• Home
  • Line#
  • Scopes#
  • Navigate#
  • Raw
  • Download
1# Copyright © 2020 Arm Ltd. All rights reserved.
2# SPDX-License-Identifier: MIT
3import os
4
5import pytest
6import pyarmnn as ann
7import numpy as np
8
9
10def test_TfLiteParserOptions_default_values():
11    parserOptions = ann.TfLiteParserOptions()
12    assert parserOptions.m_InferAndValidate == False
13    assert parserOptions.m_StandInLayerForUnsupported == False
14
15
16@pytest.fixture()
17def parser(shared_data_folder):
18    """
19    Parse and setup the test network to be used for the tests below
20    """
21    parser = ann.ITfLiteParser()
22    parser.CreateNetworkFromBinaryFile(os.path.join(shared_data_folder, 'mock_model.tflite'))
23
24    yield parser
25
26
27def test_tflite_parser_swig_destroy():
28    assert ann.ITfLiteParser.__swig_destroy__, "There is a swig python destructor defined"
29    assert ann.ITfLiteParser.__swig_destroy__.__name__ == "delete_ITfLiteParser"
30
31
32def test_check_tflite_parser_swig_ownership(parser):
33    # Check to see that SWIG has ownership for parser. This instructs SWIG to take
34    # ownership of the return value. This allows the value to be automatically
35    # garbage-collected when it is no longer in use
36    assert parser.thisown
37
38
39def test_tflite_parser_with_optional_options():
40    parserOptions = ann.TfLiteParserOptions()
41    parserOptions.m_InferAndValidate = True
42    parser = ann.ITfLiteParser(parserOptions)
43    assert parser.thisown
44
45
46def create_with_opt() :
47    parserOptions = ann.TfLiteParserOptions()
48    parserOptions.m_InferAndValidate = True
49    return ann.ITfLiteParser(parserOptions)
50
51
52def test_tflite_parser_with_optional_options_out_of_scope(shared_data_folder):
53    parser = create_with_opt()
54    network = parser.CreateNetworkFromBinaryFile(os.path.join(shared_data_folder, "mock_model.tflite"))
55
56    graphs_count = parser.GetSubgraphCount()
57    graph_id = graphs_count - 1
58
59    input_names = parser.GetSubgraphInputTensorNames(graph_id)
60    input_binding_info = parser.GetNetworkInputBindingInfo(graph_id, input_names[0])
61
62    output_names = parser.GetSubgraphOutputTensorNames(graph_id)
63
64    preferred_backends = [ann.BackendId('CpuAcc'), ann.BackendId('CpuRef')]
65
66    options = ann.CreationOptions()
67    runtime = ann.IRuntime(options)
68
69    opt_network, messages = ann.Optimize(network, preferred_backends, runtime.GetDeviceSpec(), ann.OptimizerOptions())
70    assert 0 == len(messages)
71
72    net_id, messages = runtime.LoadNetwork(opt_network)
73    assert "" == messages
74
75
76def test_tflite_get_sub_graph_count(parser):
77    graphs_count = parser.GetSubgraphCount()
78    assert graphs_count == 1
79
80
81def test_tflite_get_network_input_binding_info(parser):
82    graphs_count = parser.GetSubgraphCount()
83    graph_id = graphs_count - 1
84
85    input_names = parser.GetSubgraphInputTensorNames(graph_id)
86
87    input_binding_info = parser.GetNetworkInputBindingInfo(graph_id, input_names[0])
88
89    tensor = input_binding_info[1]
90    assert tensor.GetDataType() == 2
91    assert tensor.GetNumDimensions() == 4
92    assert tensor.GetNumElements() == 784
93    assert tensor.GetQuantizationOffset() == 128
94    assert tensor.GetQuantizationScale() == 0.007843137718737125
95
96
97def test_tflite_get_network_output_binding_info(parser):
98    graphs_count = parser.GetSubgraphCount()
99    graph_id = graphs_count - 1
100
101    output_names = parser.GetSubgraphOutputTensorNames(graph_id)
102
