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NDArray methods
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| // arg len: 2, num of methods: 59 | |
| def BlockGrad (data : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def ElementWiseSum (args : Array[NDArray], out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def Flatten (data : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def abs (data : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def add_n (args : Array[NDArray], out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def arccos (data : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def arccosh (data : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def arcsin (data : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def arcsinh (data : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def arctan (data : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def arctanh (data : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def argmax_channel (data : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def cbrt (data : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def ceil (data : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def cos (data : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def cosh (data : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def degrees (data : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def exp (data : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def expm1 (data : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def fix (data : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def flatten (data : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def floor (data : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def gamma (data : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def gammaln (data : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def identity (data : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def khatri_rao (args : Array[NDArray], out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def linalg_gelqf (A : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def linalg_potrf (A : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def linalg_potri (A : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def linalg_sumlogdiag (A : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def log (data : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def log10 (data : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def log1p (data : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def log2 (data : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def logical_not (data : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def make_loss (data : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def negative (data : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def ones_like (data : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def radians (data : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def rcbrt (data : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def reciprocal (data : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def relu (data : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def rint (data : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def round (data : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def rsqrt (data : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def shuffle (data : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def sigmoid (data : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def sign (data : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def sin (data : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def sinh (data : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def size_array (data : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def softsign (data : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def sqrt (data : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def square (data : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def stop_gradient (data : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def tan (data : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def tanh (data : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def trunc (data : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def zeros_like (data : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| // arg len: 3, num of methods: 48 | |
| def Activation (data : NDArray, act_type : String, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def BilinearSampler (data : NDArray, grid : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def Cast (data : NDArray, dtype : String, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def SoftmaxActivation (data : NDArray, mode : Option[String] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def batch_take (a : NDArray, indices : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def broadcast_add (lhs : NDArray, rhs : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def broadcast_div (lhs : NDArray, rhs : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def broadcast_equal (lhs : NDArray, rhs : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def broadcast_greater (lhs : NDArray, rhs : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def broadcast_greater_equal (lhs : NDArray, rhs : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def