package neural_nets_lib

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val unconstrained_dim : dim_constraint Variantslib.Variant.t
val fold : init:'acc__0 -> unconstrained_dim: ('acc__0 -> dim_constraint Variantslib.Variant.t -> 'acc__1) -> at_least_dim: ('acc__1 -> (Base.int -> dim_constraint) Variantslib.Variant.t -> 'acc__2) -> 'acc__2
val iter : unconstrained_dim:(dim_constraint Variantslib.Variant.t -> Base.unit) -> at_least_dim: ((Base.int -> dim_constraint) Variantslib.Variant.t -> Base.unit) -> Base.unit
val map : dim_constraint -> unconstrained_dim:(dim_constraint Variantslib.Variant.t -> 'result__) -> at_least_dim: ((Base.int -> dim_constraint) Variantslib.Variant.t -> Base.int -> 'result__) -> 'result__
val make_matcher : unconstrained_dim: (dim_constraint Variantslib.Variant.t -> 'acc__0 -> (Base.unit -> 'result__) * 'acc__1) -> at_least_dim: ((Base.int -> dim_constraint) Variantslib.Variant.t -> 'acc__1 -> (Base.int -> 'result__) * 'acc__2) -> 'acc__0 -> (dim_constraint -> 'result__) * 'acc__2
val to_rank : dim_constraint -> Base.int
val to_name : dim_constraint -> Base.string
val descriptions : (Base.string * Base.int) Base.list
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