""" Copyright (C) 2018-2021 Intel Corporation Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. """ import unittest import numpy as np from extensions.ops.ctc_greedy_decoder_seq_len import CTCGreedyDecoderSeqLenOp from mo.front.common.partial_infer.utils import int64_array from mo.graph.graph import Node from mo.utils.unittest.graph import build_graph nodes_attributes = {'logits': {'kind': 'op'}, 'logits_data': {'shape': None, 'value': None, 'kind': 'data'}, 'seq_mask': {'kind': 'op'}, 'seq_mask_data': {'shape': None, 'value': None, 'kind': 'data'}, 'ctcgreedydecoder_node': {'op': 'CTCGreedyDecoderSeqLen', 'kind': 'op', 'ctc_merge_repeated': True}, 'output1': {'shape': None, 'value': None, 'kind': 'data'}, 'last_output1': {'shape': None, 'value': None, 'kind': 'op'}, 'output2': {'shape': None, 'value': None, 'kind': 'data'} } # graph 1 edges1 = [('logits', 'logits_data'), ('seq_mask', 'seq_mask_data'), ('logits_data', 'ctcgreedydecoder_node', {'in': 0}), ('seq_mask_data', 'ctcgreedydecoder_node', {'in': 1}), ('ctcgreedydecoder_node', 'output1', {'out': 0}), ('ctcgreedydecoder_node', 'output2', {'out': 1}), ('output1', 'last_output1', {'out': 0}),] # valid test case inputs1 = {'logits_data': {'shape': int64_array([4, 100, 5])}, 'seq_mask_data': {'shape': int64_array([4])}} # invalid test case with incorrect rank for the first input tensor inputs1_inv = {'logits_data': {'shape': int64_array([4, 100, 5, 6])}, 'seq_mask_data': {'shape': int64_array([4])}} # invalid test case with incorrect rank for the second input tensor inputs2_inv = {'logits_data': {'shape': int64_array([4, 100, 5])}, 'seq_mask_data': {'shape': int64_array([4, 100])}} # invalid test case with incorrect time dimension inputs3_inv = {'logits_data': {'shape': int64_array([4, 100, 5])}, 'seq_mask_data': {'shape': int64_array([4, 101])}} # invalid test case with incorrect batch dimension inputs4_inv = {'logits_data': {'shape': int64_array([4, 100, 5])}, 'seq_mask_data': {'shape': int64_array([14, 100])}} class TestCTCGreedyDecoder(unittest.TestCase): def test_infer1(self): graph = build_graph(nodes_attributes, edges1, inputs1) ctcgreedydecoder_node = Node(graph, 'ctcgreedydecoder_node') CTCGreedyDecoderSeqLenOp.infer(ctcgreedydecoder_node) # prepare reference results ref_output1_shape = int64_array([4, 100]) # get the result res_output1_shape = graph.node['output1']['shape'] self.assertTrue(np.array_equal(ref_output1_shape, res_output1_shape), 'shapes do not match expected: {} and given: {}'.format(ref_output1_shape, res_output1_shape)) def test_infer_invalid1(self): graph = build_graph(nodes_attributes, edges1, inputs1_inv) ctcgreedydecoder_node = Node(graph, 'ctcgreedydecoder_node') self.assertRaises(AssertionError, CTCGreedyDecoderSeqLenOp.infer, ctcgreedydecoder_node) def test_infer_invalid2(self): graph = build_graph(nodes_attributes, edges1, inputs2_inv) ctcgreedydecoder_node = Node(graph, 'ctcgreedydecoder_node') self.assertRaises(AssertionError, CTCGreedyDecoderSeqLenOp.infer, ctcgreedydecoder_node) def test_infer_invalid3(self): graph = build_graph(nodes_attributes, edges1, inputs3_inv) ctcgreedydecoder_node = Node(graph, 'ctcgreedydecoder_node') self.assertRaises(AssertionError, CTCGreedyDecoderSeqLenOp.infer, ctcgreedydecoder_node) def test_infer_invalid4(self): graph = build_graph(nodes_attributes, edges1, inputs4_inv) ctcgreedydecoder_node = Node(graph, 'ctcgreedydecoder_node') self.assertRaises(AssertionError, CTCGreedyDecoderSeqLenOp.infer, ctcgreedydecoder_node)