package tensorflow

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type 'a fnn = 'a t
type ('a, 'b, 'c) t
val create : ('c * 'b) Tensor.eq -> 'a fnn -> ('a, 'b, 'c) t
val predict : ('a, 'b, 'c) t -> (Input_id.t * (float, 'c) Tensor.t) list -> (float, 'c) Tensor.t
val fit : ?addn_inputs:(Input_id.t * (float, 'c) Tensor.t) list -> ?batch_size:int -> ('a, 'b, 'c) t -> loss:Loss.t -> optimizer:Optimizer.t -> epochs:int -> input_id:Input_id.t -> xs:(float, 'c) Tensor.t -> ys:(float, 'c) Tensor.t -> unit
val save : ('a, 'b, 'c) t -> filename:string -> unit
val load : ('a, 'b, 'c) t -> filename:string -> unit
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