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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 "RsqrtCanonicalizer.h"
#include <moco/IR/TFDialect.h>
#include <moco/Support/TFShapeInferenceHelper.h>
#include <moco/Log.h>
#include <loco/Service/TypeInference.h>
#include <oops/UserExn.h>
namespace
{
template <typename T>
bool prepare_const_gen(loco::ConstGen *const_node, const loco::TensorShape &tensorshape, T value);
template <>
bool prepare_const_gen<float>(loco::ConstGen *const_node, const loco::TensorShape &tensorshape,
float value)
{
LOGGER(l);
uint32_t const_num_elements = 1;
auto dtype = loco::DataType::FLOAT32;
const_node->dtype(dtype);
auto rank = tensorshape.rank();
const_node->rank(rank);
for (uint32_t r = 0; r < rank; ++r)
{
if (tensorshape.dim(r).known())
const_node->dim(r) = tensorshape.dim(r);
else
return false;
assert(tensorshape.dim(r).value() > 0);
const_num_elements *= tensorshape.dim(r).value();
}
INFO(l) << "prepare_const_gen : Elements = " << const_num_elements;
const_node->size<loco::DataType::FLOAT32>(const_num_elements);
for (uint32_t i = 0; i < const_num_elements; ++i)
{
const_node->at<loco::DataType::FLOAT32>(i) = value;
}
return true;
}
bool canonicalize_rsqrt(loco::Graph *graph, moco::TFRsqrt *node)
{
/**
* @note This will replace TFRsqrt node with Canonical EltwiseSqrt + EltwiseRealDiv
*
* Before
* A --- TFRsqrt -- C
* After
* +- TFRsqrt --
* |
* | ConstGen --+
* | \
* A -+- EltwiseSqrt -- EltwiseDiv -- C
*
* Where
* A : features of TFRsqrt
* C : a node that uses TFSqrt as an input
* TFRsqrt is disconnected from C
* TFRsqrt is converted to 1 / EltwiseSqrt
*/
auto nodeshape = moco::node_shape(node);
if (nodeshape.domain() == loco::Domain::Unknown)
{
// We need this shape information
assert(false); // this shouldn't happen, let's add an alarm
return false;
}
auto tensorshape = nodeshape.as<loco::TensorShape>();
if (!loco::dtype_known(node))
{
// We need type of this node
return false;
}
auto sqrt_node = graph->nodes()->create<loco::EltwiseSqrt>();
auto eltdiv_node = graph->nodes()->create<loco::EltwiseDiv>();
auto const_node = graph->nodes()->create<loco::ConstGen>();
auto dtype = loco::dtype_get(node);
switch (dtype)
{
case loco::DataType::FLOAT32:
if (!prepare_const_gen<float>(const_node, tensorshape, 1.0f))
throw oops::UserExn("Cannot handle unknown shape", node->name());
break;
default:
throw oops::UserExn("Unsupported data type", node->name());
}
auto node_A = node->x();
// update connections
sqrt_node->input(node_A);
eltdiv_node->lhs(const_node);
eltdiv_node->rhs(sqrt_node);
// replace node
replace(node).with(eltdiv_node);
return true;
}
} // namespace
namespace moco
{
namespace tf
{
bool RsqrtCanonicalizer::transform(TFRsqrt *node) const
{
return canonicalize_rsqrt(node->graph(), node);
}
} // namespace tf
} // namespace moco
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