node': {'op': 'SparseReshape', 'kind': 'op'},
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'output_indices': {'shape': None, 'value': None, 'kind': 'data'},
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'output_shape': {'shape': None, 'value': None, 'kind': 'data'}}
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# graph 1
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edges1 = [('input_indices', 'sparse_reshape_node', {'in': 0}),
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('input_shape', 'sparse_reshape_node', {'in': 1}),
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('new_shape', 'sparse_reshape_node', {'in': 2}),
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('sparse_reshape_node', 'output_indices', {'out': 0}),
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('sparse_reshape_node', 'output_shape', {'out': 1})]
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inputs1 = {'input_indices': {'shape': int64_array([5, 2]), 'value': None},
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'input_shape': {'shape': int64_array([2]), 'value': int64_array([4, 5])},
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'new_shape': {'shape': int64_array([3]), 'value': int64_array([5, -1, 2])}}
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class TestSparseReshape(unittest.TestCase):
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def test_partial_infer1(self):
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graph = build_graph(nodes_attributes, edges1, inputs1)
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sparse_reshape_node = Node(graph, 'sparse_reshape_node')
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SparseReshape.infer(sparse_reshape_node)
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# prepare reference results
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ref_output_indices_shape = np.array([5, 3], dtype=np.int32)
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ref_output_shape_value = np.array([5, 2, 2], dtype=np.int32)
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# get the result
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res_output_indices_shape = graph.node['output_indices']['shape']
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res_output_shape_value = graph.node['output_shape']['value']
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self.assertTrue(np.array_equal(ref_output_indices_shape, res_output_indices_shape),
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'shapes do not match expected: {} and given: {}'.format(ref_output_indices_shape, res_output_indices_shape))
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self.assertTrue(np.array_equal(ref_output_shape_value, res_output_shape_value),
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'values do not match expected: {} and given: {}'.format(ref_output_shape_value, res_output_shape_value))
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