Template Class DistributedSampler

• Defined in File distributed.h

Inheritance Relationships

Base Type

• public torch::data::samplers::Sampler< std::vector< size_t > > (Template Class Sampler)

Derived Types

• public torch::data::samplers::DistributedRandomSampler (Class DistributedRandomSampler)

• public torch::data::samplers::DistributedSequentialSampler (Class DistributedSequentialSampler)

Class Documentation

template<typename BatchRequest = std::vector<size_t>>
class DistributedSampler : public torch::data::samplers::Sampler<std::vector<size_t>>

A Sampler that selects a subset of indices to sample from and defines a sampling behavior.

In a distributed setting, this selects a subset of the indices depending on the provided num_replicas and rank parameters. The Sampler performs a rounding operation based on the allow_duplicates parameter to decide the local sample count.

Subclassed by torch::data::samplers::DistributedRandomSampler, torch::data::samplers::DistributedSequentialSampler

Public Functions

inline DistributedSampler(size_t size, size_t num_replicas = 1, size_t rank = 0, bool allow_duplicates = true)

inline void set_epoch(size_t epoch)

Set the epoch for the current enumeration.

This can be used to alter the sample selection and shuffling behavior.

inline size_t epoch() const

Protected Functions

inline size_t local_sample_count()

Protected Attributes

size_t size_

size_t num_replicas_

size_t rank_

size_t epoch_ = {0}

bool allow_duplicates_