306 lines
14 KiB
Python
306 lines
14 KiB
Python
"""
|
|
Copyright (C) 2018-2020 Intel Corporation
|
|
|
|
Licensed under the Apache License, Version 2.0 (the "License");
|
|
you may not use this file except in compliance with the License.
|
|
You may obtain a copy of the License at
|
|
|
|
http://www.apache.org/licenses/LICENSE-2.0
|
|
|
|
Unless required by applicable law or agreed to in writing, software
|
|
distributed under the License is distributed on an "AS IS" BASIS,
|
|
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
|
See the License for the specific language governing permissions and
|
|
limitations under the License.
|
|
"""
|
|
import unittest
|
|
from argparse import Namespace
|
|
|
|
import numpy as np
|
|
|
|
from extensions.middle.AddMeanScaleValues import AddMeanScaleValues
|
|
from extensions.middle.ScaleInput import ScaleInput
|
|
from mo.graph.graph import Graph, Node
|
|
from mo.utils.cli_parser import get_mean_scale_dictionary, parse_tuple_pairs
|
|
from mo.utils.ir_engine.compare_graphs import compare_graphs
|
|
from mo.utils.unittest.graph import build_graph, regular_op_with_shaped_data, result, connect, connect_data, \
|
|
valued_const_with_data
|
|
|
|
nodes = {
|
|
**regular_op_with_shaped_data('parameter', [1, 3, 227, 227],
|
|
{'type': 'Parameter', 'op': 'Parameter', 'shape': [1, 3, 227, 227]}),
|
|
**regular_op_with_shaped_data('parameter_2', [1, 3, 227, 227],
|
|
{'type': 'Parameter', 'op': 'Parameter', 'shape': [1, 3, 227, 227]}),
|
|
|
|
**regular_op_with_shaped_data('mul_scale', [1, 3, 227, 227], {'type': 'Multiply', 'op': 'Mul'}),
|
|
**regular_op_with_shaped_data('add_mean', [1, 3, 227, 227], {'type': 'Add', 'op': 'Add'}),
|
|
|
|
**valued_const_with_data('scale', np.array([1. / 1., 1. / 2., 1. / 3.]).reshape((1, 3, 1, 1))),
|
|
**valued_const_with_data('mean', np.array([-1., -2., -3.]).reshape((1, 3, 1, 1))),
|
|
|
|
**regular_op_with_shaped_data('shape_of', [4], {'type': 'ShapeOf', 'op': 'ShapeOf'}),
|
|
**regular_op_with_shaped_data('op', [1, 3, 227, 227], {}),
|
|
**result('result'),
|
|
**result('result_2'),
|
|
}
|
|
|
|
|
|
class AddMeanScaleValuesTest(unittest.TestCase):
|
|
def check_graph_attrs(self, graph: Graph, graph_ref: Graph, parameter_node_names: list):
|
|
for node in graph.get_op_nodes():
|
|
if node.soft_get('name') in parameter_node_names:
|
|
self.assertTrue(node.soft_get('type') == 'Parameter')
|
|
out_node = node.out_node(0)
|
|
out_node_ref = Node(graph_ref, node.id).out_node(0)
|
|
self.assertTrue(out_node['fw_tensor_debug_info'] == out_node_ref['fw_tensor_debug_info'])
|
|
else:
|
|
if 0 in node.out_nodes():
|
|
out_node = node.out_node(0)
|
|
self.assertFalse('fw_tensor_debug_info' in out_node)
|
|
|
|
def set_graph_attrs(self, graph: Graph, parameter_node_names: list):
|
|
for node in graph.get_op_nodes():
|
|
if node.soft_get('name') in parameter_node_names:
|
|
self.assertTrue(node.soft_get('type') == 'Parameter')
|
|
out_node = node.out_node(0)
|
|
out_node['fw_tensor_debug_info'] = ['fw_name', 0]
|
|
|
|
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_without_data_name(self):
|
|
graph_ref = build_graph(nodes, [
|
|
*connect('parameter', '0:add_mean'),
|
|
*connect('mean', '1:add_mean'),
|
|
*connect('add_mean', 'result'),
|
|
], {'parameter': {'name': 'None'}})
|
|
|
|
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')], {'parameter': {'name': 'None'}},
|
|
