def test_bn(self):
bn_pb = FakeBNProtoLayer(FakeParam('eps', 0.0001))
mean = [1, 2.5, 3]
var = [0.5, 0.1, 1.2]
scale = [2.3, 3.4, 4.5]
shift = [0.8, 0.6, 0.4]
bn_bin = FakeBNBinLayer([
FakeParam('data', mean),
FakeParam('data', var),
FakeParam('data', scale),
FakeParam('data', shift)
])
nodes = [
('input', {
'kind': 'op',
'type': 'Identity',
'op': 'Identity'
}),
('bn', {
'type': None,
'kind': 'op',
'op': 'BN',
'pb': bn_pb,
'model_pb': bn_bin
}),
('output', {
'kind': 'op',
'type': 'Identity',
'op': 'Identity'
}),
]
edges = [
('input', 'bn', {
'in': 0,
'out': 0
}),
('bn', 'output', {
'in': 0,
'out': 0
}),
]
graph = build_graph_with_attrs(nodes, edges)
node = Node(graph, 'bn')
graph.stage = 'front'
BNToScaleShift().find_and_replace_pattern(graph)
ref_nodes = {
'input': {
'kind': 'op',
'type': 'Identity',
'op': 'Identity'
},
'scale': {
'kind': 'op',
'type': 'Const',
'op': 'Const',
'value': np.array([1.11796412, 3.2272172, 4.74282367])
},
'shift': {
'kind': 'op',
'type': 'Const',
'op': 'Const',
'value': np.array([-2.07131747, -10.87253847, -20.14270653])
},
'ss': {
'type': 'ScaleShift',
'kind': 'op',
'op': 'ScaleShift'
},
'output': {
'kind': 'op',
'type': 'Identity',
'op': 'Identity'
},
}
ref_edges = [
('input', 'ss', {
'in': 0,
'out': 0
}),
('scale', 'ss', {
'in': 1,
'out': 0
}),
('shift', 'ss', {
'in': 2,
'out': 0
}),
('ss', 'output', {
'in': 0,
'out': 0
}),
]
ref_graph = build_graph_with_edge_attrs(ref_nodes, ref_edges)
(flag, resp) = compare_graphs(graph,
ref_graph,
'input',
check_op_attrs=True)
self.assertTrue(flag, resp)
def test_get_list_from_container_list_match_empty(self):
res = get_list_from_container(FakeParam('prop', []), 'prop', int)
self.assertEqual(res, [])
def test_get_list_from_container_no_existing_param(self):
res = get_list_from_container(FakeParam("p", "1"), 'prop', int)
self.assertEqual(res, [])
def test_get_list_from_container_simple_type_match(self):
res = get_list_from_container(FakeParam('prop', 10), 'prop', int)
self.assertEqual(res, [10])
def ListFields(self):
keys = []
for k in self.dict_values.keys():
keys.append([FakeParam('name', k)])
return keys