package tensorflow

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include module type of Ops_generated
module Op_names : sig ... end
val abort : ?name:string -> ?error_msg:string -> ?exit_without_error:bool -> ?control_inputs:Node.p list -> unit -> [ `unit ] Node.t
val abs : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t
val accumulateNV2 : ?name:string -> shape:Tensorflow.Node.Dim.t list -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t list -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t
val accumulatorApplyGradient : ?name:string -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `int64 ] Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 'dtype Node.t -> [ `unit ] Node.t
val accumulatorNumAccumulated : ?name:string -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `int32 ] Node.t
val accumulatorSetGlobalStep : ?name:string -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `int64 ] Node.t -> [ `unit ] Node.t
val accumulatorTakeGradient : ?name:string -> type_: [< `float | `double | `int32 | `complex64 | `int64 ] as 'dtype Tensorflow.Node.Type.t -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `int32 ] Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 'dtype Node.t
val acos : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 | `complex64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 | `complex64 ] as 't Node.t
val acosh : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `complex64 ] as 't Node.t -> [< `float | `double | `complex64 ] as 't Node.t
val add : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 | `complex64 | `string ] as 't Node.t -> [< `float | `double | `int32 | `int64 | `complex64 | `string ] as 't Node.t -> [< `float | `double | `int32 | `int64 | `complex64 | `string ] as 't Node.t
val addManySparseToTensorsMap : ?name:string -> ?container:string -> ?shared_name:string -> ?control_inputs:Node.p list -> [ `int64 ] Node.t -> 't Node.t -> [ `int64 ] Node.t -> [ `int64 ] Node.t
val addN : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `complex64 | `int64 | `variant ] as 't Node.t list -> [< `float | `double | `int32 | `complex64 | `int64 | `variant ] as 't Node.t
val addSparseToTensorsMap : ?name:string -> ?container:string -> ?shared_name:string -> ?control_inputs:Node.p list -> [ `int64 ] Node.t -> 't Node.t -> [ `int64 ] Node.t -> [ `int64 ] Node.t
val addV2 : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 | `complex64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 | `complex64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 | `complex64 ] as 't Node.t
val adjustContrast : ?name:string -> ?control_inputs:Node.p list -> [< `int32 | `int64 | `float | `double ] as 't Node.t -> [ `float ] Node.t -> [ `float ] Node.t -> [ `float ] Node.t -> [ `float ] Node.t
val adjustContrastv2 : ?name:string -> ?control_inputs:Node.p list -> [ `float ] Node.t -> [ `float ] Node.t -> [ `float ] Node.t
val adjustHue : ?name:string -> ?control_inputs:Node.p list -> [ `float ] Node.t -> [ `float ] Node.t -> [ `float ] Node.t
val adjustSaturation : ?name:string -> ?control_inputs:Node.p list -> [ `float ] Node.t -> [ `float ] Node.t -> [ `float ] Node.t
val all : ?name:string -> ?keep_dims:bool -> ?control_inputs:Node.p list -> [ `bool ] Node.t -> [< `int32 | `int64 ] as 'tidx Node.t -> [ `bool ] Node.t
val allCandidateSampler : ?name:string -> num_true:int -> num_sampled:int -> unique:bool -> ?seed:int -> ?seed2:int -> ?control_inputs:Node.p list -> [ `int64 ] Node.t -> [ `int64 ] Node.t * [ `float ] Node.t * [ `float ] Node.t
val angle : ?name:string -> type_:[< `float | `double ] as 'tout Tensorflow.Node.Type.t -> ?control_inputs:Node.p list -> [< `complex64 ] as 't Node.t -> [< `float | `double ] as 'tout Node.t
val any : ?name:string -> ?keep_dims:bool -> ?control_inputs:Node.p list -> [ `bool ] Node.t -> [< `int32 | `int64 ] as 'tidx Node.t -> [ `bool ] Node.t
val applyAdaMax : ?name:string -> ?use_locking:bool -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t
val applyAdadelta : ?name:string -> ?use_locking:bool -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t
val applyAdagrad : ?name:string -> ?use_locking:bool -> ?update_slots:bool -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t
val applyAdagradDA : ?name:string -> ?use_locking:bool -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [ `int64 ] Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t
val applyAdam : ?name:string -> ?use_locking:bool -> ?use_nesterov:bool -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t
val applyAddSign : ?name:string -> ?use_locking:bool -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t
val applyCenteredRMSProp : ?name:string -> ?use_locking:bool -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t
val applyFtrl : ?name:string -> ?use_locking:bool -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t
val applyFtrlV2 : ?name:string -> ?use_locking:bool -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t
val applyGradientDescent : ?name:string -> ?use_locking:bool -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t
val applyMomentum : ?name:string -> ?use_locking:bool -> ?use_nesterov:bool -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t
val applyPowerSign : ?name:string -> ?use_locking:bool -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t
val applyProximalAdagrad : ?name:string -> ?use_locking:bool -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t
val applyProximalGradientDescent : ?name:string -> ?use_locking:bool -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t
val applyRMSProp : ?name:string -> ?use_locking:bool -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t
val approximateEqual : ?name:string -> ?tolerance:float -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [ `bool ] Node.t
val argMax : ?name:string -> type_:[< `int32 | `int64 ] as 'output_type Tensorflow.Node.Type.t -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `int32 | `int64 ] as 'tidx Node.t -> [< `int32 | `int64 ] as 'output_type Node.t
val argMin : ?name:string -> type_:[< `int32 | `int64 ] as 'output_type Tensorflow.Node.Type.t -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `int32 | `int64 ] as 'tidx Node.t -> [< `int32 | `int64 ] as 'output_type Node.t
val asString : ?name:string -> ?precision:int -> ?scientific:bool -> ?shortest:bool -> ?width:int -> ?fill:string -> ?control_inputs:Node.p list -> [< `int32 | `int64 | `complex64 | `float | `double | `bool ] as 't Node.t -> [ `string ] Node.t
val asin : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 | `complex64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 | `complex64 ] as 't Node.t
val asinh : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `complex64 ] as 't Node.t -> [< `float | `double | `complex64 ] as 't Node.t
val assign : ?name:string -> ?validate_shape:bool -> ?use_locking:bool -> ?control_inputs:Node.p list -> 't Node.t -> 't Node.t -> 't Node.t
val assignAdd : ?name:string -> ?use_locking:bool -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t
val assignSub : ?name:string -> ?use_locking:bool -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t
val atan : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 | `complex64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 | `complex64 ] as 't Node.t
val atan2 : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t
val atanh : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `complex64 ] as 't Node.t -> [< `float | `double | `complex64 ] as 't Node.t
val audioSpectrogram : ?name:string -> window_size:int -> stride:int -> ?magnitude_squared:bool -> ?control_inputs:Node.p list -> [ `float ] Node.t -> [ `float ] Node.t
val audioSummary : ?name:string -> sample_rate:float -> ?max_outputs:int -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `float ] Node.t -> [ `string ] Node.t
val audioSummaryV2 : ?name:string -> ?max_outputs:int -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `float ] Node.t -> [ `float ] Node.t -> [ `string ] Node.t
val avgPool : ?name:string -> ksize:int list -> strides:int list -> padding:string -> ?data_format:string -> ?control_inputs:Node.p list -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t
val avgPool3D : ?name:string -> ksize:int list -> strides:int list -> padding:string -> ?data_format:string -> ?control_inputs:Node.p list -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t
val avgPool3DGrad : ?name:string -> ksize:int list -> strides:int list -> padding:string -> ?data_format:string -> ?control_inputs:Node.p list -> [ `int32 ] Node.t -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t
val avgPoolGrad : ?name:string -> ksize:int list -> strides:int list -> padding:string -> ?data_format:string -> ?control_inputs:Node.p list -> [ `int32 ] Node.t -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t
val barrier : ?name:string -> component_types:Tensorflow.Node.Type.p list -> ?shapes:Tensorflow.Node.Dim.t list list -> ?capacity:int -> ?container:string -> ?shared_name:string -> ?control_inputs:Node.p list -> unit -> [ `string ] Node.t
val barrierClose : ?name:string -> ?cancel_pending_enqueues:bool -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `unit ] Node.t
val barrierIncompleteSize : ?name:string -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `int32 ] Node.t
val barrierInsertMany : ?name:string -> component_index:int -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `string ] Node.t -> 't Node.t -> [ `unit ] Node.t
val barrierReadySize : ?name:string -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `int32 ] Node.t
val batchCholesky : ?name:string -> ?control_inputs:Node.p list -> [< `double | `float ] as 't Node.t -> [< `double | `float ] as 't Node.t
val batchCholeskyGrad : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t
val batchDataset : ?name:string -> output_types:Tensorflow.Node.Type.p list -> output_shapes:Tensorflow.Node.Dim.t list list -> ?control_inputs:Node.p list -> [ `variant ] Node.t -> [ `int64 ] Node.t -> [ `variant ] Node.t
val batchDatasetV2 : ?name:string -> output_types:Tensorflow.Node.Type.p list -> output_shapes:Tensorflow.Node.Dim.t list list -> ?control_inputs:Node.p list -> [ `variant ] Node.t -> [ `int64 ] Node.t -> [ `bool ] Node.t -> [ `variant ] Node.t
val batchFFT : ?name:string -> ?control_inputs:Node.p list -> [ `complex64 ] Node.t -> [ `complex64 ] Node.t
val batchFFT2D : ?name:string -> ?control_inputs:Node.p list -> [ `complex64 ] Node.t -> [ `complex64 ] Node.t
val batchFFT3D : ?name:string -> ?control_inputs:Node.p list -> [ `complex64 ] Node.t -> [ `complex64 ] Node.t
val batchIFFT : ?name:string -> ?control_inputs:Node.p list -> [ `complex64 ] Node.t -> [ `complex64 ] Node.t
val batchIFFT2D : ?name:string -> ?control_inputs:Node.p list -> [ `complex64 ] Node.t -> [ `complex64 ] Node.t
val batchIFFT3D : ?name:string -> ?control_inputs:Node.p list -> [ `complex64 ] Node.t -> [ `complex64 ] Node.t
val batchMatMul : ?name:string -> ?adj_x:bool -> ?adj_y:bool -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `complex64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 ] as 't Node.t
val batchMatrixBandPart : ?name:string -> ?control_inputs:Node.p list -> 't Node.t -> [ `int64 ] Node.t -> [ `int64 ] Node.t -> 't Node.t
val batchMatrixDeterminant : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `complex64 ] as 't Node.t -> [< `float | `double | `complex64 ] as 't Node.t
val batchMatrixDiag : ?name:string -> ?control_inputs:Node.p list -> 't Node.t -> 't Node.t
val batchMatrixDiagPart : ?name:string -> ?control_inputs:Node.p list -> 't Node.t -> 't Node.t
val batchMatrixInverse : ?name:string -> ?adjoint:bool -> ?control_inputs:Node.p list -> [< `double | `float ] as 't Node.t -> [< `double | `float ] as 't Node.t
val batchMatrixSetDiag : ?name:string -> ?control_inputs:Node.p list -> 't Node.t -> 't Node.t -> 't Node.t
