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pmlpp/lin_alg/mlpp_tensor3.h

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#ifndef MLPP_TENSOR3_H
#define MLPP_TENSOR3_H
/*************************************************************************/
/* mlpp_tensor3.h */
/*************************************************************************/
/* This file is part of: */
/* PMLPP Machine Learning Library */
/* https://github.com/Relintai/pmlpp */
/*************************************************************************/
/* Copyright (c) 2023-present Péter Magyar. */
/* Copyright (c) 2022-2023 Marc Melikyan */
/* */
/* Permission is hereby granted, free of charge, to any person obtaining */
/* a copy of this software and associated documentation files (the */
/* "Software"), to deal in the Software without restriction, including */
/* without limitation the rights to use, copy, modify, merge, publish, */
/* distribute, sublicense, and/or sell copies of the Software, and to */
/* permit persons to whom the Software is furnished to do so, subject to */
/* the following conditions: */
/* */
/* The above copyright notice and this permission notice shall be */
/* included in all copies or substantial portions of the Software. */
/* */
/* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, */
/* EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF */
/* MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.*/
/* IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY */
/* CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, */
/* TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE */
/* SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. */
/*************************************************************************/
#ifdef USING_SFW
#include "sfw.h"
#include "image.h"
#else
#include "core/math/math_defs.h"
#include "core/containers/pool_vector.h"
#include "core/containers/sort_array.h"
#include "core/containers/vector.h"
#include "core/error/error_macros.h"
#include "core/math/vector2i.h"
#include "core/os/memory.h"
#include "core/object/resource.h"
#endif
#include "mlpp_matrix.h"
#include "mlpp_vector.h"
class Image;
class MLPPTensor3 : public Resource {
GDCLASS(MLPPTensor3, Resource);
public:
Array get_data();
void set_data(const Array &p_from);
_FORCE_INLINE_ real_t *ptrw() { return _data; }
_FORCE_INLINE_ const real_t *ptr() const { return _data; }
void z_slice_add(const Vector<real_t> &p_row);
void z_slice_add_pool_vector(const PoolRealArray &p_row);
void z_slice_add_mlpp_vector(const Ref<MLPPVector> &p_row);
void z_slice_add_mlpp_matrix(const Ref<MLPPMatrix> &p_matrix);
void z_slice_remove(int p_index);
// Removes the item copying the last value into the position of the one to
// remove. It's generally faster than `remove`.
void z_slice_remove_unordered(int p_index);
void z_slice_swap(int p_index_1, int p_index_2);
_FORCE_INLINE_ void clear() { resize(Size3i()); }
_FORCE_INLINE_ void reset() {
if (_data) {
memfree(_data);
_data = NULL;
_size = Size3i();
}
}
_FORCE_INLINE_ bool empty() const { return _size == Size3i(); }
