Moved lots of methods in MLPPMatrix's header to the .cpp file.

mlpp/lin_alg/mlpp_matrix.cpp

@@ -4,6 +4,511 @@
 #include "../stat/stat.h"
 #include <random>
 
+void MLPPMatrix::add_row(const Vector<real_t> &p_row) {
+	if (p_row.size() == 0) {
+		return;
+	}
+
+	if (_size.x == 0) {
+		_size.x = p_row.size();
+	}
+
+	ERR_FAIL_COND(_size.x != p_row.size());
+
+	int ci = data_size();
+
+	++_size.y;
+
+	_data = (real_t *)memrealloc(_data, data_size() * sizeof(real_t));
+	CRASH_COND_MSG(!_data, "Out of memory");
+
+	const real_t *row_arr = p_row.ptr();
+
+	for (int i = 0; i < p_row.size(); ++i) {
+		_data[ci + i] = row_arr[i];
+	}
+}
+
+void MLPPMatrix::add_row_pool_vector(const PoolRealArray &p_row) {
+	if (p_row.size() == 0) {
+		return;
+	}
+
+	if (_size.x == 0) {
+		_size.x = p_row.size();
+	}
+
+	ERR_FAIL_COND(_size.x != p_row.size());
+
+	int ci = data_size();
+
+	++_size.y;
+
+	_data = (real_t *)memrealloc(_data, data_size() * sizeof(real_t));
+	CRASH_COND_MSG(!_data, "Out of memory");
+
+	PoolRealArray::Read rread = p_row.read();
+	const real_t *row_arr = rread.ptr();
+
+	for (int i = 0; i < p_row.size(); ++i) {
+		_data[ci + i] = row_arr[i];
+	}
+}
+
+void MLPPMatrix::add_row_mlpp_vector(const Ref<MLPPVector> &p_row) {
+	ERR_FAIL_COND(!p_row.is_valid());
+
+	int p_row_size = p_row->size();
+
+	if (p_row_size == 0) {
+		return;
+	}
+
+	if (_size.x == 0) {
+		_size.x = p_row_size;
+	}
+
+	ERR_FAIL_COND(_size.x != p_row_size);
+
+	int ci = data_size();
+
+	++_size.y;
+
+	_data = (real_t *)memrealloc(_data, data_size() * sizeof(real_t));
+	CRASH_COND_MSG(!_data, "Out of memory");
+
+	const real_t *row_ptr = p_row->ptr();
+
+	for (int i = 0; i < p_row_size; ++i) {
+		_data[ci + i] = row_ptr[i];
+	}
+}
+
+void MLPPMatrix::add_rows_mlpp_matrix(const Ref<MLPPMatrix> &p_other) {
+	ERR_FAIL_COND(!p_other.is_valid());
+
+	int other_data_size = p_other->data_size();
+
+	if (other_data_size == 0) {
+		return;
+	}
+
+	Size2i other_size = p_other->size();
+
+	if (_size.x == 0) {
+		_size.x = other_size.x;
+	}
+
+	ERR_FAIL_COND(other_size.x != _size.x);
+
+	int start_offset = data_size();
+
+	_size.y += other_size.y;
+
+	_data = (real_t *)memrealloc(_data, data_size() * sizeof(real_t));
+	CRASH_COND_MSG(!_data, "Out of memory");
+
+	const real_t *other_ptr = p_other->ptr();
+
+	for (int i = 0; i < other_data_size; ++i) {
+		_data[start_offset + i] = other_ptr[i];
+	}
+}
+
+void MLPPMatrix::remove_row(int p_index) {
+	ERR_FAIL_INDEX(p_index, _size.y);
+
+	--_size.y;
+
+	int ds = data_size();
+
+	if (ds == 0) {
+		memfree(_data);
+		_data = NULL;
+		return;
+	}
+
+	for (int i = p_index * _size.x; i < ds; ++i) {
+		_data[i] = _data[i + _size.x];
+	}
+
+	_data = (real_t *)memrealloc(_data, data_size() * sizeof(real_t));
+	CRASH_COND_MSG(!_data, "Out of memory");
+}
+
+// Removes the item copying the last value into the position of the one to
+// remove. It's generally faster than `remove`.
+void MLPPMatrix::remove_row_unordered(int p_index) {
+	ERR_FAIL_INDEX(p_index, _size.y);
+
+	--_size.y;
+
+	int ds = data_size();
+
+	if (ds == 0) {
+		memfree(_data);
+		_data = NULL;
+		return;
+	}
+
+	int start_ind = p_index * _size.x;
+	int end_ind = (p_index + 1) * _size.x;
+
+	for (int i = start_ind; i < end_ind; ++i) {
+		_data[i] = _data[ds + i];
+	}
+
+	_data = (real_t *)memrealloc(_data, data_size() * sizeof(real_t));
+	CRASH_COND_MSG(!_data, "Out of memory");
+}
+
+void MLPPMatrix::swap_row(int p_index_1, int p_index_2) {
+	ERR_FAIL_INDEX(p_index_1, _size.y);
+	ERR_FAIL_INDEX(p_index_2, _size.y);
+
+	int ind1_start = p_index_1 * _size.x;
+	int ind2_start = p_index_2 * _size.x;
+
