Compute a forward-mode Jacobian-vector product.
Arguments
- fun
Function to differentiate. Its arguments and return value may be tensors, scalars, or nested containers of tensors or scalars.
- primals
List of primal argument values at which to evaluate the Jacobian of
fun. Its length must equal the number of positional parameters offun.- tangents
List of tangent values with the same nested structure and tensor shapes as
primals.- has_aux
Whether
funreturns a pair whose first element is the mathematical output to differentiate and whose second element is auxiliary data. Defaults toFALSE.
Value
If has_aux = FALSE, a list containing fun evaluated at
primals and its Jacobian-vector product evaluated with tangents. The
product has the same nested structure and tensor shapes as the output of
fun. If has_aux = TRUE, the auxiliary data is returned as a third
element.
See also
Other core ops: op_associative_scan() op_cast() op_cond() op_convert_to_numpy() op_convert_to_tensor() op_custom_gradient() op_dtype() op_fori_loop() op_is_tensor() op_map() op_rearrange() op_scan() op_scatter() op_scatter_update() op_searchsorted() op_shape() op_slice() op_slice_update() op_stop_gradient() op_subset() op_switch() op_unstack() op_vectorized_map() op_while_loop()
Other ops: op_abs() op_adaptive_average_pool() op_adaptive_max_pool() op_add() op_all() op_allclose() op_angle() op_any() op_append() op_arange() op_arccos() op_arccosh() op_arcsin() op_arcsinh() op_arctan() op_arctan2() op_arctanh() op_argmax() op_argmin() op_argpartition() op_argsort() op_array() op_array_split() op_associative_scan() op_average() op_average_pool() op_bartlett() op_batch_normalization() op_binary_crossentropy() op_bincount() op_bitwise_and() op_bitwise_invert() op_bitwise_left_shift() op_bitwise_not() op_bitwise_or() op_bitwise_right_shift() op_bitwise_xor() op_blackman() op_broadcast_to() op_cast() op_categorical_crossentropy() op_cbrt() op_cdist() op_ceil() op_celu() op_cholesky() op_cholesky_inverse() op_clip() op_concatenate() op_cond() op_conj() op_conv() op_conv_transpose() op_convert_to_numpy() op_convert_to_tensor() op_copy() op_corrcoef() op_correlate() op_cos() op_cosh() op_count_nonzero() op_cross() op_ctc_decode() op_ctc_loss() op_cumprod() op_cumsum() op_custom_gradient() op_deg2rad() op_depth_to_space() op_depthwise_conv() op_det() op_diag() op_diagflat() op_diagonal() op_diff() op_digitize() op_divide() op_divide_no_nan() op_dot() op_dot_product_attention() op_dsplit() op_dstack() op_dtype() op_eig() op_eigh() op_einsum() op_elu() op_empty() op_empty_like() op_equal() op_erf() op_erfc() op_erfinv() op_exp() op_exp2() op_expand_dims() op_expm1() op_extract_sequences() op_eye() op_fabs() op_fft() op_fft2() op_flip() op_fliplr() op_flipud() op_floor() op_floor_divide() op_fmax() op_fmin() op_fmod() op_fold() op_fori_loop() op_full() op_full_like() op_gcd() op_gelu() op_geomspace() op_get_item() op_glu() op_greater() op_greater_equal() op_hamming() op_hanning() op_hard_shrink() op_hard_sigmoid() op_hard_silu() op_hard_tanh() op_heaviside() op_histogram() op_hsplit() op_hstack() op_hypot() op_i0() op_identity() op_ifft2() op_imag() op_image_affine_transform() op_image_crop() op_image_extract_patches() op_image_extract_patches_3d() op_image_gaussian_blur() op_image_hsv_to_rgb() op_image_map_coordinates() op_image_pad() op_image_perspective_transform() op_image_resize() op_image_rgb_to_grayscale() op_image_rgb_to_hsv() op_image_scale_and_translate() op_image_sobel_edges() op_image_ssim() op_in_top_k() op_inner() op_inv() op_irfft() op_is_tensor() op_isclose() op_isfinite() op_isin() op_isinf() op_isnan() op_isneginf() op_isposinf() op_isreal() op_istft() op_kaiser() op_kron() op_layer_normalization() op_lcm() op_ldexp() op_leaky_relu() op_left_shift() op_less() op_less_equal() op_linspace() op_log() op_log10() op_log1p() op_log2() op_log_sigmoid() op_log_softmax() op_logaddexp() op_logaddexp2() op_logdet() op_logical_and() op_logical_not() op_logical_or() op_logical_xor() op_logspace() op_logsumexp() op_lstsq() op_lu_factor() op_map() op_matmul() op_matrix_rank() op_max() op_max_pool() op_maximum() op_mean() op_median() op_meshgrid() op_min() op_minimum() op_mod() op_moments() op_moveaxis() op_multi_hot() op_multiply() op_nan_to_num() op_nanargmax() op_nanargmin() op_nancumprod() op_nancumsum() op_nanmax() op_nanmean() op_nanmedian() op_nanmin() op_nanpercentile() op_nanprod() op_nanquantile() op_nanstd() op_nansum() op_nanvar() op_ndim() op_negative() op_nextafter() op_nonzero() op_norm() op_normalize() op_not_equal() op_one_hot() op_ones() op_ones_like() op_outer() op_pad() op_percentile() op_pinv() op_polar() op_power() op_prod() op_psnr() op_ptp() op_qr() op_quantile() op_rad2deg() op_ravel() op_real() op_rearrange() op_reciprocal() op_relu() op_relu6() op_repeat() op_reshape() op_rfft() op_right_shift() op_rms_normalization() op_roll() op_rot90() op_round() op_rsqrt() op_saturate_cast() op_scan() op_scatter() op_scatter_update() op_searchsorted() op_segment_max() op_segment_min() op_segment_prod() op_segment_sum() op_select() op_selu() op_separable_conv() op_shape() op_sigmoid() op_sign() op_signbit() op_silu() op_sin() op_sinc() op_sinh() op_size() op_slice() op_slice_update() op_slogdet() op_soft_shrink() op_softmax() op_softplus() op_softsign() op_solve() op_solve_triangular() op_sort() op_space_to_depth() op_sparse_categorical_crossentropy() op_sparse_plus() op_sparse_sigmoid() op_sparsemax() op_split() op_sqrt() op_square() op_squareplus() op_squeeze() op_stack() op_std() op_stft() op_stop_gradient() op_subset() op_subtract() op_sum() op_svd() op_swapaxes() op_switch() op_take() op_take_along_axis() op_tan() op_tanh() op_tanh_shrink() op_tensordot() op_threshold() op_tile() op_top_k() op_trace() op_transpose() op_trapezoid() op_tri() op_tril() op_triu() op_trunc() op_unfold() op_unique() op_unravel_index() op_unstack() op_vander() op_var() op_vdot() op_vectorize() op_vectorized_map() op_view() op_view_as_complex() op_view_as_real() op_vsplit() op_vstack() op_where() op_while_loop() op_zeros() op_zeros_like()
Examples
x <- op_convert_to_tensor(3)
op_jvp(function(x) op_square(x), list(x), list(op_convert_to_tensor(1)))
#> [[1]]
#> tf.Tensor(9.0, shape=(), dtype=float32)
#>
#> [[2]]
#> tf.Tensor(6.0, shape=(), dtype=float32)
#>