int crypto_hashblocks_sha512(
unsigned char *statebytes,
const unsigned char *in,crypto_uint16 inlen
)
{
myu64 state[8];
myu64 state_safe[8];
myu64 w[16];
unsigned char i;
myu64_convert_bigendian(state[0].v, statebytes + 0, 8);
for (i=0;i<8;i++)
state_safe[i] = state[i];
while (inlen >= 128)
{
for(i=0;i<16;i++)
myu64_convert_bigendian(w[i].v, in + 8*i, 1);
for(i=0;i<16;i++)
myF(state, w+i, i);
expand(w);
for(i=0;i<16;i++)
myF(state, w+i, i+16);
expand(w);
for(i=0;i<16;i++)
myF(state, w+i, i+32);
expand(w);
for(i=0;i<16;i++)
myF(state, w+i, i+48);
expand(w);
for(i=0;i<16;i++)
myF(state, w+i, i+64);
for(i=0;i<8;i++)
bigint_add64(state[i].v, state[i].v, state_safe[i].v);
for(i=0;i<8;i++)
state_safe[i] = state[i];
in += 128;
inlen -= 128;
}
myu64_convert_bigendian(statebytes+0, state_safe[0].v, 8);
return inlen;
}
void QL::learnWts() {
resetInputToCNN();
for(int i = 0; i < miniBatchSize; ++i) {
setInputToCNN(dExp[miniBatch[i]].fiJN, i);
}
if(numTimeLearnt < 1) {
std::ofstream myF("inputToCNN.txt");
printInfile(cnnInputSize, inputToCNN, myF);
myF.close();
}
float *qVals = caff2->forwardNGetQVal(inputToCNN);
TargetLayerInputData targ;
std::fill(targ.begin(), targ.end(), 0.0f);
FilterLayerInputData filterInp;
std::fill(filterInp.begin(), filterInp.end(), 0.0f);
prepareTarget(targ, qVals);
for(int i = 0; i < miniBatchSize; ++i) {
filterInp[i*numAction + dExp[miniBatch[i]].act] = 1;
}
resetInputToCNN();
for(int i = 0; i < miniBatchSize; ++i) {
setInputToCNN(dExp[miniBatch[i]].fiJ, i);
}
int maxLIter = info.numLearnSteps;
caff->learn(inputToCNN, targ, filterInp, maxLIter);
numTimeLearnt++;
if(numTimeLearnt - targetUpdate >= info.targetUpdateFreq) {
targetUpdate = numTimeLearnt;
caff2 = caff;
}
}
