experanto.utils.SessionBatchSampler

class SessionBatchSampler(*args, **kwargs)

Bases: Sampler

A batch sampler that cycles through sessions, ensuring each session appears exactly once before repeating any session.

Methods

__init__(dataset, batch_size[, drop_last, ...])	Initialize session batch sampler.
get_session_cycle()	Generate one cycle of sessions, with each session appearing exactly once.
get_state()	Return the state of the sampler (including RNG state).
set_state(state)	Restore the state of the sampler (including RNG state).

__init__(dataset, batch_size, drop_last=False, shuffle=False, seed=None)

Initialize session batch sampler.

Parameters:

• dataset (SessionConcatDataset) – The dataset to sample from.

• batch_size (int) – Number of samples per batch.

• drop_last (bool, optional) – Whether to drop the last batch if smaller than batch_size. Default is False.

• shuffle (bool, optional) – Whether to shuffle samples within each session. Default is False.

• seed (int, optional) – Random seed for reproducibility.

__len__()

Return the total number of batches across all sessions.

get_session_cycle()

Generate one cycle of sessions, with each session appearing exactly once. Sessions are shuffled unless their appearance order needs to be controlled.

get_state()

Return the state of the sampler (including RNG state).

set_state(state)

Restore the state of the sampler (including RNG state).