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
|
/*
* 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 "Max.h"
#include "ONNXHelpers.h"
#include "mir/ops/MaxOp.h"
namespace mir_onnx
{
static void convertMaxGeneric(const onnx::NodeProto &onnx_node, ConverterContext *context)
{
std::vector<mir::Operation::Output *> inputs = context->getNodeInputs(onnx_node);
if (inputs.size() != 2)
{
throw std::runtime_error{"Unsupported number of inputs for Max operator"};
}
mir::Graph *graph = context->getGraph();
auto result = createOp<mir::ops::MaxOp>(graph, inputs[0], inputs[1])->getOutput(0);
context->setNodeOutputs(onnx_node, {result});
}
void convertMaxV1(const onnx::NodeProto &onnx_node, ConverterContext *context)
{
convertMaxGeneric(onnx_node, context);
}
void convertMaxV6(const onnx::NodeProto &onnx_node, ConverterContext *context)
{
convertMaxGeneric(onnx_node, context);
}
void convertMaxV8(const onnx::NodeProto &onnx_node, ConverterContext *context)
{
convertMaxGeneric(onnx_node, context);
}
} // namespace mir_onnx
|
