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synced 2024-12-21 14:56:47 +01:00
Implemented tensor_vec_mult, also swapped some parameters in MLPPTensor to match the expected order.
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@ -240,7 +240,7 @@ void MLPPTensor3::shape_set(const Size3i &p_size) {
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_size = p_size;
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}
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Vector<real_t> MLPPTensor3::row_get_vector(int p_index_y, int p_index_z) const {
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Vector<real_t> MLPPTensor3::row_get_vector(int p_index_z, int p_index_y) const {
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ERR_FAIL_INDEX_V(p_index_y, _size.y, Vector<real_t>());
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ERR_FAIL_INDEX_V(p_index_z, _size.z, Vector<real_t>());
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@ -263,7 +263,7 @@ Vector<real_t> MLPPTensor3::row_get_vector(int p_index_y, int p_index_z) const {
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return ret;
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}
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PoolRealArray MLPPTensor3::row_get_pool_vector(int p_index_y, int p_index_z) const {
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PoolRealArray MLPPTensor3::row_get_pool_vector(int p_index_z, int p_index_y) const {
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ERR_FAIL_INDEX_V(p_index_y, _size.y, PoolRealArray());
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ERR_FAIL_INDEX_V(p_index_z, _size.z, PoolRealArray());
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@ -287,7 +287,7 @@ PoolRealArray MLPPTensor3::row_get_pool_vector(int p_index_y, int p_index_z) con
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return ret;
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}
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Ref<MLPPVector> MLPPTensor3::row_get_mlpp_vector(int p_index_y, int p_index_z) const {
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Ref<MLPPVector> MLPPTensor3::row_get_mlpp_vector(int p_index_z, int p_index_y) const {
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ERR_FAIL_INDEX_V(p_index_y, _size.y, Ref<MLPPVector>());
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ERR_FAIL_INDEX_V(p_index_z, _size.z, Ref<MLPPVector>());
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@ -311,7 +311,7 @@ Ref<MLPPVector> MLPPTensor3::row_get_mlpp_vector(int p_index_y, int p_index_z) c
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return ret;
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}
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void MLPPTensor3::row_get_into_mlpp_vector(int p_index_y, int p_index_z, Ref<MLPPVector> target) const {
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void MLPPTensor3::row_get_into_mlpp_vector(int p_index_z, int p_index_y, Ref<MLPPVector> target) const {
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ERR_FAIL_COND(!target.is_valid());
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ERR_FAIL_INDEX(p_index_y, _size.y);
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ERR_FAIL_INDEX(p_index_z, _size.z);
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@ -1841,21 +1841,25 @@ real_t MLPPTensor3::norm_2(std::vector<std::vector<std::vector<real_t>>> A) {
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}
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*/
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/*
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std::vector<std::vector<real_t>> MLPPTensor3::tensor_vec_mult(std::vector<std::vector<std::vector<real_t>>> A, std::vector<real_t> b) {
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std::vector<std::vector<real_t>> C;
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C.resize(A.size());
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for (uint32_t i = 0; i < C.size(); i++) {
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C[i].resize(A[0].size());
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}
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for (uint32_t i = 0; i < C.size(); i++) {
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for (uint32_t j = 0; j < C[i].size(); j++) {
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C[i][j] = dot(A[i][j], b);
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Ref<MLPPMatrix> MLPPTensor3::tensor_vec_mult(const Ref<MLPPVector> &b) {
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Ref<MLPPMatrix> C;
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C.instance();
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C->resize(Size2i(_size.y, _size.z));
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Ref<MLPPVector> row_tmp;
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row_tmp.instance();
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row_tmp->resize(_size.x);
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for (int i = 0; i < _size.z; i++) {
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for (int j = 0; j < _size.y; j++) {
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row_get_into_mlpp_vector(i, j, row_tmp);
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C->element_set(i, j, row_tmp->dot(b));
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}
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}
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return C;
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}
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*/
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/*
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// Bad implementation. Change this later.
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@ -16,11 +16,11 @@
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#else
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#include "core/containers/vector.h"
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#include "core/defs.h"
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#include "core/math_funcs.h"
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#include "core/pool_arrays.h"
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#include "core/containers/vector.h"
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#include "core/os/memory.h"
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#include "core/pool_arrays.h"
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#include "gen/resource.h"
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@ -121,10 +121,10 @@ public:
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_data[p_index_y * _size.x + p_index_x + _size.x * _size.y * p_index_z] = p_val;
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}
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Vector<real_t> row_get_vector(int p_index_y, int p_index_z) const;
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PoolRealArray row_get_pool_vector(int p_index_y, int p_index_z) const;
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Ref<MLPPVector> row_get_mlpp_vector(int p_index_y, int p_index_z) const;
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void row_get_into_mlpp_vector(int p_index_y, int p_index_z, Ref<MLPPVector> target) const;
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Vector<real_t> row_get_vector(int p_index_z, int p_index_y) const;
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PoolRealArray row_get_pool_vector(int p_index_z, int p_index_y) const;
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Ref<MLPPVector> row_get_mlpp_vector(int p_index_z, int p_index_y) const;
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void row_get_into_mlpp_vector(int p_index_z, int p_index_y, Ref<MLPPVector> target) const;
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void row_set_vector(int p_index_y, int p_index_z, const Vector<real_t> &p_row);
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void row_set_pool_vector(int p_index_y, int p_index_z, const PoolRealArray &p_row);
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@ -244,7 +244,7 @@ public:
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//real_t norm_2(std::vector<std::vector<std::vector<real_t>>> A);
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//std::vector<std::vector<real_t>> tensor_vec_mult(std::vector<std::vector<std::vector<real_t>>> A, std::vector<real_t> b);
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Ref<MLPPMatrix> tensor_vec_mult(const Ref<MLPPVector> &b);
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//std::vector<std::vector<std::vector<real_t>>> vector_wise_tensor_product(std::vector<std::vector<std::vector<real_t>>> A, std::vector<std::vector<real_t>> B);
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public:
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