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Fix pad op with int input (#4438)

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* Added operation ConvertLike to the MO

* Fixed transformations with Pad which insert Const with pad value of incorrect type

* Added constant folding to ConvertLike operation

* Fixed unit tests for Pad transformations to include ConverLike operations

* Update copyright year

* nGraph code style fix

* Added OV_ITT_SCOPED_TASK for ConvertLike constant folding
This commit is contained in:
Evgeny Lazarev
2021-02-24 09:56:36 +03:00
committed by GitHub
parent 4d9797c1fe
commit 7420bb6cb0
8 changed files with 91 additions and 12 deletions
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1
model-optimizer/automation/package_BOM.txt
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@@ -639,6 +639,7 @@ extensions/ops/box_nms.py
extensions/ops/bucketize.py
extensions/ops/Cast.py
extensions/ops/constant_fill.py
extensions/ops/ConvertLike.py
extensions/ops/copyop.py
extensions/ops/correlation.py
extensions/ops/ctc_greedy_decoder.py

10
model-optimizer/extensions/front/AttributedPadToPad.py
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@@ -1,5 +1,5 @@
"""
Copyright (C) 2020 Intel Corporation
Copyright (C) 2018-2021 Intel Corporation
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
@@ -14,7 +14,9 @@
limitations under the License.
"""
from extensions.ops.ConvertLike import ConvertLike
from mo.front.common.replacement import FrontReplacementPattern
from mo.front.tf.graph_utils import create_op_with_const_inputs
from mo.graph.graph import Graph, rename_nodes
from mo.ops.const import Const
from mo.ops.pad import Pad
@@ -39,7 +41,11 @@ class AttributedPadToPad(FrontReplacementPattern):
new_pad.in_port(1).connect(Const(graph, {'value': attr_pad.pads[:, 0]}).create_node().out_port(0))
new_pad.in_port(2).connect(Const(graph, {'value': attr_pad.pads[:, 1]}).create_node().out_port(0))
if attr_pad.soft_get('mode') == 'constant':
new_pad.in_port(3).connect(Const(graph, {'value': attr_pad.fill_value}).create_node().out_port(0))
# create Constant node of proper data type (equal to the data type of the Pad first input)
convert_pad_value = create_op_with_const_inputs(graph, ConvertLike, {0: attr_pad.fill_value},
{'name': original_name + '/pad_value_convert'})
convert_pad_value.in_port(1).connect(new_pad.in_port(0).get_source())
new_pad.in_port(3).connect(convert_pad_value.out_port(0))
attr_pad.out_port(0).get_connection().set_source(new_pad.out_port(0))
graph.remove_node(attr_pad.id)

7
model-optimizer/extensions/front/AttributedPadToPad_test.py
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@@ -1,5 +1,5 @@
"""
Copyright (C) 2018-2020 Intel Corporation
Copyright (C) 2018-2021 Intel Corporation
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
@@ -31,6 +31,7 @@ nodes_attributes = {
# new Pad layer and inputs
'pad': {'type': 'Pad', 'kind': 'op', 'op': 'Pad', 'mode': 'constant'},
'convert_like': {'type': 'ConvertLike', 'kind': 'op', 'op': 'ConvertLike'},
**const('pad_begin', int64_array([1, 3, 5])),
**const('pad_end', int64_array([2, 4, 6])),
**const('pad_fill', np.array(0.75)),
@@ -49,7 +50,9 @@ class AttributedPadToPadTest(unittest.TestCase):
[('placeholder', 'pad', {'in': 0, 'out': 0}),
('pad_begin', 'pad', {'in': 1, 'out': 0}),
('pad_end', 'pad', {'in': 2, 'out': 0}),
('pad_fill', 'pad', {'in': 3, 'out': 0}),
('pad_fill', 'convert_like', {'in': 0, 'out': 0}),
('placeholder', 'convert_like', {'in': 1, 'out': 0}),
('convert_like', 'pad', {'in': 3, 'out': 0}),
('pad', 'result')
],
{}, nodes_with_edges_only=True)

11
model-optimizer/extensions/front/tf/pad_tf_to_pad.py
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@@ -1,5 +1,5 @@
"""
Copyright (C) 2020 Intel Corporation
Copyright (C) 2018-2021 Intel Corporation
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
@@ -13,13 +13,13 @@
See the License for the specific language governing permissions and
limitations under the License.
"""
from extensions.ops.ConvertLike import ConvertLike
from extensions.ops.split import Split
from extensions.ops.transpose import Transpose
from mo.front.common.partial_infer.utils import int64_array
from mo.front.common.replacement import FrontReplacementPattern
from mo.front.tf.graph_utils import create_op_with_const_inputs
from mo.graph.graph import Graph, rename_node
from mo.ops.const import Const
from mo.ops.pad import Pad
from mo.ops.squeeze import Squeeze
@@ -47,8 +47,11 @@ class PadTFToPad(FrontReplacementPattern):
if not tfpad.in_port(2).disconnected():
tfpad.in_port(2).get_connection().set_destination(new_pad.in_port(3))
else:
new_pad.in_port(3).connect(Const(graph, {'value': 0.0, 'name': new_pad.name + '/value'}
).create_node().out_port(0))
# create Constant node of proper data type (equal to the data type of the Pad first input)
convert_pad_value = create_op_with_const_inputs(graph, ConvertLike, {0: 0.0},
{'name': original_name + '/pad_value_convert'})
convert_pad_value.in_port(1).connect(new_pad.in_port(0).get_source())
new_pad.in_port(3).connect(convert_pad_value.out_port(0))
# convert TF representation of the pads as [N, 2] to MO representation: [N] and [N]
transposed_pads = create_op_with_const_inputs(graph, Transpose, {1: int64_array([1, 0])})

