#pragma once
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#include <torch/nn/cloneable.h>
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#include <torch/nn/module.h>
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#include <vector>
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namespace torch {
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namespace nn {
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/// A list of `Module`s that registers its elements.
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///
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/// \rst
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/// .. code-block:: cpp
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///
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/// torch::nn::ModuleList mlist(
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/// torch::nn::Linear(3, 4),
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/// torch::nn::BatchNorm(4),
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/// torch::nn::Dropout(0.5)
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/// );
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///
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/// for (const auto &module : mlist) {
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/// module.pretty_print();
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/// }
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///
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/// \endrst
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///
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/// Why should you use `ModuleList` instead of a simple `std::vector`? The value
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/// a `ModuleList` provides over manually calling a sequence of modules is that
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/// it allows treating the whole container *as a single module*, such that
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/// performing a transformation on the `ModuleList` applies to each of the
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/// modules it stores (which are each a registered submodule of the
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/// `ModuleList`). For example, calling
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/// `.to(torch::kCUDA)` on a `ModuleList` will move each module in the list to
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/// CUDA memory. For example:
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///
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/// \rst
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/// .. code-block:: cpp
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///
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/// torch::nn::ModuleList mlist(
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/// torch::nn::Linear(3, 4),
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/// torch::nn::BatchNorm(4),
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/// torch::nn::Dropout(0.5)
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/// );
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///
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/// // Convert all modules to CUDA.
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/// mlist->to(torch::kCUDA);
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///
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/// \endrst
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///
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/// Finally, `ModuleList` provides a lightweight container API, such as allowing
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/// iteration over submodules, positional access, adding a new module after
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/// construction via `push_back`, as well as joining two `ModuleList`s via
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/// `extend`.
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class ModuleListImpl : public Cloneable<ModuleListImpl> {
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public:
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using Iterator = std::vector<std::shared_ptr<Module>>::iterator;
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using ConstIterator = std::vector<std::shared_ptr<Module>>::const_iterator;
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ModuleListImpl() = default;
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/// Constructs the `ModuleList` from a variadic list of modules.
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template <typename... Modules>
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explicit ModuleListImpl(Modules&&... modules) {
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modules_.reserve(sizeof...(Modules));
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push_back_var(std::forward<Modules>(modules)...);
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}
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/// Special cloning function for `ModuleList` because it does not use
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/// `reset()`.
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std::shared_ptr<Module> clone(
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const optional<Device>& device = nullopt) const override {
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auto clone = std::make_shared<ModuleListImpl>();
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for (const auto& module : modules_) {
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clone->push_back(module->clone(device));
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}
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return std::move(clone);
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}
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/// `reset()` is empty for `ModuleList`, since it does not have parameters of
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/// its own.
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void reset() override {}
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/// Pretty prints the `ModuleList` module into the given `stream`.
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void pretty_print(std::ostream& stream) const override {
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stream << "torch::nn::ModuleList";
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}
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void push_back(std::shared_ptr<Module> module) {
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modules_.push_back(std::move(module));
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const auto index = modules_.size() - 1;
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register_module(std::to_string(index), modules_[index]);
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}
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/// Adds a new `Module` to the `ModuleList` container, moving or copying
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/// it into a `shared_ptr` internally. This method allows passing value types,
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/// and letting the container deal with the boxing.
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template <typename M, typename = torch::detail::enable_if_module_t<M>>
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void push_back(M&& module) {
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using Type = typename std::remove_reference<M>::type;
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push_back(std::make_shared<Type>(std::forward<M>(module)));
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}
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/// Unwraps the contained module of a `ModuleHolder` and adds it to the
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/// `ModuleList`.
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template <typename M>
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void push_back(const ModuleHolder<M>& module_holder) {
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push_back(module_holder.ptr());
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}
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/// Iterates over the container and calls `push_back()` on each value.
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template <typename Container>
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void extend(const Container& container) {
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for (const auto& module : container) {
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push_back(module);
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}
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}
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/// Returns an iterator to the start of the `ModuleList`.
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Iterator begin() {
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return modules_.begin();
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}
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/// Returns a const iterator to the start of the `ModuleList`.
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ConstIterator begin() const {
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return modules_.begin();
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}
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/// Returns an iterator to the end of the `ModuleList`.