+	for (int i = 0; i < _size.x; ++i) {
+		SWAP(_data[ind1_start + i], _data[ind2_start + i]);
+	}
+}
+
+void MLPPMatrix::resize(const Size2i &p_size) {
+	_size = p_size;
+
+	int ds = data_size();
+
+	if (ds == 0) {
+		if (_data) {
+			memfree(_data);
+			_data = NULL;
+		}
+
+		return;
+	}
+
+	_data = (real_t *)memrealloc(_data, ds * sizeof(real_t));
+	CRASH_COND_MSG(!_data, "Out of memory");
+}
+
+Vector<real_t> MLPPMatrix::get_row_vector(int p_index_y) const {
+	ERR_FAIL_INDEX_V(p_index_y, _size.y, Vector<real_t>());
+
+	Vector<real_t> ret;
+
+	if (unlikely(_size.x == 0)) {
+		return ret;
+	}
+
+	ret.resize(_size.x);
+
+	int ind_start = p_index_y * _size.x;
+
+	real_t *row_ptr = ret.ptrw();
+
+	for (int i = 0; i < _size.x; ++i) {
+		row_ptr[i] = _data[ind_start + i];
+	}
+
+	return ret;
+}
+
+PoolRealArray MLPPMatrix::get_row_pool_vector(int p_index_y) const {
+	ERR_FAIL_INDEX_V(p_index_y, _size.y, PoolRealArray());
+
+	PoolRealArray ret;
+
+	if (unlikely(_size.x == 0)) {
+		return ret;
+	}
+
+	ret.resize(_size.x);
+
+	int ind_start = p_index_y * _size.x;
+
+	PoolRealArray::Write w = ret.write();
+	real_t *row_ptr = w.ptr();
+
+	for (int i = 0; i < _size.x; ++i) {
+		row_ptr[i] = _data[ind_start + i];
+	}
+
+	return ret;
+}
+
+Ref<MLPPVector> MLPPMatrix::get_row_mlpp_vector(int p_index_y) const {
+	ERR_FAIL_INDEX_V(p_index_y, _size.y, Ref<MLPPVector>());
+
+	Ref<MLPPVector> ret;
+	ret.instance();
+
+	if (unlikely(_size.x == 0)) {
+		return ret;
+	}
+
+	ret->resize(_size.x);
+
+	int ind_start = p_index_y * _size.x;
+
+	real_t *row_ptr = ret->ptrw();
+
+	for (int i = 0; i < _size.x; ++i) {
+		row_ptr[i] = _data[ind_start + i];
+	}
+
+	return ret;
+}
+
+void MLPPMatrix::get_row_into_mlpp_vector(int p_index_y, Ref<MLPPVector> target) const {
+	ERR_FAIL_COND(!target.is_valid());
+	ERR_FAIL_INDEX(p_index_y, _size.y);
+
+	if (unlikely(target->size() != _size.x)) {
+		target->resize(_size.x);
+	}
+
+	int ind_start = p_index_y * _size.x;
+
+	real_t *row_ptr = target->ptrw();
+
+	for (int i = 0; i < _size.x; ++i) {
+		row_ptr[i] = _data[ind_start + i];
+	}
+}
+
+void MLPPMatrix::set_row_vector(int p_index_y, const Vector<real_t> &p_row) {
+	ERR_FAIL_COND(p_row.size() != _size.x);
+	ERR_FAIL_INDEX(p_index_y, _size.y);
+
+	int ind_start = p_index_y * _size.x;
+
+	const real_t *row_ptr = p_row.ptr();
+
+	for (int i = 0; i < _size.x; ++i) {
+		_data[ind_start + i] = row_ptr[i];
+	}
+}
+
+void MLPPMatrix::set_row_pool_vector(int p_index_y, const PoolRealArray &p_row) {
+	ERR_FAIL_COND(p_row.size() != _size.x);
+	ERR_FAIL_INDEX(p_index_y, _size.y);
+
+	int ind_start = p_index_y * _size.x;
+
+	PoolRealArray::Read r = p_row.read();
+	const real_t *row_ptr = r.ptr();
+
+	for (int i = 0; i < _size.x; ++i) {
+		_data[ind_start + i] = row_ptr[i];
+	}
+}
+
+void MLPPMatrix::set_row_mlpp_vector(int p_index_y, const Ref<MLPPVector> &p_row) {
+	ERR_FAIL_COND(!p_row.is_valid());
+	ERR_FAIL_COND(p_row->size() != _size.x);
+	ERR_FAIL_INDEX(p_index_y, _size.y);
+
+	int ind_start = p_index_y * _size.x;
+
+	const real_t *row_ptr = p_row->ptr();
+
+	for (int i = 0; i < _size.x; ++i) {
+		_data[ind_start + i] = row_ptr[i];
+	}
+}
+
+void MLPPMatrix::fill(real_t p_val) {
+	if (!_data) {
+		return;
+	}
+
+	int ds = data_size();
+	for (int i = 0; i < ds; ++i) {
+		_data[i] = p_val;
+	}
+}
+
+Vector<real_t> MLPPMatrix::to_flat_vector() const {
+	Vector<real_t> ret;
+	ret.resize(data_size());
+	real_t *w = ret.ptrw();
+	memcpy(w, _data, sizeof(real_t) * data_size());
+	return ret;
+}
+
+PoolRealArray MLPPMatrix::to_flat_pool_vector() const {
+	PoolRealArray pl;
+	if (data_size()) {
+		pl.resize(data_size());
