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#pragma once
#include <torch/csrc/WindowsTorchApiMacro.h>
#include <torch/data/samplers/base.h>
#include <torch/types.h>
#include <cstddef>
#include <vector>
namespace torch {
namespace serialize {
class OutputArchive;
class InputArchive;
} // namespace serialize
} // namespace torch
namespace torch {
namespace jit {
namespace mobile {
/// A lighter `Sampler` that returns indices sequentially and cannot be
/// serialized.
class TORCH_API SequentialSampler : public torch::data::samplers::Sampler<> {
public:
/// Creates a `SequentialSampler` that will return indices in the range
/// `0...size - 1`.
explicit SequentialSampler(size_t size);
/// Resets the `SequentialSampler` to zero.
void reset(optional<size_t> new_size = nullopt) override;
/// Returns the next batch of indices.
optional<std::vector<size_t>> next(size_t batch_size) override;
/// Not supported for mobile SequentialSampler
void save(serialize::OutputArchive& archive) const override;
/// Not supported for mobile SequentialSampler
void load(serialize::InputArchive& archive) override;
/// Returns the current index of the `SequentialSampler`.
size_t index() const noexcept;
private:
size_t size_;
size_t index_{0};
};
} // namespace mobile
} // namespace jit
} // namespace torch
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