val batchMatrixSolve : ?name:string -> ?adjoint:bool -> ?control_inputs:Node.p list -> [< `double | `float ] as 't Node.t -> [< `double | `float ] as 't Node.t -> [< `double | `float ] as 't Node.t
val batchMatrixSolveLs : ?name:string -> ?fast:bool -> ?control_inputs:Node.p list -> [< `double | `float ] as 't Node.t -> [< `double | `float ] as 't Node.t -> [ `double ] Node.t -> [< `double | `float ] as 't Node.t
val batchMatrixTriangularSolve : ?name:string -> ?lower:bool -> ?adjoint:bool -> ?control_inputs:Node.p list -> [< `double | `float ] as 't Node.t -> [< `double | `float ] as 't Node.t -> [< `double | `float ] as 't Node.t
val batchNormWithGlobalNormalization : ?name:string -> variance_epsilon:float -> scale_after_normalization:bool -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t
val batchNormWithGlobalNormalizationGrad : ?name:string -> variance_epsilon:float -> scale_after_normalization:bool -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t * [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t * [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t * [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t * [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t
val batchSelfAdjointEig : ?name:string -> ?control_inputs:Node.p list -> [< `double | `float ] as 't Node.t -> [< `double | `float ] as 't Node.t
val batchSelfAdjointEigV2 : ?name:string -> ?compute_v:bool -> ?control_inputs:Node.p list -> [< `double | `float ] as 't Node.t -> [< `double | `float ] as 't Node.t * [< `double | `float ] as 't Node.t
val batchSvd : ?name:string -> ?compute_uv:bool -> ?full_matrices:bool -> ?control_inputs:Node.p list -> [< `double | `float | `complex64 ] as 't Node.t -> [< `double | `float | `complex64 ] as 't Node.t * [< `double | `float | `complex64 ] as 't Node.t * [< `double | `float | `complex64 ] as 't Node.t
val batchToSpace : ?name:string -> block_size:int -> ?control_inputs:Node.p list -> 't Node.t -> [< `int32 | `int64 ] as 'tidx Node.t -> 't Node.t
val batchToSpaceND : ?name:string -> ?control_inputs:Node.p list -> 't Node.t -> [< `int32 | `int64 ] as 'tblock_shape Node.t -> [< `int32 | `int64 ] as 'tcrops Node.t -> 't Node.t
val besselI0e : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t
val besselI1e : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t
val betainc : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t
val biasAdd : ?name:string -> ?data_format:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t
val biasAddGrad : ?name:string -> ?data_format:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t
val biasAddV1 : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t
val bincount : ?name:string -> ?control_inputs:Node.p list -> [ `int32 ] Node.t -> [ `int32 ] Node.t -> [< `int32 | `int64 | `float | `double ] as 't Node.t -> [< `int32 | `int64 | `float | `double ] as 't Node.t
val bitcast : ?name:string -> type_: [< `float | `double | `int64 | `int32 | `complex64 ] as 'type__ Tensorflow.Node.Type.t -> ?control_inputs:Node.p list -> [< `float | `double | `int64 | `int32 | `complex64 ] as 't Node.t -> [< `float | `double | `int64 | `int32 | `complex64 ] as 'type__ Node.t
val bitwiseAnd : ?name:string -> ?control_inputs:Node.p list -> [< `int32 | `int64 ] as 't Node.t -> [< `int32 | `int64 ] as 't Node.t -> [< `int32 | `int64 ] as 't Node.t
val bitwiseOr : ?name:string -> ?control_inputs:Node.p list -> [< `int32 | `int64 ] as 't Node.t -> [< `int32 | `int64 ] as 't Node.t -> [< `int32 | `int64 ] as 't Node.t
val bitwiseXor : ?name:string -> ?control_inputs:Node.p list -> [< `int32 | `int64 ] as 't Node.t -> [< `int32 | `int64 ] as 't Node.t -> [< `int32 | `int64 ] as 't Node.t
val boostedTreesMakeStatsSummary : ?name:string -> max_splits:int -> num_buckets:int -> ?control_inputs:Node.p list -> [ `int32 ] Node.t -> [ `float ] Node.t -> [ `float ] Node.t -> [ `int32 ] Node.t list -> [ `float ] Node.t
val broadcastArgs : ?name:string -> ?control_inputs:Node.p list -> [< `int32 | `int64 ] as 't Node.t -> [< `int32 | `int64 ] as 't Node.t -> [< `int32 | `int64 ] as 't Node.t
val broadcastGradientArgs : ?name:string -> ?control_inputs:Node.p list -> [< `int32 | `int64 ] as 't Node.t -> [< `int32 | `int64 ] as 't Node.t -> [< `int32 | `int64 ] as 't Node.t * [< `int32 | `int64 ] as 't Node.t
val broadcastTo : ?name:string -> ?control_inputs:Node.p list -> 't Node.t -> [< `int32 | `int64 ] as 'tidx Node.t -> 't Node.t
val bucketize : ?name:string -> boundaries:float list -> ?control_inputs:Node.p list -> [< `int32 | `int64 | `float | `double ] as 't Node.t -> [ `int32 ] Node.t
val bytesProducedStatsDataset : ?name:string -> output_types:Tensorflow.Node.Type.p list -> output_shapes:Tensorflow.Node.Dim.t list list -> ?control_inputs:Node.p list -> [ `variant ] Node.t -> [ `string ] Node.t -> [ `variant ] Node.t
val cTCGreedyDecoder : ?name:string -> ?merge_repeated:bool -> ?control_inputs:Node.p list -> [ `float ] Node.t -> [ `int32 ] Node.t -> [ `int64 ] Node.t * [ `int64 ] Node.t * [ `int64 ] Node.t * [ `float ] Node.t
val cTCLoss : ?name:string -> ?preprocess_collapse_repeated:bool -> ?ctc_merge_repeated:bool -> ?ignore_longer_outputs_than_inputs:bool -> ?control_inputs:Node.p list -> [ `float ] Node.t -> [ `int64 ] Node.t -> [ `int32 ] Node.t -> [ `int32 ] Node.t -> [ `float ] Node.t * [ `float ] Node.t
val cacheDataset : ?name:string -> output_types:Tensorflow.Node.Type.p list -> output_shapes:Tensorflow.Node.Dim.t list list -> ?control_inputs:Node.p list -> [ `variant ] Node.t -> [ `string ] Node.t -> [ `variant ] Node.t
val ceil : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t
val checkNumerics : ?name:string -> message:string -> ?control_inputs:Node.p list -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t
val cholesky : ?name:string -> ?control_inputs:Node.p list -> [< `double | `float | `complex64 ] as 't Node.t -> [< `double | `float | `complex64 ] as 't Node.t
val choleskyGrad : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t
val clipByValue : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t
val collectiveBcastRecv : ?name:string -> type_:[< `float | `double | `int32 | `int64 ] as 't Tensorflow.Node.Type.t -> group_size:int -> group_key:int -> instance_key:int -> shape:Tensorflow.Node.Dim.t list -> ?control_inputs:Node.p list -> unit -> [< `float | `double | `int32 | `int64 ] as 't Node.t
val collectiveBcastSend : ?name:string -> group_size:int -> group_key:int -> instance_key:int -> shape:Tensorflow.Node.Dim.t list -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t
val collectiveReduce : ?name:string -> group_size:int -> group_key:int -> instance_key:int -> merge_op:string -> final_op:string -> subdiv_offsets:int list -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t
val complex : ?name:string -> type_:[< `complex64 ] as 'tout Tensorflow.Node.Type.t -> ?control_inputs:Node.p list -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t -> [< `complex64 ] as 'tout Node.t
val complexAbs : ?name:string -> type_:[< `float | `double ] as 'tout Tensorflow.Node.Type.t -> ?control_inputs:Node.p list -> [< `complex64 ] as 't Node.t -> [< `float | `double ] as 'tout Node.t
val computeAccidentalHits : ?name:string -> num_true:int -> ?seed:int -> ?seed2:int -> ?control_inputs:Node.p list -> [ `int64 ] Node.t -> [ `int64 ] Node.t -> [ `int32 ] Node.t * [ `int64 ] Node.t * [ `float ] Node.t
val concat : ?name:string -> ?control_inputs:Node.p list -> [ `int32 ] Node.t -> 't Node.t list -> 't Node.t
val concatOffset : ?name:string -> ?control_inputs:Node.p list -> [ `int32 ] Node.t -> [ `int32 ] Node.t list -> [ `int32 ] Node.t list
val concatV2 : ?name:string -> ?control_inputs:Node.p list -> 't Node.t list -> [< `int32 | `int64 ] as 'tidx Node.t -> 't Node.t
val concatenateDataset : ?name:string -> output_types:Tensorflow.Node.Type.p list -> output_shapes:Tensorflow.Node.Dim.t list list -> ?control_inputs:Node.p list -> [ `variant ] Node.t -> [ `variant ] Node.t -> [ `variant ] Node.t
val conditionalAccumulator : ?name:string -> shape:Tensorflow.Node.Dim.t list -> ?container:string -> ?shared_name:string -> ?control_inputs:Node.p list -> unit -> [ `string ] Node.t
val conj : ?name:string -> ?control_inputs:Node.p list -> [< `complex64 | `variant ] as 't Node.t -> [< `complex64 | `variant ] as 't Node.t
val conjugateTranspose : ?name:string -> ?control_inputs:Node.p list -> 't Node.t -> [< `int32 | `int64 ] as 'tperm Node.t -> 't Node.t
val consumeMutexLock : ?name:string -> ?control_inputs:Node.p list -> [ `variant ] Node.t -> [ `unit ] Node.t
val controlTrigger : ?name:string -> ?control_inputs:Node.p list -> unit -> [ `unit ] Node.t
val conv2D : ?name:string -> strides:int list -> ?use_cudnn_on_gpu:bool -> padding:string -> ?data_format:string -> ?dilations:int list -> ?control_inputs:Node.p list -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t
val conv2DBackpropFilter : ?name:string -> strides:int list -> ?use_cudnn_on_gpu:bool -> padding:string -> ?data_format:string -> ?dilations:int list -> ?control_inputs:Node.p list -> [< `float | `double ] as 't Node.t -> [ `int32 ] Node.t -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t
val conv2DBackpropInput : ?name:string -> strides:int list -> ?use_cudnn_on_gpu:bool -> padding:string -> ?data_format:string -> ?dilations:int list -> ?control_inputs:Node.p list -> [ `int32 ] Node.t -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t
val conv3D : ?name:string -> strides:int list -> padding:string -> ?data_format:string -> ?dilations:int list -> ?control_inputs:Node.p list -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t
val conv3DBackpropFilter : ?name:string -> strides:int list -> padding:string -> ?dilations:int list -> ?control_inputs:Node.p list -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t
val conv3DBackpropFilterV2 : ?name:string -> strides:int list -> padding:string -> ?data_format:string -> ?dilations:int list -> ?control_inputs:Node.p list -> [< `float | `double ] as 't Node.t -> [ `int32 ] Node.t -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t
val conv3DBackpropInput : ?name:string -> strides:int list -> padding:string -> ?dilations:int list -> ?control_inputs:Node.p list -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t
val conv3DBackpropInputV2 : ?name:string -> strides:int list -> padding:string -> ?data_format:string -> ?dilations:int list -> ?control_inputs:Node.p list -> [< `int32 | `int64 ] as 'tshape Node.t -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t
val copy : ?name:string -> ?tensor_name:string -> ?control_inputs:Node.p list -> 't Node.t -> 't Node.t
val copyHost : ?name:string -> ?tensor_name:string -> ?control_inputs:Node.p list -> 't Node.t -> 't Node.t
val cos : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `complex64 ] as 't Node.t -> [< `float | `double | `complex64 ] as 't Node.t
val cosh : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `complex64 ] as 't Node.t -> [< `float | `double | `complex64 ] as 't Node.t
val countUpTo : ?name:string -> limit:int -> ?control_inputs:Node.p list -> [< `int32 | `int64 ] as 't Node.t -> [< `int32 | `int64 ] as 't Node.t
val cropAndResize : ?name:string -> ?method_:string -> ?extrapolation_value:float -> ?control_inputs:Node.p list -> [< `int32 | `int64 | `float | `double ] as 't Node.t -> [ `float ] Node.t -> [ `int32 ] Node.t -> [ `int32 ] Node.t -> [ `float ] Node.t
val cropAndResizeGradBoxes : ?name:string -> ?method_:string -> ?control_inputs:Node.p list -> [ `float ] Node.t -> [< `int32 | `int64 | `float | `double ] as 't Node.t -> [ `float ] Node.t -> [ `int32 ] Node.t -> [ `float ] Node.t
val cropAndResizeGradImage : ?name:string -> type_:[< `float | `double ] as 't Tensorflow.Node.Type.t -> ?method_:string -> ?control_inputs:Node.p list -> [ `float ] Node.t -> [ `float ] Node.t -> [ `int32 ] Node.t -> [ `int32 ] Node.t -> [< `float | `double ] as 't Node.t