_FORCE_INLINE_ int z_slice_data_size() const { return _size.x * _size.y; }
_FORCE_INLINE_ Size2i z_slice_size() const {
return Size2i(_size.x, _size.y);
}
_FORCE_INLINE_ int data_size() const { return _size.x * _size.y * _size.z; }
_FORCE_INLINE_ Size3i size() const { return _size; }
void resize(const Size3i &p_size);
void shape_set(const Size3i &p_size);
_FORCE_INLINE_ int calculate_index(int p_index_z, int p_index_y,
int p_index_x) const {
return p_index_y * _size.x + p_index_x + _size.x * _size.y * p_index_z;
}
_FORCE_INLINE_ int calculate_z_slice_index(int p_index_z) const {
return _size.x * _size.y * p_index_z;
}
_FORCE_INLINE_ const real_t &operator[](int p_index) const {
CRASH_BAD_INDEX(p_index, data_size());
return _data[p_index];
}
_FORCE_INLINE_ real_t &operator[](int p_index) {
CRASH_BAD_INDEX(p_index, data_size());
return _data[p_index];
}
_FORCE_INLINE_ real_t element_get_index(int p_index) const {
ERR_FAIL_INDEX_V(p_index, data_size(), 0);
return _data[p_index];
}
_FORCE_INLINE_ void element_set_index(int p_index, real_t p_val) {
ERR_FAIL_INDEX(p_index, data_size());
_data[p_index] = p_val;
}
_FORCE_INLINE_ real_t element_get(int p_index_z, int p_index_y,
int p_index_x) const {
ERR_FAIL_INDEX_V(p_index_x, _size.x, 0);
ERR_FAIL_INDEX_V(p_index_y, _size.y, 0);
ERR_FAIL_INDEX_V(p_index_z, _size.z, 0);
return _data[p_index_y * _size.x + p_index_x +
_size.x * _size.y * p_index_z];
}
_FORCE_INLINE_ void element_set(int p_index_z, int p_index_y, int p_index_x,
real_t p_val) {
ERR_FAIL_INDEX(p_index_x, _size.x);
ERR_FAIL_INDEX(p_index_y, _size.y);
ERR_FAIL_INDEX(p_index_z, _size.z);
_data[p_index_y * _size.x + p_index_x + _size.x * _size.y * p_index_z] =
p_val;
}
Vector<real_t> row_get_vector(int p_index_z, int p_index_y) const;
PoolRealArray row_get_pool_vector(int p_index_z, int p_index_y) const;
Ref<MLPPVector> row_get_mlpp_vector(int p_index_z, int p_index_y) const;
void row_get_into_mlpp_vector(int p_index_z, int p_index_y,
Ref<MLPPVector> target) const;
void row_set_vector(int p_index_z, int p_index_y,
const Vector<real_t> &p_row);
void row_set_pool_vector(int p_index_z, int p_index_y,
const PoolRealArray &p_row);
void row_set_mlpp_vector(int p_index_z, int p_index_y,
const Ref<MLPPVector> &p_row);
Vector<real_t> z_slice_get_vector(int p_index_z) const;
PoolRealArray z_slice_get_pool_vector(int p_index_z) const;
Ref<MLPPVector> z_slice_get_mlpp_vector(int p_index_z) const;
void z_slice_get_into_mlpp_vector(int p_index_z,
Ref<MLPPVector> target) const;
Ref<MLPPMatrix> z_slice_get_mlpp_matrix(int p_index_z) const;
void z_slice_get_into_mlpp_matrix(int p_index_z,
Ref<MLPPMatrix> target) const;
void z_slice_set_vector(int p_index_z, const Vector<real_t> &p_row);
void z_slice_set_pool_vector(int p_index_z, const PoolRealArray &p_row);
void z_slice_set_mlpp_vector(int p_index_z, const Ref<MLPPVector> &p_row);
void z_slice_set_mlpp_matrix(int p_index_z, const Ref<MLPPMatrix> &p_mat);
// TODO resize() need to be reworked for add and remove to work, in any other
// direction than z void x_slice_add(const Ref<MLPPMatrix> &p_matrix); void