+		typename PoolRealArray::Write w = pl.write();
+		real_t *dest = w.ptr();
+
+		for (int i = 0; i < data_size(); ++i) {
+			dest[i] = static_cast<real_t>(_data[i]);
+		}
+	}
+	return pl;
+}
+
+Vector<uint8_t> MLPPMatrix::to_flat_byte_array() const {
+	Vector<uint8_t> ret;
+	ret.resize(data_size() * sizeof(real_t));
+	uint8_t *w = ret.ptrw();
+	memcpy(w, _data, sizeof(real_t) * data_size());
+	return ret;
+}
+
+Ref<MLPPMatrix> MLPPMatrix::duplicate() const {
+	Ref<MLPPMatrix> ret;
+	ret.instance();
+
+	ret->set_from_mlpp_matrixr(*this);
+
+	return ret;
+}
+
+void MLPPMatrix::set_from_mlpp_matrix(const Ref<MLPPMatrix> &p_from) {
+	ERR_FAIL_COND(!p_from.is_valid());
+
+	resize(p_from->size());
+	for (int i = 0; i < p_from->data_size(); ++i) {
+		_data[i] = p_from->_data[i];
+	}
+}
+
+void MLPPMatrix::set_from_mlpp_matrixr(const MLPPMatrix &p_from) {
+	resize(p_from.size());
+	for (int i = 0; i < p_from.data_size(); ++i) {
+		_data[i] = p_from._data[i];
+	}
+}
+
+void MLPPMatrix::set_from_mlpp_vectors(const Vector<Ref<MLPPVector>> &p_from) {
+	if (p_from.size() == 0) {
+		reset();
+		return;
+	}
+
+	if (!p_from[0].is_valid()) {
+		reset();
+		return;
+	}
+
+	resize(Size2i(p_from[0]->size(), p_from.size()));
+
+	if (data_size() == 0) {
+		reset();
+		return;
+	}
+
+	for (int i = 0; i < p_from.size(); ++i) {
+		const Ref<MLPPVector> &r = p_from[i];
+
+		ERR_CONTINUE(!r.is_valid());
+		ERR_CONTINUE(r->size() != _size.x);
+
+		int start_index = i * _size.x;
+
+		const real_t *from_ptr = r->ptr();
+		for (int j = 0; j < _size.x; j++) {
+			_data[start_index + j] = from_ptr[j];
+		}
+	}
+}
+
+void MLPPMatrix::set_from_mlpp_vectors_array(const Array &p_from) {
+	if (p_from.size() == 0) {
+		reset();
+		return;
+	}
+
+	Ref<MLPPVector> v0 = p_from[0];
+
+	if (!v0.is_valid()) {
+		reset();
+		return;
+	}
+
+	resize(Size2i(v0->size(), p_from.size()));
+
+	if (data_size() == 0) {
+		reset();
+		return;
+	}
+
+	for (int i = 0; i < p_from.size(); ++i) {
+		Ref<MLPPVector> r = p_from[i];
+
+		ERR_CONTINUE(!r.is_valid());
+		ERR_CONTINUE(r->size() != _size.x);
+
+		int start_index = i * _size.x;
+
+		const real_t *from_ptr = r->ptr();
+		for (int j = 0; j < _size.x; j++) {
+			_data[start_index + j] = from_ptr[j];
+		}
+	}
+}
+
+void MLPPMatrix::set_from_vectors(const Vector<Vector<real_t>> &p_from) {
+	if (p_from.size() == 0) {
+		reset();
+		return;
+	}
+
+	resize(Size2i(p_from[0].size(), p_from.size()));
+
+	if (data_size() == 0) {
+		reset();
+		return;
+	}
+
+	for (int i = 0; i < p_from.size(); ++i) {
+		const Vector<real_t> &r = p_from[i];
+
+		ERR_CONTINUE(r.size() != _size.x);
+
+		int start_index = i * _size.x;
+
+		const real_t *from_ptr = r.ptr();
+		for (int j = 0; j < _size.x; j++) {
+			_data[start_index + j] = from_ptr[j];
+		}
+	}
+}
+
+void MLPPMatrix::set_from_arrays(const Array &p_from) {
+	if (p_from.size() == 0) {
+		reset();
+		return;
+	}
+
+	PoolRealArray p0arr = p_from[0];
+
+	resize(Size2i(p0arr.size(), p_from.size()));
+
+	if (data_size() == 0) {
+		reset();
+		return;
+	}
+
+	for (int i = 0; i < p_from.size(); ++i) {
+		PoolRealArray r = p_from[i];
+
+		ERR_CONTINUE(r.size() != _size.x);
+
+		int start_index = i * _size.x;
+
+		PoolRealArray::Read read = r.read();
+		const real_t *from_ptr = read.ptr();
+		for (int j = 0; j < _size.x; j++) {
+			_data[start_index + j] = from_ptr[j];
+		}
+	}
+}
+
 /*
 std::vector<std::vector<real_t>> MLPPMatrix::gramMatrix(std::vector<std::vector<real_t>> A) {
 	return matmult(transpose(A), A); // AtA
@@ -2226,6 +2731,28 @@ Ref<MLPPMatrix> MLPPMatrix::diagonal_zeroedn(const Ref<MLPPVector> &a) const {
 	return B;
 }
 
