glm_families            GLM families
glm_fit                 Runs multiple Fisher scoring steps
glm_fit.tensorflow.tensor
                        Runs multiple Fisher scoring steps
glm_fit_one_step        Runs one Fisher scoring step
glm_fit_one_step.tensorflow.tensor
                        Runs one Fisher Scoring step
initializer_blockwise   Blockwise Initializer
install_tfprobability   Installs TensorFlow Probability
layer_autoregressive    Masked Autoencoder for Distribution Estimation
layer_autoregressive_transform
                        An autoregressive normalizing flow layer, given
                        a 'layer_autoregressive'.
layer_categorical_mixture_of_one_hot_categorical
                        A OneHotCategorical mixture Keras layer from 'k
                        * (1 + d)' params.
layer_conv_1d_flipout   1D convolution layer (e.g. temporal
                        convolution) with Flipout
layer_conv_1d_reparameterization
                        1D convolution layer (e.g. temporal
                        convolution).
layer_conv_2d_flipout   2D convolution layer (e.g. spatial convolution
                        over images) with Flipout
layer_conv_2d_reparameterization
                        2D convolution layer (e.g. spatial convolution
                        over images)
layer_conv_3d_flipout   3D convolution layer (e.g. spatial convolution
                        over volumes) with Flipout
layer_conv_3d_reparameterization
                        3D convolution layer (e.g. spatial convolution
                        over volumes)
layer_dense_flipout     Densely-connected layer class with Flipout
                        estimator.
layer_dense_local_reparameterization
                        Densely-connected layer class with local
                        reparameterization estimator.
layer_dense_reparameterization
                        Densely-connected layer class with
                        reparameterization estimator.
layer_dense_variational
                        Dense Variational Layer
layer_distribution_lambda
                        Keras layer enabling plumbing TFP distributions
                        through Keras models
layer_independent_bernoulli
                        An Independent-Bernoulli Keras layer from
                        prod(event_shape) params
layer_independent_logistic
                        An independent Logistic Keras layer.
layer_independent_normal
                        An independent Normal Keras layer.
layer_independent_poisson
                        An independent Poisson Keras layer.
layer_kl_divergence_add_loss
                        Pass-through layer that adds a KL divergence
                        penalty to the model loss
layer_kl_divergence_regularizer
                        Regularizer that adds a KL divergence penalty
                        to the model loss
layer_mixture_logistic
                        A mixture distribution Keras layer, with
                        independent logistic components.
layer_mixture_normal    A mixture distribution Keras layer, with
                        independent normal components.
layer_mixture_same_family
                        A mixture (same-family) Keras layer.
layer_multivariate_normal_tri_l
                        A d-variate Multivariate Normal TriL Keras
                        layer from 'd+d*(d+1)/ 2' params
layer_one_hot_categorical
                        A 'd'-variate OneHotCategorical Keras layer
                        from 'd' params.
layer_variable          Variable Layer
layer_variational_gaussian_process
                        A Variational Gaussian Process Layer.
mcmc_dual_averaging_step_size_adaptation
                        Adapts the inner kernel's 'step_size' based on
                        'log_accept_prob'.
mcmc_effective_sample_size
                        Estimate a lower bound on effective sample size
                        for each independent chain.
mcmc_hamiltonian_monte_carlo
                        Runs one step of Hamiltonian Monte Carlo.
mcmc_metropolis_adjusted_langevin_algorithm
                        Runs one step of Metropolis-adjusted Langevin
                        algorithm.
mcmc_metropolis_hastings
                        Runs one step of the Metropolis-Hastings
                        algorithm.
mcmc_no_u_turn_sampler
                        Runs one step of the No U-Turn Sampler
mcmc_potential_scale_reduction
                        Gelman and Rubin (1992)'s potential scale
                        reduction for chain convergence.
mcmc_random_walk_metropolis
                        Runs one step of the RWM algorithm with
                        symmetric proposal.
mcmc_replica_exchange_mc
                        Runs one step of the Replica Exchange Monte
                        Carlo
mcmc_sample_annealed_importance_chain
                        Runs annealed importance sampling (AIS) to
                        estimate normalizing constants.