nodes_with_edges_only=True, cli=argv)
|
|
self.set_graph_attrs(graph, ['None'])
|
|
self.set_graph_attrs(graph_ref, ['None'])
|
|
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, ['None'])
|
|
|
|
def test_mean_values_explicit_and_optimized(self):
|
|
graph_ref = build_graph(nodes, [
|
|
*connect('parameter', '0:add_mean'),
|
|
*connect('mean', '1:add_mean'),
|
|
*connect('add_mean', 'result'),
|
|
*connect('parameter_2', 'result_2'),
|
|
])
|
|
|
|
argv = Namespace(mean_scale_values={'parameter': {'mean': np.array([1., 2., 3.])},
|
|
'parameter_2': {'mean': np.array([0., 0., 0.])}})
|
|
graph = build_graph(nodes, [*connect('parameter', 'result'), *connect('parameter_2', 'result_2')],
|
|
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'])
|
|
|
|
def test_mean_values_explicit_and_scale_values_optimized(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={'parameter': {'scale': np.array([1.]), 'mean': np.array([1., 2., 3.])}})
|
|
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_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(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.])]])
|
|
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'])
|
|
|
|
def test_mean_values_explicit_and_scale_values_explicit_with_shape_of(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'),
|
|
*connect_data('parameter', 'shape_of'),
|
|
*connect('shape_of', 'result_2'),
|
|
],
|
|
nodes_with_edges_only=True)
|
|
|
|
argv = Namespace(
|
|
mean_scale_values={'parameter': {'mean': np.array([1, 2, 3]), 'scale': np.array([1, 2, 3])}})
|
|
graph = build_graph(nodes,
|
|
[
|
|
*connect('parameter', 'result'),
|
|
*connect_data('parameter', 'shape_of'),
|
|
*connect('shape_of', 'result_2'),
|
|
],
|
|
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)
|
|
(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'])
|
|
|
|
def test_scale_input(self):
|
|
graph_ref = build_graph(nodes, [
|
|
*connect('parameter', '0:mul_scale'),
|
|
*connect('scale', '1:mul_scale'),
|
|
*connect('mul_scale', 'result'),
|
|
], {'scale': {'shape': [1, 1, 1, 1], 'value': np.array(1 / 255)},
|
|
'scale_d': {'shape': [1, 1, 1, 1], 'value': np.array(1 / 255)}})
|
|
|
|
graph = build_graph(nodes, connect('parameter', 'result'), nodes_with_edges_only=True, cli=Namespace(scale=255))
|
|
self.set_graph_attrs(graph, ['parameter'])
|
|
self.set_graph_attrs(graph_ref, ['parameter'])
|
|
graph.graph['layout'] = 'NCHW'
|
|
|
|
ScaleInput().find_and_replace_pattern(graph)
|
|
(flag, resp) = compare_graphs(graph, graph_ref, 'result')
|
|
self.assertTrue(flag, resp)
|
|
self.check_graph_attrs(graph, graph_ref, ['parameter'])
|
|
|
|
def test_scale_input_2(self):
|
|
graph_ref = build_graph(nodes, connect('parameter', 'result'), nodes_with_edges_only=True)
|
|
graph = build_graph(nodes, connect('parameter', 'result'), nodes_with_edges_only=True, cli=Namespace(scale=1))
|
|
self.set_graph_attrs(graph, ['parameter'])
|
|
self.set_graph_attrs(graph_ref, ['parameter'])
|
|
graph.graph['layout'] = 'NCHW'
|
|
|
|
ScaleInput().find_and_replace_pattern(graph)
|
|
(flag, resp) = compare_graphs(graph, graph_ref, 'result')
|
|
self.assertTrue(flag, resp)
|
|
self.check_graph_attrs(graph, graph_ref, ['parameter'])
|
|
|
|
def test_debug_info_absence(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.])]])
|
|
graph = build_graph(nodes, [*connect('parameter', '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, [])
|