package owl-base

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package owl-base
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Vectorised functions

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val empty : int array -> Symbol.Shape.Type.arr

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val zeros : int array -> Symbol.Shape.Type.arr

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val ones : int array -> Symbol.Shape.Type.arr

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val create : int array -> Symbol.Shape.Type.elt -> Symbol.Shape.Type.arr

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val sequential : ?a:Symbol.Shape.Type.elt -> ?step:Symbol.Shape.Type.elt -> int array -> Symbol.Shape.Type.arr

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val gaussian : ?mu:Symbol.Shape.Type.elt -> ?sigma:Symbol.Shape.Type.elt -> int array -> Symbol.Shape.Type.arr

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val bernoulli : ?p:Symbol.Shape.Type.elt -> int array -> Symbol.Shape.Type.arr

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val init : int array -> (int -> Symbol.Shape.Type.elt) -> Symbol.Shape.Type.arr

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val init_nd : int array -> (int array -> Symbol.Shape.Type.elt) -> Symbol.Shape.Type.arr

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val shape : Symbol.Shape.Type.arr -> int array

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val numel : Symbol.Shape.Type.arr -> int

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val set : Symbol.Shape.Type.arr -> int array -> Symbol.Shape.Type.elt -> unit

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val get_slice : int list list -> Symbol.Shape.Type.arr -> Symbol.Shape.Type.arr

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val set_slice : int list list -> Symbol.Shape.Type.arr -> Symbol.Shape.Type.arr -> unit

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

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val reset : Symbol.Shape.Type.arr -> unit

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val reshape : Symbol.Shape.Type.arr -> int array -> Symbol.Shape.Type.arr

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val tile : Symbol.Shape.Type.arr -> int array -> Symbol.Shape.Type.arr

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val repeat : Symbol.Shape.Type.arr -> int array -> Symbol.Shape.Type.arr

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val expand : ?hi:bool -> Symbol.Shape.Type.arr -> int -> Symbol.Shape.Type.arr

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val squeeze : ?axis:int array -> Symbol.Shape.Type.arr -> Symbol.Shape.Type.arr

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val concatenate : ?axis:int -> Symbol.Shape.Type.arr array -> Symbol.Shape.Type.arr

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

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val draw : ?axis:int -> Symbol.Shape.Type.arr -> int -> Symbol.Shape.Type.arr * 'a array

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``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.

``delay_array out_shape f x`` works in the same way as ``delay`` but is applied on an array of ndarrays. Needs the shape of the output as an argument.

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

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

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val sum_reduce : ?axis:int array -> Symbol.Shape.Type.arr -> Symbol.Shape.Type.arr

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

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

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

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

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

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

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

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

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

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

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

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

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val upsampling2d : Symbol.Shape.Type.arr -> int array -> Symbol.Shape.Type.arr

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val transpose_conv1d_backward_input : Symbol.Shape.Type.arr -> Symbol.Shape.Type.arr -> int array -> Symbol.Shape.Type.arr -> Symbol.Shape.Type.arr

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val transpose_conv1d_backward_kernel : Symbol.Shape.Type.arr -> Symbol.Shape.Type.arr -> int array -> Symbol.Shape.Type.arr -> Symbol.Shape.Type.arr

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val transpose_conv2d_backward_input : Symbol.Shape.Type.arr -> Symbol.Shape.Type.arr -> int array -> Symbol.Shape.Type.arr -> Symbol.Shape.Type.arr

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val transpose_conv2d_backward_kernel : Symbol.Shape.Type.arr -> Symbol.Shape.Type.arr -> int array -> Symbol.Shape.Type.arr -> Symbol.Shape.Type.arr

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val transpose_conv3d_backward_input : Symbol.Shape.Type.arr -> Symbol.Shape.Type.arr -> int array -> Symbol.Shape.Type.arr -> Symbol.Shape.Type.arr

