def replace_pattern(self, graph: Graph, match: dict):
scale = graph.graph['cmd_params'].scale
if scale is None or scale == 1:
return
assert (len(match['placeholder'].out_nodes()))
AddMeanScaleValues.apply_scale(graph, match['placeholder'], {'scale': mo_array([scale])})
def test_mean_values_with_data_name(self):
graph_ref = build_graph(nodes, [
*connect('parameter', '0:add_mean'),
*connect('mean', '1:add_mean'),
*connect('add_mean', 'result'),
])
mean_values = parse_tuple_pairs('(1,2,3)')
scale_values = parse_tuple_pairs('')
mean_scale = get_mean_scale_dictionary(mean_values, scale_values, None)
argv = Namespace(mean_scale_values=mean_scale)
graph = build_graph(nodes, [*connect('parameter', 'result')],
nodes_with_edges_only=True,
cli=argv)
self.set_graph_attrs(graph, ['parameter'])
self.set_graph_attrs(graph_ref, ['parameter'])
graph.graph['layout'] = 'NCHW'
AddMeanScaleValues().find_and_replace_pattern(graph)
(flag, resp) = compare_graphs(graph,
graph_ref,
'result',
check_op_attrs=True)
self.assertTrue(flag, resp)
self.check_graph_attrs(graph, graph_ref, ['parameter'])
def test_mean_values_explicit_and_scale_values_explicit_layout(self):
graph_ref = build_graph(nodes, [
*connect('parameter', '0:add_mean'),
*connect('mean', '1:add_mean'),
*connect('add_mean', '0:mul_scale'),
*connect('scale', '1:mul_scale'),
*connect('mul_scale', 'result'),
])
argv = Namespace(mean_scale_values=[[
np.array([1., 2., 3.]),
np.array([1., 2., 3.])
]],
layout_values={
'': {
'source_layout': 'nchw',
'target_layout': None
}
})
graph = build_graph(nodes, [*connect('parameter', 'result')],
nodes_with_edges_only=True,
cli=argv)
self.set_graph_attrs(graph, ['parameter'])
self.set_graph_attrs(graph_ref, ['parameter'])
graph.graph['layout'] = 'NHWC'
AddMeanScaleValues().find_and_replace_pattern(graph)
(flag, resp) = compare_graphs(graph,
graph_ref,
'result',
check_op_attrs=True)
self.assertTrue(flag, resp)
self.check_graph_attrs(graph, graph_ref, ['parameter'])
def test_insert_add_mean_scale_after_convert_different_type(self):
graph_ref = build_graph(nodes, [
*connect('parameter', 'convert'),
*connect('convert', '0:add_mean'),
*connect('mean', '1:add_mean'),
*connect('add_mean', '0:mul_scale'),
*connect('scale', '1:mul_scale'),
*connect('mul_scale', 'result'),
])
argv = Namespace(mean_scale_values=[[
np.array([1., 2., 3.]),
np.array([1., 2., 3.])
]])
graph = build_graph(
nodes,
[*connect('parameter', 'convert'), *connect('convert', 'result')],
nodes_with_edges_only=True,
cli=argv)
graph.graph['layout'] = 'NCHW'
AddMeanScaleValues().find_and_replace_pattern(graph)
(flag, resp) = compare_graphs(graph,
graph_ref,
'result',
check_op_attrs=True)
self.assertTrue(flag, resp)
self.check_graph_attrs(graph, graph_ref, [])
add_node = graph.get_op_nodes(type="Add")[0]
self.assertTrue(
add_node.in_port(1).get_connection().get_source().node['value'].
dtype == np.float32)
def test_insert_add_mean_scale_after_convert(self):
graph_ref = build_graph(nodes, [
*connect('parameter', 'convert'),
*connect('convert', '0:add_mean'),
*connect('mean', '1:add_mean'),
*connect('add_mean', '0:mul_scale'),
*connect('scale', '1:mul_scale'),
*connect('mul_scale', 'result'),
])
argv = Namespace(mean_scale_values=[[
np.array([1., 2., 3.]),
np.array([1., 2., 3.])
