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// Copyright 2018 Yahoo Holdings. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
#include "dense_add_dimension_optimizer.h"
#include "dense_replace_type_function.h"
#include <vespa/eval/eval/value_type.h>
#include <vespa/eval/eval/operation.h>
#include <vespa/eval/eval/value.h>
#include <vespa/log/log.h>
LOG_SETUP(".eval.tensor.dense.add_dimension_optimizer");
namespace vespalib::tensor {
using eval::ValueType;
using eval::TensorFunction;
using eval::as;
using namespace eval::tensor_function;
using namespace eval::operation;
namespace {
bool same_cell_type(const TensorFunction &a, const TensorFunction &b) {
return (a.result_type().cell_type() == b.result_type().cell_type());
}
bool is_unit_constant(const TensorFunction &node) {
if (auto const_value = as<ConstValue>(node)) {
for (const auto &dim: node.result_type().dimensions()) {
if (dim.size != 1) {
return false;
}
}
return (const_value->value().as_double() == 1.0);
}
return false;
}
} // namespace vespalib::tensor::<unnamed>
const TensorFunction &
DenseAddDimensionOptimizer::optimize(const eval::TensorFunction &expr, Stash &stash)
{
if (auto join = as<Join>(expr)) {
const TensorFunction &lhs = join->lhs();
const TensorFunction &rhs = join->rhs();
if ((join->function() == Mul::f) &&
lhs.result_type().is_dense() &&
rhs.result_type().is_dense())
{
if (is_unit_constant(lhs) && same_cell_type(rhs, expr)) {
return DenseReplaceTypeFunction::create_compact(expr.result_type(), rhs, stash);
}
if (is_unit_constant(rhs) && same_cell_type(lhs, expr)) {
return DenseReplaceTypeFunction::create_compact(expr.result_type(), lhs, stash);
}
}
}
return expr;
}
} // namespace vespalib::tensor
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