+bool MLPPMatrix::is_equal_approx(const Ref<MLPPMatrix> &p_with, real_t tolerance) const {
+	ERR_FAIL_COND_V(!p_with.is_valid(), false);
+
+	if (unlikely(this == p_with.ptr())) {
+		return true;
+	}
+
+	if (_size != p_with->size()) {
+		return false;
+	}
+
+	int ds = data_size();
+
+	for (int i = 0; i < ds; ++i) {
+		if (!Math::is_equal_approx(_data[i], p_with->_data[i], tolerance)) {
+			return false;
+		}
+	}
+
+	return true;
+}
+
 String MLPPMatrix::to_string() {
 	String str;
 
@@ -2247,6 +2774,37 @@ String MLPPMatrix::to_string() {
 	return str;
 }
 
+MLPPMatrix::MLPPMatrix() {
+	_data = NULL;
+}
+
+MLPPMatrix::MLPPMatrix(const MLPPMatrix &p_from) {
+	_data = NULL;
+
+	resize(p_from.size());
+	for (int i = 0; i < p_from.data_size(); ++i) {
+		_data[i] = p_from._data[i];
+	}
+}
+
+MLPPMatrix::MLPPMatrix(const Vector<Vector<real_t>> &p_from) {
+	_data = NULL;
+
+	set_from_vectors(p_from);
+}
+
+MLPPMatrix::MLPPMatrix(const Array &p_from) {
+	_data = NULL;
+
+	set_from_arrays(p_from);
+}
+
+MLPPMatrix::~MLPPMatrix() {
+	if (_data) {
+		reset();
+	}
+}
+
 std::vector<real_t> MLPPMatrix::to_flat_std_vector() const {
 	std::vector<real_t> ret;
 	ret.resize(data_size());

mlpp/lin_alg/mlpp_matrix.h

@@ -26,175 +26,18 @@ public:
 		return _data;
 	}
 
-	_FORCE_INLINE_ void add_row(const Vector<real_t> &p_row) {
+	void add_row(const Vector<real_t> &p_row);
-		if (p_row.size() == 0) {
+	void add_row_pool_vector(const PoolRealArray &p_row);
-			return;
+	void add_row_mlpp_vector(const Ref<MLPPVector> &p_row);
-		}
+	void add_rows_mlpp_matrix(const Ref<MLPPMatrix> &p_other);
 
