def test_shape_only(self):
graph = build_graph(
nodes_attributes, [('node_in_1', 'quantize'),
('node_in_2', 'quantize'),
('node_in_3', 'quantize'),
('node_in_4', 'quantize'),
('node_in_5', 'quantize'),
('quantize', 'node_out_1'),
('node_out_1', 'op_output')], {
'node_out_1': {
'shape': None
},
'node_in_1': {
'shape': np.array([1, 3, 10, 20])
},
'node_in_2': {
'shape': np.array([1, 3, 10, 20])
},
'node_in_3': {
'shape': np.array([1, 3, 10, 20])
},
'node_in_4': {
'shape': np.array([1, 3, 10, 20])
},
'node_in_5': {
'shape': np.array([1, 3, 10, 20])
},
})
quantize_node = Node(graph, 'quantize')
FakeQuantize.infer(quantize_node)
quantize_shape = np.array([1, 3, 10, 20])
res_shape = graph.node['node_out_1']['shape']
for i in range(0, len(quantize_shape)):
self.assertEqual(quantize_shape[i], res_shape[i])
def test_shape_and_value(self):
graph = build_graph(nodes_attributes,
[('node_in_1', 'quantize'),
('node_in_2', 'quantize'),
('node_in_3', 'quantize'),
('node_in_4', 'quantize'),
('node_in_5', 'quantize'),
('quantize', 'node_out_1'),
('node_out_1', 'op_output')
],
{
'node_out_1': {
'shape': None,
'value': None,
},
'node_in_1': {
'shape': np.array([4]),
'value': np.array([5, 17, 0, 100], dtype=np.float32),
},
'node_in_2': {
'shape': np.array([4]),
'value': np.array([0, 12, 12, 12], dtype=np.float32),
},
'node_in_3': {
'shape': np.array([4]),
'value': np.array([10, 20, 20, 20], dtype=np.float32),
},
'node_in_4': {
'shape': np.array([4]),
'value': np.array([0, 0, 0, 0], dtype=np.float32),
},
'node_in_5': {
'shape': np.array([4]),
'value': np.array([1, 1, 1, 1], dtype=np.float32),
},
})
exp_node = Node(graph, 'quantize')
FakeQuantize.infer(exp_node)
quantize_shape = np.array([4])
quantize_value = np.array([0, 1, 0, 1], dtype=np.float32)
res_shape = graph.node['node_out_1']['shape']
res_value = graph.node['node_out_1']['value']
for i in range(0, len(quantize_shape)):
self.assertEqual(quantize_shape[i], res_shape[i])
for i in range(0, len(quantize_value)):
self.assertAlmostEqual(quantize_value[i], res_value[i], places=6)