torch_mist.estimators.generative.factories
Module Contents
Functions
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- torch_mist.estimators.generative.factories.ba(entropy_y: float | torch.Tensor, x_dim: int | None = None, y_dim: int | None = None, hidden_dims: List[int] | None = None, q_Y_given_X: pyro.distributions.ConditionalDistribution | None = None, transform_name: str = 'conditional_linear', n_transforms: int = 1) torch_mist.estimators.generative.implementations.BA
- torch_mist.estimators.generative.factories.club(x_dim: int | None = None, y_dim: int | None = None, hidden_dims: List[int] | None = None, q_Y_given_X: pyro.distributions.ConditionalDistribution | None = None, transform_name: str = 'conditional_linear', n_transforms: int = 1) torch_mist.estimators.generative.implementations.CLUB
- torch_mist.estimators.generative.factories.doe(x_dim: int | None = None, y_dim: int | None = None, hidden_dims: List[int] | None = None, q_Y_given_X: pyro.distributions.ConditionalDistribution | None = None, q_Y: torch.distributions.Distribution | None = None, conditional_transform_name: str = 'conditional_linear', n_conditional_transforms: int = 1, marginal_transform_name: str = 'linear', n_marginal_transforms: int = 1) torch_mist.estimators.generative.implementations.DoE
- torch_mist.estimators.generative.factories.dummy_generative(**kwargs) torch_mist.estimators.generative.implementations.DummyGenerativeMIEstimator
- torch_mist.estimators.generative.factories.gm(x_dim: int | None = None, y_dim: int | None = None, hidden_dims: List[int] = None, q_XY: torch_mist.distributions.joint.base.JointDistribution | None = None, q_Y: torch.distributions.Distribution | None = None, q_X: torch.distributions.Distribution | None = None, joint_transform_name: str = 'affine_autoregressive', n_joint_transforms: int = 1, marginal_transform_name: str = 'linear', n_marginal_transforms: int = 1) torch_mist.estimators.generative.implementations.GM
- torch_mist.estimators.generative.factories.l1out(x_dim: int | None = None, y_dim: int | None = None, hidden_dims: List[int] | None = None, q_Y_given_X: pyro.distributions.ConditionalDistribution | None = None, transform_name: str = 'conditional_linear', n_transforms: int = 1) torch_mist.estimators.generative.implementations.L1Out