Build a scale-and-shift function using a multi-layer neural network
This will be wrapped in a make_template to ensure the variables are only
created once. It takes the d-dimensional input x[0:d] and returns the D-d
dimensional outputs loc ("mu") and log_scale ("alpha").
tfb_real_nvp_default_template( hidden_layers, shift_only = FALSE, activation = tf$nn$relu, name = NULL, ... )
hidden_layers |
list-like of non-negative integer, scalars indicating the number
of units in each hidden layer. Default: |
shift_only |
logical indicating if only the shift term shall be computed (i.e. NICE bijector). Default: FALSE. |
activation |
Activation function (callable). Explicitly setting to NULL implies a linear activation. |
name |
A name for ops managed by this function. Default: "tfb_real_nvp_default_template". |
... |
tf$layers$dense arguments |
The default template does not support conditioning and will raise an exception if condition_kwargs are passed to it. To use conditioning in real nvp bijector, implement a conditioned shift/scale template that handles the condition_kwargs.
list of:
shift: Float-like Tensor of shift terms
log_scale: Float-like Tensor of log(scale) terms
For usage examples see tfb_forward(), tfb_inverse(), tfb_inverse_log_det_jacobian().
Other bijectors:
tfb_absolute_value(),
tfb_affine_linear_operator(),
tfb_affine_scalar(),
tfb_affine(),
tfb_batch_normalization(),
tfb_blockwise(),
tfb_chain(),
tfb_cholesky_outer_product(),
tfb_cholesky_to_inv_cholesky(),
tfb_correlation_cholesky(),
tfb_cumsum(),
tfb_discrete_cosine_transform(),
tfb_expm1(),
tfb_exp(),
tfb_ffjord(),
tfb_fill_scale_tri_l(),
tfb_fill_triangular(),
tfb_gompertz_cdf(),
tfb_gumbel_cdf(),
tfb_gumbel(),
tfb_identity(),
tfb_inline(),
tfb_invert(),
tfb_iterated_sigmoid_centered(),
tfb_kumaraswamy_cdf(),
tfb_kumaraswamy(),
tfb_lambert_w_tail(),
tfb_masked_autoregressive_default_template(),
tfb_masked_autoregressive_flow(),
tfb_masked_dense(),
tfb_matrix_inverse_tri_l(),
tfb_matvec_lu(),
tfb_normal_cdf(),
tfb_ordered(),
tfb_pad(),
tfb_permute(),
tfb_power_transform(),
tfb_rational_quadratic_spline(),
tfb_real_nvp(),
tfb_reciprocal(),
tfb_reshape(),
tfb_scale_matvec_diag(),
tfb_scale_matvec_linear_operator(),
tfb_scale_matvec_lu(),
tfb_scale_matvec_tri_l(),
tfb_scale_tri_l(),
tfb_scale(),
tfb_shifted_gompertz_cdf(),
tfb_shift(),
tfb_sigmoid(),
tfb_sinh_arcsinh(),
tfb_sinh(),
tfb_softmax_centered(),
tfb_softplus(),
tfb_softsign(),
tfb_split(),
tfb_square(),
tfb_tanh(),
tfb_transform_diagonal(),
tfb_transpose(),
tfb_weibull_cdf(),
tfb_weibull()
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