class MXNet::NDArray::Internal

Defined in:

Class Method Summary

Class Method Detail

def self._add(lhs : MXNet::NDArray?, rhs : MXNet::NDArray?, **kwargs) #

def self._arange(start, **kwargs) #

def self._broadcast_backward(**kwargs) #

def self._CachedOp(**kwargs) #

def self._cond(data : Array(MXNet::NDArray), num_args, num_outputs, cond_input_locs, then_input_locs, else_input_locs, **kwargs) #

def self._copy(data : MXNet::NDArray?, **kwargs) #

def self._copyto(data : MXNet::NDArray?, **kwargs) #

def self._crop_assign(lhs : MXNet::NDArray?, rhs : MXNet::NDArray?, begin _begin, end _end, **kwargs) #

def self._crop_assign_scalar(data : MXNet::NDArray?, begin _begin, end _end, **kwargs) #

def self._CrossDeviceCopy(**kwargs) #

def self._CustomFunction(**kwargs) #

def self._cvcopyMakeBorder(top, bot, left, right, **kwargs) #

def self._cvimdecode(**kwargs) #

def self._cvimread(filename, **kwargs) #

def self._cvimresize(w, h, **kwargs) #

def self._Div(lhs : MXNet::NDArray?, rhs : MXNet::NDArray?, **kwargs) #

def self._div(lhs : MXNet::NDArray?, rhs : MXNet::NDArray?, **kwargs) #

def self._div_scalar(data : MXNet::NDArray?, scalar, **kwargs) #

def self._DivScalar(data : MXNet::NDArray?, scalar, **kwargs) #

def self._Equal(lhs : MXNet::NDArray?, rhs : MXNet::NDArray?, **kwargs) #

def self._equal(lhs : MXNet::NDArray?, rhs : MXNet::NDArray?, **kwargs) #

def self._equal_scalar(data : MXNet::NDArray?, scalar, **kwargs) #

def self._EqualScalar(data : MXNet::NDArray?, scalar, **kwargs) #

def self._eye(n, **kwargs) #

def self._foreach(data : Array(MXNet::NDArray), num_args, num_outputs, num_out_data, in_state_locs, in_data_locs, remain_locs, **kwargs) #

def self._full(value, **kwargs) #

def self._grad_add(lhs : MXNet::NDArray?, rhs : MXNet::NDArray?, **kwargs) #

def self._Greater(lhs : MXNet::NDArray?, rhs : MXNet::NDArray?, **kwargs) #

def self._greater(lhs : MXNet::NDArray?, rhs : MXNet::NDArray?, **kwargs) #

def self._Greater_Equal(lhs : MXNet::NDArray?, rhs : MXNet::NDArray?, **kwargs) #

def self._greater_equal(lhs : MXNet::NDArray?, rhs : MXNet::NDArray?, **kwargs) #

def self._greater_equal_scalar(data : MXNet::NDArray?, scalar, **kwargs) #

def self._greater_scalar(data : MXNet::NDArray?, scalar, **kwargs) #

def self._GreaterEqualScalar(data : MXNet::NDArray?, scalar, **kwargs) #

def self._GreaterScalar(data : MXNet::NDArray?, scalar, **kwargs) #

def self._histogram(data : MXNet::NDArray?, bins : MXNet::NDArray?, **kwargs) #

def self._Hypot(lhs : MXNet::NDArray?, rhs : MXNet::NDArray?, **kwargs) #

def self._hypot(lhs : MXNet::NDArray?, rhs : MXNet::NDArray?, **kwargs) #

def self._hypot_scalar(data : MXNet::NDArray?, scalar, **kwargs) #

def self._HypotScalar(data : MXNet::NDArray?, scalar, **kwargs) #

def self._identity_with_attr_like_rhs(lhs : MXNet::NDArray?, rhs : MXNet::NDArray?, **kwargs) #

def self._image_adjust_lighting(data : MXNet::NDArray?, alpha, **kwargs) #

def self._image_flip_left_right(data : MXNet::NDArray?, **kwargs) #

def self._image_flip_top_bottom(data : MXNet::NDArray?, **kwargs) #

def self._image_normalize(data : MXNet::NDArray?, mean, std, **kwargs) #

def self._image_random_brightness(data : MXNet::NDArray?, min_factor, max_factor, **kwargs) #

def self._image_random_color_jitter(data : MXNet::NDArray?, brightness, contrast, saturation, hue, **kwargs) #

def self._image_random_contrast(data : MXNet::NDArray?, min_factor, max_factor, **kwargs) #

def self._image_random_flip_left_right(data : MXNet::NDArray?, **kwargs) #

def self._image_random_flip_top_bottom(data : MXNet::NDArray?, **kwargs) #

def self._image_random_hue(data : MXNet::NDArray?, min_factor, max_factor, **kwargs) #

