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/*
* 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 "AveragePool.h"
#include "ONNXHelpers.h"
#include "mir/ops/PoolOp.h"
namespace mir_onnx
{
void AveragePoolNodeConverter::convert(const onnx::NodeProto &onnx_node,
ConverterContext *context) const
{
const auto opset_version = context->getOpsetVersion(onnx_node.domain());
if (opset_version >= 10)
convertV10(onnx_node, context);
else if (opset_version >= 7)
convertV7(onnx_node, context);
else if (opset_version >= 1)
convertV1(onnx_node, context);
else
throw std::runtime_error("Not supported opset version on Add operation!");
}
void AveragePoolNodeConverter::convertV1(const onnx::NodeProto &onnx_node,
ConverterContext *context) const
{
const auto auto_pad = getStringAttribute(onnx_node, "auto_pad", "NOTSET");
// auto_pad must be either NOTSET, SAME_UPPER, SAME_LOWER or VALID.
if (auto_pad != "NOTSET")
throw std::runtime_error("Supported only explicit padding!");
std::vector<mir::Operation::Output *> inputs = context->getNodeInputs(onnx_node);
mir::Graph *graph = context->getGraph();
mir::ops::PoolOp::BorderType border_type = mir::ops::PoolOp::BorderType::EMPTY;
mir::ops::PoolOp::PoolingType pool_type = mir::ops::PoolOp::PoolingType::AVG;
KernelStridesPadding cdata;
// Transpose ONNX NCHW to MIR NHWC
auto t_input = convertONNXToMIR(graph, inputs[0]);
getKernelStridesPadding(onnx_node, cdata);
auto result =
createOp<mir::ops::PoolOp>(graph, t_input, pool_type, cdata.kernel_shape, cdata.strides_shape,
cdata.padding_before, cdata.padding_after, border_type)
->getOutput(0);
result = convertMIRToONNX(graph, result);
context->setNodeOutputs(onnx_node, {result});
}
void AveragePoolNodeConverter::convertV7(const onnx::NodeProto &onnx_node,
ConverterContext *context) const
{
const auto count_include_pad = getIntAttribute(onnx_node, "count_include_pad", 0);
if (count_include_pad != 0)
throw std::runtime_error("Not supported count_include_pad attribute!");
convertV1(onnx_node, context);
}
void AveragePoolNodeConverter::convertV10(const onnx::NodeProto &onnx_node,
ConverterContext *context) const
{
const auto ceil_mode = getIntAttribute(onnx_node, "ceil_mode", 0);
if (ceil_mode != 0)
throw std::runtime_error("Not supported ceil_mode attribute!");
convertV7(onnx_node, context);
}
} // namespace mir_onnx
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