broadcast_hypot (lhs : NDArray, rhs : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def broadcast_lesser (lhs : NDArray, rhs : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def broadcast_lesser_equal (lhs : NDArray, rhs : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def broadcast_logical_and (lhs : NDArray, rhs : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def broadcast_logical_or (lhs : NDArray, rhs : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def broadcast_logical_xor (lhs : NDArray, rhs : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def broadcast_maximum (lhs : NDArray, rhs : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def broadcast_minimum (lhs : NDArray, rhs : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def broadcast_minus (lhs : NDArray, rhs : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def broadcast_mod (lhs : NDArray, rhs : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def broadcast_mul (lhs : NDArray, rhs : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def broadcast_not_equal (lhs : NDArray, rhs : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def broadcast_plus (lhs : NDArray, rhs : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def broadcast_power (lhs : NDArray, rhs : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def broadcast_sub (lhs : NDArray, rhs : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def broadcast_to (data : NDArray, shape : Option[Shape] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def cast (data : NDArray, dtype : String, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def cast_storage (data : NDArray, stype : String, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def choose_element_0index (lhs : NDArray, rhs : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def depth_to_space (data : NDArray, block_size : Int, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def diag (data : NDArray, k : Option[Int] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def elemwise_add (lhs : NDArray, rhs : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def elemwise_div (lhs : NDArray, rhs : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def elemwise_mul (lhs : NDArray, rhs : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def elemwise_sub (lhs : NDArray, rhs : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def expand_dims (data : NDArray, axis : Int, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def flip (data : NDArray, axis : Shape, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def gather_nd (data : NDArray, indices : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def ravel_multi_index (data : NDArray, shape : Option[Shape] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def reshape_like (lhs : NDArray, rhs : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def reverse (data : NDArray, axis : Shape, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def smooth_l1 (data : NDArray, scalar : MXFloat, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def softmax_cross_entropy (data : NDArray, label : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def space_to_depth (data : NDArray, block_size : Int, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def squeeze (data : Array[NDArray], axis : Option[Shape] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def tile (data : NDArray, reps : Shape, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def transpose (data : NDArray, axes : Option[Shape] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def unravel_index (data : NDArray, shape : Option[Shape] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| // arg len: 4, num of methods: 27 | |
| def Concat (data : Array[NDArray], num_args : Int, dim : Option[Int] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def GridGenerator (data : NDArray, transform_type : String, target_shape : Option[Shape] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def L2Normalization (data : NDArray, eps : Option[MXFloat] = None, mode : Option[String] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def LinearRegressionOutput (data : NDArray, label : NDArray, grad_scale : Option[MXFloat] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def LogisticRegressionOutput (data : NDArray, label : NDArray, grad_scale : Option[MXFloat] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def MAERegressionOutput (data : NDArray, label : NDArray, grad_scale : Option[MXFloat] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def SwapAxis (data : NDArray, dim1 : Option[Int] = None, dim2 : Option[Int] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def argmax (data : NDArray, axis : Option[Int] = None, keepdims : Option[Boolean] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def argmin (data : NDArray, axis : Option[Int] = None, keepdims : Option[Boolean] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def broadcast_axes (data : NDArray, axis : Option[Shape] = None, size : Option[Shape] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def broadcast_axis (data : NDArray, axis : Option[Shape] = None, size : Option[Shape] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def clip (data : NDArray, a_min : MXFloat, a_max : MXFloat, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def concat (data : Array[NDArray], num_args : Int, dim : Option[Int] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def