def test_caffe_priorbox_density_infer(self):
graph = build_graph(
nodes_attributes, [('node_1', 'pb'), ('pb', 'node_3')], {
'node_3': {
'is_output': True,
'shape': None
},
'node_1': {
'shape': np.array([1, 128, 32, 32])
},
'pb': {
'aspect_ratio': np.array([1]),
'flip': 1,
'min_size': np.array([]),
'max_size': np.array([]),
'fixed_size': np.array([32, 64, 128]),
'density': np.array([1, 2, 4]),
}
})
graph.graph['layout'] = 'NCHW'
pb_node = Node(graph, 'pb')
PriorBoxOp.priorbox_infer(pb_node)
exp_shape = np.array([1, 2, 4 * 32 * 32 * 21])
res_shape = graph.node['node_3']['shape']
for i in range(0, len(exp_shape)):
self.assertEqual(exp_shape[i], res_shape[i])
def test_tf_priorbox_infer(self):
graph = build_graph(
nodes_attributes, [('node_1', 'pb'), ('pb', 'node_3'),
('node_3', 'op_output')], {
'node_3': {
'shape': None
},
'node_1': {
'shape': np.array([1, 19, 19, 384])
},
'pb': {
'aspect_ratio': np.array([1]),
'flip': 0,
'min_size': np.array([1]),
'max_size': np.array([1])
}
})
graph.graph['layout'] = 'NHWC'
pb_node = Node(graph, 'pb')
PriorBoxOp.priorbox_infer(pb_node)
exp_shape = np.array([1, 2, 4 * 19 * 19 * 2])
res_shape = graph.node['node_3']['shape']
for i in range(0, len(exp_shape)):
self.assertEqual(exp_shape[i], res_shape[i])