kompute/src/OpTensorCopy.cpp

#include "kompute/operations/OpTensorCopy.hpp"

namespace kp {

OpTensorCopy::OpTensorCopy()
{
    SPDLOG_DEBUG("Kompute OpTensorCopy constructor base");
}

OpTensorCopy::OpTensorCopy(std::shared_ptr<vk::PhysicalDevice> physicalDevice,
                           std::shared_ptr<vk::Device> device,
                           std::shared_ptr<vk::CommandBuffer> commandBuffer,
                           std::vector<std::shared_ptr<Tensor>> tensors)
  : OpBase(physicalDevice, device, commandBuffer, tensors, false)
{
    SPDLOG_DEBUG("Kompute OpTensorCopy constructor with params");
}

OpTensorCopy::~OpTensorCopy()
{
    SPDLOG_DEBUG("Kompute OpTensorCopy destructor started");
}

void
OpTensorCopy::init()
{
    SPDLOG_DEBUG("Kompute OpTensorCopy init called");

    if (this->mTensors.size() < 2) {
        throw std::runtime_error(
          "Kompute OpTensorCopy called with less than 2 tensor");
    }

    for (std::shared_ptr<Tensor> tensor : this->mTensors) {
        if (!tensor->isInit()) {
            throw std::runtime_error(
              "Kompute OpTensorCopy tensor parameter has not been initialized");
        }
        if (tensor->tensorType() == Tensor::TensorTypes::eStorage) {
            throw std::runtime_error("Kompute OpTensorCopy tensor parameter is "
                                     "of TensorTypes::eStorage and hence "
                                     "cannot be used to receive or pass data.");
        }
    }
}

void
OpTensorCopy::record()
{
    SPDLOG_DEBUG("Kompute OpTensorCopy record called");

    // We iterate from the second tensor onwards and record a copy to all
    for (size_t i = 1; i < this->mTensors.size(); i++) {
        this->mTensors[i]->recordCopyFrom(
          this->mCommandBuffer, this->mTensors[0], false);
    }
}

void
OpTensorCopy::preEval()
{
    SPDLOG_DEBUG("Kompute OpTensorCopy preEval called");
}

void
OpTensorCopy::postEval()
{
    SPDLOG_DEBUG("Kompute OpTensorCopy postEval called");

    // Copy the data from the first tensor into all the tensors
    for (size_t i = 1; i < this->mTensors.size(); i++) {
        this->mTensors[i]->setData(this->mTensors[0]->data());
    }
}

}