Reshapes the event_shape of a Tensor
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)).
tfb_reshape( event_shape_out, event_shape_in = c(-1), validate_args = FALSE, name = NULL )
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. |
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_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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