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Fixed mapping of input name #3737

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merged 10 commits into from
Dec 28, 2020
Merged

Fixed mapping of input name #3737

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4c9de6d
Fixed mapping of input name
popovaan Dec 24, 2020
e8844ae
Fixed unit tests
popovaan Dec 25, 2020
00a78fd
Fixed mapping of input name
popovaan Dec 24, 2020
06b548a
Fixed unit tests
popovaan Dec 25, 2020
db26058
Merge branch 'mapping_bug_fix' of https://github.com/popovaan/openvin…
popovaan Dec 25, 2020
81275ca
attributes check fix
popovaan Dec 28, 2020
b0f3663
Merge remote-tracking branch 'upstream/master' into mapping_bug_fix
popovaan Dec 28, 2020
459cacf
PEP8 code format
popovaan Dec 28, 2020
d93dbc2
code duplicate removal
popovaan Dec 28, 2020
3382a86
variable rename
popovaan Dec 28, 2020
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7 changes: 7 additions & 0 deletions model-optimizer/extensions/middle/AddMeanScaleValues.py
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Original file line number Diff line number Diff line change
Expand Up @@ -64,7 +64,14 @@ def insert_pre_processing(graph: Graph, input_node: Node, node_mean_scale_values

for dst in input_node.out_port(0).get_destinations():
if dst.node.soft_get('type') != 'ShapeOf':
# After the insertion of additional operations model optimizer
# should keep the link to the input layer. Parameter node in framework
# should map to parameter node in IR.
# For this reason 'fw_tensor_debug_info' should be kept in data node.
tmp = input_node.out_node(0)['fw_tensor_debug_info']
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dst.get_connection().set_source(preprocessing.out_port(0))
input_node.out_node(0)['fw_tensor_debug_info'] = tmp
del preprocessing.out_node(0)['fw_tensor_debug_info']

input_node.out_port(0).connect(preprocessing.in_port(0))

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73 changes: 71 additions & 2 deletions model-optimizer/extensions/middle/AddMeanScaleValues_test.py
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Original file line number Diff line number Diff line change
Expand Up @@ -24,6 +24,7 @@
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
from mo.graph.graph import Graph, Node
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nodes = {
**regular_op_with_shaped_data('parameter', [1, 3, 227, 227],
Expand All @@ -45,6 +46,25 @@


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'),
Expand All @@ -58,18 +78,21 @@ def test_mean_values_with_data_name(self):
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('')
Expand All @@ -78,11 +101,14 @@ def test_mean_values_without_data_name(self):

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, [
Expand All @@ -96,13 +122,16 @@ def test_mean_values_explicit_and_optimized(self):
'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, [
Expand All @@ -113,11 +142,14 @@ def test_mean_values_explicit_and_scale_values_optimized(self):

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, [
Expand All @@ -129,11 +161,14 @@ def test_mean_values_optimized_and_scale_values_explicit(self):
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, [
Expand All @@ -147,11 +182,14 @@ def test_mean_values_explicit_and_scale_values_explicit(self):
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):
"""
Expand All @@ -173,13 +211,16 @@ def test_mean_values_explicit_and_scale_values_explicit_on_cutted_graph(self):
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,
Expand All @@ -203,16 +244,38 @@ def test_mean_values_explicit_and_scale_values_explicit_with_shape_of(self):
*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'])


class ScaleInputTests(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_scale_input(self):
graph_ref = build_graph(nodes, [
*connect('parameter', '0:mul_scale'),
Expand All @@ -222,17 +285,23 @@ def test_scale_input(self):
'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.assertTrue(flag, resp)
self.check_graph_attrs(graph, graph_ref, ['parameter'])