def test_tf_infer(self):
new_width = 100
new_height = 125
new_attrs = nodes_attributes.copy()
new_attrs.update({
'new_shape': {
'value': np.array([new_height, new_width]),
'type': 'Const',
'kind': 'op'
}
})
graph = build_graph(
new_attrs, [('node_1', 'resample'), ('new_shape', 'resample'),
('resample', 'node_3'), ('node_3', 'op_output')], {
'node_3': {
'shape': None
},
'node_1': {
'shape': np.array([1, 224, 227, 3])
},
'resample': {
'antialias': 1,
'resample_type': 'LINEAR',
'factor': 1.0,
'fw': 'tf'
}
})
graph.graph['layout'] = 'NHWC'
resample_node = Node(graph, 'resample')
ResampleOp.resample_infer(resample_node)
exp_shape = np.array([1, new_height, new_width, 3])
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_resample_infer(self):
graph = build_graph(
nodes_attributes, [('node_1', 'resample'), ('resample', 'node_3'),
('node_3', 'op_output')], {
'node_3': {
'shape': None
},
'node_1': {
'shape': np.array([1, 3, 227, 227])
},
'resample': {
'antialias': 1,
'height': 384,
'width': 512,
'resample_type': 'LINEAR',
'factor': 1.0
}
})
graph.graph['layout'] = 'NCHW'
resample_node = Node(graph, 'resample')
ResampleOp.resample_infer(resample_node)
exp_shape = np.array([1, 3, 384, 512])
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_caffe_factor_infer(self):
factor = 3.0
graph = build_graph(nodes_attributes,
[('node_1', 'resample'),
('resample', 'node_3')],
{'node_3': {'is_output': True, 'shape': None},
'node_1': {'shape': np.array([1, 3, 224, 227])},
'resample': {'antialias': 1,
'resample_type': 'LINEAR',
'factor': factor}
})
graph.graph['layout'] = 'NCHW'
resample_node = Node(graph, 'resample')
ResampleOp.resample_infer(resample_node)
exp_shape = np.array([1, 3, 224 * factor, 227 * factor])
res_shape = graph.node['node_3']['shape']
for i in range(0, len(exp_shape)):
self.assertEqual(exp_shape[i], res_shape[i])