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Iterator end() {
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return modules_.end();
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}
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/// Returns a const iterator to the end of the `ModuleList`.
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ConstIterator end() const {
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return modules_.end();
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}
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/// Attempts to return the module at the given index as the requested type.
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/// Throws an exception if the index is out of bounds or the types do not
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/// match.
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template <typename T>
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T& at(size_t index) {
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static_assert(
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torch::detail::is_module<T>::value,
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"Can only call ModuleList::at with an nn::Module type");
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TORCH_CHECK(index < size(), "Index out of range");
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return *modules_[index]->as<T>();
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}
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/// Attempts to return the module at the given index as the requested type.
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/// Throws an exception if the index is out of bounds or the types do not
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/// match.
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template <typename T>
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const T& at(size_t index) const {
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static_assert(
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torch::detail::is_module<T>::value,
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"Can only call ModuleList::at with an nn::Module type");
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TORCH_CHECK(index < size(), "Index out of range");
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return *modules_[index]->as<T>();
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}
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/// Attempts to return a `std::shared_ptr` whose dynamic type is that of the
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/// underlying module at the given index. Throws an exception if the index is
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/// out of bounds.
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std::shared_ptr<Module> ptr(size_t index) const {
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TORCH_CHECK(index < size(), "Index out of range");
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return modules_[index];
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}
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/// Attempts to return a `std::shared_ptr` whose type is the one provided.
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/// Throws an exception if the index is out of bounds or the types do not
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/// match.
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template <typename T>
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std::shared_ptr<T> ptr(size_t index) const {
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static_assert(
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torch::detail::is_module<T>::value,
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"Can only call ModuleList::ptr with an nn::Module type");
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TORCH_CHECK(index < size(), "Index out of range");
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return std::dynamic_pointer_cast<T>(modules_[index]);
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}
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/// Like `ptr(index)`.
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std::shared_ptr<Module> operator[](size_t index) const {
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// This is the only method we can call without a type.
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return ptr(index);
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}
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/// The current size of the `ModuleList` container.
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size_t size() const noexcept {
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return modules_.size();
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}
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/// True if there are no modules in the `ModuleList`.
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bool is_empty() const noexcept {
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return size() == 0;
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}
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void insert(size_t index, std::shared_ptr<Module> module) {
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TORCH_CHECK(index <= size(), "Index out of range");
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if (index == size())
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push_back(module);
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else {
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modules_.insert(
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modules_.begin() + Iterator::difference_type(index),
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std::move(module));
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for (size_t i = index; i < size() - 1; ++i)
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replace_module(std::to_string(index), modules_[index]);
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register_module(std::to_string(size() - 1), modules_.back());
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}
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}
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/// Unwraps the contained module of a `ModuleHolder` and inserts it in the
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/// `ModuleList`.
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template <typename M>
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void insert(size_t index, const ModuleHolder<M>& module_holder) {
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insert(index, module_holder.ptr());
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}
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/// inserts a new `Module` to the `ModuleList` container, moving or copying
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/// it into a `shared_ptr` internally. This method allows passing value types,
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/// and letting the container deal with the boxing.
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template <typename M, typename = torch::detail::enable_if_module_t<M>>
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void insert(size_t index, M&& module) {
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using Type = typename std::remove_reference<M>::type;
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insert(index, std::make_shared<Type>(std::forward<M>(module)));
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}
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private:
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template <typename Head, typename... Tail>
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void push_back_var(Head&& head, Tail&&... tail) {
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push_back(std::forward<Head>(head));
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// Recursively calls this method, until the parameter pack only thas this
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// entry left. Then calls `push_back()` a final time (above).
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push_back_var(std::forward<Tail>(tail)...);
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}
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/// The base case, when the list of modules is empty.
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void push_back_var() {}
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// Box the AnyModules to give ModuleList reference semantics, like the rest of
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// the API. Note that this is not required otherwise, this could just be a
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// `vector<AnyModule>`.
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std::vector<std::shared_ptr<Module>> modules_;
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};
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/// A `ModuleHolder` subclass for `ModuleListImpl`.
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/// See the documentation for `ModuleListImpl` class to learn what methods it
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/// provides, or the documentation for `ModuleHolder` to learn about PyTorch's
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/// module storage semantics.
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TORCH_MODULE(ModuleList);
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} // namespace nn
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} // namespace torch
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