fill_element_0index (lhs : NDArray, mhs : NDArray, rhs : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def hard_sigmoid (data : NDArray, alpha : Option[MXFloat] = None, beta : Option[MXFloat] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def linalg_syrk (A : NDArray, transpose : Option[Boolean] = None, alpha : Option[Double] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def log_softmax (data : NDArray, axis : Option[Int] = None, temperature : Option[Double] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def repeat (data : NDArray, repeats : Int, axis : Option[Int] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def sample_exponential (lam : NDArray, shape : Option[Shape] = None, dtype : Option[String] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def sample_poisson (lam : NDArray, shape : Option[Shape] = None, dtype : Option[String] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def scatter_nd (data : NDArray, indices : NDArray, shape : Shape, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def slice_like (data : NDArray, shape_like : NDArray, axes : Option[Shape] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def softmax (data : NDArray, axis : Option[Int] = None, temperature : Option[Double] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def sort (data : NDArray, axis : Option[Int] = None, is_ascend : Option[Boolean] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def stack (data : Array[NDArray], axis : Option[Int] = None, num_args : Int, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def swapaxes (data : NDArray, dim1 : Option[Int] = None, dim2 : Option[Int] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def where (condition : NDArray, x : NDArray, y : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| // arg len: 5, num of methods: 36 | |
| def Dropout (data : NDArray, p : Option[MXFloat] = None, mode : Option[String] = None, axes : Option[Shape] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def IdentityAttachKLSparseReg (data : NDArray, sparseness_target : Option[MXFloat] = None, penalty : Option[MXFloat] = None, momentum : Option[MXFloat] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def InstanceNorm (data : NDArray, gamma : NDArray, beta : NDArray, eps : Option[MXFloat] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def MakeLoss (data : NDArray, grad_scale : Option[MXFloat] = None, valid_thresh : Option[MXFloat] = None, normalization : Option[String] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def Pad (data : NDArray, mode : String, pad_width : Shape, constant_value : Option[Double] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def ROIPooling (data : NDArray, rois : NDArray, pooled_size : Shape, spatial_scale : MXFloat, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def SequenceLast (data : NDArray, sequence_length : NDArray, use_sequence_length : Option[Boolean] = None, axis : Option[Int] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def SequenceReverse (data : NDArray, sequence_length : NDArray, use_sequence_length : Option[Boolean] = None, axis : Option[Int] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def SliceChannel (data : NDArray, num_outputs : Int, axis : Option[Int] = None, squeeze_axis : Option[Boolean] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def argsort (data : NDArray, axis : Option[Int] = None, is_ascend : Option[Boolean] = None, dtype : Option[String] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def broadcast_like (lhs : NDArray, rhs : NDArray, lhs_axes : Option[Shape] = None, rhs_axes : Option[Shape] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def crop (data : NDArray, begin : Shape, end : Shape, step : Option[Shape] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def max (data : NDArray, axis : Option[Shape] = None, keepdims : Option[Boolean] = None, exclude : Option[Boolean] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def max_axis (data : NDArray, axis : Option[Shape] = None, keepdims : Option[Boolean] = None, exclude : Option[Boolean] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def mean (data : NDArray, axis : Option[Shape] = None, keepdims : Option[Boolean] = None, exclude : Option[Boolean] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def min (data : NDArray, axis : Option[Shape] = None, keepdims : Option[Boolean] = None, exclude : Option[Boolean] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def min_axis (data : NDArray, axis : Option[Shape] = None, keepdims : Option[Boolean] = None, exclude : Option[Boolean] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def nanprod (data : NDArray, axis : Option[Shape] = None, keepdims : Option[Boolean] = None, exclude : Option[Boolean] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def nansum (data : NDArray, axis : Option[Shape] = None, keepdims : Option[Boolean] = None, exclude : Option[Boolean] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def norm (data : NDArray, ord : Option[Int] = None, axis : Option[Shape] = None, keepdims : Option[Boolean] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def pad (data : NDArray, mode : String, pad_width : Shape, constant_value : Option[Double] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def prod (data : NDArray, axis : Option[Shape] = None, keepdims : Option[Boolean] = None, exclude : Option[Boolean] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def