mcmc_sample_chain       Implements Markov chain Monte Carlo via
                        repeated 'TransitionKernel' steps.
mcmc_sample_halton_sequence
                        Returns a sample from the 'dim' dimensional
                        Halton sequence.
mcmc_simple_step_size_adaptation
                        Adapts the inner kernel's 'step_size' based on
                        'log_accept_prob'.
mcmc_slice_sampler      Runs one step of the slice sampler using a hit
                        and run approach
mcmc_transformed_transition_kernel
                        Applies a bijector to the MCMC's state space
mcmc_uncalibrated_hamiltonian_monte_carlo
                        Runs one step of Uncalibrated Hamiltonian Monte
                        Carlo
mcmc_uncalibrated_langevin
                        Runs one step of Uncalibrated Langevin
                        discretized diffusion.
mcmc_uncalibrated_random_walk
                        Generate proposal for the Random Walk
                        Metropolis algorithm.
params_size_categorical_mixture_of_one_hot_categorical
                        number of 'params' needed to create a
                        CategoricalMixtureOfOneHotCategorical
                        distribution
params_size_independent_bernoulli
                        number of 'params' needed to create an
                        IndependentBernoulli distribution
params_size_independent_logistic
                        number of 'params' needed to create an
                        IndependentLogistic distribution
params_size_independent_normal
                        number of 'params' needed to create an
                        IndependentNormal distribution
params_size_independent_poisson
                        number of 'params' needed to create an
                        IndependentPoisson distribution
params_size_mixture_logistic
                        number of 'params' needed to create a
                        MixtureLogistic distribution
params_size_mixture_normal
                        number of 'params' needed to create a
                        MixtureNormal distribution
params_size_mixture_same_family
                        number of 'params' needed to create a
                        MixtureSameFamily distribution
params_size_multivariate_normal_tri_l
                        number of 'params' needed to create a
                        MultivariateNormalTriL distribution
params_size_one_hot_categorical
                        number of 'params' needed to create a
                        OneHotCategorical distribution
sts_additive_state_space_model
                        A state space model representing a sum of
                        component state space models.
sts_autoregressive      Formal representation of an autoregressive
                        model.
sts_autoregressive_state_space_model
                        State space model for an autoregressive
                        process.
sts_build_factored_surrogate_posterior
                        Build a variational posterior that factors over
                        model parameters.
sts_build_factored_variational_loss
                        Build a loss function for variational inference
                        in STS models.
sts_constrained_seasonal_state_space_model
                        Seasonal state space model with effects
                        constrained to sum to zero.
sts_decompose_by_component
                        Decompose an observed time series into
                        contributions from each component.
sts_decompose_forecast_by_component
                        Decompose a forecast distribution into
                        contributions from each component.
sts_dynamic_linear_regression
                        Formal representation of a dynamic linear
                        regression model.
sts_dynamic_linear_regression_state_space_model
                        State space model for a dynamic linear
                        regression from provided covariates.
sts_fit_with_hmc        Draw posterior samples using Hamiltonian Monte
                        Carlo (HMC)
sts_forecast            Construct predictive distribution over future
                        observations
sts_linear_regression   Formal representation of a linear regression
                        from provided covariates.
sts_local_level         Formal representation of a local level model
sts_local_level_state_space_model
                        State space model for a local level
sts_local_linear_trend
                        Formal representation of a local linear trend
                        model
sts_local_linear_trend_state_space_model
                        State space model for a local linear trend
sts_one_step_predictive
                        Compute one-step-ahead predictive distributions
                        for all timesteps
sts_sample_uniform_initial_state
                        Initialize from a uniform [-2, 2] distribution
                        in unconstrained space.
sts_seasonal            Formal representation of a seasonal effect
                        model.
sts_seasonal_state_space_model
                        State space model for a seasonal effect.
sts_semi_local_linear_trend
                        Formal representation of a semi-local linear
                        trend model.
sts_semi_local_linear_trend_state_space_model
                        State space model for a semi-local linear
                        trend.
sts_smooth_seasonal     Formal representation of a smooth seasonal
                        effect model
sts_smooth_seasonal_state_space_model
                        State space model for a smooth seasonal effect
sts_sparse_linear_regression
                        Formal representation of a sparse linear
                        regression.
