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Simplified hadamard_product in MLPPMatrix.
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@ -250,20 +250,21 @@ void MLPPMatrix::hadamard_product(const Ref<MLPPMatrix> &B) {
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ERR_FAIL_COND(!B.is_valid());
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ERR_FAIL_COND(_size != B->size());
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int ds = data_size();
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const real_t *b_ptr = B->ptr();
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real_t *c_ptr = ptrw();
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for (int i = 0; i < _size.y; i++) {
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for (int j = 0; j < _size.x; j++) {
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int ind_i_j = calculate_index(i, j);
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c_ptr[ind_i_j] = c_ptr[ind_i_j] * b_ptr[ind_i_j];
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}
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for (int i = 0; i < ds; i++) {
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c_ptr[i] = c_ptr[i] * b_ptr[i];
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}
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}
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Ref<MLPPMatrix> MLPPMatrix::hadamard_productn(const Ref<MLPPMatrix> &B) const {
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ERR_FAIL_COND_V(!B.is_valid(), Ref<MLPPMatrix>());
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ERR_FAIL_COND_V(_size != B->size(), Ref<MLPPMatrix>());
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int ds = data_size();
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Ref<MLPPMatrix> C;
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C.instance();
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C->resize(_size);
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@ -272,11 +273,8 @@ Ref<MLPPMatrix> MLPPMatrix::hadamard_productn(const Ref<MLPPMatrix> &B) const {
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const real_t *b_ptr = B->ptr();
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real_t *c_ptr = C->ptrw();
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for (int i = 0; i < _size.y; i++) {
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for (int j = 0; j < _size.x; j++) {
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int ind_i_j = calculate_index(i, j);
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c_ptr[ind_i_j] = a_ptr[ind_i_j] * b_ptr[ind_i_j];
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}
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for (int i = 0; i < ds; i++) {
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c_ptr[i] = a_ptr[i] * b_ptr[i];
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}
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return C;
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@ -290,15 +288,14 @@ void MLPPMatrix::hadamard_productb(const Ref<MLPPMatrix> &A, const Ref<MLPPMatri
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resize(a_size);
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}
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int ds = data_size();
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const real_t *a_ptr = A->ptr();
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const real_t *b_ptr = B->ptr();
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real_t *c_ptr = ptrw();
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for (int i = 0; i < a_size.y; i++) {
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for (int j = 0; j < a_size.x; j++) {
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int ind_i_j = A->calculate_index(i, j);
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c_ptr[ind_i_j] = a_ptr[ind_i_j] * b_ptr[ind_i_j];
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}
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for (int i = 0; i < ds; i++) {
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c_ptr[i] = a_ptr[i] * b_ptr[i];
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}
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}
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