Function update_pooling

src/insert_pad.cpp:73–106

}

static void update_pooling(const instruction_ref& input, const instruction_ref& ins, module& m)
{
    auto op = any_cast<op::pooling>(ins->get_operator());
    if(op.mode == op::pooling_mode::average)
    {
        return;
    }
    auto kdims = input->get_shape().ndim() - 2;
    if(std::equal(op.padding.begin(),
                  op.padding.begin() + kdims,
                  op.padding.begin() + kdims,
                  op.padding.end()))
        return;

    std::vector<int64_t> padding(input->get_shape().ndim() * 2, 0);
    std::vector<size_t> pads_l(op.padding.begin(), op.padding.begin() + kdims);
    std::vector<size_t> pads_r(op.padding.begin() + kdims, op.padding.end());
    op.padding = std::vector<size_t>(kdims * 2, 0);
    std::copy(pads_l.begin(), pads_l.end(), padding.begin() + 2);
    std::copy(pads_r.begin(), pads_r.end(), padding.begin() + kdims + 2 + 2);

    float pad_val = 0.0f; // for the lpnorm
    if(op.mode == op::pooling_mode::max)
    {
        // maxpool uses lowest value for padding
        pad_val = std::numeric_limits<float>::lowest();
    }
    auto pad_op   = m.insert_instruction(ins, op::pad{padding, pad_val}, input);

    auto new_inputs    = ins->inputs();
    new_inputs.front() = pad_op;

    m.replace_instruction(ins, op, new_inputs);
}

void insert_pad::apply(module& m) const
{