eliminate_concat.cpp 3.46 KB
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#include <iterator>
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#include <migraphx/eliminate_concat.hpp>
#include <migraphx/program.hpp>
#include <migraphx/instruction.hpp>
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#include <migraphx/op/load.hpp>
#include <migraphx/op/identity.hpp>
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#include <migraphx/iterator_for.hpp>
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#include <migraphx/ranges.hpp>
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#include <migraphx/dfor.hpp>
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namespace migraphx {
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inline namespace MIGRAPHX_INLINE_NS {
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void eliminate_concat::apply(program& p) const
{
    for(auto ins : iterator_for(p))
    {
        // Look for the concat operator
        if(ins->name() != concat_opt.name())
            continue;
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        // If any inputs are builtin or context free then abort
        // If any inputs are used more than once, then abort since there could
        // be errors due to aliasing
        if(std::any_of(ins->inputs().begin(), ins->inputs().end(), [](auto arg) {
               return arg->name().front() == '@' or
                      (arg->get_operator().is_context_free() and
                       not contains({"concat", "identity"}, arg->name())) or
                      arg->outputs().size() > 1;
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           }))
            continue;
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        // We can only do this optimization when concat axis is either the leftmost
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        // axis OR the sizes to the left of this axis are all equal to 1
        // Since we've already checked that the non-axis dimensions are identical
        // we only need to check the first input
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        auto lens      = ins->inputs().front()->get_shape().lens();
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        auto concat_op = concat_opt.get_concat(ins->get_operator());
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        if(concat_op.axis == 0 ||
           std::all_of(lens.begin(), lens.begin() + concat_op.axis, [](auto x) { return x == 1; }))
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        {
            // Last input should be an allocation
            auto last = ins->inputs().back();
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            if(last->name() != concat_opt.allocate())
                continue;
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            // Where are the allocations for the tensors to be concatenated?
            std::vector<instruction_ref> allocations;

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            std::transform(
                ins->inputs().begin(),
                std::prev(ins->inputs().end()),
                std::back_inserter(allocations),
                [&](instruction_ref x) { return instruction::get_output_alias(x, true); });
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            if(std::any_of(allocations.begin(), allocations.end(), [&](auto x) {
                   return x->name() != concat_opt.allocate();
               }))
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                continue;

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            // Need to sort the allocations, so that we know where to
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            // insert the "super"-allocation
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            std::sort(
                allocations.begin(), allocations.end(), [&](instruction_ref x, instruction_ref y) {
                    return std::distance(p.begin(), x) < std::distance(p.begin(), y);
                });
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            // Move "super" allocation to the front
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            auto first = allocations.front();
            auto super = p.move_instruction(last, first);
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            // Replace each allocation with a load
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            std::size_t offset = 0;
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            for(auto alloc : allocations)
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            {
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                op::load op{alloc->get_shape(), offset};
                p.replace_instruction(alloc, op, {super});
                offset += alloc->get_shape().bytes();
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            }
            std::vector<instruction_ref> args = {super};
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            std::copy(ins->inputs().begin(), ins->inputs().end() - 1, std::back_inserter(args));
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            p.replace_instruction(ins, migraphx::op::identity{}, args);
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        }
    }
}
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} // namespace MIGRAPHX_INLINE_NS
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} // namespace migraphx