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Distribution Classes

Custom distribution classes for RL, extending PyTorch distributions.

Delta(param[, atol, rtol, batch_shape, ...])

Delta distribution.

IndependentNormal(loc, scale[, upscale, ...])

Implements a Normal distribution with location scaling.

MaskedCategorical([logits, probs, mask, ...])

MaskedCategorical distribution.

NormalParamExtractor([scale_mapping, scale_lb])

A non-parametric nn.Module that splits its input into loc and scale parameters.

OneHotCategorical([logits, probs, grad_method])

One-hot categorical distribution.

ReparamGradientStrategy(value[, names, ...])

TanhDelta(param[, low, high, event_dims, ...])

Implements a Tanh transformed_in Delta distribution.

TanhNormal(loc, scale[, upscale, low, high, ...])

Implements a TanhNormal distribution with location scaling.

TruncatedNormal(loc, scale[, upscale, low, ...])

Implements a Truncated Normal distribution with location scaling.

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