Shortcuts

Class RandomSampler

Inheritance Relationships

Base Type

Class Documentation

class torch::data::samplers::RandomSampler : public torch::data::samplers::Sampler<>

A Sampler that returns random indices.

Public Functions

RandomSampler(int64_t size, Dtype index_dtype = torch::kInt64)

Constructs a RandomSampler with a size and dtype for the stored indices.

The constructor will eagerly allocate all required indices, which is the sequence 0 ... size - 1. index_dtype is the data type of the stored indices. You can change it to influence memory usage.

~RandomSampler() override
void reset(optional<size_t> new_size = nullopt) override

Resets the RandomSampler to a new set of indices.

optional<std::vector<size_t>> next(size_t batch_size) override

Returns the next batch of indices.

void save(serialize::OutputArchive &archive) const override

Serializes the RandomSampler to the archive.

void load(serialize::InputArchive &archive) override

Deserializes the RandomSampler from the archive.

size_t index() const noexcept

Returns the current index of the RandomSampler.

Docs

Access comprehensive developer documentation for PyTorch

View Docs

Tutorials

Get in-depth tutorials for beginners and advanced developers

View Tutorials

Resources

Find development resources and get your questions answered

View Resources