val cross : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t
val cudnnRNN : ?name:string -> ?rnn_mode:string -> ?input_mode:string -> ?direction:string -> ?dropout:float -> ?seed:int -> ?seed2:int -> ?is_training:bool -> ?control_inputs:Node.p list -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t * [< `float | `double ] as 't Node.t * [< `float | `double ] as 't Node.t * [< `float | `double ] as 't Node.t
val cudnnRNNBackprop : ?name:string -> ?rnn_mode:string -> ?input_mode:string -> ?direction:string -> ?dropout:float -> ?seed:int -> ?seed2:int -> ?control_inputs:Node.p list -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t * [< `float | `double ] as 't Node.t * [< `float | `double ] as 't Node.t * [< `float | `double ] as 't Node.t
val cudnnRNNCanonicalToParams : ?name:string -> ?rnn_mode:string -> ?input_mode:string -> ?direction:string -> ?dropout:float -> ?seed:int -> ?seed2:int -> ?control_inputs:Node.p list -> [ `int32 ] Node.t -> [ `int32 ] Node.t -> [ `int32 ] Node.t -> [< `float | `double ] as 't Node.t list -> [< `float | `double ] as 't Node.t list -> [< `float | `double ] as 't Node.t
val cudnnRNNParamsSize : ?name:string -> type_:[< `int32 | `int64 ] as 's Tensorflow.Node.Type.t -> ?rnn_mode:string -> ?input_mode:string -> ?direction:string -> ?dropout:float -> ?seed:int -> ?seed2:int -> ?control_inputs:Node.p list -> [ `int32 ] Node.t -> [ `int32 ] Node.t -> [ `int32 ] Node.t -> [< `int32 | `int64 ] as 's Node.t
val cumprod : ?name:string -> ?exclusive:bool -> ?reverse:bool -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `int32 | `int64 ] as 'tidx Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t
val cumsum : ?name:string -> ?exclusive:bool -> ?reverse:bool -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `int32 | `int64 ] as 'tidx Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t
val dataFormatDimMap : ?name:string -> ?src_format:string -> ?dst_format:string -> ?control_inputs:Node.p list -> [< `int32 | `int64 ] as 't Node.t -> [< `int32 | `int64 ] as 't Node.t
val dataFormatVecPermute : ?name:string -> ?src_format:string -> ?dst_format:string -> ?control_inputs:Node.p list -> [< `int32 | `int64 ] as 't Node.t -> [< `int32 | `int64 ] as 't Node.t
val datasetToGraph : ?name:string -> ?control_inputs:Node.p list -> [ `variant ] Node.t -> [ `string ] Node.t
val datasetToTFRecord : ?name:string -> ?control_inputs:Node.p list -> [ `variant ] Node.t -> [ `string ] Node.t -> [ `string ] Node.t -> [ `unit ] Node.t
val debugGradientIdentity : ?name:string -> ?control_inputs:Node.p list -> 't Node.t -> 't Node.t
val debugGradientRefIdentity : ?name:string -> ?control_inputs:Node.p list -> 't Node.t -> 't Node.t
val debugIdentity : ?name:string -> ?device_name:string -> ?tensor_name:string -> ?gated_grpc:bool -> ?control_inputs:Node.p list -> 't Node.t -> 't Node.t
val debugNanCount : ?name:string -> ?device_name:string -> ?tensor_name:string -> ?gated_grpc:bool -> ?control_inputs:Node.p list -> 't Node.t -> [ `int64 ] Node.t
val debugNumericSummary : ?name:string -> ?device_name:string -> ?tensor_name:string -> ?lower_bound:float -> ?upper_bound:float -> ?mute_if_healthy:bool -> ?gated_grpc:bool -> ?control_inputs:Node.p list -> 't Node.t -> [ `double ] Node.t
val decodeBase64 : ?name:string -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `string ] Node.t
val decodeCompressed : ?name:string -> ?compression_type:string -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `string ] Node.t
val decodeJSONExample : ?name:string -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `string ] Node.t
val decodePng : ?name:string -> type_:'dtype Tensorflow.Node.Type.t -> ?channels:int -> ?control_inputs:Node.p list -> [ `string ] Node.t -> 'dtype Node.t
val decodeRaw : ?name:string -> type_: [< `float | `double | `int32 | `int64 ] as 'out_type Tensorflow.Node.Type.t -> ?little_endian:bool -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [< `float | `double | `int32 | `int64 ] as 'out_type Node.t
val decodeWav : ?name:string -> ?desired_channels:int -> ?desired_samples:int -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `float ] Node.t * [ `int32 ] Node.t
val deepCopy : ?name:string -> ?control_inputs:Node.p list -> 't Node.t -> 't Node.t
val deleteSessionTensor : ?name:string -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `unit ] Node.t
val denseToDenseSetOperation : ?name:string -> set_operation:string -> ?validate_indices:bool -> ?control_inputs:Node.p list -> [< `int32 | `int64 | `string ] as 't Node.t -> [< `int32 | `int64 | `string ] as 't Node.t -> [ `int64 ] Node.t * [< `int32 | `int64 | `string ] as 't Node.t * [ `int64 ] Node.t
val denseToSparseBatchDataset : ?name:string -> output_types:Tensorflow.Node.Type.p list -> output_shapes:Tensorflow.Node.Dim.t list list -> ?control_inputs:Node.p list -> [ `variant ] Node.t -> [ `int64 ] Node.t -> [ `int64 ] Node.t -> [ `variant ] Node.t
val denseToSparseSetOperation : ?name:string -> set_operation:string -> ?validate_indices:bool -> ?control_inputs:Node.p list -> [< `int32 | `int64 | `string ] as 't Node.t -> [ `int64 ] Node.t -> [< `int32 | `int64 | `string ] as 't Node.t -> [ `int64 ] Node.t -> [ `int64 ] Node.t * [< `int32 | `int64 | `string ] as 't Node.t * [ `int64 ] Node.t
val depthToSpace : ?name:string -> block_size:int -> ?data_format:string -> ?control_inputs:Node.p list -> 't Node.t -> 't Node.t
val depthwiseConv2dNative : ?name:string -> strides:int list -> padding:string -> ?data_format:string -> ?dilations:int list -> ?control_inputs:Node.p list -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t
val depthwiseConv2dNativeBackpropFilter : ?name:string -> strides:int list -> padding:string -> ?data_format:string -> ?dilations:int list -> ?control_inputs:Node.p list -> [< `float | `double ] as 't Node.t -> [ `int32 ] Node.t -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t
val depthwiseConv2dNativeBackpropInput : ?name:string -> strides:int list -> padding:string -> ?data_format:string -> ?dilations:int list -> ?control_inputs:Node.p list -> [ `int32 ] Node.t -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t
val dequantize : ?name:string -> ?mode:string -> ?control_inputs:Node.p list -> 't Node.t -> [ `float ] Node.t -> [ `float ] Node.t -> [ `float ] Node.t
val deserializeManySparse : ?name:string -> type_1:'dtype Tensorflow.Node.Type.t -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `int64 ] Node.t * 'dtype Node.t * [ `int64 ] Node.t
val deserializeSparse : ?name:string -> type_1:'dtype Tensorflow.Node.Type.t -> ?control_inputs:Node.p list -> [< `string | `variant ] as 'tserialized Node.t -> [ `int64 ] Node.t * 'dtype Node.t * [ `int64 ] Node.t
val destroyTemporaryVariable : ?name:string -> var_name:string -> ?control_inputs:Node.p list -> 't Node.t -> 't Node.t
val diag : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 | `complex64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 | `complex64 ] as 't Node.t
val diagPart : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 | `complex64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 | `complex64 ] as 't Node.t
val digamma : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t
val dilation2D : ?name:string -> strides:int list -> rates:int list -> padding:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t
val dilation2DBackpropFilter : ?name:string -> strides:int list -> rates:int list -> padding:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t
val dilation2DBackpropInput : ?name:string -> strides:int list -> rates:int list -> padding:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t
val div : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 | `complex64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 | `complex64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 | `complex64 ] as 't Node.t
val drawBoundingBoxes : ?name:string -> ?control_inputs:Node.p list -> [< `float ] as 't Node.t -> [ `float ] Node.t -> [< `float ] as 't Node.t
val dynamicPartition : ?name:string -> num_partitions:int -> ?control_inputs:Node.p list -> 't Node.t -> [ `int32 ] Node.t -> 't Node.t list
val dynamicStitch : ?name:string -> ?control_inputs:Node.p list -> [ `int32 ] Node.t list -> 't Node.t list -> 't Node.t
val editDistance : ?name:string -> ?normalize:bool -> ?control_inputs:Node.p list -> [ `int64 ] Node.t -> 't Node.t -> [ `int64 ] Node.t -> [ `int64 ] Node.t -> 't Node.t -> [ `int64 ] Node.t -> [ `float ] Node.t
val elu : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t
val eluGrad : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t
val empty : ?name:string -> type_:'dtype Tensorflow.Node.Type.t -> ?init:bool -> ?control_inputs:Node.p list -> [ `int32 ] Node.t -> 'dtype Node.t
val emptyTensorList : ?name:string -> ?control_inputs:Node.p list -> [< `int32 | `int64 ] as 'shape_type Node.t -> [ `variant ] Node.t
val encodeBase64 : ?name:string -> ?pad:bool -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `string ] Node.t
val encodePng : ?name:string -> ?compression:int -> ?control_inputs:Node.p list -> 't Node.t -> [ `string ] Node.t
val encodeWav : ?name:string -> ?control_inputs:Node.p list -> [ `float ] Node.t -> [ `int32 ] Node.t -> [ `string ] Node.t
val enter : ?name:string -> frame_name:string -> ?is_constant:bool -> ?parallel_iterations:int -> ?control_inputs:Node.p list -> 't Node.t -> 't Node.t
val equal : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 | `complex64 | `string | `bool ] as 't Node.t -> [< `float | `double | `int32 | `int64 | `complex64 | `string | `bool ] as 't Node.t -> [ `bool ] Node.t
val erf : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t
val erfc : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t
val exit : ?name:string -> ?control_inputs:Node.p list -> 't Node.t -> 't Node.t
val exp : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `complex64 ] as 't Node.t -> [< `float | `double | `complex64 ] as 't Node.t
val expandDims : ?name:string -> ?control_inputs:Node.p list -> 't Node.t -> [< `int32 | `int64 ] as 'tdim Node.t -> 't Node.t
val expm1 : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `complex64 ] as 't Node.t -> [< `float | `double | `complex64 ] as 't Node.t
val extractGlimpse : ?name:string -> ?centered:bool -> ?normalized:bool -> ?uniform_noise:bool -> ?control_inputs:Node.p list -> [ `float ] Node.t -> [ `int32 ] Node.t -> [ `float ] Node.t -> [ `float ] Node.t
val extractImagePatches : ?name:string -> ksizes:int list -> strides:int list -> rates:int list -> padding:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t
val extractJpegShape : ?name:string -> type_:[< `int32 | `int64 ] as 'output_type Tensorflow.Node.Type.t -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [< `int32 | `int64 ] as 'output_type Node.t
val fFT : ?name:string -> ?control_inputs:Node.p list -> [< `complex64 ] as 'tcomplex Node.t -> [< `complex64 ] as 'tcomplex Node.t
val fFT2D : ?name:string -> ?control_inputs:Node.p list -> [< `complex64 ] as 'tcomplex Node.t -> [< `complex64 ] as 'tcomplex Node.t
val fFT3D : ?name:string -> ?control_inputs:Node.p list -> [< `complex64 ] as 'tcomplex Node.t -> [< `complex64 ] as 'tcomplex Node.t
val fIFOQueue : ?name:string -> component_types:Tensorflow.Node.Type.p list -> ?shapes:Tensorflow.Node.Dim.t list list -> ?capacity:int -> ?container:string -> ?shared_name:string -> ?control_inputs:Node.p list -> unit -> [ `string ] Node.t
val fact : ?name:string -> ?control_inputs:Node.p list -> unit -> [ `string ] Node.t
val fakeParam : ?name:string -> type_:'dtype Tensorflow.Node.Type.t -> shape:Tensorflow.Node.Dim.t list -> ?control_inputs:Node.p list -> unit -> 'dtype Node.t
val fakeQuantWithMinMaxArgs : ?name:string -> ?min:float -> ?max:float -> ?num_bits:int -> ?narrow_range:bool -> ?control_inputs:Node.p list -> [ `float ] Node.t -> [ `float ] Node.t