// x_slice_remove(int p_index);
void x_slice_get_into(int p_index_x, Ref<MLPPMatrix> target) const;
Ref<MLPPMatrix> x_slice_get(int p_index_x) const;
void x_slice_set(int p_index_x, const Ref<MLPPMatrix> &p_mat);
// void y_slice_add(const Ref<MLPPMatrix> &p_matrix);
// void y_slice_remove(int p_index);
void y_slice_get_into(int p_index_y, Ref<MLPPMatrix> target) const;
Ref<MLPPMatrix> y_slice_get(int p_index_y) const;
void y_slice_set(int p_index_y, const Ref<MLPPMatrix> &p_mat);
public:
// Image api
enum ImageChannelFlags {
IMAGE_CHANNEL_FLAG_R = 1 << 0,
IMAGE_CHANNEL_FLAG_G = 1 << 1,
IMAGE_CHANNEL_FLAG_B = 1 << 2,
IMAGE_CHANNEL_FLAG_A = 1 << 3,
IMAGE_CHANNEL_FLAG_NONE = 0,
IMAGE_CHANNEL_FLAG_RG = IMAGE_CHANNEL_FLAG_R | IMAGE_CHANNEL_FLAG_G,
IMAGE_CHANNEL_FLAG_RGB =
IMAGE_CHANNEL_FLAG_R | IMAGE_CHANNEL_FLAG_G | IMAGE_CHANNEL_FLAG_B,
IMAGE_CHANNEL_FLAG_GB = IMAGE_CHANNEL_FLAG_G | IMAGE_CHANNEL_FLAG_B,
IMAGE_CHANNEL_FLAG_GBA =
IMAGE_CHANNEL_FLAG_G | IMAGE_CHANNEL_FLAG_B | IMAGE_CHANNEL_FLAG_A,
IMAGE_CHANNEL_FLAG_BA = IMAGE_CHANNEL_FLAG_B | IMAGE_CHANNEL_FLAG_A,
IMAGE_CHANNEL_FLAG_RGBA = IMAGE_CHANNEL_FLAG_R | IMAGE_CHANNEL_FLAG_G |
IMAGE_CHANNEL_FLAG_B | IMAGE_CHANNEL_FLAG_A,
};
void z_slices_add_image(const Ref<Image> &p_img,
const int p_channels = IMAGE_CHANNEL_FLAG_RGBA);
Ref<Image> z_slice_get_image(const int p_index_z) const;
Ref<Image> z_slices_get_image(const int p_index_r = -1,
const int p_index_g = -1,
const int p_index_b = -1,
const int p_index_a = -1) const;
void z_slice_get_into_image(
Ref<Image> p_target, const int p_index_z,
const int p_target_channels = IMAGE_CHANNEL_FLAG_RGB) const;
void z_slices_get_into_image(Ref<Image> p_target, const int p_index_r = -1,
const int p_index_g = -1,
const int p_index_b = -1,
const int p_index_a = -1) const;
void z_slice_set_image(const Ref<Image> &p_img, const int p_index_z,
const int p_image_channel_flag = IMAGE_CHANNEL_FLAG_R);
void z_slices_set_image(const Ref<Image> &p_img, const int p_index_r = -1,
const int p_index_g = -1, const int p_index_b = -1,
const int p_index_a = -1);
void set_from_image(const Ref<Image> &p_img,
const int p_channels = IMAGE_CHANNEL_FLAG_RGBA);
// void x_slices_add_image(const Ref<Image> &p_img, const int p_channels =
// IMAGE_CHANNEL_FLAG_RGBA);
Ref<Image> x_slice_get_image(const int p_index_x) const;
void x_slice_get_into_image(
Ref<Image> p_target, const int p_index_x,
const int p_target_channels = IMAGE_CHANNEL_FLAG_RGB) const;
void x_slice_set_image(const Ref<Image> &p_img, const int p_index_x,
const int p_image_channel_flag = IMAGE_CHANNEL_FLAG_R);
// void y_slices_add_image(const Ref<Image> &p_img, const int p_channels =
// IMAGE_CHANNEL_FLAG_RGBA);
Ref<Image> y_slice_get_image(const int p_index_y) const;
void y_slice_get_into_image(
Ref<Image> p_target, const int p_index_y,
const int p_target_channels = IMAGE_CHANNEL_FLAG_RGB) const;
void y_slice_set_image(const Ref<Image> &p_img, const int p_index_y,
const int p_image_channel_flag = IMAGE_CHANNEL_FLAG_R);
public:
// math api
void add(const Ref<MLPPTensor3> &B);
Ref<MLPPTensor3> addn(const Ref<MLPPTensor3> &B) const;