def self._image_random_lighting(data : MXNet::NDArray?, **kwargs) #

def self._image_random_saturation(data : MXNet::NDArray?, min_factor, max_factor, **kwargs) #

def self._image_to_tensor(data : MXNet::NDArray?, **kwargs) #

def self._imdecode(mean : MXNet::NDArray?, index, x0, y0, x1, y1, c, size, **kwargs) #

def self._Lesser(lhs : MXNet::NDArray?, rhs : MXNet::NDArray?, **kwargs) #

def self._lesser(lhs : MXNet::NDArray?, rhs : MXNet::NDArray?, **kwargs) #

def self._Lesser_Equal(lhs : MXNet::NDArray?, rhs : MXNet::NDArray?, **kwargs) #

def self._lesser_equal(lhs : MXNet::NDArray?, rhs : MXNet::NDArray?, **kwargs) #

def self._lesser_equal_scalar(data : MXNet::NDArray?, scalar, **kwargs) #

def self._lesser_scalar(data : MXNet::NDArray?, scalar, **kwargs) #

def self._LesserEqualScalar(data : MXNet::NDArray?, scalar, **kwargs) #

def self._LesserScalar(data : MXNet::NDArray?, scalar, **kwargs) #

def self._Logical_And(lhs : MXNet::NDArray?, rhs : MXNet::NDArray?, **kwargs) #

def self._logical_and(lhs : MXNet::NDArray?, rhs : MXNet::NDArray?, **kwargs) #

def self._logical_and_scalar(data : MXNet::NDArray?, scalar, **kwargs) #

def self._Logical_Or(lhs : MXNet::NDArray?, rhs : MXNet::NDArray?, **kwargs) #

def self._logical_or(lhs : MXNet::NDArray?, rhs : MXNet::NDArray?, **kwargs) #

def self._logical_or_scalar(data : MXNet::NDArray?, scalar, **kwargs) #

def self._Logical_Xor(lhs : MXNet::NDArray?, rhs : MXNet::NDArray?, **kwargs) #

def self._logical_xor(lhs : MXNet::NDArray?, rhs : MXNet::NDArray?, **kwargs) #

def self._logical_xor_scalar(data : MXNet::NDArray?, scalar, **kwargs) #

def self._LogicalAndScalar(data : MXNet::NDArray?, scalar, **kwargs) #

def self._LogicalOrScalar(data : MXNet::NDArray?, scalar, **kwargs) #

def self._LogicalXorScalar(data : MXNet::NDArray?, scalar, **kwargs) #

def self._Maximum(lhs : MXNet::NDArray?, rhs : MXNet::NDArray?, **kwargs) #

def self._maximum(lhs : MXNet::NDArray?, rhs : MXNet::NDArray?, **kwargs) #

def self._maximum_scalar(data : MXNet::NDArray?, scalar, **kwargs) #

def self._MaximumScalar(data : MXNet::NDArray?, scalar, **kwargs) #

def self._Minimum(lhs : MXNet::NDArray?, rhs : MXNet::NDArray?, **kwargs) #

def self._minimum(lhs : MXNet::NDArray?, rhs : MXNet::NDArray?, **kwargs) #

def self._minimum_scalar(data : MXNet::NDArray?, scalar, **kwargs) #

def self._MinimumScalar(data : MXNet::NDArray?, scalar, **kwargs) #

def self._Minus(lhs : MXNet::NDArray?, rhs : MXNet::NDArray?, **kwargs) #

def self._minus(lhs : MXNet::NDArray?, rhs : MXNet::NDArray?, **kwargs) #

def self._minus_scalar(data : MXNet::NDArray?, scalar, **kwargs) #

def self._MinusScalar(data : MXNet::NDArray?, scalar, **kwargs) #

def self._Mod(lhs : MXNet::NDArray?, rhs : MXNet::NDArray?, **kwargs) #

def self._mod(lhs : MXNet::NDArray?, rhs : MXNet::NDArray?, **kwargs) #

def self._mod_scalar(data : MXNet::NDArray?, scalar, **kwargs) #

def self._ModScalar(data : MXNet::NDArray?, scalar, **kwargs) #

def self._Mul(lhs : MXNet::NDArray?, rhs : MXNet::NDArray?, **kwargs) #

def self._mul(lhs : MXNet::NDArray?, rhs : MXNet::NDArray?, **kwargs) #

def self._mul_scalar(data : MXNet::NDArray?, scalar, **kwargs) #

def self._MulScalar(data : MXNet::NDArray?, scalar, **kwargs) #

def self._Native(data : Array(MXNet::NDArray), info, **kwargs) #

def self._NDArray(data : Array(MXNet::NDArray), info, **kwargs) #

def self._NoGradient(**kwargs) #

def self._Not_Equal(lhs : MXNet::NDArray?, rhs : MXNet::NDArray?, **kwargs) #

