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#include "cpu/nematus/model.h"
namespace amunmt {
namespace CPU {
namespace Nematus {
Weights::Transition::Transition(const NpzConverter& model, TransitionType type, std::string prefix,
std::string infix)
: depth_(findTransitionDepth(model, prefix, infix)), type_(type)
{
for (int i = 1; i <= depth_; ++i) {
U_.emplace_back(model[name(prefix, "U", infix, i)]);
Ux_.emplace_back(model[name(prefix, "Ux", infix, i)]);
B_.emplace_back(model(name(prefix, "b", infix, i), true));
U_lns_.emplace_back(model[name(prefix, "U", infix, i, "_lns")]);
U_lnb_.emplace_back(model[name(prefix, "U", infix, i, "_lnb")]);
Ux_lns_.emplace_back(model[name(prefix, "Ux", infix, i, "_lns")]);
Ux_lnb_.emplace_back(model[name(prefix, "Ux", infix, i, "_lnb")]);
switch(type) {
case TransitionType::Encoder:
Bx1_.emplace_back(1, Ux_.back().dim(1));
const_cast<mblas::Matrix&>(Bx1_.back()) = 0.0f;
Bx2_.emplace_back(model(name(prefix, "bx", infix, i), true));
break;
case TransitionType::Decoder:
Bx1_.emplace_back(model(name(prefix, "bx", infix, i), true));
Bx2_.emplace_back(1, Ux_.back().dim(1));
const_cast<mblas::Matrix&>(Bx2_.back()) = 0.0f;
break;
}
}
}
int Weights::Transition::findTransitionDepth(const NpzConverter& model, std::string prefix, std::string infix) {
int currentDepth = 0;
while (true) {
if (model.has(prefix + "b" + infix + "_drt_" + std::to_string(currentDepth + 1))) {
++currentDepth;
} else {
break;
}
}
std::cerr << "Found transition depth: " << currentDepth << std::endl;
return currentDepth;
}
int Weights::Transition::size() const {
return depth_;
}
Weights::Transition::TransitionType Weights::Transition::type() const {
return type_;
}
std::string Weights::Transition::name(const std::string& prefix, std::string name, std::string infix,
int index, std::string suffix)
{
return prefix + name + infix + "_drt_" + std::to_string(index) + suffix;
}
Weights::Embeddings::Embeddings(const NpzConverter& model, const std::vector<std::pair<std::string, bool>> keys)
: E_(model.getFirstOfMany(keys))
{}
Weights::GRU::GRU(const NpzConverter& model, std::string prefix, std::vector<std::string> keys)
: W_(model[prefix + keys.at(0)]),
B_(model(prefix + keys.at(1), true)),
U_(model[prefix + keys.at(2)]),
Wx_(model[prefix + keys.at(3)]),
Bx1_(model(prefix + keys.at(4), true)),
Bx2_(Bx1_.rows(), Bx1_.columns()),
Bx3_(B_.rows(), B_.columns()),
Ux_(model[prefix + keys.at(5)]),
W_lns_(model[prefix + keys.at(6)]),
W_lnb_(model[prefix + keys.at(7)]),
Wx_lns_(model[prefix + keys.at(8)]),
Wx_lnb_(model[prefix + keys.at(9)]),
U_lns_(model[prefix + keys.at(10)]),
U_lnb_(model[prefix + keys.at(11)]),
Ux_lns_(model[prefix + keys.at(12)]),
Ux_lnb_(model[prefix + keys.at(13)])
{
const_cast<mblas::Matrix&>(Bx2_) = 0.0f;
const_cast<mblas::Matrix&>(Bx3_) = 0.0f;
}
//////////////////////////////////////////////////////////////////////////////
Weights::DecInit::DecInit(const NpzConverter& model)
: Wi_(model["ff_state_W"]),
Bi_(model("ff_state_b", true)),
lns_(model["ff_state_ln_s"]),
lnb_(model["ff_state_ln_b"])
{}
Weights::DecGRU2::DecGRU2(const NpzConverter& model, std::string prefix, std::vector<std::string> keys)
: W_(model[prefix + keys.at(0)]), // Wc
B_(1, W_.dim(1)),
U_(model[prefix + keys.at(1)]), // U_nl