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val transpose_conv3d_backward_kernel : Symbol.Shape.Type.arr -> Symbol.Shape.Type.arr -> int array -> Symbol.Shape.Type.arr -> Symbol.Shape.Type.arr

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val dilated_conv1d_backward_input : Symbol.Shape.Type.arr -> Symbol.Shape.Type.arr -> int array -> int array -> Symbol.Shape.Type.arr -> Symbol.Shape.Type.arr

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val dilated_conv1d_backward_kernel : Symbol.Shape.Type.arr -> Symbol.Shape.Type.arr -> int array -> int array -> Symbol.Shape.Type.arr -> Symbol.Shape.Type.arr

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val dilated_conv2d_backward_input : Symbol.Shape.Type.arr -> Symbol.Shape.Type.arr -> int array -> int array -> Symbol.Shape.Type.arr -> Symbol.Shape.Type.arr

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val dilated_conv2d_backward_kernel : Symbol.Shape.Type.arr -> Symbol.Shape.Type.arr -> int array -> int array -> Symbol.Shape.Type.arr -> Symbol.Shape.Type.arr

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val dilated_conv3d_backward_input : Symbol.Shape.Type.arr -> Symbol.Shape.Type.arr -> int array -> int array -> Symbol.Shape.Type.arr -> Symbol.Shape.Type.arr

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val dilated_conv3d_backward_kernel : Symbol.Shape.Type.arr -> Symbol.Shape.Type.arr -> int array -> int array -> Symbol.Shape.Type.arr -> Symbol.Shape.Type.arr

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val max_pool1d_backward : Owl_types.padding -> Symbol.Shape.Type.arr -> int array -> int array -> Symbol.Shape.Type.arr -> Symbol.Shape.Type.arr

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val max_pool2d_backward : Owl_types.padding -> Symbol.Shape.Type.arr -> int array -> int array -> Symbol.Shape.Type.arr -> Symbol.Shape.Type.arr

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val max_pool3d_backward : Owl_types.padding -> Symbol.Shape.Type.arr -> int array -> int array -> Symbol.Shape.Type.arr -> Symbol.Shape.Type.arr

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val avg_pool1d_backward : Owl_types.padding -> Symbol.Shape.Type.arr -> int array -> int array -> Symbol.Shape.Type.arr -> Symbol.Shape.Type.arr

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val avg_pool2d_backward : Owl_types.padding -> Symbol.Shape.Type.arr -> int array -> int array -> Symbol.Shape.Type.arr -> Symbol.Shape.Type.arr

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val avg_pool3d_backward : Owl_types.padding -> Symbol.Shape.Type.arr -> int array -> int array -> Symbol.Shape.Type.arr -> Symbol.Shape.Type.arr

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val upsampling2d_backward : Symbol.Shape.Type.arr -> int array -> Symbol.Shape.Type.arr -> Symbol.Shape.Type.arr

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val row_num : Symbol.Shape.Type.arr -> int

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val col_num : Symbol.Shape.Type.arr -> int

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val rows : Symbol.Shape.Type.arr -> int array -> Symbol.Shape.Type.arr

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val copy_row_to : Symbol.Shape.Type.arr -> 'a -> 'b -> unit

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val copy_col_to : Symbol.Shape.Type.arr -> 'a -> 'b -> unit

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val transpose : ?axis:int array -> Symbol.Shape.Type.arr -> Symbol.Shape.Type.arr

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val to_rows : Symbol.Shape.Type.arr -> 'a array

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val to_cols : Symbol.Shape.Type.arr -> 'a array

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val of_array : Symbol.Shape.Type.elt array -> int array -> Symbol.Shape.Type.arr

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val of_arrays : Symbol.Shape.Type.elt array array -> Symbol.Shape.Type.arr

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val to_arrays : Symbol.Shape.Type.arr -> Symbol.Shape.Type.elt array array

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Scalar functions
module Scalar : sig ... end
module Mat : sig ... end
module Linalg : sig ... end