The cross product of x1 and x2 in R^3 is a vector
perpendicular to both x1 and x2. If x1 and x2 are arrays of
vectors, the vectors are defined by the last axis of x1 and x2
by default, and these axes can have dimensions 2 or 3.
Where the dimension of either x1 or x2 is 2, the third component of
the input vector is assumed to be zero and the cross product calculated
accordingly.
In cases where both input vectors have dimension 2, the z-component of the cross product is returned.
Arguments
- x1
Components of the first vector(s).
- x2
Components of the second vector(s).
- axisa
Axis of
x1that defines the vector(s). Defaults to-1.- axisb
Axis of
x2that defines the vector(s). Defaults to-1.- axisc
Axis of the result containing the cross product vector(s). Ignored if both input vectors have dimension 2, as the return is scalar. By default, the last axis.
- axis
If defined, the axis of
x1,x2and the result that defines the vector(s) and cross product(s). Overridesaxisa,axisbandaxisc.
Note
Torch backend does not support two dimensional vectors, or the
arguments axisa, axisb and axisc. Use axis instead.
See also
Other numpy ops: op_abs() op_add() op_all() 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_average() op_bincount() op_broadcast_to() op_ceil() op_clip() op_concatenate() op_conj() op_copy() op_correlate() op_cos() op_cosh() op_count_nonzero() op_ctc_decode() op_cumprod() op_cumsum() op_diag() op_diagonal() op_diff() op_digitize() op_divide() op_divide_no_nan() op_dot() op_einsum() op_empty() op_equal() op_exp() op_expand_dims() op_expm1() op_eye() op_flip() op_floor() op_floor_divide() op_full() op_full_like() op_get_item() op_greater() op_greater_equal() op_hstack() op_identity() op_imag() op_isclose() op_isfinite() op_isinf() op_isnan() op_less() op_less_equal() op_linspace() op_log() op_log10() op_log1p() op_log2() op_logaddexp() op_logical_and() op_logical_not() op_logical_or() op_logical_xor() op_logspace() op_lstsq() op_matmul() op_max() op_maximum() op_mean() op_median() op_meshgrid() op_min() op_minimum() op_mod() op_moveaxis() op_multiply() op_nan_to_num() op_ndim() op_negative() op_nonzero() op_not_equal() op_ones() op_ones_like() op_outer() op_pad() op_power() op_prod() op_quantile() op_ravel() op_real() op_reciprocal() op_repeat() op_reshape() op_roll() op_round() op_select() op_sign() op_sin() op_sinh() op_size() op_sort() op_split() op_sqrt() op_square() op_squeeze() op_stack() op_std() op_subtract() op_sum() op_swapaxes() op_take() op_take_along_axis() op_tan() op_tanh() op_tensordot() op_tile() op_trace() op_transpose() op_tri() op_tril() op_triu() op_var() op_vdot() op_vectorize() op_vstack() op_where() op_zeros() op_zeros_like()
Other ops: op_abs() op_add() op_all() 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_associative_scan() op_average() op_average_pool() op_batch_normalization() op_binary_crossentropy() op_bincount() op_broadcast_to() op_cast() op_categorical_crossentropy() op_ceil() op_cholesky() op_clip() op_concatenate() op_cond() op_conj() op_conv() op_conv_transpose() op_convert_to_numpy() op_convert_to_tensor() op_copy() op_correlate() op_cos() op_cosh() op_count_nonzero() op_ctc_decode() op_ctc_loss() op_cumprod() op_cumsum() op_custom_gradient() op_depthwise_conv() op_det() op_diag() op_diagonal() op_diff() op_digitize() op_divide() op_divide_no_nan() op_dot() op_dtype() op_eig() op_eigh() op_einsum() op_elu() op_empty() op_equal() op_erf() op_erfinv() op_exp() op_expand_dims() op_expm1() op_extract_sequences() op_eye() op_fft() op_fft2() op_flip() op_floor() op_floor_divide() op_fori_loop() op_full() op_full_like() op_gelu() op_get_item() op_greater() op_greater_equal() op_hard_sigmoid() op_hard_silu() op_hstack() op_identity() op_imag() op_image_affine_transform() op_image_crop() op_image_extract_patches() op_image_hsv_to_rgb() op_image_map_coordinates() op_image_pad() op_image_resize() op_image_rgb_to_grayscale() op_image_rgb_to_hsv() op_in_top_k() op_inv() op_irfft() op_is_tensor() op_isclose() op_isfinite() op_isinf() op_isnan() op_istft() op_leaky_relu() op_less() op_less_equal() op_linspace() op_log() op_log10() op_log1p() op_log2() op_log_sigmoid() op_log_softmax() op_logaddexp() 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_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_ndim() op_negative() op_nonzero() op_norm() op_normalize() op_not_equal() op_one_hot() op_ones() op_ones_like() op_outer() op_pad() op_power() op_prod() op_psnr() op_qr() op_quantile() op_ravel() op_real() op_reciprocal() op_relu() op_relu6() op_repeat() op_reshape() op_rfft() op_roll() op_round() op_rsqrt() op_scan() op_scatter() op_scatter_update() op_searchsorted() op_segment_max() op_segment_sum() op_select() op_selu() op_separable_conv() op_shape() op_sigmoid() op_sign() op_silu() op_sin() op_sinh() op_size() op_slice() op_slice_update() op_slogdet() op_softmax() op_softplus() op_softsign() op_solve() op_solve_triangular() op_sort() op_sparse_categorical_crossentropy() op_split() op_sqrt() op_square() op_squeeze() op_stack() op_std() op_stft() op_stop_gradient() op_subtract() op_sum() op_svd() op_swapaxes() op_switch() op_take() op_take_along_axis() op_tan() op_tanh() op_tensordot() op_tile() op_top_k() op_trace() op_transpose() op_tri() op_tril() op_triu() op_unstack() op_var() op_vdot() op_vectorize() op_vectorized_map() op_vstack() op_where() op_while_loop() op_zeros() op_zeros_like()