val fakeQuantWithMinMaxArgsGradient : ?name:string -> ?min:float -> ?max:float -> ?num_bits:int -> ?narrow_range:bool -> ?control_inputs:Node.p list -> [ `float ] Node.t -> [ `float ] Node.t -> [ `float ] Node.t
val fakeQuantWithMinMaxVars : ?name:string -> ?num_bits:int -> ?narrow_range:bool -> ?control_inputs:Node.p list -> [ `float ] Node.t -> [ `float ] Node.t -> [ `float ] Node.t -> [ `float ] Node.t
val fakeQuantWithMinMaxVarsGradient : ?name:string -> ?num_bits:int -> ?narrow_range:bool -> ?control_inputs:Node.p list -> [ `float ] Node.t -> [ `float ] Node.t -> [ `float ] Node.t -> [ `float ] Node.t -> [ `float ] Node.t * [ `float ] Node.t * [ `float ] Node.t
val fakeQuantWithMinMaxVarsPerChannel : ?name:string -> ?num_bits:int -> ?narrow_range:bool -> ?control_inputs:Node.p list -> [ `float ] Node.t -> [ `float ] Node.t -> [ `float ] Node.t -> [ `float ] Node.t
val fakeQuantWithMinMaxVarsPerChannelGradient : ?name:string -> ?num_bits:int -> ?narrow_range:bool -> ?control_inputs:Node.p list -> [ `float ] Node.t -> [ `float ] Node.t -> [ `float ] Node.t -> [ `float ] Node.t -> [ `float ] Node.t * [ `float ] Node.t * [ `float ] Node.t
val featureStatsDataset : ?name:string -> output_types:Tensorflow.Node.Type.p list -> output_shapes:Tensorflow.Node.Dim.t list list -> ?control_inputs:Node.p list -> [ `variant ] Node.t -> [ `string ] Node.t -> [ `variant ] Node.t
val fill : ?name:string -> ?control_inputs:Node.p list -> [< `int32 | `int64 ] as 'index_type Node.t -> 't Node.t -> 't Node.t
val fixedLengthRecordDataset : ?name:string -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `int64 ] Node.t -> [ `int64 ] Node.t -> [ `int64 ] Node.t -> [ `int64 ] Node.t -> [ `variant ] Node.t
val fixedLengthRecordReader : ?name:string -> ?header_bytes:int -> record_bytes:int -> ?footer_bytes:int -> ?hop_bytes:int -> ?container:string -> ?shared_name:string -> ?control_inputs:Node.p list -> unit -> [ `string ] Node.t
val fixedUnigramCandidateSampler : ?name:string -> num_true:int -> num_sampled:int -> unique:bool -> range_max:int -> ?vocab_file:string -> ?distortion:float -> ?num_reserved_ids:int -> ?num_shards:int -> ?shard:int -> ?unigrams:float list -> ?seed:int -> ?seed2:int -> ?control_inputs:Node.p list -> [ `int64 ] Node.t -> [ `int64 ] Node.t * [ `float ] Node.t * [ `float ] Node.t
val floor : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t
val floorDiv : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 | `complex64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 | `complex64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 | `complex64 ] as 't Node.t
val floorMod : ?name:string -> ?control_inputs:Node.p list -> [< `int32 | `int64 | `float | `double ] as 't Node.t -> [< `int32 | `int64 | `float | `double ] as 't Node.t -> [< `int32 | `int64 | `float | `double ] as 't Node.t
val fractionalAvgPool : ?name:string -> pooling_ratio:float list -> ?pseudo_random:bool -> ?overlapping:bool -> ?deterministic:bool -> ?seed:int -> ?seed2:int -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t * [ `int64 ] Node.t * [ `int64 ] Node.t
val fractionalAvgPoolGrad : ?name:string -> ?overlapping:bool -> ?control_inputs:Node.p list -> [ `int64 ] Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [ `int64 ] Node.t -> [ `int64 ] Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t
val fractionalMaxPool : ?name:string -> pooling_ratio:float list -> ?pseudo_random:bool -> ?overlapping:bool -> ?deterministic:bool -> ?seed:int -> ?seed2:int -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t * [ `int64 ] Node.t * [ `int64 ] Node.t
val fractionalMaxPoolGrad : ?name:string -> ?overlapping:bool -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [ `int64 ] Node.t -> [ `int64 ] Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t
val fusedBatchNorm : ?name:string -> ?epsilon:float -> ?data_format:string -> ?is_training:bool -> ?control_inputs:Node.p list -> [< `float ] as 't Node.t -> [< `float ] as 't Node.t -> [< `float ] as 't Node.t -> [< `float ] as 't Node.t -> [< `float ] as 't Node.t -> [< `float ] as 't Node.t * [< `float ] as 't Node.t * [< `float ] as 't Node.t * [< `float ] as 't Node.t * [< `float ] as 't Node.t
val fusedBatchNormGrad : ?name:string -> ?epsilon:float -> ?data_format:string -> ?is_training:bool -> ?control_inputs:Node.p list -> [< `float ] as 't Node.t -> [< `float ] as 't Node.t -> [< `float ] as 't Node.t -> [< `float ] as 't Node.t -> [< `float ] as 't Node.t -> [< `float ] as 't Node.t * [< `float ] as 't Node.t * [< `float ] as 't Node.t * [< `float ] as 't Node.t * [< `float ] as 't Node.t
val fusedBatchNormGradV2 : ?name:string -> ?epsilon:float -> ?data_format:string -> ?is_training:bool -> ?control_inputs:Node.p list -> [< `float ] as 't Node.t -> [< `float ] as 't Node.t -> [ `float ] Node.t -> [< `float ] as 'u Node.t -> [< `float ] as 'u Node.t -> [< `float ] as 't Node.t * [< `float ] as 'u Node.t * [< `float ] as 'u Node.t * [< `float ] as 'u Node.t * [< `float ] as 'u Node.t
val fusedBatchNormV2 : ?name:string -> ?epsilon:float -> ?data_format:string -> ?is_training:bool -> ?control_inputs:Node.p list -> [< `float ] as 't Node.t -> [< `float ] as 'u Node.t -> [< `float ] as 'u Node.t -> [< `float ] as 'u Node.t -> [< `float ] as 'u Node.t -> [< `float ] as 't Node.t * [< `float ] as 'u Node.t * [< `float ] as 'u Node.t * [< `float ] as 'u Node.t * [< `float ] as 'u Node.t
val fusedPadConv2D : ?name:string -> mode:string -> strides:int list -> padding:string -> ?control_inputs:Node.p list -> [< `float | `double ] as 't Node.t -> [ `int32 ] Node.t -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t
val fusedResizeAndPadConv2D : ?name:string -> ?resize_align_corners:bool -> mode:string -> strides:int list -> padding:string -> ?control_inputs:Node.p list -> [< `float | `double ] as 't Node.t -> [ `int32 ] Node.t -> [ `int32 ] Node.t -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t
val gather : ?name:string -> ?validate_indices:bool -> ?control_inputs:Node.p list -> 'tparams Node.t -> [< `int32 | `int64 ] as 'tindices Node.t -> 'tparams Node.t
val gatherNd : ?name:string -> ?control_inputs:Node.p list -> 'tparams Node.t -> [< `int32 | `int64 ] as 'tindices Node.t -> 'tparams Node.t
val gatherV2 : ?name:string -> ?control_inputs:Node.p list -> 'tparams Node.t -> [< `int32 | `int64 ] as 'tindices Node.t -> [< `int32 | `int64 ] as 'taxis Node.t -> 'tparams Node.t
val generateVocabRemapping : ?name:string -> new_vocab_offset:int -> num_new_vocab:int -> ?old_vocab_size:int -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `string ] Node.t -> [ `int64 ] Node.t * [ `int32 ] Node.t
val getSessionHandle : ?name:string -> ?control_inputs:Node.p list -> 't Node.t -> [ `string ] Node.t
val getSessionTensor : ?name:string -> type_:'dtype Tensorflow.Node.Type.t -> ?control_inputs:Node.p list -> [ `string ] Node.t -> 'dtype Node.t
val greater : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [ `bool ] Node.t
val greaterEqual : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [ `bool ] Node.t
val guaranteeConst : ?name:string -> ?control_inputs:Node.p list -> 't Node.t -> 't Node.t
val hSVToRGB : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t
val hashTable : ?name:string -> ?container:string -> ?shared_name:string -> ?use_node_name_sharing:bool -> ?control_inputs:Node.p list -> unit -> [ `string ] Node.t
val histogramFixedWidth : ?name:string -> type_:[< `int32 | `int64 ] as 'dtype Tensorflow.Node.Type.t -> ?control_inputs:Node.p list -> [< `int32 | `int64 | `float | `double ] as 't Node.t -> [< `int32 | `int64 | `float | `double ] as 't Node.t -> [ `int32 ] Node.t -> [< `int32 | `int64 ] as 'dtype Node.t
val histogramSummary : ?name:string -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [ `string ] Node.t
val iFFT : ?name:string -> ?control_inputs:Node.p list -> [< `complex64 ] as 'tcomplex Node.t -> [< `complex64 ] as 'tcomplex Node.t
val iFFT2D : ?name:string -> ?control_inputs:Node.p list -> [< `complex64 ] as 'tcomplex Node.t -> [< `complex64 ] as 'tcomplex Node.t
val iFFT3D : ?name:string -> ?control_inputs:Node.p list -> [< `complex64 ] as 'tcomplex Node.t -> [< `complex64 ] as 'tcomplex Node.t
val iRFFT : ?name:string -> ?control_inputs:Node.p list -> [ `complex64 ] Node.t -> [ `int32 ] Node.t -> [ `float ] Node.t
val iRFFT2D : ?name:string -> ?control_inputs:Node.p list -> [ `complex64 ] Node.t -> [ `int32 ] Node.t -> [ `float ] Node.t
val iRFFT3D : ?name:string -> ?control_inputs:Node.p list -> [ `complex64 ] Node.t -> [ `int32 ] Node.t -> [ `float ] Node.t
val identity : ?name:string -> ?control_inputs:Node.p list -> 't Node.t -> 't Node.t
val identityReader : ?name:string -> ?container:string -> ?shared_name:string -> ?control_inputs:Node.p list -> unit -> [ `string ] Node.t
val igamma : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t
val igammaGradA : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t
val igammac : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t
val imag : ?name:string -> type_:[< `float | `double ] as 'tout Tensorflow.Node.Type.t -> ?control_inputs:Node.p list -> [< `complex64 ] as 't Node.t -> [< `float | `double ] as 'tout Node.t
val imageSummary : ?name:string -> ?max_images:int -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [< `float | `double ] as 't Node.t -> [ `string ] Node.t
val immutableConst : ?name:string -> type_:'dtype Tensorflow.Node.Type.t -> shape:Tensorflow.Node.Dim.t list -> memory_region_name:string -> ?control_inputs:Node.p list -> unit -> 'dtype Node.t
val inTopK : ?name:string -> k:int -> ?control_inputs:Node.p list -> [ `float ] Node.t -> [< `int32 | `int64 ] as 't Node.t -> [ `bool ] Node.t
val inTopKV2 : ?name:string -> ?control_inputs:Node.p list -> [ `float ] Node.t -> [< `int32 | `int64 ] as 't Node.t -> [< `int32 | `int64 ] as 't Node.t -> [ `bool ] Node.t
val initializeTable : ?name:string -> ?control_inputs:Node.p list -> [ `string ] Node.t -> 'tkey Node.t -> 'tval Node.t -> [ `unit ] Node.t
val initializeTableFromTextFile : ?name:string -> key_index:int -> value_index:int -> ?vocab_size:int -> ?delimiter:string -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `string ] Node.t -> [ `unit ] Node.t
val inplaceAdd : ?name:string -> ?control_inputs:Node.p list -> 't Node.t -> [ `int32 ] Node.t -> 't Node.t -> 't Node.t
val inplaceSub : ?name:string -> ?control_inputs:Node.p list -> 't Node.t -> [ `int32 ] Node.t -> 't Node.t -> 't Node.t
val inplaceUpdate : ?name:string -> ?control_inputs:Node.p list -> 't Node.t -> [ `int32 ] Node.t -> 't Node.t -> 't Node.t
val inv : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 | `complex64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 | `complex64 ] as 't Node.t
val invGrad : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `complex64 ] as 't Node.t -> [< `float | `double | `complex64 ] as 't Node.t -> [< `float | `double | `complex64 ] as 't Node.t
val invert : ?name:string -> ?control_inputs:Node.p list -> [< `int32 | `int64 ] as 't Node.t -> [< `int32 | `int64 ] as 't Node.t
val invertPermutation : ?name:string -> ?control_inputs:Node.p list -> [< `int32 | `int64 ] as 't Node.t -> [< `int32 | `int64 ] as 't Node.t
val isFinite : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double ] as 't Node.t -> [ `bool ] Node.t
val isInf : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double ] as 't Node.t -> [ `bool ] Node.t
val isNan : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double ] as 't Node.t -> [ `bool ] Node.t
val isVariableInitialized : ?name:string -> ?control_inputs:Node.p list -> 'dtype Node.t -> [ `bool ] Node.t
val l2Loss : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t
val lMDBReader : ?name:string -> ?container:string -> ?shared_name:string -> ?control_inputs:Node.p list -> unit -> [ `string ] Node.t
val lRN : ?name:string -> ?depth_radius:int -> ?bias:float -> ?alpha:float -> ?beta:float -> ?control_inputs:Node.p list -> [< `float ] as 't Node.t -> [< `float ] as 't Node.t
