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pointer to bias so that array will be updated and saved #29

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pointer to bias so that array will be updated and saved #29

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4 changes: 2 additions & 2 deletions SLIDE/Layer.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -86,7 +86,7 @@ Layer::Layer(size_t noOfNodes, int previousLayerNumOfNodes, int layerID, NodeTyp
{
_Nodes[i].Update(previousLayerNumOfNodes, i, _layerID, type, batchsize, _weights+previousLayerNumOfNodes*i,
_bias[i], _adamAvgMom+previousLayerNumOfNodes*i , _adamAvgVel+previousLayerNumOfNodes*i, _train_array);
addtoHashTable(_Nodes[i]._weights, previousLayerNumOfNodes, _Nodes[i]._bias, i);
addtoHashTable(_Nodes[i]._weights, previousLayerNumOfNodes, *_Nodes[i]._bias, i);
}
auto t2 = std::chrono::high_resolution_clock::now();
auto timeDiffInMiliseconds = std::chrono::duration_cast<std::chrono::microseconds>(t2 - t1).count();
Expand Down Expand Up @@ -418,7 +418,7 @@ int Layer::queryActiveNodeandComputeActivations(int** activenodesperlayer, float
for (size_t s = 0; s < _noOfNodes; s++) {
float tmp = innerproduct(activenodesperlayer[layerIndex], activeValuesperlayer[layerIndex],
lengths[layerIndex], _Nodes[s]._weights);
tmp += _Nodes[s]._bias;
tmp += *_Nodes[s]._bias;
if (find(label, label + labelsize, s) != label + labelsize) {
sortW.push_back(make_pair(-1000000000, s));
what++;
Expand Down
4 changes: 2 additions & 2 deletions SLIDE/Network.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -245,13 +245,13 @@ int Network::ProcessInput(int **inputIndices, float **inputValues, int *lengths,

tmp->_adamAvgMombias = BETA1 * tmp->_adamAvgMombias + (1 - BETA1) * tmp->_tbias;
tmp->_adamAvgVelbias = BETA2 * tmp->_adamAvgVelbias + (1 - BETA2) * tmp->_tbias * tmp->_tbias;
tmp->_bias += ratio*tmplr * tmp->_adamAvgMombias / (sqrt(tmp->_adamAvgVelbias) + EPS);
*tmp->_bias += ratio*tmplr * tmp->_adamAvgMombias / (sqrt(tmp->_adamAvgVelbias) + EPS);
tmp->_tbias = 0;
}
else
{
std::copy(tmp->_mirrorWeights, tmp->_mirrorWeights+(tmp->_dim) , tmp->_weights);
tmp->_bias = tmp->_mirrorbias;
*tmp->_bias = tmp->_mirrorbias;
}
if (tmpRehash) {
int *hashes;
Expand Down
12 changes: 6 additions & 6 deletions SLIDE/Node.cpp
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Expand Up @@ -30,12 +30,12 @@ Node::Node(int dim, int nodeID, int layerID, NodeType type, int batchsize, float
_activeInputs = 0;

_weights = weights;
_bias = bias;
_mirrorbias = _bias;
//_bias = bias;
//_mirrorbias = _bias;

}

void Node::Update(int dim, int nodeID, int layerID, NodeType type, int batchsize, float *weights, float bias, float *adamAvgMom, float *adamAvgVel, train* train_blob)
void Node::Update(int dim, int nodeID, int layerID, NodeType type, int batchsize, float *weights, float &bias, float *adamAvgMom, float *adamAvgVel, train* train_blob)
{
_dim = dim;
_IDinLayer = nodeID;
Expand All @@ -55,8 +55,8 @@ void Node::Update(int dim, int nodeID, int layerID, NodeType type, int batchsize
_activeInputs = 0;

_weights = weights;
_bias = bias;
_mirrorbias = _bias;
_bias = &bias;
_mirrorbias = *_bias;

}

Expand Down Expand Up @@ -100,7 +100,7 @@ float Node::getActivation(int* indices, float* values, int length, int inputID)
{
_train[inputID]._lastActivations += _weights[indices[i]] * values[i];
}
_train[inputID]._lastActivations += _bias;
_train[inputID]._lastActivations += (*_bias);

switch (_type)
{
Expand Down
4 changes: 2 additions & 2 deletions SLIDE/Node.h
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Original file line number Diff line number Diff line change
Expand Up @@ -81,15 +81,15 @@ class Node
float* _adamAvgVel;
float* _t; //for adam
int* _update;
float _bias =0;
float *_bias = NULL;
float _tbias = 0;
float _adamAvgMombias=0;
float _adamAvgVelbias=0;
float _mirrorbias =0;

Node(){};
Node(int dim, int nodeID, int layerID, NodeType type, int batchsize, float *weights, float bias, float *adamAvgMom, float *adamAvgVel);
void Update(int dim, int nodeID, int layerID, NodeType type, int batchsize, float *weights, float bias, float *adamAvgMom, float *adamAvgVel, train* train_blob);
void Update(int dim, int nodeID, int layerID, NodeType type, int batchsize, float *weights, float &bias, float *adamAvgMom, float *adamAvgVel, train* train_blob);
void updateWeights(float* newWeights, float newbias);
float getLastActivation(int inputID);
void incrementDelta(int inputID, float incrementValue);
Expand Down