random_exponential (lam : Option[MXFloat] = None, shape : Option[Shape] = None, ctx : Option[String] = None, dtype : Option[String] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def random_poisson (lam : Option[MXFloat] = None, shape : Option[Shape] = None, ctx : Option[String] = None, dtype : Option[String] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def sample_gamma (alpha : NDArray, shape : Option[Shape] = None, dtype : Option[String] = None, beta : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def sample_generalized_negative_binomial (mu : NDArray, shape : Option[Shape] = None, dtype : Option[String] = None, alpha : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def sample_multinomial (data : NDArray, shape : Option[Shape] = None, get_prob : Option[Boolean] = None, dtype : Option[String] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def sample_negative_binomial (k : NDArray, shape : Option[Shape] = None, dtype : Option[String] = None, p : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def sample_normal (mu : NDArray, shape : Option[Shape] = None, dtype : Option[String] = None, sigma : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def sample_uniform (low : NDArray, shape : Option[Shape] = None, dtype : Option[String] = None, high : NDArray, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def slice (data : NDArray, begin : Shape, end : Shape, step : Option[Shape] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def slice_axis (data : NDArray, axis : Int, begin : Int, end : Int, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def split (data : NDArray, num_outputs : Int, axis : Option[Int] = None, squeeze_axis : Option[Boolean] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def sum (data : NDArray, axis : Option[Shape] = None, keepdims : Option[Boolean] = None, exclude : Option[Boolean] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def sum_axis (data : NDArray, axis : Option[Shape] = None, keepdims : Option[Boolean] = None, exclude : Option[Boolean] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def take (a : NDArray, indices : NDArray, axis : Option[Int] = None, mode : Option[String] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| // arg len: 6, num of methods: 21 | |
| def Crop (data : Array[NDArray], num_args : Int, offset : Option[Shape] = None, h_w : Option[Shape] = None, center_crop : Option[Boolean] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def LRN (data : NDArray, alpha : Option[MXFloat] = None, beta : Option[MXFloat] = None, knorm : Option[MXFloat] = None, nsize : Int, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def Reshape (data : NDArray, shape : Option[Shape] = None, reverse : Option[Boolean] = None, target_shape : Option[Shape] = None, keep_highest : Option[Boolean] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def SVMOutput (data : NDArray, label : NDArray, margin : Option[MXFloat] = None, regularization_coefficient : Option[MXFloat] = None, use_linear : Option[Boolean] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def SequenceMask (data : NDArray, sequence_length : NDArray, use_sequence_length : Option[Boolean] = None, value : Option[MXFloat] = None, axis : Option[Int] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def SpatialTransformer (data : NDArray, loc : NDArray, target_shape : Option[Shape] = None, transform_type : String, sampler_type : String, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def batch_dot (lhs : NDArray, rhs : NDArray, transpose_a : Option[Boolean] = None, transpose_b : Option[Boolean] = None, forward_stype : Option[String] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def dot (lhs : NDArray, rhs : NDArray, transpose_a : Option[Boolean] = None, transpose_b : Option[Boolean] = None, forward_stype : Option[String] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def linalg_trmm (A : NDArray, B : NDArray, transpose : Option[Boolean] = None, rightside : Option[Boolean] = None, alpha : Option[Double] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def linalg_trsm (A : NDArray, B : NDArray, transpose : Option[Boolean] = None, rightside : Option[Boolean] = None, alpha : Option[Double] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def normal (loc : Option[MXFloat] = None, scale : Option[MXFloat] = None, shape : Option[Shape] = None, ctx : Option[String] = None, dtype : Option[String] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def one_hot (indices : NDArray, depth : Int, on_value : Option[Double] = None, off_value : Option[Double] = None, dtype : Option[String] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def pick (data : NDArray, index : NDArray, axis : Option[Int] = None, keepdims : Option[Boolean] = None, mode : Option[String] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def random_gamma (alpha : Option[MXFloat] = None, beta : Option[MXFloat] = None, shape : Option[Shape] = None, ctx : Option[String] = None, dtype : Option[String] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def random_generalized_negative_binomial (mu : Option[MXFloat] = None, alpha : Option[MXFloat] = None, shape : Option[Shape] = None, ctx : Option[String] = None, dtype : Option[String] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def random_negative_binomial (k : Option[Int] = None, p : Option[MXFloat] = None, shape : Option[Shape] = None, ctx : Option[String] = None, dtype : Option[String] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def random_normal (loc : Option[MXFloat] = None, scale : Option[MXFloat] = None, shape : Option[Shape] = None, ctx : Option[String] = None, dtype : Option[String] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def random_uniform (low : Option[MXFloat] = None, high : Option[MXFloat] = None, shape : Option[Shape] = None, ctx : Option[String] = None, dtype : Option[String] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def reshape (data : NDArray, shape : Option[Shape] = None, reverse : Option[Boolean] = None, target_shape : Option[Shape] = None, keep_highest : Option[Boolean] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def shape_array (data : NDArray, lhs_begin : Option[Int] = None, lhs_end : Option[Int] = None, rhs_begin : Option[Int] = None, rhs_end : Option[Int] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def uniform (low : Option[MXFloat] = None, high : Option[MXFloat] = None, shape : Option[Shape] = None, ctx : Option[String] = None, dtype : Option[String] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| // arg len: 7, num of methods: 7 | |
| def Embedding (data : NDArray, weight : NDArray, input_dim : Int, output_dim : Int, dtype : Option[String] = None, sparse_grad : Option[Boolean] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def FullyConnected (data : NDArray, weight : NDArray, bias : NDArray, num_hidden : Int, no_bias : Option[Boolean] = None, flatten : Option[Boolean] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def LayerNorm (data : NDArray, gamma : NDArray, beta : NDArray, axis : Option[Int] = None, eps : Option[MXFloat] = None, output_mean_var : Option[Boolean] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def LeakyReLU (data : NDArray, gamma : NDArray, act_type : Option[String] = None, slope : Option[MXFloat] = None, lower_bound : Option[MXFloat] = None, upper_bound : Option[MXFloat] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def linalg_gemm2 (A : NDArray, B : NDArray, transpose_a : Option[Boolean] = None, transpose_b : Option[Boolean] = None, alpha : Option[Double] = None, axis : Option[Int] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def signsgd_update (weight : NDArray, grad : NDArray, lr : MXFloat, wd : Option[MXFloat] = None, rescale_grad : Option[MXFloat] = None, clip_gradient : Option[MXFloat] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def topk (data : NDArray, axis : Option[Int] = None, k : Option[Int] = None, ret_typ : Option[String] = None, is_ascend : Option[Boolean] = None, dtype : Option[String] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| // arg len: 8, num of methods: 3 | |
| def Pooling_v1 (data : NDArray, kernel : Option[Shape] = None, pool_type : Option[String] = None, global_pool : Option[Boolean] = None, pooling_convention : Option[String] = None, stride : Option[Shape] = None, pad : Option[Shape] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def UpSampling (data : Array[NDArray], scale : Int, num_filter : Option[Int] = None, sample_type : String, multi_input_mode : Option[String] = None, num_args : Int, workspace : Option[Long] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def sgd_update (weight : NDArray, grad : NDArray, lr : MXFloat, wd : Option[MXFloat] = None, rescale_grad : Option[MXFloat] = None, clip_gradient : Option[MXFloat] = None, lazy_update : Option[Boolean] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| // arg len: 9, num of methods: 4 | |
| def BatchNorm_v1 (data : NDArray, gamma : NDArray, beta : NDArray, eps : Option[MXFloat] = None, momentum : Option[MXFloat] = None, fix_gamma : Option[Boolean] = None, use_global_stats : Option[Boolean] = None, output_mean_var : Option[Boolean] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def Correlation (data1 : NDArray, data2 : NDArray, kernel_size : Option[Int] = None, max_displacement : Option[Int] = None, stride1 : Option[Int] = None, stride2 : Option[Int] = None, pad_size : Option[Int] = None, is_multiply : Option[Boolean] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def linalg_gemm (A : NDArray, B : NDArray, C : NDArray, transpose_a : Option[Boolean] = None, transpose_b : Option[Boolean] = None, alpha : Option[Double] = None, beta : Option[Double] = None, axis : Option[Int] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def mp_sgd_update (weight : NDArray, grad : NDArray, weight32 : NDArray, lr : MXFloat, wd : Option[MXFloat] = None, rescale_grad : Option[MXFloat] = None, clip_gradient : Option[MXFloat] = None, lazy_update : Option[Boolean] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| // arg len: 10, num of methods: 3 | |
| def Softmax (data : NDArray, grad_scale : Option[MXFloat] = None, ignore_label : Option[MXFloat] = None, multi_output : Option[Boolean] = None, use_ignore : Option[Boolean] = None, preserve_shape : Option[Boolean] = None, normalization : Option[String] = None, out_grad : Option[Boolean] = None, smooth_alpha : Option[MXFloat] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def sgd_mom_update (weight : NDArray, grad : NDArray, mom : NDArray, lr : MXFloat, momentum : Option[MXFloat] = None, wd : Option[MXFloat] = None, rescale_grad : Option[MXFloat] = None, clip_gradient : Option[MXFloat] = None, lazy_update : Option[Boolean] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def signum_update (weight : NDArray, grad : NDArray, mom : NDArray, lr : MXFloat, momentum : Option[MXFloat] = None, wd : Option[MXFloat] = None, rescale_grad : Option[MXFloat] = None, clip_gradient : Option[MXFloat] = None, wd_lh : Option[MXFloat] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| // arg len: 11, num of methods: 6 | |
