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More setter cleanup to MLPPTensor3.
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@ -44,7 +44,7 @@ void MLPPTensor3::set_from_std_vectors(const std::vector<std::vector<std::vector
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return;
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}
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resize(Size3i(p_from[1].size(), p_from.size(), p_from[0].size()));
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resize(Size3i(p_from[1].size(), p_from[0].size(), p_from.size()));
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if (data_size() == 0) {
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reset();
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@ -656,15 +656,39 @@ public:
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return ret;
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}
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Ref<MLPPMatrix> duplicate() const {
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Ref<MLPPMatrix> ret;
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Ref<MLPPTensor3> duplicate() const {
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Ref<MLPPTensor3> ret;
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ret.instance();
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//ret->set_from_mlpp_matrixr(*this);
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ret->set_from_mlpp_tensor3r(*this);
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return ret;
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}
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_FORCE_INLINE_ void set_from_mlpp_tensor3(const Ref<MLPPTensor3> &p_from) {
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ERR_FAIL_COND(!p_from.is_valid());
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resize(p_from->size());
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int ds = p_from->data_size();
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const real_t *ptr = p_from->ptr();
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for (int i = 0; i < ds; ++i) {
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_data[i] = ptr[i];
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}
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}
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_FORCE_INLINE_ void set_from_mlpp_tensor3r(const MLPPTensor3 &p_from) {
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resize(p_from.size());
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int ds = p_from.data_size();
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const real_t *ptr = p_from.ptr();
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for (int i = 0; i < ds; ++i) {
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_data[i] = ptr[i];
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}
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}
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_FORCE_INLINE_ void set_from_mlpp_matrix(const Ref<MLPPMatrix> &p_from) {
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ERR_FAIL_COND(!p_from.is_valid());
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@ -724,6 +748,42 @@ public:
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}
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}
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_FORCE_INLINE_ void set_from_mlpp_matricess(const Vector<Ref<MLPPMatrix>> &p_from) {
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if (p_from.size() == 0) {
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reset();
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return;
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}
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if (!p_from[0].is_valid()) {
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reset();
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return;
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}
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resize(Size3i(p_from[0]->size().x, p_from[0]->size().y, p_from.size()));
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if (data_size() == 0) {
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reset();
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return;
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}
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Size2i fms = feature_map_size();
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int fmds = feature_map_data_size();
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for (int i = 0; i < p_from.size(); ++i) {
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const Ref<MLPPMatrix> &r = p_from[i];
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ERR_CONTINUE(!r.is_valid());
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ERR_CONTINUE(r->size() != fms);
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int start_index = calculate_feature_map_index(i);
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const real_t *from_ptr = r->ptr();
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for (int j = 0; j < fmds; j++) {
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_data[start_index + j] = from_ptr[j];
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}
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}
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}
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_FORCE_INLINE_ void set_from_mlpp_vectors_array(const Array &p_from) {
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if (p_from.size() == 0) {
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reset();
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@ -759,58 +819,39 @@ public:
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}
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}
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_FORCE_INLINE_ void set_from_vectors(const Vector<Vector<real_t>> &p_from) {
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_FORCE_INLINE_ void set_from_mlpp_matrices_array(const Array &p_from) {
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if (p_from.size() == 0) {
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reset();
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return;
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}
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resize(Size3i(p_from[0].size(), p_from.size(), 1));
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Ref<MLPPMatrix> v0 = p_from[0];
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if (!v0.is_valid()) {
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reset();
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return;
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}
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resize(Size3i(v0->size().x, v0->size().y, p_from.size()));
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if (data_size() == 0) {
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reset();
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return;
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}
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for (int i = 0; i < p_from.size(); ++i) {
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const Vector<real_t> &r = p_from[i];
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ERR_CONTINUE(r.size() != _size.x);
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int start_index = i * _size.x;
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const real_t *from_ptr = r.ptr();
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for (int j = 0; j < _size.x; j++) {
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_data[start_index + j] = from_ptr[j];
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}
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}
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}
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_FORCE_INLINE_ void set_from_arrays(const Array &p_from) {
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if (p_from.size() == 0) {
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reset();
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return;
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}
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PoolRealArray p0arr = p_from[0];
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resize(Size3i(p0arr.size(), p_from.size(), 1));
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if (data_size() == 0) {
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reset();
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return;
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}
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Size2i fms = feature_map_size();
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int fmds = feature_map_data_size();
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for (int i = 0; i < p_from.size(); ++i) {
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PoolRealArray r = p_from[i];
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Ref<MLPPMatrix> r = p_from[i];
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ERR_CONTINUE(r.size() != _size.x);
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ERR_CONTINUE(!r.is_valid());
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ERR_CONTINUE(r->size() != fms);
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int start_index = i * _size.x;
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int start_index = calculate_feature_map_index(i);
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PoolRealArray::Read read = r.read();
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const real_t *from_ptr = read.ptr();
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for (int j = 0; j < _size.x; j++) {
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const real_t *from_ptr = r->ptr();
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for (int j = 0; j < fmds; j++) {
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_data[start_index + j] = from_ptr[j];
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}
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}
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@ -858,16 +899,10 @@ public:
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}
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}
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MLPPTensor3(const Vector<Vector<real_t>> &p_from) {
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_data = NULL;
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set_from_vectors(p_from);
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}
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MLPPTensor3(const Array &p_from) {
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_data = NULL;
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set_from_arrays(p_from);
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set_from_mlpp_matrices_array(p_from);
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}
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_FORCE_INLINE_ ~MLPPTensor3() {
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