-		if (_size.x == 0) {
+	void remove_row(int p_index);
-			_size.x = p_row.size();
-		}
-
-		ERR_FAIL_COND(_size.x != p_row.size());
-
-		int ci = data_size();
-
-		++_size.y;
-
-		_data = (real_t *)memrealloc(_data, data_size() * sizeof(real_t));
-		CRASH_COND_MSG(!_data, "Out of memory");
-
-		const real_t *row_arr = p_row.ptr();
-
-		for (int i = 0; i < p_row.size(); ++i) {
-			_data[ci + i] = row_arr[i];
-		}
-	}
-
-	_FORCE_INLINE_ void add_row_pool_vector(const PoolRealArray &p_row) {
-		if (p_row.size() == 0) {
-			return;
-		}
-
-		if (_size.x == 0) {
-			_size.x = p_row.size();
-		}
-
-		ERR_FAIL_COND(_size.x != p_row.size());
-
-		int ci = data_size();
-
-		++_size.y;
-
-		_data = (real_t *)memrealloc(_data, data_size() * sizeof(real_t));
-		CRASH_COND_MSG(!_data, "Out of memory");
-
-		PoolRealArray::Read rread = p_row.read();
-		const real_t *row_arr = rread.ptr();
-
-		for (int i = 0; i < p_row.size(); ++i) {
-			_data[ci + i] = row_arr[i];
-		}
-	}
-
-	_FORCE_INLINE_ void add_row_mlpp_vector(const Ref<MLPPVector> &p_row) {
-		ERR_FAIL_COND(!p_row.is_valid());
-
-		int p_row_size = p_row->size();
-
-		if (p_row_size == 0) {
-			return;
-		}
-
-		if (_size.x == 0) {
-			_size.x = p_row_size;
-		}
-
-		ERR_FAIL_COND(_size.x != p_row_size);
-
-		int ci = data_size();
-
-		++_size.y;
-
-		_data = (real_t *)memrealloc(_data, data_size() * sizeof(real_t));
-		CRASH_COND_MSG(!_data, "Out of memory");
-
-		const real_t *row_ptr = p_row->ptr();
-
-		for (int i = 0; i < p_row_size; ++i) {
-			_data[ci + i] = row_ptr[i];
-		}
-	}
-
-	_FORCE_INLINE_ void add_rows_mlpp_matrix(const Ref<MLPPMatrix> &p_other) {
-		ERR_FAIL_COND(!p_other.is_valid());
-
-		int other_data_size = p_other->data_size();
-
-		if (other_data_size == 0) {
-			return;
-		}
-
-		Size2i other_size = p_other->size();
-
-		if (_size.x == 0) {
-			_size.x = other_size.x;
-		}
-
-		ERR_FAIL_COND(other_size.x != _size.x);
-
-		int start_offset = data_size();
-
-		_size.y += other_size.y;
-
-		_data = (real_t *)memrealloc(_data, data_size() * sizeof(real_t));
-		CRASH_COND_MSG(!_data, "Out of memory");
-
-		const real_t *other_ptr = p_other->ptr();
-
-		for (int i = 0; i < other_data_size; ++i) {
-			_data[start_offset + i] = other_ptr[i];
-		}
-	}
-
-	void remove_row(int p_index) {
-		ERR_FAIL_INDEX(p_index, _size.y);
-
-		--_size.y;
-
-		int ds = data_size();
-
-		if (ds == 0) {
-			memfree(_data);
-			_data = NULL;
-			return;
-		}
-
-		for (int i = p_index * _size.x; i < ds; ++i) {
-			_data[i] = _data[i + _size.x];
-		}
-
-		_data = (real_t *)memrealloc(_data, data_size() * sizeof(real_t));
-		CRASH_COND_MSG(!_data, "Out of memory");
-	}
 
 	// Removes the item copying the last value into the position of the one to
 	// remove. It's generally faster than `remove`.
-	void remove_row_unordered(int p_index) {
+	void remove_row_unordered(int p_index);
-		ERR_FAIL_INDEX(p_index, _size.y);
 
-		--_size.y;
+	void swap_row(int p_index_1, int p_index_2);
-
-		int ds = data_size();
-
-		if (ds == 0) {
-			memfree(_data);
-			_data = NULL;
-			return;
-		}
-
-		int start_ind = p_index * _size.x;
-		int end_ind = (p_index + 1) * _size.x;
-
-		for (int i = start_ind; i < end_ind; ++i) {
-			_data[i] = _data[ds + i];
-		}
-
-		_data = (real_t *)memrealloc(_data, data_size() * sizeof(real_t));
-		CRASH_COND_MSG(!_data, "Out of memory");
-	}
-
-	void swap_row(int p_index_1, int p_index_2) {
-		ERR_FAIL_INDEX(p_index_1, _size.y);
-		ERR_FAIL_INDEX(p_index_2, _size.y);
-
-		int ind1_start = p_index_1 * _size.x;
-		int ind2_start = p_index_2 * _size.x;
-
-		for (int i = 0; i < _size.x; ++i) {
-			SWAP(_data[ind1_start + i], _data[ind2_start + i]);
-		}
-	}
 
 	_FORCE_INLINE_ void clear() { resize(Size2i()); }
 	_FORCE_INLINE_ void reset() {
@@ -209,23 +52,7 @@ public:
 	_FORCE_INLINE_ int data_size() const { return _size.x * _size.y; }
 	_FORCE_INLINE_ Size2i size() const { return _size; }
 
