blob: 7eb2b183d053809778d9ed9457a7bb24febf503d (
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
|
/*
* Copyright (c) 2018 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 "Conv2DNode.h"
#include <cassert>
#include "NodeVisitor.h"
namespace neurun
{
namespace model
{
namespace operation
{
void Conv2DNode::accept(NodeVisitor &&v) const { v.visit(*this); }
Conv2DNode::Conv2DNode(const model::operation::Node::InitParam &init_param)
: model::operation::Node{OperandConstraint::createExact(3u)}
{
assert(init_param.input_count == 7 && init_param.output_count == 1);
// Each input should be interpreted as follows:
//
//
// 0 -> IFM Tensor Index
// 1 -> Kernel Tensor Index
// 2 -> Bias Tensor Index
// 3 -> Padding Code (ANEURALNETWORKS_PADDING_SAME or ANEURALNETWORKS_PADDING_VALID) Index
// 4 -> Stride (width) Index
// 5 -> Stride (height) INdex
// 6 -> Activation Index
setInputs({init_param.inputs[0], init_param.inputs[1], init_param.inputs[2]});
setOutputs({init_param.outputs[0]});
_param.padding_index = operand::Index{init_param.inputs[3]};
_param.hstride_index = operand::Index{init_param.inputs[4]};
_param.vstride_index = operand::Index{init_param.inputs[5]};
_param.activation_index = operand::Index{init_param.inputs[6]};
}
} // namespace operation
} // namespace model
} // namespace neurun
|
