reference/generated/torchrl.data.replay_buffers.WriterEnsemble

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WriterEnsemble

class torchrl.data.replay_buffers.WriterEnsemble(*writers)

An ensemble of writers.

This class is designed to work with ReplayBufferEnsemble. It contains the member writers used by a replay-buffer ensemble.

Parameters:

writers (sequence of Writer) – the writers to make the composite writer.

Warning

This class does not write directly. A routed ReplayBufferEnsemble dispatches writes to its member writers; otherwise, index the parent ensemble before writing.

add()

Inserts one piece of data at an appropriate index, and returns that index.

extend()

Inserts a series of data points at appropriate indices, and returns a tensor containing the indices.

generations_of(index: TensorDictBase) → Tensor

Returns the generation stamp for each physical slot in index.

A slot’s stamp advances once per write it receives, so a single extend that wraps the storage advances a reused slot once per write. Comparing a stamp captured at sampling time against the current stamp tells you whether the slot still holds the data you sampled.

Writers that do not track slot reuse – and writers constructed with track_generations=False, which is the default – report -1 everywhere. Never-written slots also report -1, so -1 means “no usable stamp” rather than “generation zero”.

Parameters:

index (int or torch.Tensor) – dim-0 slot indices. A 1-D tensor is always read as a batch of slot indices; for a storage with ndim > 1, pass a tuple of per-dimension indices (as extend() returns) to identify a single cell – only its dim-0 component is used, since a generation stamps a whole dim-0 slot.

Returns:

int64 stamps shaped like the dim-0 component of index, on index’s device.

Return type:

torch.Tensor

property tracks_generations: bool

bool(x) -> bool

Returns True when the argument x is true, False otherwise. The builtins True and False are the only two instances of the class bool. The class bool is a subclass of the class int, and cannot be subclassed.