def test_cumsum_value_prop_exclusive(self):
graph = build_graph(nodes_attributes, [
*connect('data', '0:cumsum'),
*connect('axis', '1:cumsum'),
('cumsum', 'cumsum_d', {
'out': 0
}),
('cumsum_d', 'output'),
], {
'data_d': {
'value': np.array([1., 2., 3., 4., 5.]).astype(np.float32),
'shape': [5]
},
'cumsum': {
'reverse': False,
'exclusive': True
}
},
nodes_with_edges_only=True)
cumsum_node = Node(graph, 'cumsum')
CumSum.infer(cumsum_node)
self.assertTrue(
np.array_equal(
cumsum_node.out_port(0).data.get_value(),
np.array([0., 1., 3., 6., 10.]).astype(np.float32)))
def extract(cls, node):
exclusive = node.pb.attr['exclusive'].b
reverse = node.pb.attr['reverse'].b
CumSum.update_node_stat(node, {
'exclusive': exclusive,
'reverse': reverse
})
return cls.enabled
def extract(cls, node):
exclusive = onnx_attr(node, 'exclusive', 'i', 0)
reverse = onnx_attr(node, 'reverse', 'i', 0)
CumSum.update_node_stat(node, {
'exclusive': exclusive,
'reverse': reverse
})
return cls.enabled
def test_cumsum_axis(self):
graph = build_graph(nodes_attributes,
[*connect('data', '0:cumsum'),
*connect('axis', '1:cumsum'),
*connect('cumsum', '0:identity'),
('identity', 'identity_d', {'out': 0}),
('identity_d', 'output'),
],
{'cumsum': {'reverse': False, 'exclusive': False}
}, nodes_with_edges_only=True)
cumsum_node = Node(graph, 'cumsum')
CumSum.infer(cumsum_node)
self.assertTrue(np.array_equal(cumsum_node.out_port(0).data.get_shape(), int64_array([1, 3, 224, 224])))
