blob: da4af15c1e4954de844e47b2c3ad9fce3d2fe20b (
plain)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
|
/*
* Copyright (c) 2019 Samsung Electronics Co., Ltd. All Rights Reserved
*
* 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.
*/
#include <logo/ResolveRedundantReshapePass.h>
#include <loco/Service/ShapeInference.h>
#include <loco.h>
#include <cassert>
namespace
{
bool shape_inference_done(loco::FixedReshape *reshape)
{
return loco::shape_known(reshape) && loco::shape_known(reshape->input());
}
bool are_same_tensor_shapes(const loco::NodeShape &lhs, const loco::NodeShape &rhs)
{
assert(lhs.domain() == loco::Domain::Tensor);
assert(rhs.domain() == loco::Domain::Tensor);
auto lts = lhs.as<loco::TensorShape>();
auto rts = rhs.as<loco::TensorShape>();
if (lts.rank() != rts.rank())
return false;
for (uint32_t axis = 0; axis < lts.rank(); ++axis)
{
assert(lts.dim(axis).known());
assert(rts.dim(axis).known());
if (lts.dim(axis).value() != rts.dim(axis).value())
return false;
}
return true;
}
/// @return true when 'reshape' has same input and output shape
bool is_redundant_reshape(loco::FixedReshape *reshape)
{
auto input_shape = loco::shape_get(reshape->input());
auto output_shape = loco::shape_get(reshape);
// Note that FixedReshape's input and output are always tensor
return are_same_tensor_shapes(input_shape, output_shape);
}
} // namespace
namespace logo
{
/**
* @brief Bypass redundant FixedReshape
*
* Before:
*
* In ----- FixedReshape ----- [Out]*
*
* After:
*
* In ------------------------ [Out]*
* \
* ------ FixedReshape
*/
bool ResolveRedundantReshapePass::run(loco::Graph *graph)
{
bool changed = false;
for (auto node : loco::postorder_traversal(loco::output_nodes(graph)))
{
if (auto reshape = dynamic_cast<loco::FixedReshape *>(node))
{
if (shape_inference_done(reshape))
{
if (is_redundant_reshape(reshape))
{
replace(reshape).with(reshape->input());
changed = true;
}
}
}
}
return changed;
}
} // namespace logo
|