sts_sum                 Sum of structural time series components.
tfb_absolute_value      Computes'Y = g(X) = Abs(X)', element-wise
tfb_affine              Affine bijector
tfb_affine_linear_operator
                        ComputesY = g(X; shift, scale) = scale @ X +
                        shift
tfb_affine_scalar       AffineScalar bijector
tfb_batch_normalization
                        Computes'Y = g(X)' s.t. 'X = g^-1(Y) = (Y -
                        mean(Y)) / std(Y)'
tfb_blockwise           Bijector which applies a list of bijectors to
                        blocks of a Tensor
tfb_chain               Bijector which applies a sequence of bijectors
tfb_cholesky_outer_product
                        Computes'g(X) = X @ X.T' where 'X' is
                        lower-triangular, positive-diagonal matrix
tfb_cholesky_to_inv_cholesky
                        Maps the Cholesky factor of M to the Cholesky
                        factor of 'M^{-1}'
tfb_correlation_cholesky
                        Maps unconstrained reals to Cholesky-space
                        correlation matrices.
tfb_cumsum              Computes the cumulative sum of a tensor along a
                        specified axis.
tfb_discrete_cosine_transform
                        Computes'Y = g(X) = DCT(X)', where DCT type is
                        indicated by the type arg
tfb_exp                 Computes'Y=g(X)=exp(X)'
tfb_expm1               Computes'Y = g(X) = exp(X) - 1'
tfb_ffjord              Implements a continuous normalizing flow X->Y
                        defined via an ODE.
tfb_fill_scale_tri_l    Transforms unconstrained vectors to TriL
                        matrices with positive diagonal
tfb_fill_triangular     Transforms vectors to triangular
tfb_forward             Returns the forward Bijector evaluation, i.e.,
                        'X = g(Y)'.
tfb_forward_log_det_jacobian
                        Returns the result of the forward evaluation of
                        the log determinant of the Jacobian
tfb_gompertz_cdf        Compute Y = g(X) = 1 - exp(-c * (exp(rate * X)
                        - 1), the Gompertz CDF.
tfb_gumbel              Computes'Y = g(X) = exp(-exp(-(X - loc) /
                        scale))'
tfb_gumbel_cdf          Compute 'Y = g(X) = exp(-exp(-(X - loc) /
                        scale))', the Gumbel CDF.
tfb_identity            Computes'Y = g(X) = X'
tfb_inline              Bijector constructed from custom functions
tfb_inverse             Returns the inverse Bijector evaluation, i.e.,
                        'X = g^{-1}(Y)'.
tfb_inverse_log_det_jacobian
                        Returns the result of the inverse evaluation of
                        the log determinant of the Jacobian
tfb_invert              Bijector which inverts another Bijector
tfb_iterated_sigmoid_centered
                        Bijector which applies a Stick Breaking
                        procedure.
tfb_kumaraswamy         Computes'Y = g(X) = (1 - (1 - X)**(1 / b))**(1
                        / a)', with X in [0, 1]
tfb_kumaraswamy_cdf     Computes'Y = g(X) = (1 - (1 - X)**(1 / b))**(1
                        / a)', with X in [0, 1]
tfb_lambert_w_tail      LambertWTail transformation for heavy-tail
                        Lambert W x F random variables.
tfb_masked_autoregressive_default_template
                        Masked Autoregressive Density Estimator
tfb_masked_autoregressive_flow
                        Affine MaskedAutoregressiveFlow bijector
tfb_masked_dense        Autoregressively masked dense layer
tfb_matrix_inverse_tri_l
                        Computes 'g(L) = inv(L)', where L is a
                        lower-triangular matrix
tfb_matvec_lu           Matrix-vector multiply using LU decomposition
tfb_normal_cdf          Computes'Y = g(X) = NormalCDF(x)'
tfb_ordered             Bijector which maps a tensor x_k that has
                        increasing elements in the last dimension to an
                        unconstrained tensor y_k
tfb_pad                 Pads a value to the 'event_shape' of a
                        'Tensor'.