103    output_binding_info1 = parser.GetNetworkOutputBindingInfo(graph_id, output_names[0])
104
105    # Check the tensor info retrieved from GetNetworkOutputBindingInfo
106    tensor1 = output_binding_info1[1]
107
108    assert tensor1.GetDataType() == 2
109    assert tensor1.GetNumDimensions() == 2
110    assert tensor1.GetNumElements() == 10
111    assert tensor1.GetQuantizationOffset() == 0
112    assert tensor1.GetQuantizationScale() == 0.00390625
113
114
115def test_tflite_get_subgraph_input_tensor_names(parser):
116    graphs_count = parser.GetSubgraphCount()
117    graph_id = graphs_count - 1
118
119    input_names = parser.GetSubgraphInputTensorNames(graph_id)
120
121    assert input_names == ('input_1',)
122
123
124def test_tflite_get_subgraph_output_tensor_names(parser):
125    graphs_count = parser.GetSubgraphCount()
126    graph_id = graphs_count - 1
127
128    output_names = parser.GetSubgraphOutputTensorNames(graph_id)
129
130    assert output_names[0] == 'dense/Softmax'
131
132
133def test_tflite_filenotfound_exception(shared_data_folder):
134    parser = ann.ITfLiteParser()
135
136    with pytest.raises(RuntimeError) as err:
137        parser.CreateNetworkFromBinaryFile(os.path.join(shared_data_folder, 'some_unknown_network.tflite'))
138
139    # Only check for part of the exception since the exception returns
140    # absolute path which will change on different machines.
141    assert 'Cannot find the file' in str(err.value)
142
143
144def test_tflite_parser_end_to_end(shared_data_folder):
145    parser = ann.ITfLiteParser()
146
147    network = parser.CreateNetworkFromBinaryFile(os.path.join(shared_data_folder, "mock_model.tflite"))
148
149    graphs_count = parser.GetSubgraphCount()
150    graph_id = graphs_count - 1
151
152    input_names = parser.GetSubgraphInputTensorNames(graph_id)
153    input_binding_info = parser.GetNetworkInputBindingInfo(graph_id, input_names[0])
154
155    output_names = parser.GetSubgraphOutputTensorNames(graph_id)
156
157    preferred_backends = [ann.BackendId('CpuAcc'), ann.BackendId('CpuRef')]
158
159    options = ann.CreationOptions()
160    runtime = ann.IRuntime(options)
161
162    opt_network, messages = ann.Optimize(network, preferred_backends, runtime.GetDeviceSpec(), ann.OptimizerOptions())
163    assert 0 == len(messages)
164
165    net_id, messages = runtime.LoadNetwork(opt_network)
166    assert "" == messages
167
168    # Load test image data stored in input_lite.npy
169    input_tensor_data = np.load(os.path.join(shared_data_folder, 'tflite_parser/input_lite.npy'))
170    input_tensors = ann.make_input_tensors([input_binding_info], [input_tensor_data])
171
172    output_tensors = []
173    for index, output_name in enumerate(output_names):
174        out_bind_info = parser.GetNetworkOutputBindingInfo(graph_id, output_name)
175        out_tensor_info = out_bind_info[1]
176        out_tensor_id = out_bind_info[0]
177        output_tensors.append((out_tensor_id,
178                               ann.Tensor(out_tensor_info)))
179
180    runtime.EnqueueWorkload(net_id, input_tensors, output_tensors)
181
182    output_vectors = []
183    for index, out_tensor in enumerate(output_tensors):
184        output_vectors.append(out_tensor[1].get_memory_area())
185
186    # Load golden output file for result comparison.
187    expected_outputs = np.load(os.path.join(shared_data_folder, 'tflite_parser/golden_output_lite.npy'))
188
189    # Check that output matches golden output
190    assert (expected_outputs == output_vectors[0]).all()
191