openvino/model-optimizer/unit_tests/extensions/ops/data_augmentation_test.py

53 lines
2.1 KiB
Python

# Copyright (C) 2018-2021 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
import unittest
import numpy as np
from extensions.ops.data_augmentation import DataAugmentationOp
from mo.graph.graph import Node
from unit_tests.utils.graph import build_graph
nodes_attributes = {
'node_1': {'type': 'Identity', 'kind': 'op'},
'da': {'type': 'DataAugmentation', 'kind': 'op'},
'node_3': {'type': 'Identity', 'kind': 'op'},
'op_output': { 'kind': 'op', 'op': 'Result'}
}
class TestConcatPartialInfer(unittest.TestCase):
def test_tf_concat_infer(self):
graph = build_graph(nodes_attributes,
[
('node_1', 'da'),
('da', 'node_3'),
('node_3', 'op_output')
],
{
'node_3': {'shape': None},
'node_1': {'shape': np.array([1, 3, 227, 227])},
'da': {'crop_width': 225,
'crop_height': 225,
'write_augmented': "",
'max_multiplier': 255.0,
'augment_during_test': True,
'recompute_mean': 0,
'write_mean': "",
'mean_per_pixel': False,
'mean': 0,
'mode': "add",
'bottomwidth': 0,
'bottomheight': 0,
'num': 0,
'chromatic_eigvec': [0.0]}
})
da_node = Node(graph, 'da')
DataAugmentationOp.data_augmentation_infer(da_node)
exp_shape = np.array([1, 3, 225, 225])
res_shape = graph.node['node_3']['shape']
for i in range(0, len(exp_shape)):
self.assertEqual(exp_shape[i], res_shape[i])