-	void resize(const Size2i &p_size) {
+	void resize(const Size2i &p_size);
-		_size = p_size;
-
-		int ds = data_size();
-
-		if (ds == 0) {
-			if (_data) {
-				memfree(_data);
-				_data = NULL;
-			}
-
-			return;
-		}
-
-		_data = (real_t *)memrealloc(_data, ds * sizeof(real_t));
-		CRASH_COND_MSG(!_data, "Out of memory");
-	}
 
 	_FORCE_INLINE_ int calculate_index(int p_index_y, int p_index_x) const {
 		return p_index_y * _size.x + p_index_x;
@@ -266,322 +93,29 @@ public:
 		_data[p_index_y * _size.x + p_index_x] = p_val;
 	}
 
-	_FORCE_INLINE_ Vector<real_t> get_row_vector(int p_index_y) const {
+	Vector<real_t> get_row_vector(int p_index_y) const;
-		ERR_FAIL_INDEX_V(p_index_y, _size.y, Vector<real_t>());
+	PoolRealArray get_row_pool_vector(int p_index_y) const;
+	Ref<MLPPVector> get_row_mlpp_vector(int p_index_y) const;
+	void get_row_into_mlpp_vector(int p_index_y, Ref<MLPPVector> target) const;
 
-		Vector<real_t> ret;
+	void set_row_vector(int p_index_y, const Vector<real_t> &p_row);
+	void set_row_pool_vector(int p_index_y, const PoolRealArray &p_row);
+	void set_row_mlpp_vector(int p_index_y, const Ref<MLPPVector> &p_row);
 
-		if (unlikely(_size.x == 0)) {
+	void fill(real_t p_val);
-			return ret;
-		}
 
-		ret.resize(_size.x);
+	Vector<real_t> to_flat_vector() const;
+	PoolRealArray to_flat_pool_vector() const;
+	Vector<uint8_t> to_flat_byte_array() const;
 
-		int ind_start = p_index_y * _size.x;
+	Ref<MLPPMatrix> duplicate() const;
 