11
model-optimizer/extensions/front/tf/pad_tf_to_pad_test.py
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@@ -1,5 +1,5 @@
"""
Copyright (C) 2018-2020 Intel Corporation
Copyright (C) 2018-2021 Intel Corporation
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
@@ -19,7 +19,7 @@ import unittest
import numpy as np
from extensions.front.tf.pad_tf_to_pad import PadTFToPad
from mo.front.common.partial_infer.utils import int64_array
from mo.front.common.partial_infer.utils import int64_array, float_array
from mo.utils.ir_engine.compare_graphs import compare_graphs
from mo.utils.unittest.graph import build_graph, const
@@ -27,7 +27,7 @@ nodes_attributes = {
'placeholder': {'shape': None, 'type': 'Parameter', 'kind': 'op', 'op': 'Parameter'},
'tfpad': {'type': None, 'kind': 'op', 'op': 'TFPad', 'mode': 'constant', 'name': 'tfpad_name'},
**const('paddings', int64_array([1, 2, 3, 4, 5, 6]).reshape([3, 2])),
**const('fill', int64_array(5.75)),
**const('fill', float_array(5.75)),
'result': {'type': 'Result', 'value': None, 'kind': 'op', 'op': 'Result'},
# new Pad layer and sub-graph
@@ -40,6 +40,7 @@ nodes_attributes = {
**const('squeeze_1_axis', int64_array([0])),
'squeeze_2': {'type': 'Squeeze', 'kind': 'op', 'op': 'Squeeze'},
**const('squeeze_2_axis', int64_array([0])),
'convert_like': {'type': 'ConvertLike', 'kind': 'op', 'op': 'ConvertLike'},
**const('pad_fill', np.array(0.0)),
}
@@ -86,7 +87,9 @@ class PadTFToPadTest(unittest.TestCase):
{}, nodes_with_edges_only=True)
graph.get_op_nodes(op='TFPad')[0].add_input_port(2)
graph_ref = build_graph(nodes_attributes, common_edges + [('pad_fill', 'pad', {'in': 3, 'out': 0})],
graph_ref = build_graph(nodes_attributes, common_edges + [('pad_fill', 'convert_like', {'in': 0, 'out': 0}),
('placeholder', 'convert_like', {'in': 1, 'out': 0}),
('convert_like', 'pad', {'in': 3, 'out': 0})],
{}, nodes_with_edges_only=True)
self._run_test(graph, graph_ref)

44
model-optimizer/extensions/ops/ConvertLike.py Normal file
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@@ -0,0 +1,44 @@
"""
Copyright (C) 2018-2021 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.
"""
from mo.front.common.partial_infer.elemental import copy_shape_infer
from mo.graph.graph import Node, Graph
from mo.ops.op import Op
class ConvertLike(Op):
op = 'ConvertLike'
enabled = False
def __init__(self, graph: Graph, attrs: dict):
mandatory_props = {
'op': self.op,
'type': self.op,
'version': 'opset1',
'infer': copy_shape_infer,
'type_infer': self.type_infer,
'in_ports_count': 2,
'out_ports_count': 1,
}
super().__init__(graph, mandatory_props, attrs)
@staticmethod
def type_infer(node: Node):
assert node.is_in_port_connected(1), 'The second input is not connected for a node {}.' \
''.format(node.soft_get('name'), node.id)
node.out_port(0).set_data_type(node.in_port(1).get_data_type())

3
ngraph/core/include/ngraph/op/convert_like.hpp
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@@ -42,6 +42,9 @@ namespace ngraph
virtual std::shared_ptr<Node>
clone_with_new_inputs(const OutputVector& new_args) const override;
bool constant_fold(OutputVector& output_values,
const OutputVector& input_values) override;
};
} // namespace v1

16
ngraph/core/src/op/convert_like.cpp
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@@ -17,6 +17,8 @@
#include <memory>
#include "itt.hpp"
#include "ngraph/op/constant.hpp"
#include "ngraph/op/convert.hpp"
#include "ngraph/op/convert_like.hpp"
using namespace std;
@@ -48,3 +50,17 @@ shared_ptr<Node> op::v1::ConvertLike::clone_with_new_inputs(const OutputVector&
check_new_args_count(this, new_args);
return make_shared<ConvertLike>(new_args.at(0), new_args.at(1));
}
bool op::v1::ConvertLike::constant_fold(OutputVector& output_values,
const OutputVector& input_values)
{
OV_ITT_SCOPED_TASK(itt::domains::nGraph, "op::v1::ConvertLike::constant_fold");
if (auto data_const =
std::dynamic_pointer_cast<op::Constant>(input_values[0].get_node_shared_ptr()))
{
auto convert = make_shared<Convert>(input_values[0], input_values[1].get_element_type());
convert->constant_fold(output_values, OutputVector{data_const});
return true;
}
return false;
}