op_polar: Constructs a complex tensor whose elements are Cartesian

In keras3: R Interface to 'Keras'

Constructs a complex tensor whose elements are Cartesian

Description

coordinates corresponding to the polar coordinates with absolute value abs and angle angle.

The operation is numerically equivalent to torch.polar(). It is not equivalent to scipy.lingalg.polar() which performs Singular Value Decomposition.

Given the magnitude (abs_) and angle (angle), this function computes the corresponding complex number in the form of real + imaginary * 1i, where:

• real = abs_ * cos(angle)

• imaginary = abs_ * sin(angle)

Usage

op_polar(abs_, angle)

Arguments

abs_	The magnitude (absolute value) of the complex number.
angle	The angle (in radians) of the complex number.

Value

A complex number (or array of complex numbers) with the same shape as abs_ and angle.

Examples

abs_ <- random_normal(c(1, 2))
angle <- random_normal(c(1, 2))
op_shape(op_polar(abs_, angle))

## shape(1, 2)

op_polar(abs_, angle)

## tf.Tensor([[-0.10252866-1.2460487j -0.2586355 -1.0352845j]], shape=(1, 2), dtype=complex64)

See Also

Other nn ops:
op_average_pool()
op_batch_normalization()
op_binary_crossentropy()
op_categorical_crossentropy()
op_celu()
op_conv()
op_conv_transpose()
op_ctc_loss()
op_depthwise_conv()
op_dot_product_attention()
op_elu()
op_gelu()
op_glu()
op_hard_shrink()
op_hard_sigmoid()
op_hard_silu()
op_hard_tanh()
op_leaky_relu()
op_log_sigmoid()
op_log_softmax()
op_max_pool()
op_moments()
op_multi_hot()
op_normalize()
op_one_hot()
op_psnr()
op_relu()
op_relu6()
op_rms_normalization()
op_selu()
op_separable_conv()
op_sigmoid()
op_silu()
op_soft_shrink()
op_softmax()
op_softplus()
op_softsign()
op_sparse_categorical_crossentropy()
op_sparse_plus()
op_sparsemax()
op_squareplus()
op_tanh_shrink()
op_threshold()
op_unravel_index()

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_bitwise_and()
op_bitwise_invert()
op_bitwise_left_shift()
op_bitwise_not()
op_bitwise_or()
op_bitwise_right_shift()
op_bitwise_xor()
op_broadcast_to()
op_cast()
op_categorical_crossentropy()
op_ceil()
op_celu()
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_cross()
op_ctc_decode()
op_ctc_loss()
op_cumprod()
op_cumsum()
op_custom_gradient()
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_dtype()
op_eig()
op_eigh()
op_einsum()
op_elu()
op_empty()
op_equal()
op_erf()
op_erfinv()
op_exp()
op_exp2()
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_glu()
op_greater()
op_greater_equal()
op_hard_shrink()
op_hard_sigmoid()
op_hard_silu()
op_hard_tanh()
op_histogram()
op_hstack()
op_identity()
op_ifft2()
op_imag()
op_image_affine_transform()
op_image_crop()
op_image_extract_patches()
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_in_top_k()
op_inner()
op_inv()
op_irfft()
op_is_tensor()
op_isclose()
op_isfinite()
op_isinf()
op_isnan()
op_istft()
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_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_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_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_sum()
op_select()
op_selu()
op_separable_conv()
op_shape()
op_sigmoid()
op_sign()
op_signbit()
op_silu()
op_sin()
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_sparse_categorical_crossentropy()
op_sparse_plus()
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_tri()
op_tril()
op_triu()
op_trunc()
op_unravel_index()
op_unstack()
op_var()
op_vdot()
op_vectorize()
op_vectorized_map()
op_vstack()
op_where()
op_while_loop()
op_zeros()
op_zeros_like()

keras3 documentation built on June 8, 2025, 1:36 p.m.