-		real_t *row_ptr = ret.ptrw();
+	void set_from_mlpp_matrix(const Ref<MLPPMatrix> &p_from);
-
+	void set_from_mlpp_matrixr(const MLPPMatrix &p_from);
-		for (int i = 0; i < _size.x; ++i) {
+	void set_from_mlpp_vectors(const Vector<Ref<MLPPVector>> &p_from);
-			row_ptr[i] = _data[ind_start + i];
+	void set_from_mlpp_vectors_array(const Array &p_from);
-		}
+	void set_from_vectors(const Vector<Vector<real_t>> &p_from);
-
+	void set_from_arrays(const Array &p_from);
-		return ret;
-	}
-
-	_FORCE_INLINE_ PoolRealArray get_row_pool_vector(int p_index_y) const {
-		ERR_FAIL_INDEX_V(p_index_y, _size.y, PoolRealArray());
-
-		PoolRealArray ret;
-
-		if (unlikely(_size.x == 0)) {
-			return ret;
-		}
-
-		ret.resize(_size.x);
-
-		int ind_start = p_index_y * _size.x;
-
-		PoolRealArray::Write w = ret.write();
-		real_t *row_ptr = w.ptr();
-
-		for (int i = 0; i < _size.x; ++i) {
-			row_ptr[i] = _data[ind_start + i];
-		}
-
-		return ret;
-	}
-
-	_FORCE_INLINE_ Ref<MLPPVector> get_row_mlpp_vector(int p_index_y) const {
-		ERR_FAIL_INDEX_V(p_index_y, _size.y, Ref<MLPPVector>());
-
-		Ref<MLPPVector> ret;
-		ret.instance();
-
-		if (unlikely(_size.x == 0)) {
-			return ret;
-		}
-
-		ret->resize(_size.x);
-
-		int ind_start = p_index_y * _size.x;
-
-		real_t *row_ptr = ret->ptrw();
-
-		for (int i = 0; i < _size.x; ++i) {
-			row_ptr[i] = _data[ind_start + i];
-		}
-
-		return ret;
-	}
-
-	_FORCE_INLINE_ void get_row_into_mlpp_vector(int p_index_y, Ref<MLPPVector> target) const {
-		ERR_FAIL_COND(!target.is_valid());
-		ERR_FAIL_INDEX(p_index_y, _size.y);
-
-		if (unlikely(target->size() != _size.x)) {
-			target->resize(_size.x);
-		}
-
-		int ind_start = p_index_y * _size.x;
-
-		real_t *row_ptr = target->ptrw();
-
-		for (int i = 0; i < _size.x; ++i) {
-			row_ptr[i] = _data[ind_start + i];
-		}
-	}
-
-	_FORCE_INLINE_ void set_row_vector(int p_index_y, const Vector<real_t> &p_row) {
-		ERR_FAIL_COND(p_row.size() != _size.x);
-		ERR_FAIL_INDEX(p_index_y, _size.y);
-
-		int ind_start = p_index_y * _size.x;
-
-		const real_t *row_ptr = p_row.ptr();
-
-		for (int i = 0; i < _size.x; ++i) {
-			_data[ind_start + i] = row_ptr[i];
-		}
-	}
-
-	_FORCE_INLINE_ void set_row_pool_vector(int p_index_y, const PoolRealArray &p_row) {
-		ERR_FAIL_COND(p_row.size() != _size.x);
-		ERR_FAIL_INDEX(p_index_y, _size.y);
-
-		int ind_start = p_index_y * _size.x;
-
-		PoolRealArray::Read r = p_row.read();
-		const real_t *row_ptr = r.ptr();
-
-		for (int i = 0; i < _size.x; ++i) {
-			_data[ind_start + i] = row_ptr[i];
-		}
-	}
-
-	_FORCE_INLINE_ void set_row_mlpp_vector(int p_index_y, const Ref<MLPPVector> &p_row) {
-		ERR_FAIL_COND(!p_row.is_valid());
-		ERR_FAIL_COND(p_row->size() != _size.x);
-		ERR_FAIL_INDEX(p_index_y, _size.y);
-
-		int ind_start = p_index_y * _size.x;
-
-		const real_t *row_ptr = p_row->ptr();
-
-		for (int i = 0; i < _size.x; ++i) {
-			_data[ind_start + i] = row_ptr[i];
-		}
-	}
-
-	void fill(real_t p_val) {
-		if (!_data) {
-			return;
-		}
-
-		int ds = data_size();
-		for (int i = 0; i < ds; ++i) {
-			_data[i] = p_val;
-		}
-	}
-
-	Vector<real_t> to_flat_vector() const {
-		Vector<real_t> ret;
-		ret.resize(data_size());
-		real_t *w = ret.ptrw();
-		memcpy(w, _data, sizeof(real_t) * data_size());
-		return ret;
-	}
-
-	PoolRealArray to_flat_pool_vector() const {
-		PoolRealArray pl;
-		if (data_size()) {
-			pl.resize(data_size());
-			typename PoolRealArray::Write w = pl.write();
-			real_t *dest = w.ptr();
-
-			for (int i = 0; i < data_size(); ++i) {
-				dest[i] = static_cast<real_t>(_data[i]);
-			}
-		}
-		return pl;
-	}
-
-	Vector<uint8_t> to_flat_byte_array() const {
-		Vector<uint8_t> ret;
-		ret.resize(data_size() * sizeof(real_t));
-		uint8_t *w = ret.ptrw();
-		memcpy(w, _data, sizeof(real_t) * data_size());
-		return ret;
-	}
-
-	Ref<MLPPMatrix> duplicate() const {
-		Ref<MLPPMatrix> ret;
-		ret.instance();
-
-		ret->set_from_mlpp_matrixr(*this);
-
-		return ret;
-	}
-
-	_FORCE_INLINE_ void set_from_mlpp_matrix(const Ref<MLPPMatrix> &p_from) {
-		ERR_FAIL_COND(!p_from.is_valid());
-
-		resize(p_from->size());
-		for (int i = 0; i < p_from->data_size(); ++i) {
-			_data[i] = p_from->_data[i];
-		}
-	}
-
-	_FORCE_INLINE_ void set_from_mlpp_matrixr(const MLPPMatrix &p_from) {
-		resize(p_from.size());
-		for (int i = 0; i < p_from.data_size(); ++i) {
-			_data[i] = p_from._data[i];
-		}
-	}
-
-	_FORCE_INLINE_ void set_from_mlpp_vectors(const Vector<Ref<MLPPVector>> &p_from) {
-		if (p_from.size() == 0) {
-			reset();
-			return;
-		}
-
-		if (!p_from[0].is_valid()) {
-			reset();
-			return;
-		}
-
-		resize(Size2i(p_from[0]->size(), p_from.size()));
-
-		if (data_size() == 0) {
-			reset();
-			return;
-		}
-
-		for (int i = 0; i < p_from.size(); ++i) {
-			const Ref<MLPPVector> &r = p_from[i];
-
-			ERR_CONTINUE(!r.is_valid());
-			ERR_CONTINUE(r->size() != _size.x);
-
-			int start_index = i * _size.x;
-
-			const real_t *from_ptr = r->ptr();
-			for (int j = 0; j < _size.x; j++) {
-				_data[start_index + j] = from_ptr[j];
-			}
-		}
-	}
-
-	_FORCE_INLINE_ void set_from_mlpp_vectors_array(const Array &p_from) {
-		if (p_from.size() == 0) {
-			reset();
-			return;
-		}
-
-		Ref<MLPPVector> v0 = p_from[0];
-
-		if (!v0.is_valid()) {
-			reset();
-			return;
-		}
-
-		resize(Size2i(v0->size(), p_from.size()));
-
-		if (data_size() == 0) {
-			reset();
-			return;
-		}
-
-		for (int i = 0; i < p_from.size(); ++i) {
-			Ref<MLPPVector> r = p_from[i];
-
-			ERR_CONTINUE(!r.is_valid());
-			ERR_CONTINUE(r->size() != _size.x);
-
-			int start_index = i * _size.x;
-
-			const real_t *from_ptr = r->ptr();
-			for (int j = 0; j < _size.x; j++) {
-				_data[start_index + j] = from_ptr[j];
-			}
-		}
-	}
-
-	_FORCE_INLINE_ void set_from_vectors(const Vector<Vector<real_t>> &p_from) {
-		if (p_from.size() == 0) {
-			reset();
-			return;
-		}
-
-		resize(Size2i(p_from[0].size(), p_from.size()));
-
-		if (data_size() == 0) {
-			reset();
-			return;
-		}
-
-		for (int i = 0; i < p_from.size(); ++i) {
-			const Vector<real_t> &r = p_from[i];
-
-			ERR_CONTINUE(r.size() != _size.x);
-
-			int start_index = i * _size.x;
-
-			const real_t *from_ptr = r.ptr();
-			for (int j = 0; j < _size.x; j++) {
-				_data[start_index + j] = from_ptr[j];
-			}
-		}
-	}
-
-	_FORCE_INLINE_ void set_from_arrays(const Array &p_from) {
-		if (p_from.size() == 0) {
-			reset();
-			return;
-		}
-
-		PoolRealArray p0arr = p_from[0];
-
-		resize(Size2i(p0arr.size(), p_from.size()));
-
-		if (data_size() == 0) {
-			reset();
-			return;
-		}
-
-		for (int i = 0; i < p_from.size(); ++i) {
-			PoolRealArray r = p_from[i];
-
-			ERR_CONTINUE(r.size() != _size.x);
-
-			int start_index = i * _size.x;
-
-			PoolRealArray::Read read = r.read();
-			const real_t *from_ptr = read.ptr();
-			for (int j = 0; j < _size.x; j++) {
-				_data[start_index + j] = from_ptr[j];
-			}
-		}
-	}
 