tfb_permute             Permutes the rightmost dimension of a Tensor
tfb_power_transform     Computes'Y = g(X) = (1 + X * c)**(1 / c)',
                        where 'X >= -1 / c'
tfb_rational_quadratic_spline
                        A piecewise rational quadratic spline, as
                        developed in Conor et al.(2019).
tfb_real_nvp            RealNVP affine coupling layer for vector-valued
                        events
tfb_real_nvp_default_template
                        Build a scale-and-shift function using a
                        multi-layer neural network
tfb_reciprocal          A Bijector that computes 'b(x) = 1. / x'
tfb_reshape             Reshapes the event_shape of a Tensor
tfb_scale               Compute Y = g(X; scale) = scale * X.
tfb_scale_matvec_diag   Compute Y = g(X; scale) = scale @ X
tfb_scale_matvec_linear_operator
                        Compute Y = g(X; scale) = scale @ X.
tfb_scale_matvec_lu     Matrix-vector multiply using LU decomposition.
tfb_scale_matvec_tri_l
                        Compute Y = g(X; scale) = scale @ X.
tfb_scale_tri_l         Transforms unconstrained vectors to TriL
                        matrices with positive diagonal
tfb_shift               Compute Y = g(X; shift) = X + shift.
tfb_shifted_gompertz_cdf
                        Compute 'Y = g(X) = (1 - exp(-rate * X)) *
                        exp(-c * exp(-rate * X))'
tfb_sigmoid             Computes'Y = g(X) = 1 / (1 + exp(-X))'
tfb_sinh                Bijector that computes 'Y = sinh(X)'.
tfb_sinh_arcsinh        Computes'Y = g(X) = Sinh( (Arcsinh(X) +
                        skewness) * tailweight )'
tfb_softmax_centered    Computes Y = g(X) = exp([X 0]) / sum(exp([X
                        0]))
tfb_softplus            Computes 'Y = g(X) = Log[1 + exp(X)]'
tfb_softsign            Computes Y = g(X) = X / (1 + |X|)
tfb_split               Split a 'Tensor' event along an axis into a
                        list of 'Tensor's.
tfb_square              Computes'g(X) = X^2'; X is a positive real
                        number.
tfb_tanh                Computes 'Y = tanh(X)'
tfb_transform_diagonal
                        Applies a Bijector to the diagonal of a matrix
tfb_transpose           Computes'Y = g(X) = transpose_rightmost_dims(X,
                        rightmost_perm)'
tfb_weibull             Computes'Y = g(X) = 1 - exp((-X / scale) **
                        concentration)' where X >= 0
tfb_weibull_cdf         Compute Y = g(X) = 1 - exp((-X / scale) **
                        concentration), X >= 0.
tfd_autoregressive      Autoregressive distribution
tfd_batch_reshape       Batch-Reshaping distribution
tfd_bates               Bates distribution.
tfd_bernoulli           Bernoulli distribution
tfd_beta                Beta distribution
tfd_beta_binomial       Beta-Binomial compound distribution
tfd_binomial            Binomial distribution
tfd_blockwise           Blockwise distribution
tfd_categorical         Categorical distribution over integers
tfd_cauchy              Cauchy distribution with location 'loc' and
                        scale 'scale'
tfd_cdf                 Cumulative distribution function. Given random
                        variable X, the cumulative distribution
                        function cdf is: 'cdf(x) := P[X <= x]'
tfd_chi                 Chi distribution
tfd_chi2                Chi Square distribution
tfd_cholesky_lkj        The CholeskyLKJ distribution on cholesky
                        factors of correlation matrices
tfd_continuous_bernoulli
                        Continuous Bernoulli distribution.
tfd_covariance          Covariance.
tfd_cross_entropy       Computes the (Shannon) cross entropy.
tfd_deterministic       Scalar 'Deterministic' distribution on the real
                        line
tfd_dirichlet           Dirichlet distribution
tfd_dirichlet_multinomial
                        Dirichlet-Multinomial compound distribution
tfd_doublesided_maxwell
                        Double-sided Maxwell distribution.
tfd_empirical           Empirical distribution
tfd_entropy             Shannon entropy in nats.
tfd_exp_relaxed_one_hot_categorical
                        ExpRelaxedOneHotCategorical distribution with
                        temperature and logits.
tfd_exponential         Exponential distribution
tfd_finite_discrete     The finite discrete distribution.
