ComputesY = g(X) = transpose_rightmost_dims(X, rightmost_perm)
This bijector is semantically similar to tf.transpose except that it
transposes only the rightmost "event" dimensions. That is, unlike
tf$transpose the perm argument is itself a permutation of
tf$range(rightmost_transposed_ndims) rather than tf$range(tf$rank(x)),
i.e., users specify the (rightmost) dimensions to permute, not all dimensions.
tfb_transpose( perm = NULL, rightmost_transposed_ndims = NULL, validate_args = FALSE, name = "transpose" )
perm |
Positive integer vector-shaped Tensor representing permutation of
rightmost dims (for forward transformation). Note that the 0th index
represents the first of the rightmost dims and the largest value must be
rightmost_transposed_ndims - 1 and corresponds to |
rightmost_transposed_ndims |
Positive integer scalar-shaped Tensor
representing the number of rightmost dimensions to permute.
Only one of perm and rightmost_transposed_ndims can (and must) be
specified. Default value: |
validate_args |
Logical, default FALSE. Whether to validate input with asserts. If validate_args is FALSE, and the inputs are invalid, correct behavior is not guaranteed. |
name |
name prefixed to Ops created by this class. |
The actual (forward) transformation is:
sample_batch_ndims <- tf$rank(x) - tf$size(perm)
perm = tf$concat(list(tf$range(sample_batch_ndims), sample_batch_ndims + perm),axis=0)
tf$transpose(x, perm)
a bijector instance.
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_default_template(),
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_weibull_cdf(),
tfb_weibull()
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