| def Pooling (data : NDArray, kernel : Option[Shape] = None, pool_type : Option[String] = None, global_pool : Option[Boolean] = None, cudnn_off : Option[Boolean] = None, pooling_convention : Option[String] = None, stride : Option[Shape] = None, pad : Option[Shape] = None, p_value : Option[Int] = None, count_include_pad : Option[Boolean] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def RNN (data : NDArray, parameters : NDArray, state : NDArray, state_cell : NDArray, state_size : Int, num_layers : Int, bidirectional : Option[Boolean] = None, mode : String, p : Option[MXFloat] = None, state_outputs : Option[Boolean] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def SoftmaxOutput (data : NDArray, label : NDArray, grad_scale : Option[MXFloat] = None, ignore_label : Option[MXFloat] = None, multi_output : Option[Boolean] = None, use_ignore : Option[Boolean] = None, preserve_shape : Option[Boolean] = None, normalization : Option[String] = None, out_grad : Option[Boolean] = None, smooth_alpha : Option[MXFloat] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def ftrl_update (weight : NDArray, grad : NDArray, z : NDArray, n : NDArray, lr : MXFloat, lamda1 : Option[MXFloat] = None, beta : Option[MXFloat] = None, wd : Option[MXFloat] = None, rescale_grad : Option[MXFloat] = None, clip_gradient : Option[MXFloat] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def mp_sgd_mom_update (weight : NDArray, grad : NDArray, mom : NDArray, weight32 : NDArray, lr : MXFloat, momentum : Option[MXFloat] = None, wd : Option[MXFloat] = None, rescale_grad : Option[MXFloat] = None, clip_gradient : Option[MXFloat] = None, lazy_update : Option[Boolean] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def rmsprop_update (weight : NDArray, grad : NDArray, n : NDArray, lr : MXFloat, gamma1 : Option[MXFloat] = None, epsilon : Option[MXFloat] = None, wd : Option[MXFloat] = None, rescale_grad : Option[MXFloat] = None, clip_gradient : Option[MXFloat] = None, clip_weights : Option[MXFloat] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| // arg len: 13, num of methods: 2 | |
| def BatchNorm (data : NDArray, gamma : NDArray, beta : NDArray, moving_mean : NDArray, moving_var : NDArray, eps : Option[Double] = None, momentum : Option[MXFloat] = None, fix_gamma : Option[Boolean] = None, use_global_stats : Option[Boolean] = None, output_mean_var : Option[Boolean] = None, axis : Option[Int] = None, cudnn_off : Option[Boolean] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def adam_update (weight : NDArray, grad : NDArray, mean : NDArray, vari : NDArray, lr : MXFloat, beta1 : Option[MXFloat] = None, beta2 : Option[MXFloat] = None, epsilon : Option[MXFloat] = None, wd : Option[MXFloat] = None, rescale_grad : Option[MXFloat] = None, clip_gradient : Option[MXFloat] = None, lazy_update : Option[Boolean] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| // arg len: 14, num of methods: 2 | |
| def ftml_update (weight : NDArray, grad : NDArray, d : NDArray, v : NDArray, z : NDArray, lr : MXFloat, beta1 : Option[MXFloat] = None, beta2 : Option[MXFloat] = None, epsilon : Option[Double] = None, t : Int, wd : Option[MXFloat] = None, rescale_grad : Option[MXFloat] = None, clip_grad : Option[MXFloat] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def rmspropalex_update (weight : NDArray, grad : NDArray, n : NDArray, g : NDArray, delta : NDArray, lr : MXFloat, gamma1 : Option[MXFloat] = None, gamma2 : Option[MXFloat] = None, epsilon : Option[MXFloat] = None, wd : Option[MXFloat] = None, rescale_grad : Option[MXFloat] = None, clip_gradient : Option[MXFloat] = None, clip_weights : Option[MXFloat] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| // arg len: 15, num of methods: 2 | |
| def Convolution (data : NDArray, weight : NDArray, bias : NDArray, kernel : Shape, stride : Option[Shape] = None, dilate : Option[Shape] = None, pad : Option[Shape] = None, num_filter : Int, num_group : Option[Int] = None, workspace : Option[Long] = None, no_bias : Option[Boolean] = None, cudnn_tune : Option[String] = None, cudnn_off : Option[Boolean] = None, layout : Option[String] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| def Convolution_v1 (data : NDArray, weight : NDArray, bias : NDArray, kernel : Shape, stride : Option[Shape] = None, dilate : Option[Shape] = None, pad : Option[Shape] = None, num_filter : Int, num_group : Option[Int] = None, workspace : Option[Long] = None, no_bias : Option[Boolean] = None, cudnn_tune : Option[String] = None, cudnn_off : Option[Boolean] = None, layout : Option[String] = None, out : Option[NDArray] = None) : NDArrayFuncReturn | |
| // arg len: 17, num of methods: 1 | |
| def Deconvolution (data : NDArray, weight : NDArray, bias : NDArray, kernel : Shape, stride : Option[Shape] = None, dilate : Option[Shape] = None, pad : Option[Shape] = None, adj : Option[Shape] = None, target_shape : Option[Shape] = None, num_filter : Int, num_group : Option[Int] = None, workspace : Option[Long] = None, no_bias : Option[Boolean] = None, cudnn_tune : Option[String] = None, cudnn_off : Option[Boolean] = None, layout : Option[String] = None, out : Option[NDArray] = None) : NDArrayFuncReturn |
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