def self._not_equal(lhs : MXNet::NDArray?, rhs : MXNet::NDArray?, **kwargs) #

def self._not_equal_scalar(data : MXNet::NDArray?, scalar, **kwargs) #

def self._NotEqualScalar(data : MXNet::NDArray?, scalar, **kwargs) #

def self._onehot_encode(**kwargs) #

def self._ones(**kwargs) #

def self._Plus(lhs : MXNet::NDArray?, rhs : MXNet::NDArray?, **kwargs) #

def self._plus(lhs : MXNet::NDArray?, rhs : MXNet::NDArray?, **kwargs) #

def self._plus_scalar(data : MXNet::NDArray?, scalar, **kwargs) #

def self._PlusScalar(data : MXNet::NDArray?, scalar, **kwargs) #

def self._Power(lhs : MXNet::NDArray?, rhs : MXNet::NDArray?, **kwargs) #

def self._power(lhs : MXNet::NDArray?, rhs : MXNet::NDArray?, **kwargs) #

def self._power_scalar(data : MXNet::NDArray?, scalar, **kwargs) #

def self._PowerScalar(data : MXNet::NDArray?, scalar, **kwargs) #

def self._random_exponential(**kwargs) #

def self._random_gamma(**kwargs) #

def self._random_generalized_negative_binomial(**kwargs) #

def self._random_negative_binomial(**kwargs) #

def self._random_normal(**kwargs) #

def self._random_poisson(**kwargs) #

def self._random_randint(low, high, **kwargs) #

def self._random_uniform(**kwargs) #

def self._ravel_multi_index(data : MXNet::NDArray?, **kwargs) #

def self._rdiv_scalar(data : MXNet::NDArray?, scalar, **kwargs) #

def self._RDivScalar(data : MXNet::NDArray?, scalar, **kwargs) #

def self._rminus_scalar(data : MXNet::NDArray?, scalar, **kwargs) #

def self._RMinusScalar(data : MXNet::NDArray?, scalar, **kwargs) #

def self._rmod_scalar(data : MXNet::NDArray?, scalar, **kwargs) #

def self._RModScalar(data : MXNet::NDArray?, scalar, **kwargs) #

def self._rpower_scalar(data : MXNet::NDArray?, scalar, **kwargs) #

def self._RPowerScalar(data : MXNet::NDArray?, scalar, **kwargs) #

def self._sample_exponential(lam : MXNet::NDArray?, **kwargs) #

def self._sample_gamma(alpha : MXNet::NDArray?, beta : MXNet::NDArray?, **kwargs) #

def self._sample_generalized_negative_binomial(mu : MXNet::NDArray?, alpha : MXNet::NDArray?, **kwargs) #

def self._sample_multinomial(data : MXNet::NDArray?, **kwargs) #

def self._sample_negative_binomial(k : MXNet::NDArray?, p : MXNet::NDArray?, **kwargs) #

def self._sample_normal(mu : MXNet::NDArray?, sigma : MXNet::NDArray?, **kwargs) #

def self._sample_poisson(lam : MXNet::NDArray?, **kwargs) #

def self._sample_uniform(low : MXNet::NDArray?, high : MXNet::NDArray?, **kwargs) #

def self._scatter_elemwise_div(lhs : MXNet::NDArray?, rhs : MXNet::NDArray?, **kwargs) #

def self._scatter_minus_scalar(data : MXNet::NDArray?, scalar, **kwargs) #

def self._scatter_plus_scalar(data : MXNet::NDArray?, scalar, **kwargs) #

def self._scatter_set_nd(lhs : MXNet::NDArray?, rhs : MXNet::NDArray?, indices : MXNet::NDArray?, shape, **kwargs) #

def self._set_value(**kwargs) #

def self._shuffle(data : MXNet::NDArray?, **kwargs) #

def self._slice_assign(lhs : MXNet::NDArray?, rhs : MXNet::NDArray?, begin _begin, end _end, **kwargs) #

def self._slice_assign_scalar(data : MXNet::NDArray?, begin _begin, end _end, **kwargs) #

def self._square_sum(data : MXNet::NDArray?, **kwargs) #

def self._sub(lhs : MXNet::NDArray?, rhs : MXNet::NDArray?, **kwargs) #

def self._unravel_index(data : MXNet::NDArray?, **kwargs) #

def self._while_loop(data : Array(MXNet::NDArray), num_args, num_outputs, num_out_data, max_iterations, cond_input_locs, func_input_locs, func_var_locs, **kwargs) #

def self._zeros(**kwargs) #