vuron/adept: Платформа для обучения и вывода нейронных сетей, с API приближенным к PyTorch.

src/tensor.cpp
253 строки6 KB
kolkir
Adam optimizer implementation
01 мар 2025, 17:03
01 мар 2025, 17:032fcc751
#include <adept/nn/init.hpp>
#include <adept/tensor.hpp>
#include <adept/tensor_print.hpp>
#include "dispatch/tensor_creation.hpp"

namespace adept {

Tensor Tensor::empty(const TensorProperties& props) {
  return make_empty_tensor(props);
}

Tensor Tensor::zero(const TensorProperties& props) {
  auto t = make_empty_tensor(props);
  fill_zero(t);
  return t;
}

Tensor Tensor::uniform(float32_t start, float32_t end, const TensorProperties& props) {
  auto t = make_empty_tensor(props);
  fill_uniform(start, end, t);
  return t;
}

Tensor Tensor::normal(float32_t mean, float32_t std, const TensorProperties& props) {
  auto t = make_empty_tensor(props);
  fill_normal(mean, std, t);
  return t;
}

Tensor Tensor::from_blob(const void* data, const TensorProperties& props) {
  return make_tensor_from_blob(data, props);
}

Tensor Tensor::stack(const std::vector<Tensor>& tensors) {
  if (tensors.empty()) {
    THROW_ERROR("Can't stack empty container");
  }
  return stack_tensors(tensors);
}

Tensor::Tensor(std::shared_ptr<DeviceTensor> impl) : impl_{impl} {};

Tensor::Tensor(const Tensor& other) : impl_(other.impl_) {}
Tensor& Tensor::operator=(const Tensor& other) {
  if (&other != this) {
    impl_ = other.impl_;
  }
  return *this;
}
Tensor::Tensor(Tensor&& other) : impl_(std::move(other.impl_)) {}
Tensor& Tensor::operator=(Tensor&& other) {
  if (&other != this) {
    impl_ = std::move(other.impl_);
  }
  return *this;
}

std::shared_ptr<DeviceTensor> Tensor::impl() const {
  return impl_;
}

const TensorProperties& Tensor::properties() const {
  CHECK(defined(), "Tensor is not defined!");
  return impl_->properties();
}

const Shape& Tensor::shape() const {
  return properties().shape;
}

dtype_t Tensor::dtype() const {
  return properties().dtype;
}

device_t Tensor::device() const {
  return properties().device;
}

bool Tensor::is_shape_aligned() const {
  CHECK(defined(), "Tensor is not defined!");
  return impl_->is_shape_aligned();
}

Tensor Tensor::squeeze(index_t dim) const {
  CHECK(defined(), "Tensor is not defined!");
  return Tensor(impl_->squeeze(dim));
}

Tensor Tensor::unsqueeze(index_t dim) const {
  CHECK(defined(), "Tensor is not defined!");
  return Tensor(impl_->unsqueeze(dim));
}

Tensor Tensor::clone() const {
  return clone_tensor(*this);
}

bool Tensor::defined() const {
  return impl_.get() != nullptr;
}

Tensor Tensor::add_(const Tensor& other) {
  CHECK(defined(), "Tensor is not defined!");
  CHECK(other.defined(), "operand Tensor is not defined!");
  impl_->add(*other.impl_);
  return {impl_};
}
Tensor Tensor::operator+=(const Tensor& other) {
  return add_(other);
}

Tensor Tensor::add_(float32_t scalar) {
  CHECK(defined(), "Tensor is not defined!");
  impl_->add(scalar);
  return {impl_};
}
Tensor Tensor::operator+=(float32_t scalar) {
  return add_(scalar);
}

Tensor Tensor::sub_(const Tensor& other) {
  CHECK(defined(), "Tensor is not defined!");
  CHECK(other.defined(), "operand Tensor is not defined!");
  impl_->sub(*other.impl_);
  return {impl_};
}
Tensor Tensor::operator-=(const Tensor& other) {
  return sub_(other);
}

Tensor Tensor::sub_(float32_t scalar) {
  CHECK(defined(), "Tensor is not defined!");
  impl_->sub(scalar);
  return {impl_};
}
Tensor Tensor::operator-=(float32_t scalar) {
  return sub_(scalar);
}

Tensor Tensor::mul_(const Tensor& other) {
  CHECK(defined(), "Tensor is not defined!");
  CHECK(other.defined(), "operand Tensor is not defined!");
  impl_->mul(*other.impl_);
  return {impl_};
}
Tensor Tensor::operator*=(const Tensor& other) {
  return mul_(other);
}

Tensor Tensor::mul_(float32_t scalar) {
  CHECK(defined(), "Tensor is not defined!");
  impl_->mul(scalar);
  return {impl_};
}
Tensor Tensor::operator*=(float32_t scalar) {
  return mul_(scalar);
}

Tensor Tensor::div_(const Tensor& other) {
  CHECK(defined(), "Tensor is not defined!");
  CHECK(other.defined(), "operand Tensor is not defined!");
  impl_->div(*other.impl_);
  return {impl_};
}
Tensor Tensor::operator/=(const Tensor& other) {
  return div_(other);
}

Tensor Tensor::div_(float32_t value) {
  CHECK(defined(), "Tensor is not defined!");
  impl_->div(value);
  return {impl_};
}
Tensor Tensor::operator/=(float32_t scalar) {
  return div_(scalar);
}

Tensor Tensor::gt_(float32_t value) const {
  CHECK(defined(), "Tensor is not defined!");
  return impl_->gt(value);
}
Tensor Tensor::ge_(float32_t value) const {
  CHECK(defined(), "Tensor is not defined!");
  return impl_->ge(value);
}
Tensor Tensor::lt_(float32_t value) const {
  CHECK(defined(), "Tensor is not defined!");
  return impl_->lt(value);
}
Tensor Tensor::le_(float32_t value) const {
  CHECK(defined(), "Tensor is not defined!");
  return impl_->le(value);
}

Tensor Tensor::neg_() {
  CHECK(defined(), "Tensor is not defined!");
  impl_->neg();
  return {impl_};
}

Tensor Tensor::exp_() {
  CHECK(defined(), "Tensor is not defined!");
  impl_->exp();
  return {impl_};
}

Tensor Tensor::sqrt_() {
  CHECK(defined(), "Tensor is not defined!");
  impl_->sqrt();
  return {impl_};
}

Tensor Tensor::sqrt() const {
  CHECK(defined(), "Tensor is not defined!");
  return clone_tensor(*this).sqrt_();
}

Tensor Tensor::operator-() {
  return neg_();
}

Tensor Tensor::sum() const {
  CHECK(defined(), "Tensor is not defined!");
  return (impl_->sum());
}

Tensor Tensor::sum_dim0() const {
  CHECK(defined(), "Tensor is not defined!");
  return (impl_->sum_dim0());
}

Tensor Tensor::mean() const {
  CHECK(defined(), "Tensor is not defined!");
  return (impl_->mean());
}

Tensor Tensor::transpose2d() const {
  CHECK(defined(), "Tensor is not defined!");
  return impl_->transpose2d();
}

Tensor Tensor::matmul(const Tensor& other) const {
  CHECK(defined(), "Tensor is not defined!");
  CHECK(other.defined(), "operand Tensor is not defined!");
  return impl_->matmul(*other.impl_);
}

std::string Tensor::to_string() const {
  std::stringstream out;
  out << *this;
  return out.str();
}
}  // namespace adept