Mila
Deep Neural Network Library
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Implementation of the Residual connection module for neural networks. More...
#include <memory>
#include <vector>
#include <string>
#include <iostream>
#include <sstream>
#include <type_traits>
#include <stdexcept>
import Dnn.Modules.Linear;
import Serialization.ModelArchive;
import Compute.CudaMemoryResource;
import Compute.CpuMemoryResource;
import Compute.MemoryResource;
import Dnn.Modules.Residual:Config;
import Dnn.Module;
import Dnn.Tensor;
import Compute.OperationRegistry;
import Compute.BinaryOperation;
import Dnn.TensorTraits;
import Compute.Precision;
import Compute.ComputeDevice;
import Compute.DeviceType;
import Dnn.TensorHelpers;
import Compute.OperationAttributes;
import Compute.OperationBase;
import Compute.DeviceContext;
Classes | |
class | Mila::Dnn::Residual< TDeviceType, TInput, TOutput > |
A class implementing a residual connection module. More... | |
Namespaces | |
namespace | Mila |
namespace | Mila::Dnn |
Typedefs | |
template<typename TInput = float, typename TOutput = TInput> | |
using | Mila::Dnn::CpuResidual = Residual< DeviceType::Cpu, TInput, TOutput > |
Type alias for CPU-based residual module with customizable tensor types. | |
template<typename TInput = float, typename TOutput = TInput> | |
using | Mila::Dnn::CudaResidual = Residual< DeviceType::Cuda, TInput, TOutput > |
Type alias for CUDA-based residual module with customizable tensor types. | |
Implementation of the Residual connection module for neural networks.
Provides a flexible implementation of residual connections which can be configured with different connection types and scaling factors. Supports automatic dimension matching via projection layers.