val lRNGrad : ?name:string -> ?depth_radius:int -> ?bias:float -> ?alpha:float -> ?beta:float -> ?control_inputs:Node.p list -> [< `float ] as 't Node.t -> [< `float ] as 't Node.t -> [< `float ] as 't Node.t -> [< `float ] as 't Node.t
val latencyStatsDataset : ?name:string -> output_types:Tensorflow.Node.Type.p list -> output_shapes:Tensorflow.Node.Dim.t list list -> ?control_inputs:Node.p list -> [ `variant ] Node.t -> [ `string ] Node.t -> [ `variant ] Node.t
val learnedUnigramCandidateSampler : ?name:string -> num_true:int -> num_sampled:int -> unique:bool -> range_max:int -> ?seed:int -> ?seed2:int -> ?control_inputs:Node.p list -> [ `int64 ] Node.t -> [ `int64 ] Node.t * [ `float ] Node.t * [ `float ] Node.t
val leftShift : ?name:string -> ?control_inputs:Node.p list -> [< `int32 | `int64 ] as 't Node.t -> [< `int32 | `int64 ] as 't Node.t -> [< `int32 | `int64 ] as 't Node.t
val less : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [ `bool ] Node.t
val lessEqual : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [ `bool ] Node.t
val lgamma : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t
val linSpace : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t -> [< `int32 | `int64 ] as 'tidx Node.t -> [< `float | `double ] as 't Node.t
val listDiff : ?name:string -> type_1:[< `int32 | `int64 ] as 'out_idx Tensorflow.Node.Type.t -> ?control_inputs:Node.p list -> 't Node.t -> 't Node.t -> 't Node.t * [< `int32 | `int64 ] as 'out_idx Node.t
val loadAndRemapMatrix : ?name:string -> num_rows:int -> num_cols:int -> ?max_rows_in_memory:int -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `string ] Node.t -> [ `int64 ] Node.t -> [ `int64 ] Node.t -> [ `float ] Node.t -> [ `float ] Node.t
val log : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `complex64 ] as 't Node.t -> [< `float | `double | `complex64 ] as 't Node.t
val log1p : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `complex64 ] as 't Node.t -> [< `float | `double | `complex64 ] as 't Node.t
val logMatrixDeterminant : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `complex64 ] as 't Node.t -> [< `float | `double | `complex64 ] as 't Node.t * [< `float | `double | `complex64 ] as 't Node.t
val logSoftmax : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t
val logUniformCandidateSampler : ?name:string -> num_true:int -> num_sampled:int -> unique:bool -> range_max:int -> ?seed:int -> ?seed2:int -> ?control_inputs:Node.p list -> [ `int64 ] Node.t -> [ `int64 ] Node.t * [ `float ] Node.t * [ `float ] Node.t
val logicalAnd : ?name:string -> ?control_inputs:Node.p list -> [ `bool ] Node.t -> [ `bool ] Node.t -> [ `bool ] Node.t
val logicalNot : ?name:string -> ?control_inputs:Node.p list -> [ `bool ] Node.t -> [ `bool ] Node.t
val logicalOr : ?name:string -> ?control_inputs:Node.p list -> [ `bool ] Node.t -> [ `bool ] Node.t -> [ `bool ] Node.t
val lookupTableExport : ?name:string -> type_:'tkeys Tensorflow.Node.Type.t -> type_1:'tvalues Tensorflow.Node.Type.t -> ?control_inputs:Node.p list -> [ `string ] Node.t -> 'tkeys Node.t * 'tvalues Node.t
val lookupTableFind : ?name:string -> ?control_inputs:Node.p list -> [ `string ] Node.t -> 'tin Node.t -> 'tout Node.t -> 'tout Node.t
val lookupTableImport : ?name:string -> ?control_inputs:Node.p list -> [ `string ] Node.t -> 'tin Node.t -> 'tout Node.t -> [ `unit ] Node.t
val lookupTableInsert : ?name:string -> ?control_inputs:Node.p list -> [ `string ] Node.t -> 'tin Node.t -> 'tout Node.t -> [ `unit ] Node.t
val lookupTableSize : ?name:string -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `int64 ] Node.t
val loopCond : ?name:string -> ?control_inputs:Node.p list -> [ `bool ] Node.t -> [ `bool ] Node.t
val mapClear : ?name:string -> ?capacity:int -> ?memory_limit:int -> dtypes:Tensorflow.Node.Type.p list -> ?container:string -> ?shared_name:string -> ?control_inputs:Node.p list -> unit -> [ `unit ] Node.t
val mapIncompleteSize : ?name:string -> ?capacity:int -> ?memory_limit:int -> dtypes:Tensorflow.Node.Type.p list -> ?container:string -> ?shared_name:string -> ?control_inputs:Node.p list -> unit -> [ `int32 ] Node.t
val mapSize : ?name:string -> ?capacity:int -> ?memory_limit:int -> dtypes:Tensorflow.Node.Type.p list -> ?container:string -> ?shared_name:string -> ?control_inputs:Node.p list -> unit -> [ `int32 ] Node.t
val matMul : ?name:string -> ?transpose_a:bool -> ?transpose_b:bool -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `complex64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 ] as 't Node.t
val matchingFiles : ?name:string -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `string ] Node.t
val matrixBandPart : ?name:string -> ?control_inputs:Node.p list -> 't Node.t -> [< `int32 | `int64 ] as 'tindex Node.t -> [< `int32 | `int64 ] as 'tindex Node.t -> 't Node.t
val matrixDeterminant : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `complex64 ] as 't Node.t -> [< `float | `double | `complex64 ] as 't Node.t
val matrixDiag : ?name:string -> ?control_inputs:Node.p list -> 't Node.t -> 't Node.t
val matrixDiagPart : ?name:string -> ?control_inputs:Node.p list -> 't Node.t -> 't Node.t
val matrixExponential : ?name:string -> ?control_inputs:Node.p list -> [< `double | `float | `complex64 ] as 't Node.t -> [< `double | `float | `complex64 ] as 't Node.t
val matrixInverse : ?name:string -> ?adjoint:bool -> ?control_inputs:Node.p list -> [< `double | `float | `complex64 ] as 't Node.t -> [< `double | `float | `complex64 ] as 't Node.t
val matrixLogarithm : ?name:string -> ?control_inputs:Node.p list -> [< `complex64 ] as 't Node.t -> [< `complex64 ] as 't Node.t
val matrixSetDiag : ?name:string -> ?control_inputs:Node.p list -> 't Node.t -> 't Node.t -> 't Node.t
val matrixSolve : ?name:string -> ?adjoint:bool -> ?control_inputs:Node.p list -> [< `double | `float | `complex64 ] as 't Node.t -> [< `double | `float | `complex64 ] as 't Node.t -> [< `double | `float | `complex64 ] as 't Node.t
val matrixSolveLs : ?name:string -> ?fast:bool -> ?control_inputs:Node.p list -> [< `double | `float | `complex64 ] as 't Node.t -> [< `double | `float | `complex64 ] as 't Node.t -> [ `double ] Node.t -> [< `double | `float | `complex64 ] as 't Node.t
val matrixTriangularSolve : ?name:string -> ?lower:bool -> ?adjoint:bool -> ?control_inputs:Node.p list -> [< `double | `float | `complex64 ] as 't Node.t -> [< `double | `float | `complex64 ] as 't Node.t -> [< `double | `float | `complex64 ] as 't Node.t
val max : ?name:string -> ?keep_dims:bool -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `int32 | `int64 ] as 'tidx Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t
val maxPool : ?name:string -> ksize:int list -> strides:int list -> padding:string -> ?data_format:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t
val maxPool3D : ?name:string -> ksize:int list -> strides:int list -> padding:string -> ?data_format:string -> ?control_inputs:Node.p list -> [< `float ] as 't Node.t -> [< `float ] as 't Node.t
val maxPool3DGrad : ?name:string -> ksize:int list -> strides:int list -> padding:string -> ?data_format:string -> ?control_inputs:Node.p list -> [< `float ] as 'tInput Node.t -> [< `float ] as 'tInput Node.t -> [< `float ] as 't Node.t -> [< `float ] as 't Node.t
val maxPool3DGradGrad : ?name:string -> ksize:int list -> strides:int list -> padding:string -> ?data_format:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t
val maxPoolGrad : ?name:string -> ksize:int list -> strides:int list -> padding:string -> ?data_format:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t
val maxPoolGradGrad : ?name:string -> ksize:int list -> strides:int list -> padding:string -> ?data_format:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t
val maxPoolGradGradV2 : ?name:string -> padding:string -> ?data_format:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [ `int32 ] Node.t -> [ `int32 ] Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t
val maxPoolGradGradWithArgmax : ?name:string -> ksize:int list -> strides:int list -> padding:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [< `int32 | `int64 ] as 'targmax Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t
val maxPoolGradV2 : ?name:string -> padding:string -> ?data_format:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [ `int32 ] Node.t -> [ `int32 ] Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t
val maxPoolGradWithArgmax : ?name:string -> ksize:int list -> strides:int list -> padding:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [< `int32 | `int64 ] as 'targmax Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t
val maxPoolV2 : ?name:string -> padding:string -> ?data_format:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [ `int32 ] Node.t -> [ `int32 ] Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t
val maxPoolWithArgmax : ?name:string -> type_1:[< `int32 | `int64 ] as 'targmax Tensorflow.Node.Type.t -> ksize:int list -> strides:int list -> padding:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t * [< `int32 | `int64 ] as 'targmax Node.t
val maximum : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t
val mean : ?name:string -> ?keep_dims:bool -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `int32 | `int64 ] as 'tidx Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t
val merge : ?name:string -> ?control_inputs:Node.p list -> 't Node.t list -> 't Node.t * [ `int32 ] Node.t
val mergeSummary : ?name:string -> ?control_inputs:Node.p list -> [ `string ] Node.t list -> [ `string ] Node.t
val mergeV2Checkpoints : ?name:string -> ?delete_old_dirs:bool -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `string ] Node.t -> [ `unit ] Node.t
val mfcc : ?name:string -> ?upper_frequency_limit:float -> ?lower_frequency_limit:float -> ?filterbank_channel_count:int -> ?dct_coefficient_count:int -> ?control_inputs:Node.p list -> [ `float ] Node.t -> [ `int32 ] Node.t -> [ `float ] Node.t
val min : ?name:string -> ?keep_dims:bool -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `int32 | `int64 ] as 'tidx Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t
val minimum : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t
val mirrorPad : ?name:string -> mode:string -> ?control_inputs:Node.p list -> 't Node.t -> [< `int32 | `int64 ] as 'tpaddings Node.t -> 't Node.t
val mirrorPadGrad : ?name:string -> mode:string -> ?control_inputs:Node.p list -> 't Node.t -> [< `int32 | `int64 ] as 'tpaddings Node.t -> 't Node.t
val mod_ : ?name:string -> ?control_inputs:Node.p list -> [< `int32 | `int64 | `float | `double ] as 't Node.t -> [< `int32 | `int64 | `float | `double ] as 't Node.t -> [< `int32 | `int64 | `float | `double ] as 't Node.t
val mul : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 | `complex64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 | `complex64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 | `complex64 ] as 't Node.t
val multinomial : ?name:string -> type_:[< `int32 | `int64 ] as 'output_dtype Tensorflow.Node.Type.t -> ?seed:int -> ?seed2:int -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [ `int32 ] Node.t -> [< `int32 | `int64 ] as 'output_dtype Node.t
val mutableDenseHashTable : ?name:string -> ?container:string -> ?shared_name:string -> ?use_node_name_sharing:bool -> ?value_shape:Tensorflow.Node.Dim.t list -> ?initial_num_buckets:int -> ?max_load_factor:float -> ?control_inputs:Node.p list -> 'key_dtype Node.t -> [ `string ] Node.t
val mutableHashTable : ?name:string -> ?container:string -> ?shared_name:string -> ?use_node_name_sharing:bool -> ?control_inputs:Node.p list -> unit -> [ `string ] Node.t
val mutableHashTableOfTensors : ?name:string -> ?container:string -> ?shared_name:string -> ?use_node_name_sharing:bool -> ?value_shape:Tensorflow.Node.Dim.t list -> ?control_inputs:Node.p list -> unit -> [ `string ] Node.t
