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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 "SoftmaxCanonicalizer.h"
#include <moco/IR/TFDialect.h>
#include <moco/Support/TFShapeInferenceHelper.h>
#include <moco/Log.h>
namespace
{
bool canonicalize_softmax(loco::Graph *graph, moco::TFSoftmax *node)
{
LOGGER(l);
INFO(l) << "TFNodeCanonicalize TFSoftmax begin";
/**
* This will replace shape inferred TFSoftmax node into canonical TensorSoftmax
*
* Before
* In ---- TFSoftmax ---- Out(s)
*
* After
* ------ TFSoftmax
* /
* In ---- TensorSoftmax ----- Out(s)
*/
auto nodeshape = moco::node_shape(node);
// Canonicalization into TensorSoftmax is valid when softmax has shape info
assert(nodeshape.domain() != loco::Domain::Unknown);
auto softmax_tensor_shape = nodeshape.as<loco::TensorShape>();
// Create loco node to replace
auto softmax = graph->nodes()->create<loco::TensorSoftmax>();
// replace
auto in = node->logits();
softmax->input(in);
softmax->axis(softmax_tensor_shape.rank() - 1);
replace(node).with(softmax);
INFO(l) << "TFNodeCanonicalize TFSoftmax done";
return true;
}
} // namespace
namespace moco
{
namespace tf
{
bool SoftmaxCanonicalizer::transform(TFSoftmax *node) const
{
return canonicalize_softmax(node->graph(), node);
}
} // namespace tf
} // namespace moco
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