Computation.Operator

This document is auto-generated for Owl’s APIs. #195 entries have been extracted.

Github: {Signature} {Implementation}

Vectorised functions

val noop : arr -> arr

TODO

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val empty : int array -> arr

TODO

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val zeros : int array -> arr

TODO

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val ones : int array -> arr

TODO

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val create : int array -> elt -> arr

TODO

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val sequential : ?a:elt -> ?step:elt -> int array -> arr

TODO

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val uniform : ?a:elt -> ?b:elt -> int array -> arr

TODO

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val gaussian : ?mu:elt -> ?sigma:elt -> int array -> arr

TODO

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val bernoulli : ?p:elt -> int array -> arr

TODO

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val init : int array -> (int -> elt) -> arr

TODO

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val shape : arr -> int array

TODO

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val numel : arr -> int

TODO

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val get : arr -> int array -> elt

TODO

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val set : arr -> int array -> elt -> unit

TODO

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val get_slice : int list list -> arr -> arr

TODO

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val set_slice : int list list -> arr -> arr -> unit

TODO

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val copy : arr -> arr

TODO

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val copy_ : out:'a -> 'b -> 'c

TODO

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val reset : arr -> unit

TODO

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val reshape : arr -> int array -> arr

TODO

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val reverse : arr -> arr

TODO

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val tile : arr -> int array -> arr

TODO

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val repeat : arr -> int array -> arr

TODO

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val pad : ?v:elt -> int list list -> arr -> arr

TODO

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val concatenate : ?axis:int -> arr array -> arr

TODO

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val split : ?axis:int -> 'a -> 'b -> 'c

TODO

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val draw : ?axis:int -> arr -> int -> arr * 'a array

TODO

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val map : (elt -> elt) -> arr -> arr

TODO

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val fold : ?axis:int -> (elt -> elt -> elt) -> elt -> arr -> arr

TODO

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val scan : ?axis:int -> (elt -> elt -> elt) -> arr -> arr

TODO

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val one_hot : int -> arr -> arr

TODO

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val delay : (Device.A.arr -> Device.A.arr) -> arr -> arr

delay f x returns f x. It allows to use a function that is not tracked by the computation graph and delay its evaluation. The output must have the same shape as the input.

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val lazy_print : ?max_row:int -> ?max_col:int -> ?header:bool -> ?fmt:(Device.A.elt -> string) -> arr -> arr

lazy_print x prints the output of x when it is evaluated. Is implemented as an identity node. For information about the optional parameters, refer to the print function of the Ndarray module.

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val print : ?max_row:'a -> ?max_col:'b -> ?header:'c -> ?fmt:'d -> 'e -> unit

TODO

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val abs : arr -> arr

TODO

val neg : arr -> arr

TODO

val floor : arr -> arr

TODO

val ceil : arr -> arr

TODO

val round : arr -> arr

TODO

val sqr : arr -> arr

TODO

val sqrt : arr -> arr

TODO

val log : arr -> arr

TODO

val log2 : arr -> arr

TODO

val log10 : arr -> arr

TODO

val exp : arr -> arr

TODO

val sin : arr -> arr

TODO

val cos : arr -> arr

TODO

val tan : arr -> arr

TODO

val sinh : arr -> arr

TODO

val cosh : arr -> arr

TODO

val tanh : arr -> arr

TODO

val asin : arr -> arr

TODO

val acos : arr -> arr

TODO

val atan : arr -> arr

TODO

val asinh : arr -> arr

TODO

val acosh : arr -> arr

TODO

val atanh : arr -> arr

TODO

val min : ?axis:int -> arr -> arr

TODO

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val max : ?axis:int -> arr -> arr

TODO

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val sum : ?axis:int -> arr -> arr

TODO

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val sum_reduce : ?axis:int array -> arr -> arr

TODO

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val signum : arr -> arr

TODO

val sigmoid : arr -> arr

TODO

val relu : arr -> arr

TODO

val min' : arr -> elt

TODO

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val max' : arr -> elt

TODO

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val sum' : arr -> elt

TODO

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val l1norm' : arr -> elt

TODO

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val l2norm' : arr -> elt

TODO

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val l2norm_sqr' : arr -> elt