val neg : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 | `complex64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 | `complex64 ] as 't Node.t
val negTrain : ?name:string -> vocab_count:int list -> num_negative_samples:int -> ?control_inputs:Node.p list -> [ `float ] Node.t -> [ `float ] Node.t -> [ `int32 ] Node.t -> [ `int32 ] Node.t -> [ `float ] Node.t -> [ `unit ] Node.t
val nextIteration : ?name:string -> ?control_inputs:Node.p list -> 't Node.t -> 't Node.t
val noOp : ?name:string -> ?control_inputs:Node.p list -> unit -> [ `unit ] Node.t
val nonMaxSuppression : ?name:string -> ?iou_threshold:float -> ?control_inputs:Node.p list -> [ `float ] Node.t -> [ `float ] Node.t -> [ `int32 ] Node.t -> [ `int32 ] Node.t
val nonMaxSuppressionV2 : ?name:string -> ?control_inputs:Node.p list -> [ `float ] Node.t -> [ `float ] Node.t -> [ `int32 ] Node.t -> [ `float ] Node.t -> [ `int32 ] Node.t
val nonMaxSuppressionV3 : ?name:string -> ?control_inputs:Node.p list -> [ `float ] Node.t -> [ `float ] Node.t -> [ `int32 ] Node.t -> [ `float ] Node.t -> [ `float ] Node.t -> [ `int32 ] Node.t
val nonMaxSuppressionWithOverlaps : ?name:string -> ?control_inputs:Node.p list -> [ `float ] Node.t -> [ `float ] Node.t -> [ `int32 ] Node.t -> [ `float ] Node.t -> [ `float ] Node.t -> [ `int32 ] Node.t
val notEqual : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 | `complex64 | `string | `bool ] as 't Node.t -> [< `float | `double | `int32 | `int64 | `complex64 | `string | `bool ] as 't Node.t -> [ `bool ] Node.t
val nthElement : ?name:string -> ?reverse:bool -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [ `int32 ] Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t
val oneHot : ?name:string -> ?axis:int -> ?control_inputs:Node.p list -> [< `int32 | `int64 ] as 'tI Node.t -> [ `int32 ] Node.t -> 't Node.t -> 't Node.t -> 't Node.t
val onesLike : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 | `complex64 | `bool ] as 't Node.t -> [< `float | `double | `int32 | `int64 | `complex64 | `bool ] as 't Node.t
val optimizeDataset : ?name:string -> output_types:Tensorflow.Node.Type.p list -> output_shapes:Tensorflow.Node.Dim.t list list -> ?control_inputs:Node.p list -> [ `variant ] Node.t -> [ `string ] Node.t -> [ `variant ] Node.t
val orderedMapClear : ?name:string -> ?capacity:int -> ?memory_limit:int -> dtypes:Tensorflow.Node.Type.p list -> ?container:string -> ?shared_name:string -> ?control_inputs:Node.p list -> unit -> [ `unit ] Node.t
val orderedMapIncompleteSize : ?name:string -> ?capacity:int -> ?memory_limit:int -> dtypes:Tensorflow.Node.Type.p list -> ?container:string -> ?shared_name:string -> ?control_inputs:Node.p list -> unit -> [ `int32 ] Node.t
val orderedMapSize : ?name:string -> ?capacity:int -> ?memory_limit:int -> dtypes:Tensorflow.Node.Type.p list -> ?container:string -> ?shared_name:string -> ?control_inputs:Node.p list -> unit -> [ `int32 ] Node.t
val pack : ?name:string -> ?axis:int -> ?control_inputs:Node.p list -> 't Node.t list -> 't Node.t
val pad : ?name:string -> ?control_inputs:Node.p list -> 't Node.t -> [< `int32 | `int64 ] as 'tpaddings Node.t -> 't Node.t
val padV2 : ?name:string -> ?control_inputs:Node.p list -> 't Node.t -> [< `int32 | `int64 ] as 'tpaddings Node.t -> 't Node.t -> 't Node.t
val paddingFIFOQueue : ?name:string -> component_types:Tensorflow.Node.Type.p list -> ?shapes:Tensorflow.Node.Dim.t list list -> ?capacity:int -> ?container:string -> ?shared_name:string -> ?control_inputs:Node.p list -> unit -> [ `string ] Node.t
val parallelConcat : ?name:string -> shape:Tensorflow.Node.Dim.t list -> ?control_inputs:Node.p list -> 't Node.t list -> 't Node.t
val parallelDynamicStitch : ?name:string -> ?control_inputs:Node.p list -> [ `int32 ] Node.t list -> 't Node.t list -> 't Node.t
val parameterizedTruncatedNormal : ?name:string -> ?seed:int -> ?seed2:int -> ?control_inputs:Node.p list -> [< `int32 | `int64 ] as 't Node.t -> [< `float | `double ] as 'dtype Node.t -> [< `float | `double ] as 'dtype Node.t -> [< `float | `double ] as 'dtype Node.t -> [< `float | `double ] as 'dtype Node.t -> [< `float | `double ] as 'dtype Node.t
val parseTensor : ?name:string -> type_:'out_type Tensorflow.Node.Type.t -> ?control_inputs:Node.p list -> [ `string ] Node.t -> 'out_type Node.t
val placeholderV2 : ?name:string -> type_:'dtype Tensorflow.Node.Type.t -> shape:Tensorflow.Node.Dim.t list -> ?control_inputs:Node.p list -> unit -> 'dtype Node.t
val placeholderWithDefault : ?name:string -> shape:Tensorflow.Node.Dim.t list -> ?control_inputs:Node.p list -> 'dtype Node.t -> 'dtype Node.t
val polygamma : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t
val pow : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 | `complex64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 | `complex64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 | `complex64 ] as 't Node.t
val prefetchDataset : ?name:string -> output_types:Tensorflow.Node.Type.p list -> output_shapes:Tensorflow.Node.Dim.t list list -> ?control_inputs:Node.p list -> [ `variant ] Node.t -> [ `int64 ] Node.t -> [ `variant ] Node.t
val preventGradient : ?name:string -> ?message:string -> ?control_inputs:Node.p list -> 't Node.t -> 't Node.t
val priorityQueue : ?name:string -> ?component_types:Tensorflow.Node.Type.p list -> shapes:Tensorflow.Node.Dim.t list list -> ?capacity:int -> ?container:string -> ?shared_name:string -> ?control_inputs:Node.p list -> unit -> [ `string ] Node.t
val prod : ?name:string -> ?keep_dims:bool -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `int32 | `int64 ] as 'tidx Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t
val qr : ?name:string -> ?full_matrices:bool -> ?control_inputs:Node.p list -> [< `double | `float | `complex64 ] as 't Node.t -> [< `double | `float | `complex64 ] as 't Node.t * [< `double | `float | `complex64 ] as 't Node.t
val quantizeAndDequantize : ?name:string -> ?signed_input:bool -> ?num_bits:int -> ?range_given:bool -> ?input_min:float -> ?input_max:float -> ?control_inputs:Node.p list -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t
val quantizeAndDequantizeV2 : ?name:string -> ?signed_input:bool -> ?num_bits:int -> ?range_given:bool -> ?control_inputs:Node.p list -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t
val quantizeAndDequantizeV3 : ?name:string -> ?signed_input:bool -> ?range_given:bool -> ?control_inputs:Node.p list -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t -> [ `int32 ] Node.t -> [< `float | `double ] as 't Node.t
val quantizeDownAndShrinkRange : ?name:string -> type_:'out_type Tensorflow.Node.Type.t -> ?control_inputs:Node.p list -> 'tinput Node.t -> [ `float ] Node.t -> [ `float ] Node.t -> 'out_type Node.t * [ `float ] Node.t * [ `float ] Node.t
val quantizeV2 : ?name:string -> type_:'t Tensorflow.Node.Type.t -> ?mode:string -> ?round_mode:string -> ?control_inputs:Node.p list -> [ `float ] Node.t -> [ `float ] Node.t -> [ `float ] Node.t -> 't Node.t * [ `float ] Node.t * [ `float ] Node.t
val quantizedAdd : ?name:string -> type_:'toutput Tensorflow.Node.Type.t -> ?control_inputs:Node.p list -> 't1 Node.t -> 't2 Node.t -> [ `float ] Node.t -> [ `float ] Node.t -> [ `float ] Node.t -> [ `float ] Node.t -> 'toutput Node.t * [ `float ] Node.t * [ `float ] Node.t
val quantizedAvgPool : ?name:string -> ksize:int list -> strides:int list -> padding:string -> ?control_inputs:Node.p list -> 't Node.t -> [ `float ] Node.t -> [ `float ] Node.t -> 't Node.t * [ `float ] Node.t * [ `float ] Node.t
val quantizedBatchNormWithGlobalNormalization : ?name:string -> type_:'out_type Tensorflow.Node.Type.t -> variance_epsilon:float -> scale_after_normalization:bool -> ?control_inputs:Node.p list -> 'tinput Node.t -> [ `float ] Node.t -> [ `float ] Node.t -> 'tinput Node.t -> [ `float ] Node.t -> [ `float ] Node.t -> 'tinput Node.t -> [ `float ] Node.t -> [ `float ] Node.t -> 'tinput Node.t -> [ `float ] Node.t -> [ `float ] Node.t -> 'tinput Node.t -> [ `float ] Node.t -> [ `float ] Node.t -> 'out_type Node.t * [ `float ] Node.t * [ `float ] Node.t
val quantizedBiasAdd : ?name:string -> type_:'out_type Tensorflow.Node.Type.t -> ?control_inputs:Node.p list -> 't1 Node.t -> 't2 Node.t -> [ `float ] Node.t -> [ `float ] Node.t -> [ `float ] Node.t -> [ `float ] Node.t -> 'out_type Node.t * [ `float ] Node.t * [ `float ] Node.t
val quantizedConcat : ?name:string -> ?control_inputs:Node.p list -> [ `int32 ] Node.t -> 't Node.t list -> [ `float ] Node.t list -> [ `float ] Node.t list -> 't Node.t * [ `float ] Node.t * [ `float ] Node.t
val quantizedConv2D : ?name:string -> type_:'out_type Tensorflow.Node.Type.t -> strides:int list -> padding:string -> ?dilations:int list -> ?control_inputs:Node.p list -> 'tinput Node.t -> 'tfilter Node.t -> [ `float ] Node.t -> [ `float ] Node.t -> [ `float ] Node.t -> [ `float ] Node.t -> 'out_type Node.t * [ `float ] Node.t * [ `float ] Node.t
val quantizedInstanceNorm : ?name:string -> ?output_range_given:bool -> ?given_y_min:float -> ?given_y_max:float -> ?variance_epsilon:float -> ?min_separation:float -> ?control_inputs:Node.p list -> 't Node.t -> [ `float ] Node.t -> [ `float ] Node.t -> 't Node.t * [ `float ] Node.t * [ `float ] Node.t
val quantizedMatMul : ?name:string -> type_:'toutput Tensorflow.Node.Type.t -> ?transpose_a:bool -> ?transpose_b:bool -> ?control_inputs:Node.p list -> 't1 Node.t -> 't2 Node.t -> [ `float ] Node.t -> [ `float ] Node.t -> [ `float ] Node.t -> [ `float ] Node.t -> 'toutput Node.t * [ `float ] Node.t * [ `float ] Node.t
val quantizedMaxPool : ?name:string -> ksize:int list -> strides:int list -> padding:string -> ?control_inputs:Node.p list -> 't Node.t -> [ `float ] Node.t -> [ `float ] Node.t -> 't Node.t * [ `float ] Node.t * [ `float ] Node.t
val quantizedMul : ?name:string -> type_:'toutput Tensorflow.Node.Type.t -> ?control_inputs:Node.p list -> 't1 Node.t -> 't2 Node.t -> [ `float ] Node.t -> [ `float ] Node.t -> [ `float ] Node.t -> [ `float ] Node.t -> 'toutput Node.t * [ `float ] Node.t * [ `float ] Node.t
val quantizedRelu : ?name:string -> type_:'out_type Tensorflow.Node.Type.t -> ?control_inputs:Node.p list -> 'tinput Node.t -> [ `float ] Node.t -> [ `float ] Node.t -> 'out_type Node.t * [ `float ] Node.t * [ `float ] Node.t
val quantizedRelu6 : ?name:string -> type_:'out_type Tensorflow.Node.Type.t -> ?control_inputs:Node.p list -> 'tinput Node.t -> [ `float ] Node.t -> [ `float ] Node.t -> 'out_type Node.t * [ `float ] Node.t * [ `float ] Node.t
val quantizedReluX : ?name:string -> type_:'out_type Tensorflow.Node.Type.t -> ?control_inputs:Node.p list -> 'tinput Node.t -> [ `float ] Node.t -> [ `float ] Node.t -> [ `float ] Node.t -> 'out_type Node.t * [ `float ] Node.t * [ `float ] Node.t
val quantizedReshape : ?name:string -> ?control_inputs:Node.p list -> 't Node.t -> [< `int32 | `int64 ] as 'tshape Node.t -> [ `float ] Node.t -> [ `float ] Node.t -> 't Node.t * [ `float ] Node.t * [ `float ] Node.t
val quantizedResizeBilinear : ?name:string -> ?align_corners:bool -> ?control_inputs:Node.p list -> [< `float ] as 't Node.t -> [ `int32 ] Node.t -> [ `float ] Node.t -> [ `float ] Node.t -> [< `float ] as 't Node.t * [ `float ] Node.t * [ `float ] Node.t
val queueClose : ?name:string -> ?cancel_pending_enqueues:bool -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `unit ] Node.t
val queueIsClosed : ?name:string -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `bool ] Node.t
val queueSize : ?name:string -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `int32 ] Node.t
val rFFT : ?name:string -> ?control_inputs:Node.p list -> [ `float ] Node.t -> [ `int32 ] Node.t -> [ `complex64 ] Node.t
val rFFT2D : ?name:string -> ?control_inputs:Node.p list -> [ `float ] Node.t -> [ `int32 ] Node.t -> [ `complex64 ] Node.t
val rFFT3D : ?name:string -> ?control_inputs:Node.p list -> [ `float ] Node.t -> [ `int32 ] Node.t -> [ `complex64 ] Node.t
val rGBToHSV : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t