tfd_gamma               Gamma distribution
tfd_gamma_gamma         Gamma-Gamma distribution
tfd_gaussian_process    Marginal distribution of a Gaussian process at
                        finitely many points.
tfd_gaussian_process_regression_model
                        Posterior predictive distribution in a
                        conjugate GP regression model.
tfd_generalized_normal
                        The Generalized Normal distribution.
tfd_generalized_pareto
                        The Generalized Pareto distribution.
tfd_geometric           Geometric distribution
tfd_gumbel              Scalar Gumbel distribution with location 'loc'
                        and 'scale' parameters
tfd_half_cauchy         Half-Cauchy distribution
tfd_half_normal         Half-Normal distribution with scale 'scale'
tfd_hidden_markov_model
                        Hidden Markov model distribution
tfd_horseshoe           Horseshoe distribution
tfd_independent         Independent distribution from batch of
                        distributions
tfd_inverse_gamma       InverseGamma distribution
tfd_inverse_gaussian    Inverse Gaussian distribution
tfd_johnson_s_u         Johnson's SU-distribution.
tfd_joint_distribution_named
                        Joint distribution parameterized by named
                        distribution-making functions.
tfd_joint_distribution_named_auto_batched
                        Joint distribution parameterized by named
                        distribution-making functions.
tfd_joint_distribution_sequential
                        Joint distribution parameterized by
                        distribution-making functions
tfd_joint_distribution_sequential_auto_batched
                        Joint distribution parameterized by
                        distribution-making functions.
tfd_kl_divergence       Computes the Kullback-Leibler divergence.
tfd_kumaraswamy         Kumaraswamy distribution
tfd_laplace             Laplace distribution with location 'loc' and
                        'scale' parameters
tfd_linear_gaussian_state_space_model
                        Observation distribution from a linear Gaussian
                        state space model
tfd_lkj                 LKJ distribution on correlation matrices
tfd_log_cdf             Log cumulative distribution function.
tfd_log_logistic        The log-logistic distribution.
tfd_log_normal          Log-normal distribution
tfd_log_prob            Log probability density/mass function.
tfd_log_survival_function
                        Log survival function.
tfd_logistic            Logistic distribution with location 'loc' and
                        'scale' parameters
tfd_logit_normal        The Logit-Normal distribution
tfd_mean                Mean.
tfd_mixture             Mixture distribution
tfd_mixture_same_family
                        Mixture (same-family) distribution
tfd_mode                Mode.
tfd_multinomial         Multinomial distribution
tfd_multivariate_normal_diag
                        Multivariate normal distribution on 'R^k'
tfd_multivariate_normal_diag_plus_low_rank
                        Multivariate normal distribution on 'R^k'
tfd_multivariate_normal_full_covariance
                        Multivariate normal distribution on 'R^k'
tfd_multivariate_normal_linear_operator
                        The multivariate normal distribution on 'R^k'
tfd_multivariate_normal_tri_l
                        The multivariate normal distribution on 'R^k'
tfd_multivariate_student_t_linear_operator
                        Multivariate Student's t-distribution on 'R^k'
tfd_negative_binomial   NegativeBinomial distribution
tfd_normal              Normal distribution with loc and scale
                        parameters
tfd_one_hot_categorical
                        OneHotCategorical distribution
tfd_pareto              Pareto distribution
tfd_pert                Modified PERT distribution for modeling expert
                        predictions.
tfd_pixel_cnn           The Pixel CNN++ distribution
tfd_plackett_luce       Plackett-Luce distribution over permutations.
tfd_poisson             Poisson distribution
tfd_poisson_log_normal_quadrature_compound
                        'PoissonLogNormalQuadratureCompound'
                        distribution
tfd_power_spherical     The Power Spherical distribution over unit
                        vectors on 'S^{n-1}'.
tfd_prob                Probability density/mass function.
tfd_probit_bernoulli    ProbitBernoulli distribution.
tfd_quantile            Quantile function. Aka "inverse cdf" or
                        "percent point function".
