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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 "locoex/Service/COpShapeInferenceRule.h"
#include "locoex/COpDialect.h"
#include "locoex/COpNode.h"
#include "locoex/COpCall.h"
#include <loco/Service/ShapeInference.h>
#include <cassert>
namespace locoex
{
bool COpShapeInferenceRule::recognize(const loco::Dialect *d) const
{
return COpDialect::get() == d;
}
bool COpShapeInferenceRule::infer(const loco::Node *node, loco::NodeShape &shape) const
{
assert(node->dialect() == COpDialect::get());
assert(dynamic_cast<const COpNode *>(node) != nullptr);
auto cop_call = dynamic_cast<const COpCall *>(node);
// Note that the shape of custom op is considered as TensorShape
// TODO Decide how to deal with this shape error cases
for (uint32_t n = 0; n < cop_call->arity(); n++)
if (loco::shape_get(cop_call->input(n)).domain() != loco::Domain::Tensor)
throw std::runtime_error("Input of custom op must belong to Tensor domain.");
loco::TensorShape out_shape;
out_shape.rank(cop_call->rank());
for (uint32_t d = 0; d < cop_call->rank(); d++)
out_shape.dim(d) = cop_call->dim(d);
shape.set(out_shape);
return true;
}
} // namespace locoex
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