Bx3_(model(prefix + keys.at(2), true)), // b_nl
Wx_(model[prefix + keys.at(3)]), // Wcx
Bx1_(1, Wx_.dim(1)),
Ux_(model[prefix + keys.at(4)]), // Ux_nl
Bx2_(model(prefix + keys.at(5), true)), // bx_nl
W_lns_(model[prefix + keys.at(6)]), // Wc_lns
W_lnb_(model[prefix + keys.at(7)]), // Wc_nlb
Wx_lns_(model[prefix + keys.at(8)]), // Wcx_lns
Wx_lnb_(model[prefix + keys.at(9)]), // Wcx_lnb
U_lns_(model[prefix + keys.at(10)]), // U_nl_lns
U_lnb_(model[prefix + keys.at(11)]), // U_nl_lnb
Ux_lns_(model[prefix + keys.at(12)]), // Ux_nl_lns
Ux_lnb_(model[prefix + keys.at(13)]) // Ux_nl_lnb
{
const_cast<mblas::Matrix&>(B_) = 0.0f;
const_cast<mblas::Matrix&>(Bx1_) = 0.0f;
}
Weights::DecAttention::DecAttention(const NpzConverter& model)
: V_(model("decoder_U_att", true)),
W_(model["decoder_W_comb_att"]),
B_(model("decoder_b_att", true)),
U_(model["decoder_Wc_att"]),
C_(model["decoder_c_tt"]),
Wc_att_lns_(model["decoder_Wc_att_lns"]),
Wc_att_lnb_(model["decoder_Wc_att_lnb"]),
W_comb_lns_(model["decoder_W_comb_att_lns"]),
W_comb_lnb_(model["decoder_W_comb_att_lnb"])
{}
Weights::DecSoftmax::DecSoftmax(const NpzConverter& model)
: W1_(model["ff_logit_lstm_W"]),
B1_(model("ff_logit_lstm_b", true)),
W2_(model["ff_logit_prev_W"]),
B2_(model("ff_logit_prev_b", true)),
W3_(model["ff_logit_ctx_W"]),
B3_(model("ff_logit_ctx_b", true)),
W4_(model.getFirstOfMany({std::make_pair(std::string("ff_logit_W"), false),
std::make_pair(std::string("Wemb_dec"), true),
std::make_pair(std::string("Wemb"), true)})),
B4_(model("ff_logit_b", true)),
lns_1_(model["ff_logit_lstm_ln_s"]),
lns_2_(model["ff_logit_prev_ln_s"]),
lns_3_(model["ff_logit_ctx_ln_s"]),
lnb_1_(model["ff_logit_lstm_ln_b"]),
lnb_2_(model["ff_logit_prev_ln_b"]),
lnb_3_(model["ff_logit_ctx_ln_b"])
{}
//////////////////////////////////////////////////////////////////////////////
Weights::Weights(const NpzConverter& model, size_t)
: encEmbeddings_(model, std::vector<std::pair<std::string, bool>>(
{std::make_pair(std::string("Wemb"), false),
std::make_pair(std::string("Wemb_dec"), false)})),
decEmbeddings_(model, std::vector<std::pair<std::string, bool>>(
{std::make_pair(std::string("Wemb_dec"), false),
std::make_pair(std::string("Wemb"), false)})),
encForwardGRU_(model, "encoder_", {"W", "b", "U", "Wx", "bx", "Ux", "W_lns", "W_lnb", "Wx_lns",
"Wx_lnb", "U_lns", "U_lnb", "Ux_lns", "Ux_lnb" }),
encBackwardGRU_(model, "encoder_r_", {"W", "b", "U", "Wx", "bx", "Ux", "W_lns", "W_lnb",
"Wx_lns", "Wx_lnb", "U_lns", "U_lnb", "Ux_lns", "Ux_lnb" }),
decInit_(model),
decGru1_(model, "decoder_", {"W", "b", "U", "Wx", "bx", "Ux", "W_lns", "W_lnb", "Wx_lns",
"Wx_lnb", "U_lns", "U_lnb", "Ux_lns", "Ux_lnb" }),
decGru2_(model, "decoder_", {"Wc", "U_nl", "b_nl", "Wcx", "Ux_nl", "bx_nl", "Wc_lns", "Wc_lnb",
"Wcx_lns", "Wcx_lnb", "U_nl_lns", "U_nl_lnb", "Ux_nl_lns",
"Ux_nl_lnb"}),
decAttention_(model),
decSoftmax_(model),
encForwardTransition_(model, Weights::Transition::TransitionType::Encoder, "encoder_"),
encBackwardTransition_(model,Weights::Transition::TransitionType::Encoder, "encoder_r_"),
decTransition_(model, Weights::Transition::TransitionType::Decoder, "decoder_", "_nl")
{}
} // namespace Nematus
} // namespace cpu
} // namespace amunmt
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