tfd_quantized           Distribution representing the quantization 'Y =
                        ceiling(X)'
tfd_relaxed_bernoulli   RelaxedBernoulli distribution with temperature
                        and logits parameters
tfd_relaxed_one_hot_categorical
                        RelaxedOneHotCategorical distribution with
                        temperature and logits
tfd_sample              Generate samples of the specified shape.
tfd_sample_distribution
                        Sample distribution via independent draws.
tfd_sinh_arcsinh        The SinhArcsinh transformation of a
                        distribution on (-inf, inf)
tfd_spherical_uniform   The uniform distribution over unit vectors on
                        'S^{n-1}'.
tfd_stddev              Standard deviation.
tfd_student_t           Student's t-distribution
tfd_student_t_process   Marginal distribution of a Student's T process
                        at finitely many points
tfd_survival_function   Survival function.
tfd_transformed_distribution
                        A Transformed Distribution
tfd_triangular          Triangular distribution with 'low', 'high' and
                        'peak' parameters
tfd_truncated_cauchy    The Truncated Cauchy distribution.
tfd_truncated_normal    Truncated Normal distribution
tfd_uniform             Uniform distribution with 'low' and 'high'
                        parameters
tfd_variance            Variance.
tfd_variational_gaussian_process
                        Posterior predictive of a variational Gaussian
                        process
tfd_vector_deterministic
                        Vector Deterministic Distribution
tfd_vector_diffeomixture
                        VectorDiffeomixture distribution
tfd_vector_exponential_diag
                        The vectorization of the Exponential
                        distribution on 'R^k'
tfd_vector_exponential_linear_operator
                        The vectorization of the Exponential
                        distribution on 'R^k'
tfd_vector_laplace_diag
                        The vectorization of the Laplace distribution
                        on 'R^k'
tfd_vector_laplace_linear_operator
                        The vectorization of the Laplace distribution
                        on 'R^k'
tfd_vector_sinh_arcsinh_diag
                        The (diagonal) SinhArcsinh transformation of a
                        distribution on 'R^k'
tfd_von_mises           The von Mises distribution over angles
tfd_von_mises_fisher    The von Mises-Fisher distribution over unit
                        vectors on 'S^{n-1}'
tfd_weibull             The Weibull distribution with 'concentration'
                        and 'scale' parameters.
tfd_wishart             The matrix Wishart distribution on positive
                        definite matrices
tfd_wishart_linear_operator
                        The matrix Wishart distribution on positive
                        definite matrices
tfd_wishart_tri_l       The matrix Wishart distribution parameterized
                        with Cholesky factors.
tfd_zipf                Zipf distribution
tfp                     Handle to the 'tensorflow_probability' module
tfp_version             TensorFlow Probability Version
vi_amari_alpha          The Amari-alpha Csiszar-function in log-space
vi_arithmetic_geometric
                        The Arithmetic-Geometric Csiszar-function in
                        log-space
vi_chi_square           The chi-square Csiszar-function in log-space
vi_csiszar_vimco        Use VIMCO to lower the variance of the gradient
                        of csiszar_function(Avg(logu))
vi_dual_csiszar_function
                        Calculates the dual Csiszar-function in
                        log-space
vi_fit_surrogate_posterior
                        Fit a surrogate posterior to a target
                        (unnormalized) log density
vi_jeffreys             The Jeffreys Csiszar-function in log-space
vi_jensen_shannon       The Jensen-Shannon Csiszar-function in
                        log-space
vi_kl_forward           The forward Kullback-Leibler Csiszar-function
                        in log-space
vi_kl_reverse           The reverse Kullback-Leibler Csiszar-function
                        in log-space
vi_log1p_abs            The log1p-abs Csiszar-function in log-space
vi_modified_gan         The Modified-GAN Csiszar-function in log-space
vi_monte_carlo_variational_loss
                        Monte-Carlo approximation of an f-Divergence
                        variational loss
vi_pearson              The Pearson Csiszar-function in log-space
vi_squared_hellinger    The Squared-Hellinger Csiszar-function in
                        log-space
vi_symmetrized_csiszar_function
                        Symmetrizes a Csiszar-function in log-space
vi_t_power              The T-Power Csiszar-function in log-space
vi_total_variation      The Total Variation Csiszar-function in
                        log-space
vi_triangular           The Triangular Csiszar-function in log-space