void addb(const Ref<MLPPTensor3> &A, const Ref<MLPPTensor3> &B);
void sub(const Ref<MLPPTensor3> &B);
Ref<MLPPTensor3> subn(const Ref<MLPPTensor3> &B) const;
void subb(const Ref<MLPPTensor3> &A, const Ref<MLPPTensor3> &B);
void division_element_wise(const Ref<MLPPTensor3> &B);
Ref<MLPPTensor3> division_element_wisen(const Ref<MLPPTensor3> &B) const;
void division_element_wiseb(const Ref<MLPPTensor3> &A,
const Ref<MLPPTensor3> &B);
void sqrt();
Ref<MLPPTensor3> sqrtn() const;
void sqrtb(const Ref<MLPPTensor3> &A);
void exponentiate(real_t p);
Ref<MLPPTensor3> exponentiaten(real_t p) const;
void exponentiateb(const Ref<MLPPTensor3> &A, real_t p);
void scalar_multiply(const real_t scalar);
Ref<MLPPTensor3> scalar_multiplyn(const real_t scalar) const;
void scalar_multiplyb(const real_t scalar, const Ref<MLPPTensor3> &A);
void scalar_add(const real_t scalar);
Ref<MLPPTensor3> scalar_addn(const real_t scalar) const;
void scalar_addb(const real_t scalar, const Ref<MLPPTensor3> &A);
void hadamard_product(const Ref<MLPPTensor3> &B);
Ref<MLPPTensor3> hadamard_productn(const Ref<MLPPTensor3> &B) const;
void hadamard_productb(const Ref<MLPPTensor3> &A, const Ref<MLPPTensor3> &B);
void max(const Ref<MLPPTensor3> &B);
Ref<MLPPTensor3> maxn(const Ref<MLPPTensor3> &B) const;
void maxb(const Ref<MLPPTensor3> &A, const Ref<MLPPTensor3> &B);
void abs();
Ref<MLPPTensor3> absn() const;
void absb(const Ref<MLPPTensor3> &A);
Ref<MLPPVector> flatten() const;
void flatteno(Ref<MLPPVector> out) const;
// real_t norm_2(std::vector<std::vector<std::vector<real_t>>> A);
Ref<MLPPMatrix> tensor_vec_mult(const Ref<MLPPVector> &b);
// 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);
public:
void fill(real_t p_val);
Vector<real_t> to_flat_vector() const;
PoolRealArray to_flat_pool_vector() const;
Vector<uint8_t> to_flat_byte_array() const;
Ref<MLPPTensor3> duplicate_fast() const;
void set_from_mlpp_tensor3(const Ref<MLPPTensor3> &p_from);
void set_from_mlpp_tensor3r(const MLPPTensor3 &p_from);
void set_from_mlpp_matrix(const Ref<MLPPMatrix> &p_from);
void set_from_mlpp_matrixr(const MLPPMatrix &p_from);
void set_from_mlpp_vectors(const Vector<Ref<MLPPVector>> &p_from);
void set_from_mlpp_matricess(const Vector<Ref<MLPPMatrix>> &p_from);
void set_from_mlpp_vectors_array(const Array &p_from);
void set_from_mlpp_matrices_array(const Array &p_from);
bool
is_equal_approx(const Ref<MLPPTensor3> &p_with,
real_t tolerance = static_cast<real_t>(CMP_EPSILON)) const;
String to_string();
MLPPTensor3();
MLPPTensor3(const MLPPMatrix &p_from);
MLPPTensor3(const Array &p_from);
~MLPPTensor3();
// TODO: These are temporary
std::vector<real_t> to_flat_std_vector() const;
void set_from_std_vectors(
const std::vector<std::vector<std::vector<real_t>>> &p_from);
std::vector<std::vector<std::vector<real_t>>> to_std_vector();
MLPPTensor3(const std::vector<std::vector<std::vector<real_t>>> &p_from);
protected:
static void _bind_methods();
protected:
Size3i _size;
real_t *_data;
};
VARIANT_ENUM_CAST(MLPPTensor3::ImageChannelFlags);
#endif
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