val randomCrop : ?name:string -> ?seed:int -> ?seed2:int -> ?control_inputs:Node.p list -> [< `int32 | `int64 | `float | `double ] as 't Node.t -> [ `int64 ] Node.t -> [< `int32 | `int64 | `float | `double ] as 't Node.t
val randomDataset : ?name:string -> output_types:Tensorflow.Node.Type.p list -> output_shapes:Tensorflow.Node.Dim.t list list -> ?control_inputs:Node.p list -> [ `int64 ] Node.t -> [ `int64 ] Node.t -> [ `variant ] Node.t
val randomGamma : ?name:string -> ?seed:int -> ?seed2:int -> ?control_inputs:Node.p list -> [< `int32 | `int64 ] as 's Node.t -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t
val randomGammaGrad : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t
val randomPoisson : ?name:string -> ?seed:int -> ?seed2:int -> ?control_inputs:Node.p list -> [< `int32 | `int64 ] as 's Node.t -> [< `float | `double ] as 'dtype Node.t -> [< `float | `double ] as 'dtype Node.t
val randomPoissonV2 : ?name:string -> type_: [< `float | `double | `int32 | `int64 ] as 'dtype Tensorflow.Node.Type.t -> ?seed:int -> ?seed2:int -> ?control_inputs:Node.p list -> [< `int32 | `int64 ] as 's Node.t -> [< `float | `double | `int32 | `int64 ] as 'r Node.t -> [< `float | `double | `int32 | `int64 ] as 'dtype Node.t
val randomShuffle : ?name:string -> ?seed:int -> ?seed2:int -> ?control_inputs:Node.p list -> 't Node.t -> 't Node.t
val randomShuffleQueue : ?name:string -> component_types:Tensorflow.Node.Type.p list -> ?shapes:Tensorflow.Node.Dim.t list list -> ?capacity:int -> ?min_after_dequeue:int -> ?seed:int -> ?seed2:int -> ?container:string -> ?shared_name:string -> ?control_inputs:Node.p list -> unit -> [ `string ] Node.t
val randomStandardNormal : ?name:string -> type_:[< `float | `double ] as 'dtype Tensorflow.Node.Type.t -> ?seed:int -> ?seed2:int -> ?control_inputs:Node.p list -> [< `int32 | `int64 ] as 't Node.t -> [< `float | `double ] as 'dtype Node.t
val randomUniform : ?name:string -> type_:[< `float | `double ] as 'dtype Tensorflow.Node.Type.t -> ?seed:int -> ?seed2:int -> ?control_inputs:Node.p list -> [< `int32 | `int64 ] as 't Node.t -> [< `float | `double ] as 'dtype Node.t
val randomUniformInt : ?name:string -> ?seed:int -> ?seed2:int -> ?control_inputs:Node.p list -> [< `int32 | `int64 ] as 't Node.t -> [< `int32 | `int64 ] as 'tout Node.t -> [< `int32 | `int64 ] as 'tout Node.t -> [< `int32 | `int64 ] as 'tout Node.t
val rangeDataset : ?name:string -> output_types:Tensorflow.Node.Type.p list -> output_shapes:Tensorflow.Node.Dim.t list list -> ?control_inputs:Node.p list -> [ `int64 ] Node.t -> [ `int64 ] Node.t -> [ `int64 ] Node.t -> [ `variant ] Node.t
val rank : ?name:string -> ?control_inputs:Node.p list -> 't Node.t -> [ `int32 ] Node.t
val readFile : ?name:string -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `string ] Node.t
val readerNumRecordsProduced : ?name:string -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `int64 ] Node.t
val readerNumWorkUnitsCompleted : ?name:string -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `int64 ] Node.t
val readerRead : ?name:string -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `string ] Node.t -> [ `string ] Node.t * [ `string ] Node.t
val readerReadUpTo : ?name:string -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `string ] Node.t -> [ `int64 ] Node.t -> [ `string ] Node.t * [ `string ] Node.t
val readerReset : ?name:string -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `unit ] Node.t
val readerRestoreState : ?name:string -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `string ] Node.t -> [ `unit ] Node.t
val readerSerializeState : ?name:string -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `string ] Node.t
val real : ?name:string -> type_:[< `float | `double ] as 'tout Tensorflow.Node.Type.t -> ?control_inputs:Node.p list -> [< `complex64 ] as 't Node.t -> [< `float | `double ] as 'tout Node.t
val realDiv : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 | `complex64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 | `complex64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 | `complex64 ] as 't Node.t
val reciprocal : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 | `complex64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 | `complex64 ] as 't Node.t
val reciprocalGrad : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `complex64 ] as 't Node.t -> [< `float | `double | `complex64 ] as 't Node.t -> [< `float | `double | `complex64 ] as 't Node.t
val recordInput : ?name:string -> file_pattern:string -> ?file_random_seed:int -> ?file_shuffle_shift_ratio:float -> ?file_buffer_size:int -> ?file_parallelism:int -> ?batch_size:int -> ?compression_type:string -> ?control_inputs:Node.p list -> unit -> [ `string ] Node.t
val reduceJoin : ?name:string -> ?keep_dims:bool -> ?separator:string -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `int32 ] Node.t -> [ `string ] Node.t
val refEnter : ?name:string -> frame_name:string -> ?is_constant:bool -> ?parallel_iterations:int -> ?control_inputs:Node.p list -> 't Node.t -> 't Node.t
val refExit : ?name:string -> ?control_inputs:Node.p list -> 't Node.t -> 't Node.t
val refIdentity : ?name:string -> ?control_inputs:Node.p list -> 't Node.t -> 't Node.t
val refMerge : ?name:string -> ?control_inputs:Node.p list -> 't Node.t list -> 't Node.t * [ `int32 ] Node.t
val refNextIteration : ?name:string -> ?control_inputs:Node.p list -> 't Node.t -> 't Node.t
val refSelect : ?name:string -> ?control_inputs:Node.p list -> [ `int32 ] Node.t -> 't Node.t list -> 't Node.t
val refSwitch : ?name:string -> ?control_inputs:Node.p list -> 't Node.t -> [ `bool ] Node.t -> 't Node.t * 't Node.t
val regexFullMatch : ?name:string -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `string ] Node.t -> [ `bool ] Node.t
val regexReplace : ?name:string -> ?replace_global:bool -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `string ] Node.t -> [ `string ] Node.t -> [ `string ] Node.t
val relu : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t
val relu6 : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t
val relu6Grad : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t
val reluGrad : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t
val repeatDataset : ?name:string -> output_types:Tensorflow.Node.Type.p list -> output_shapes:Tensorflow.Node.Dim.t list list -> ?control_inputs:Node.p list -> [ `variant ] Node.t -> [ `int64 ] Node.t -> [ `variant ] Node.t
val requantizationRange : ?name:string -> ?control_inputs:Node.p list -> 'tinput Node.t -> [ `float ] Node.t -> [ `float ] Node.t -> [ `float ] Node.t * [ `float ] Node.t
val requantize : ?name:string -> type_:'out_type Tensorflow.Node.Type.t -> ?control_inputs:Node.p list -> 'tinput Node.t -> [ `float ] Node.t -> [ `float ] Node.t -> [ `float ] Node.t -> [ `float ] Node.t -> 'out_type Node.t * [ `float ] Node.t * [ `float ] Node.t
val reshape : ?name:string -> ?control_inputs:Node.p list -> 't Node.t -> [< `int32 | `int64 ] as 'tshape Node.t -> 't Node.t
val resizeArea : ?name:string -> ?align_corners:bool -> ?control_inputs:Node.p list -> [< `int32 | `int64 | `float | `double ] as 't Node.t -> [ `int32 ] Node.t -> [ `float ] Node.t
val resizeBicubic : ?name:string -> ?align_corners:bool -> ?control_inputs:Node.p list -> [< `int32 | `int64 | `float | `double ] as 't Node.t -> [ `int32 ] Node.t -> [ `float ] Node.t
val resizeBicubicGrad : ?name:string -> ?align_corners:bool -> ?control_inputs:Node.p list -> [ `float ] Node.t -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t
val resizeBilinear : ?name:string -> ?align_corners:bool -> ?control_inputs:Node.p list -> [< `int32 | `int64 | `float | `double ] as 't Node.t -> [ `int32 ] Node.t -> [ `float ] Node.t
val resizeBilinearGrad : ?name:string -> ?align_corners:bool -> ?control_inputs:Node.p list -> [ `float ] Node.t -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t
val resizeNearestNeighbor : ?name:string -> ?align_corners:bool -> ?control_inputs:Node.p list -> [< `int32 | `int64 | `float | `double ] as 't Node.t -> [ `int32 ] Node.t -> [< `int32 | `int64 | `float | `double ] as 't Node.t
val resizeNearestNeighborGrad : ?name:string -> ?align_corners:bool -> ?control_inputs:Node.p list -> [< `int32 | `float | `double ] as 't Node.t -> [ `int32 ] Node.t -> [< `int32 | `float | `double ] as 't Node.t
val restore : ?name:string -> type_:'dt Tensorflow.Node.Type.t -> ?preferred_shard:int -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `string ] Node.t -> 'dt Node.t
val restoreSlice : ?name:string -> type_:'dt Tensorflow.Node.Type.t -> ?preferred_shard:int -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `string ] Node.t -> [ `string ] Node.t -> 'dt Node.t
val reverse : ?name:string -> ?control_inputs:Node.p list -> [< `int32 | `int64 | `bool | `float | `double | `complex64 | `string ] as 't Node.t -> [ `bool ] Node.t -> [< `int32 | `int64 | `bool | `float | `double | `complex64 | `string ] as 't Node.t
val reverseSequence : ?name:string -> seq_dim:int -> ?batch_dim:int -> ?control_inputs:Node.p list -> 't Node.t -> [< `int32 | `int64 ] as 'tlen Node.t -> 't Node.t
val reverseV2 : ?name:string -> ?control_inputs:Node.p list -> [< `int32 | `int64 | `bool | `float | `double | `complex64 | `string ] as 't Node.t -> [< `int32 | `int64 ] as 'tidx Node.t -> [< `int32 | `int64 | `bool | `float | `double | `complex64 | `string ] as 't Node.t
val rightShift : ?name:string -> ?control_inputs:Node.p list -> [< `int32 | `int64 ] as 't Node.t -> [< `int32 | `int64 ] as 't Node.t -> [< `int32 | `int64 ] as 't Node.t
val rint : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t
val roll : ?name:string -> ?control_inputs:Node.p list -> 't Node.t -> [< `int32 | `int64 ] as 'tshift Node.t -> [< `int32 | `int64 ] as 'taxis Node.t -> 't Node.t
val round : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 | `complex64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 | `complex64 ] as 't Node.t
val rpc : ?name:string -> ?protocol:string -> ?fail_fast:bool -> ?timeout_in_ms:int -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `string ] Node.t -> [ `string ] Node.t -> [ `string ] Node.t
val rsqrt : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `complex64 ] as 't Node.t -> [< `float | `double | `complex64 ] as 't Node.t
val rsqrtGrad : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `complex64 ] as 't Node.t -> [< `float | `double | `complex64 ] as 't Node.t -> [< `float | `double | `complex64 ] as 't Node.t
val sampleDistortedBoundingBox : ?name:string -> ?seed:int -> ?seed2:int -> ?min_object_covered:float -> ?aspect_ratio_range:float list -> ?area_range:float list -> ?max_attempts:int -> ?use_image_if_no_bounding_boxes:bool -> ?control_inputs:Node.p list -> [< `int32 | `int64 ] as 't Node.t -> [ `float ] Node.t -> [< `int32 | `int64 ] as 't Node.t * [< `int32 | `int64 ] as 't Node.t * [ `float ] Node.t
val sampleDistortedBoundingBoxV2 : ?name:string -> ?seed:int -> ?seed2:int -> ?aspect_ratio_range:float list -> ?area_range:float list -> ?max_attempts:int -> ?use_image_if_no_bounding_boxes:bool -> ?control_inputs:Node.p list -> [< `int32 | `int64 ] as 't Node.t -> [ `float ] Node.t -> [ `float ] Node.t -> [< `int32 | `int64 ] as 't Node.t * [< `int32 | `int64 ] as 't Node.t * [ `float ] Node.t
val scalarSummary : ?name:string -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [ `string ] Node.t
val scatterAdd : ?name:string -> ?use_locking:bool -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `int32 | `int64 ] as 'tindices Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t
val scatterDiv : ?name:string -> ?use_locking:bool -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `int32 | `int64 ] as 'tindices Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t
val scatterMax : ?name:string -> ?use_locking:bool -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [< `int32 | `int64 ] as 'tindices Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t
