tfb_reshape {tfprobability} | R Documentation |
Reshapes the event_shape of a Tensor
Description
The semantics generally follow that of tf$reshape()
, with a few differences:
The user must provide both the input and output shape, so that the transformation can be inverted. If an input shape is not specified, the default assumes a vector-shaped input, i.e.,
event_shape_in = list(-1)
.The Reshape bijector automatically broadcasts over the leftmost dimensions of its input (sample_shape and batch_shape); only the rightmost event_ndims_in dimensions are reshaped. The number of dimensions to reshape is inferred from the provided event_shape_in (
event_ndims_in = length(event_shape_in))
.
Usage
tfb_reshape(
event_shape_out,
event_shape_in = c(-1),
validate_args = FALSE,
name = NULL
)
Arguments
event_shape_out |
An integer-like vector-shaped Tensor representing the event shape of the transformed output. |
event_shape_in |
An optional integer-like vector-shape Tensor representing the event shape of the input. This is required in order to define inverse operations; the default of list(-1) assumes a vector-shaped input. |
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. |
Value
a bijector instance.
See Also
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_ascending()
,
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_glow()
,
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_rayleigh_cdf()
,
tfb_real_nvp_default_template()
,
tfb_real_nvp()
,
tfb_reciprocal()
,
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()