96 lines
4.1 KiB
Python
96 lines
4.1 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.ctc_greedy_decoder import CTCGreedyDecoderOp
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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 = {'logits': {'kind': 'op'},
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'logits_data': {'shape': None, 'value': None, 'kind': 'data'},
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'seq_mask': {'kind': 'op'},
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'seq_mask_data': {'shape': None, 'value': None, 'kind': 'data'},
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'ctcgreedydecoder_node': {'op': 'CTCGreedyDecoder', 'kind': 'op',
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'ctc_merge_repeated': True},
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'output': {'shape': None, 'value': None, 'kind': 'data'}}
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# graph 1
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edges1 = [('logits', 'logits_data'),
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('seq_mask', 'seq_mask_data'),
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('logits_data', 'ctcgreedydecoder_node', {'in': 0}),
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('seq_mask_data', 'ctcgreedydecoder_node', {'in': 1}),
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('ctcgreedydecoder_node', 'output', {'out': 0})]
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# valid test case
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inputs1 = {'logits_data': {'shape': int64_array([100, 4, 5])},
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'seq_mask_data': {'shape': int64_array([100, 4])}}
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# invalid test case with incorrect rank for the first input tensor
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inputs1_inv = {'logits_data': {'shape': int64_array([100, 4, 5, 6])},
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'seq_mask_data': {'shape': int64_array([100, 4])}}
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# invalid test case with incorrect rank for the second input tensor
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inputs2_inv = {'logits_data': {'shape': int64_array([100, 4, 5])},
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'seq_mask_data': {'shape': int64_array([100])}}
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# invalid test case with incorrect time dimension
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inputs3_inv = {'logits_data': {'shape': int64_array([100, 4, 5])},
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'seq_mask_data': {'shape': int64_array([101, 4])}}
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# invalid test case with incorrect batch dimension
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inputs4_inv = {'logits_data': {'shape': int64_array([100, 4, 5])},
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'seq_mask_data': {'shape': int64_array([100, 14])}}
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class TestCTCGreedyDecoder(unittest.TestCase):
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def test_infer1(self):
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graph = build_graph(nodes_attributes, edges1, inputs1)
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ctcgreedydecoder_node = Node(graph, 'ctcgreedydecoder_node')
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CTCGreedyDecoderOp.infer(ctcgreedydecoder_node)
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# prepare reference results
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ref_output_shape = int64_array([4, 100, 1, 1])
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# get the result
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res_output_shape = graph.node['output']['shape']
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self.assertTrue(np.array_equal(ref_output_shape, res_output_shape),
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'shapes do not match expected: {} and given: {}'.format(ref_output_shape, res_output_shape))
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def test_infer_invalid1(self):
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graph = build_graph(nodes_attributes, edges1, inputs1_inv)
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ctcgreedydecoder_node = Node(graph, 'ctcgreedydecoder_node')
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self.assertRaises(AssertionError, CTCGreedyDecoderOp.infer, ctcgreedydecoder_node)
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def test_infer_invalid2(self):
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graph = build_graph(nodes_attributes, edges1, inputs2_inv)
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ctcgreedydecoder_node = Node(graph, 'ctcgreedydecoder_node')
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self.assertRaises(AssertionError, CTCGreedyDecoderOp.infer, ctcgreedydecoder_node)
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def test_infer_invalid3(self):
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graph = build_graph(nodes_attributes, edges1, inputs3_inv)
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ctcgreedydecoder_node = Node(graph, 'ctcgreedydecoder_node')
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self.assertRaises(AssertionError, CTCGreedyDecoderOp.infer, ctcgreedydecoder_node)
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def test_infer_invalid4(self):
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graph = build_graph(nodes_attributes, edges1, inputs4_inv)
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ctcgreedydecoder_node = Node(graph, 'ctcgreedydecoder_node')
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self.assertRaises(AssertionError, CTCGreedyDecoderOp.infer, ctcgreedydecoder_node)
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