# Copyright (C) 2018-2021 Intel Corporation # SPDX-License-Identifier: Apache-2.0 import unittest import numpy as np from extensions.ops.sparse_reshape import SparseReshape from mo.front.common.partial_infer.utils import int64_array from mo.graph.graph import Node from unit_tests.utils.graph import build_graph nodes_attributes = {'input_indices': {'shape': None, 'value': None, 'kind': 'data'}, 'input_shape': {'shape': None, 'value': None, 'kind': 'data'}, 'new_shape': {'shape': None, 'value': None, 'kind': 'data'}, 'sparse_reshape_node': {'op': 'SparseReshape', 'kind': 'op'}, 'output_indices': {'shape': None, 'value': None, 'kind': 'data'}, 'output_shape': {'shape': None, 'value': None, 'kind': 'data'}} # graph 1 edges1 = [('input_indices', 'sparse_reshape_node', {'in': 0}), ('input_shape', 'sparse_reshape_node', {'in': 1}), ('new_shape', 'sparse_reshape_node', {'in': 2}), ('sparse_reshape_node', 'output_indices', {'out': 0}), ('sparse_reshape_node', 'output_shape', {'out': 1})] inputs1 = {'input_indices': {'shape': int64_array([5, 2]), 'value': None}, 'input_shape': {'shape': int64_array([2]), 'value': int64_array([4, 5])}, 'new_shape': {'shape': int64_array([3]), 'value': int64_array([5, -1, 2])}} class TestSparseReshape(unittest.TestCase): def test_partial_infer1(self): graph = build_graph(nodes_attributes, edges1, inputs1) sparse_reshape_node = Node(graph, 'sparse_reshape_node') SparseReshape.infer(sparse_reshape_node) # prepare reference results ref_output_indices_shape = np.array([5, 3], dtype=np.int32) ref_output_shape_value = np.array([5, 2, 2], dtype=np.int32) # get the result res_output_indices_shape = graph.node['output_indices']['shape'] res_output_shape_value = graph.node['output_shape']['value'] self.assertTrue(np.array_equal(ref_output_indices_shape, res_output_indices_shape), 'shapes do not match expected: {} and given: {}'.format(ref_output_indices_shape, res_output_indices_shape)) self.assertTrue(np.array_equal(ref_output_shape_value, res_output_shape_value), 'values do not match expected: {} and given: {}'.format(ref_output_shape_value, res_output_shape_value))