 	//std::vector<std::vector<real_t>> gramMatrix(std::vector<std::vector<real_t>> A);
 	//bool linearIndependenceChecker(std::vector<std::vector<real_t>> A);
@@ -785,59 +319,16 @@ public:
 	void diagonal_zeroed(const Ref<MLPPVector> &a);
 	Ref<MLPPMatrix> diagonal_zeroedn(const Ref<MLPPVector> &a) const;
 
-	_FORCE_INLINE_ bool is_equal_approx(const Ref<MLPPMatrix> &p_with, real_t tolerance = static_cast<real_t>(CMP_EPSILON)) const {
+	bool is_equal_approx(const Ref<MLPPMatrix> &p_with, real_t tolerance = static_cast<real_t>(CMP_EPSILON)) const;
-		ERR_FAIL_COND_V(!p_with.is_valid(), false);
-
-		if (unlikely(this == p_with.ptr())) {
-			return true;
-		}
-
-		if (_size != p_with->size()) {
-			return false;
-		}
-
-		int ds = data_size();
-
-		for (int i = 0; i < ds; ++i) {
-			if (!Math::is_equal_approx(_data[i], p_with->_data[i], tolerance)) {
-				return false;
-			}
-		}
-
-		return true;
-	}
 
 	String to_string();
 
-	_FORCE_INLINE_ MLPPMatrix() {
+	MLPPMatrix();
-		_data = NULL;
+	MLPPMatrix(const MLPPMatrix &p_from);
-	}
+	MLPPMatrix(const Vector<Vector<real_t>> &p_from);
-	_FORCE_INLINE_ MLPPMatrix(const MLPPMatrix &p_from) {
+	MLPPMatrix(const Array &p_from);
-		_data = NULL;
 
-		resize(p_from.size());
+	~MLPPMatrix();
-		for (int i = 0; i < p_from.data_size(); ++i) {
-			_data[i] = p_from._data[i];
-		}
-	}
-
-	MLPPMatrix(const Vector<Vector<real_t>> &p_from) {
-		_data = NULL;
-
-		set_from_vectors(p_from);
-	}
-
-	MLPPMatrix(const Array &p_from) {
-		_data = NULL;
-
-		set_from_arrays(p_from);
-	}
-
-	_FORCE_INLINE_ ~MLPPMatrix() {
-		if (_data) {
-			reset();
-		}
-	}
 
 	// TODO: These are temporary
 	std::vector<real_t> to_flat_std_vector() const;