TODO

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val clip_by_value : ?amin:elt -> ?amax:elt -> arr -> arr

TODO

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val clip_by_l2norm : elt -> arr -> arr

TODO

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val pow : arr -> arr -> arr

TODO

val scalar_pow : elt -> arr -> arr

TODO

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val pow_scalar : arr -> elt -> arr

TODO

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val atan2 : arr -> arr -> arr

TODO

val scalar_atan2 : elt -> arr -> arr

TODO

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val atan2_scalar : arr -> elt -> arr

TODO

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val hypot : arr -> arr -> arr

TODO

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val min2 : arr -> arr -> arr

TODO

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val max2 : arr -> arr -> arr

TODO

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val add : arr -> arr -> arr

TODO

val sub : arr -> arr -> arr

TODO

val mul : arr -> arr -> arr

TODO

val div : arr -> arr -> arr

TODO

val add_scalar : arr -> elt -> arr

TODO

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val sub_scalar : arr -> elt -> arr

TODO

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val mul_scalar : arr -> elt -> arr

TODO

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val div_scalar : arr -> elt -> arr

TODO

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val scalar_add : elt -> arr -> arr

TODO

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val scalar_sub : elt -> arr -> arr

TODO

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val scalar_mul : elt -> arr -> arr

TODO

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val scalar_div : elt -> arr -> arr

TODO

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val fma : arr -> arr -> arr -> arr

TODO

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val elt_equal : arr -> arr -> arr

TODO

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val elt_not_equal : arr -> arr -> arr

TODO

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val elt_less : arr -> arr -> arr

TODO

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val elt_greater : arr -> arr -> arr

TODO

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val elt_less_equal : arr -> arr -> arr

TODO

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val elt_greater_equal : arr -> arr -> arr

TODO

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val elt_equal_scalar : arr -> elt -> arr

TODO

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val elt_not_equal_scalar : arr -> elt -> arr

TODO

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val elt_less_scalar : arr -> elt -> arr

TODO

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val elt_greater_scalar : arr -> elt -> arr

TODO

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val elt_less_equal_scalar : arr -> elt -> arr

TODO

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val elt_greater_equal_scalar : arr -> elt -> arr

TODO

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val conv1d : ?padding:Owl_types.padding -> arr -> arr -> int array -> arr

TODO

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val conv2d : ?padding:Owl_types.padding -> arr -> arr -> int array -> arr

TODO

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val conv3d : ?padding:Owl_types.padding -> arr -> arr -> int array -> arr

TODO

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val transpose_conv1d : ?padding:Owl_types.padding -> arr -> arr -> int array -> arr

TODO

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val transpose_conv2d : ?padding:Owl_types.padding -> arr -> arr -> int array -> arr

TODO

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val transpose_conv3d : ?padding:Owl_types.padding -> arr -> arr -> int array -> arr

TODO

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val dilated_conv1d : ?padding:Owl_types.padding -> arr -> arr -> int array -> int array -> arr

TODO

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val dilated_conv2d : ?padding:Owl_types.padding -> arr -> arr -> int array -> int array -> arr

TODO

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val dilated_conv3d : ?padding:Owl_types.padding -> arr -> arr -> int array -> int array -> arr

TODO

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val max_pool1d : ?padding:Owl_types.padding -> arr -> int array -> int array -> arr

TODO

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val max_pool2d : ?padding:Owl_types.padding -> arr -> int array -> int array -> arr

TODO

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val max_pool3d : ?padding:Owl_types.padding -> arr -> int array -> int array -> arr

TODO

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val avg_pool1d : ?padding:Owl_types.padding -> arr -> int array -> int array -> arr

TODO

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val avg_pool2d : ?padding:Owl_types.padding -> arr -> int array -> int array -> arr

TODO

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val avg_pool3d : ?padding:Owl_types.padding -> arr -> int array -> int array -> arr

TODO

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val upsampling2d : arr -> int array -> arr

TODO

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val conv1d_backward_input : arr -> arr -> int array -> arr -> arr

TODO

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val conv1d_backward_kernel : arr -> arr -> int array -> arr -> arr

TODO

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val conv2d_backward_input : arr -> arr -> int array -> arr -> arr

TODO

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val conv2d_backward_kernel : arr -> arr -> int array -> arr -> arr

