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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 "moco/Import/Nodes/AvgPool.h"
#include <moco/IR/Nodes/TFAvgPool.h>
#include <moco/Names.h>
#include "Convert.h"
#include <loco/IR/PermutingCodec.h>
#include <plier/tf/Convert.h>
#include <oops/UserExn.h>
#include <memory>
#include <cassert>
#include <stdexcept>
using namespace plier::tf;
namespace
{
using namespace moco;
class TFAvgPoolGraphUpdate final : public GraphUpdate
{
public:
TFAvgPoolGraphUpdate(TFAvgPool *node, const TensorName &name)
: _avgpool_node(node), _value_name(name)
{
}
void input(const SymbolTable *) const override;
private:
TFAvgPool *_avgpool_node;
const TensorName _value_name;
};
void TFAvgPoolGraphUpdate::input(const SymbolTable *node_table) const
{
loco::Node *value_node = node_table->node(_value_name);
_avgpool_node->value(value_node);
}
} // namespace
namespace moco
{
bool AvgPoolGraphBuilder::validate(const tensorflow::NodeDef &node) const
{
if (node.input_size() != 1)
return false;
// note: even though "data_format" is not entered when a model is written,
// TF seems to generate "data_format" field into a pb file
if (!plier::tf::has_attrs(node, {"T", "data_format", "ksize", "padding", "strides"}))
return false;
auto tf_ksize = get_list_attr(node, "ksize");
auto ksize = as_int64_list(tf_ksize);
if (ksize.size() != 4)
{
// TODO support ksize length for 1 and 2
throw oops::UserExn("AvgPool only supports ksize length 4", node.name());
}
auto tf_strides = get_list_attr(node, "strides");
auto strides = as_int64_list(tf_strides);
if (strides.size() != 4)
{
// TODO support strides length for 1 and 2
throw oops::UserExn("AvgPool only supports strides length 4", node.name());
}
return true;
}
void AvgPoolGraphBuilder::build(const tensorflow::NodeDef &node, GraphBuilderContext *context) const
{
assert(context != nullptr);
loco::Graph *graph = context->graph();
SymbolTable *tensor_names = context->tensor_names();
UpdateQueue *updates = context->updates();
// name of loco nodes
::std::string avgPool2d_name = node.name();
// tensorflow data_format: one of NHWC or NCHW.
auto data_layout = get_string_attr(node, "data_format");
auto avgPool_node = graph->nodes()->create<TFAvgPool>();
avgPool_node->name(node.name());
avgPool_node->data_layout(data_layout);
// padding
auto padding = moco::str_toupper(get_string_attr(node, "padding"));
avgPool_node->padding(padding);
// ksize
auto tf_ksize = get_list_attr(node, "ksize");
auto ksize = as_int64_list(tf_ksize);
avgPool_node->ksize(ksize);
// strides
auto tf_strides = get_list_attr(node, "strides");
auto strides = as_int64_list(tf_strides);
avgPool_node->strides(strides);
// To set the input node of encode_node with avgPool2d_name
TensorName output_name(avgPool2d_name, 0);
tensor_names->enroll(output_name, avgPool_node);
// Record ifm inputs to featureEncode_node
auto update = std::make_unique<TFAvgPoolGraphUpdate>(avgPool_node, TensorName(node.input(0)));
updates->enroll(std::move(update));
}
} // namespace moco
// TODO Consider a case when TF AvgPool is for 3D.
// AvgPool works for 2D and other Dimensions, such as 3D
// So, in future, some other GraphBuilder decide if AvgPoolGraphBuilder is used or
// other GraphBuilder is used for TF AvgPool
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