]])
graph = build_graph(
nodes,
[*connect('parameter', 'convert'), *connect('convert', 'result')],
nodes_with_edges_only=True,
cli=argv)
graph.graph['layout'] = 'NCHW'
AddMeanScaleValues().find_and_replace_pattern(graph)
(flag, resp) = compare_graphs(graph,
graph_ref,
'result',
check_op_attrs=True)
self.assertTrue(flag, resp)
self.check_graph_attrs(graph, graph_ref, [])
def test_mean_values_with_colon_in_node_name_and_port(self):
graph_ref = build_graph(nodes, [
*connect('parameter', '0:add_mean'),
*connect('mean', '1:add_mean'),
*connect('add_mean', 'result'),
])
argv = Namespace(mean_scale_values={
'0:param:0': {
'scale': np.array([1.]),
'mean': np.array([1., 2., 3.])
}
})
graph = build_graph(nodes, [*connect('parameter', 'result')], {
'parameter': {
'name': 'param:0',
'id': 'param:0/placeholder_0',
'initial_node_name': 'param:0'
}
},
nodes_with_edges_only=True,
cli=argv)
self.set_graph_attrs(graph, ['parameter'])
self.set_graph_attrs(graph_ref, ['parameter'])
graph.graph['layout'] = 'NCHW'
AddMeanScaleValues().find_and_replace_pattern(graph)
(flag, resp) = compare_graphs(graph,
graph_ref,
'result',
check_op_attrs=True)
self.assertTrue(flag, resp)
def test_mean_values_optimized_and_scale_values_explicit(self):
graph_ref = build_graph(nodes, [
*connect('parameter', '0:mul_scale'),
*connect('scale', '1:mul_scale'),
*connect('mul_scale', 'result'),
])
argv = Namespace(
mean_scale_values={
'parameter': {
'scale': np.array([1., 2., 3.]),
'mean': np.array([0., 0., 0.])
}
})
graph = build_graph(nodes, [*connect('parameter', 'result')],
nodes_with_edges_only=True,
cli=argv)
self.set_graph_attrs(graph, ['parameter'])
self.set_graph_attrs(graph_ref, ['parameter'])
graph.graph['layout'] = 'NCHW'
AddMeanScaleValues().find_and_replace_pattern(graph)
(flag, resp) = compare_graphs(graph,
graph_ref,
'result',
check_op_attrs=True)
self.assertTrue(flag, resp)
self.check_graph_attrs(graph, graph_ref, ['parameter'])
def test_mean_values_explicit_and_scale_values_explicit_on_cutted_graph(self):
"""
Test case when user cutted start of the network and specified mean/scale value to the new input node 'node_3'.
"""
graph_ref = build_graph(nodes, [
*connect('parameter', '0:add_mean'),
*connect('mean', '1:add_mean'),
*connect('add_mean', 'result'),
*connect('parameter_2', '0:mul_scale'),
*connect('scale', '1:mul_scale'),
*connect('mul_scale', 'op'),
*connect('op', 'result_2'),
])
argv = Namespace(
mean_scale_values={'parameter': {'mean': np.array([1, 2, 3])}, 'op': {'scale': np.array([1, 2, 3])}})
graph = build_graph(
nodes, [*connect('parameter', 'result'), *connect('parameter_2', 'op'), *connect('op', 'result_2')],
{'parameter_2': {'initial_node_name': 'op'}}, nodes_with_edges_only=True, cli=argv)
self.set_graph_attrs(graph, ['parameter', 'parameter_2'])
self.set_graph_attrs(graph_ref, ['parameter', 'parameter_2'])
graph.graph['layout'] = 'NCHW'
AddMeanScaleValues().find_and_replace_pattern(graph)
(flag, resp) = compare_graphs(graph, graph_ref, 'result', check_op_attrs=True)
self.assertTrue(flag, resp)
(flag, resp) = compare_graphs(graph, graph_ref, 'result_2', check_op_attrs=True)
self.assertTrue(flag, resp)
self.check_graph_attrs(graph, graph_ref, ['parameter', 'parameter_2'])