TODO

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val conv3d_backward_input : arr -> arr -> int array -> arr -> arr

TODO

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val conv3d_backward_kernel : arr -> arr -> int array -> arr -> arr

TODO

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val transpose_conv1d_backward_input : arr -> arr -> int array -> arr -> arr

TODO

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val transpose_conv1d_backward_kernel : arr -> arr -> int array -> arr -> arr

TODO

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val transpose_conv2d_backward_input : arr -> arr -> int array -> arr -> arr

TODO

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val transpose_conv2d_backward_kernel : arr -> arr -> int array -> arr -> arr

TODO

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val transpose_conv3d_backward_input : arr -> arr -> int array -> arr -> arr

TODO

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val transpose_conv3d_backward_kernel : arr -> arr -> int array -> arr -> arr

TODO

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val dilated_conv1d_backward_input : arr -> arr -> int array -> int array -> arr -> arr

TODO

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val dilated_conv1d_backward_kernel : arr -> arr -> int array -> int array -> arr -> arr

TODO

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val dilated_conv2d_backward_input : arr -> arr -> int array -> int array -> arr -> arr

TODO

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val dilated_conv2d_backward_kernel : arr -> arr -> int array -> int array -> arr -> arr

TODO

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val dilated_conv3d_backward_input : arr -> arr -> int array -> int array -> arr -> arr

TODO

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val dilated_conv3d_backward_kernel : arr -> arr -> int array -> int array -> arr -> arr

TODO

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val max_pool1d_backward : padding -> arr -> int array -> int array -> arr -> arr

TODO

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val max_pool2d_backward : padding -> arr -> int array -> int array -> arr -> arr

TODO

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val max_pool3d_backward : padding -> arr -> int array -> int array -> arr -> arr

TODO

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val avg_pool1d_backward : padding -> arr -> int array -> int array -> arr -> arr

TODO

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val avg_pool2d_backward : padding -> arr -> int array -> int array -> arr -> arr

TODO

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val avg_pool3d_backward : padding -> arr -> int array -> int array -> arr -> arr

TODO

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val upsampling2d_backward : arr -> int array -> arr -> arr

TODO

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val row_num : arr -> int

TODO

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val col_num : arr -> int

TODO

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val row : arr -> 'a -> arr

TODO

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val rows : arr -> int array -> arr

TODO

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val copy_row_to : arr -> 'a -> 'b -> unit

TODO

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val copy_col_to : arr -> 'a -> 'b -> unit

TODO

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val inv : arr -> arr

TODO

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val trace : arr -> elt

TODO

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val dot : arr -> arr -> arr

TODO

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val transpose : ?axis:int array -> arr -> arr

TODO

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val to_rows : arr -> 'a array

TODO

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val of_rows : arr array -> arr

TODO

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val of_array : 'a -> 'b -> 'c

TODO

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val of_arrays : 'a -> 'b

TODO

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Scalar functions

val add : elt -> elt -> elt

TODO

val sub : elt -> elt -> elt

TODO

val mul : elt -> elt -> elt

TODO

val div : elt -> elt -> elt

TODO

val pow : elt -> elt -> elt

TODO

val atan2 : elt -> elt -> elt

TODO

val abs : elt -> elt

TODO

val neg : elt -> elt

TODO

val sqr : elt -> elt

TODO

val sqrt : elt -> elt

TODO

val exp : elt -> elt

TODO

val log : elt -> elt

TODO

val log2 : elt -> elt

TODO

val log10 : elt -> elt

TODO

val signum : elt -> elt

TODO

val floor : elt -> elt

TODO

val ceil : elt -> elt

TODO

val round : elt -> elt

TODO

val sin : elt -> elt

TODO

val cos : elt -> elt

TODO

val tan : elt -> elt

TODO

val sinh : elt -> elt

TODO

val cosh : elt -> elt

TODO

val tanh : elt -> elt

TODO

val asin : elt -> elt

TODO

val acos : elt -> elt

TODO

val atan : elt -> elt

TODO

val asinh : elt -> elt

TODO

val acosh : elt -> elt

TODO

val atanh : elt -> elt

TODO

val relu : elt -> elt

TODO

val sigmoid : elt -> elt

TODO