torch_mist.distributions.transforms.implementations

Submodules

• torch_mist.distributions.transforms.implementations.linear
• torch_mist.distributions.transforms.implementations.normalize
• torch_mist.distributions.transforms.implementations.permute

Package Contents

Classes

Linear
ConditionalLinear
Permute
EMANormalize

class torch_mist.distributions.transforms.implementations.Linear(input_dim, loc=None, scale=None, initial_scale=None, epsilon=1e-06)

Bases: ConditionedLinear, pyro.distributions.TransformModule

_params()

class torch_mist.distributions.transforms.implementations.ConditionalLinear(net, loc=None, scale=None, initial_scale=None, epsilon=1e-06, skip_connection=False)

Bases: pyro.distributions.ConditionalTransformModule

domain

codomain

bijective = True

_params(context)

condition(context)

class torch_mist.distributions.transforms.implementations.Permute(permutation, *, dim=-1, cache_size=1)

Bases: pyro.distributions.transforms.Permute, pyro.distributions.TransformModule

update_device()

_call(x)

_inverse(y)

log_abs_det_jacobian(x, y)

class torch_mist.distributions.transforms.implementations.EMANormalize(input_dim: int, epsilon: float = 1e-06, gamma: float = 0.99, normalize_inverse=True)

Bases: torch_mist.distributions.transforms.implementations.linear.Linear

_update_params(t: torch.Tensor)

_inverse(y: torch.Tensor) → torch.Tensor

_call(x: torch.Tensor) → torch.Tensor