val scatterMin : ?name:string -> ?use_locking:bool -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [< `int32 | `int64 ] as 'tindices Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t
val scatterMul : ?name:string -> ?use_locking:bool -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `int32 | `int64 ] as 'tindices Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t
val scatterNd : ?name:string -> ?control_inputs:Node.p list -> [< `int32 | `int64 ] as 'tindices Node.t -> 't Node.t -> [< `int32 | `int64 ] as 'tindices Node.t -> 't Node.t
val scatterNdAdd : ?name:string -> ?use_locking:bool -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `int32 | `int64 ] as 'tindices Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t
val scatterNdNonAliasingAdd : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `int32 | `int64 ] as 'tindices Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t
val scatterNdSub : ?name:string -> ?use_locking:bool -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `int32 | `int64 ] as 'tindices Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t
val scatterNdUpdate : ?name:string -> ?use_locking:bool -> ?control_inputs:Node.p list -> 't Node.t -> [< `int32 | `int64 ] as 'tindices Node.t -> 't Node.t -> 't Node.t
val scatterSub : ?name:string -> ?use_locking:bool -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `int32 | `int64 ] as 'tindices Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t
val scatterUpdate : ?name:string -> ?use_locking:bool -> ?control_inputs:Node.p list -> 't Node.t -> [< `int32 | `int64 ] as 'tindices Node.t -> 't Node.t -> 't Node.t
val sdcaFprint : ?name:string -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `int64 ] Node.t
val sdcaShrinkL1 : ?name:string -> l1:float -> l2:float -> ?control_inputs:Node.p list -> [ `float ] Node.t list -> [ `unit ] Node.t
val segmentMax : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [< `int32 | `int64 ] as 'tindices Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t
val segmentMean : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `int32 | `int64 ] as 'tindices Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t
val segmentMin : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [< `int32 | `int64 ] as 'tindices Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t
val segmentProd : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `int32 | `int64 ] as 'tindices Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t
val segmentSum : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `int32 | `int64 ] as 'tindices Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t
val select : ?name:string -> ?control_inputs:Node.p list -> [ `bool ] Node.t -> 't Node.t -> 't Node.t -> 't Node.t
val selfAdjointEig : ?name:string -> ?control_inputs:Node.p list -> [< `double | `float ] as 't Node.t -> [< `double | `float ] as 't Node.t
val selfAdjointEigV2 : ?name:string -> ?compute_v:bool -> ?control_inputs:Node.p list -> [< `double | `float | `complex64 ] as 't Node.t -> [< `double | `float | `complex64 ] as 't Node.t * [< `double | `float | `complex64 ] as 't Node.t
val selu : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t
val seluGrad : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t
val serializeManySparse : ?name:string -> type_:[< `string | `variant ] as 'out_type Tensorflow.Node.Type.t -> ?control_inputs:Node.p list -> [ `int64 ] Node.t -> 't Node.t -> [ `int64 ] Node.t -> [< `string | `variant ] as 'out_type Node.t
val serializeSparse : ?name:string -> type_:[< `string | `variant ] as 'out_type Tensorflow.Node.Type.t -> ?control_inputs:Node.p list -> [ `int64 ] Node.t -> 't Node.t -> [ `int64 ] Node.t -> [< `string | `variant ] as 'out_type Node.t
val serializeTensor : ?name:string -> ?control_inputs:Node.p list -> 't Node.t -> [ `string ] Node.t
val setSize : ?name:string -> ?validate_indices:bool -> ?control_inputs:Node.p list -> [ `int64 ] Node.t -> [< `int32 | `int64 | `string ] as 't Node.t -> [ `int64 ] Node.t -> [ `int32 ] Node.t
val shape : ?name:string -> type_:[< `int32 | `int64 ] as 'out_type Tensorflow.Node.Type.t -> ?control_inputs:Node.p list -> 't Node.t -> [< `int32 | `int64 ] as 'out_type Node.t
val shapeN : ?name:string -> type_:[< `int32 | `int64 ] as 'out_type Tensorflow.Node.Type.t -> ?control_inputs:Node.p list -> 't Node.t list -> [< `int32 | `int64 ] as 'out_type Node.t list
val shardedFilename : ?name:string -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `int32 ] Node.t -> [ `int32 ] Node.t -> [ `string ] Node.t
val shardedFilespec : ?name:string -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `int32 ] Node.t -> [ `string ] Node.t
val shuffleAndRepeatDataset : ?name:string -> output_types:Tensorflow.Node.Type.p list -> output_shapes:Tensorflow.Node.Dim.t list list -> ?control_inputs:Node.p list -> [ `variant ] Node.t -> [ `int64 ] Node.t -> [ `int64 ] Node.t -> [ `int64 ] Node.t -> [ `int64 ] Node.t -> [ `variant ] Node.t
val shuffleDataset : ?name:string -> ?reshuffle_each_iteration:bool -> output_types:Tensorflow.Node.Type.p list -> output_shapes:Tensorflow.Node.Dim.t list list -> ?control_inputs:Node.p list -> [ `variant ] Node.t -> [ `int64 ] Node.t -> [ `int64 ] Node.t -> [ `int64 ] Node.t -> [ `variant ] Node.t
val sigmoid : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `complex64 ] as 't Node.t -> [< `float | `double | `complex64 ] as 't Node.t
val sigmoidGrad : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `complex64 ] as 't Node.t -> [< `float | `double | `complex64 ] as 't Node.t -> [< `float | `double | `complex64 ] as 't Node.t
val sign : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 | `complex64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 | `complex64 ] as 't Node.t
val sin : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `complex64 ] as 't Node.t -> [< `float | `double | `complex64 ] as 't Node.t
val sinh : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `complex64 ] as 't Node.t -> [< `float | `double | `complex64 ] as 't Node.t
val sinkDataset : ?name:string -> ?control_inputs:Node.p list -> [ `variant ] Node.t -> [ `variant ] Node.t
val size : ?name:string -> type_:[< `int32 | `int64 ] as 'out_type Tensorflow.Node.Type.t -> ?control_inputs:Node.p list -> 't Node.t -> [< `int32 | `int64 ] as 'out_type Node.t
val skipDataset : ?name:string -> output_types:Tensorflow.Node.Type.p list -> output_shapes:Tensorflow.Node.Dim.t list list -> ?control_inputs:Node.p list -> [ `variant ] Node.t -> [ `int64 ] Node.t -> [ `variant ] Node.t
val skipgram : ?name:string -> filename:string -> batch_size:int -> ?window_size:int -> ?min_count:int -> ?subsample:float -> ?control_inputs:Node.p list -> unit -> [ `string ] Node.t * [ `int32 ] Node.t * [ `int64 ] Node.t * [ `int32 ] Node.t * [ `int64 ] Node.t * [ `int32 ] Node.t * [ `int32 ] Node.t
val slice : ?name:string -> ?control_inputs:Node.p list -> 't Node.t -> [< `int32 | `int64 ] as 'index Node.t -> [< `int32 | `int64 ] as 'index Node.t -> 't Node.t
val slideDataset : ?name:string -> output_types:Tensorflow.Node.Type.p list -> output_shapes:Tensorflow.Node.Dim.t list list -> ?control_inputs:Node.p list -> [ `variant ] Node.t -> [ `int64 ] Node.t -> [ `int64 ] Node.t -> [ `variant ] Node.t
val snapshot : ?name:string -> ?control_inputs:Node.p list -> 't Node.t -> 't Node.t
val softmax : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t
val softmaxCrossEntropyWithLogits : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t * [< `float | `double ] as 't Node.t
val softplus : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t
val softplusGrad : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t
val softsign : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t
val softsignGrad : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t
val spaceToBatch : ?name:string -> block_size:int -> ?control_inputs:Node.p list -> 't Node.t -> [< `int32 | `int64 ] as 'tpaddings Node.t -> 't Node.t
val spaceToBatchND : ?name:string -> ?control_inputs:Node.p list -> 't Node.t -> [< `int32 | `int64 ] as 'tblock_shape Node.t -> [< `int32 | `int64 ] as 'tpaddings Node.t -> 't Node.t
val spaceToDepth : ?name:string -> block_size:int -> ?data_format:string -> ?control_inputs:Node.p list -> 't Node.t -> 't Node.t
val sparseAccumulatorApplyGradient : ?name:string -> has_known_shape:bool -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `int64 ] Node.t -> [ `int64 ] Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 'dtype Node.t -> [ `int64 ] Node.t -> [ `unit ] Node.t
val sparseAccumulatorTakeGradient : ?name:string -> type_1: [< `float | `double | `int32 | `complex64 | `int64 ] as 'dtype Tensorflow.Node.Type.t -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `int32 ] Node.t -> [ `int64 ] Node.t * [< `float | `double | `int32 | `complex64 | `int64 ] as 'dtype Node.t * [ `int64 ] Node.t
val sparseAdd : ?name:string -> ?control_inputs:Node.p list -> [ `int64 ] Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [ `int64 ] Node.t -> [ `int64 ] Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [ `int64 ] Node.t -> [< `float | `double | `int32 | `int64 ] as 'treal Node.t -> [ `int64 ] Node.t * [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t * [ `int64 ] Node.t
val sparseAddGrad : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [ `int64 ] Node.t -> [ `int64 ] Node.t -> [ `int64 ] Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t * [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t
val sparseApplyAdadelta : ?name:string -> ?use_locking:bool -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `int32 | `int64 ] as 'tindices Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t
val sparseApplyAdagrad : ?name:string -> ?use_locking:bool -> ?update_slots:bool -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `int32 | `int64 ] as 'tindices Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t
val sparseApplyAdagradDA : ?name:string -> ?use_locking:bool -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `int32 | `int64 ] as 'tindices Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [ `int64 ] Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t
val sparseApplyCenteredRMSProp : ?name:string -> ?use_locking:bool -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `int32 | `int64 ] as 'tindices Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t
val sparseApplyFtrl : ?name:string -> ?use_locking:bool -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `int32 | `int64 ] as 'tindices Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t
val sparseApplyFtrlV2 : ?name:string -> ?use_locking:bool -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `int32 | `int64 ] as 'tindices Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t
val sparseApplyMomentum : ?name:string -> ?use_locking:bool -> ?use_nesterov:bool -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `int32 | `int64 ] as 'tindices Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t
val sparseApplyProximalAdagrad : ?name:string -> ?use_locking:bool -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `int32 | `int64 ] as 'tindices Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t
val sparseApplyProximalGradientDescent : ?name:string -> ?use_locking:bool -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `int32 | `int64 ] as 'tindices Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t
val sparseApplyRMSProp : ?name:string -> ?use_locking:bool -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `int32 | `int64 ] as 'tindices Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t
val sparseConcat : ?name:string -> concat_dim:int -> ?control_inputs:Node.p list -> [ `int64 ] Node.t list -> 't Node.t list -> [ `int64 ] Node.t list -> [ `int64 ] Node.t * 't Node.t * [ `int64 ] Node.t
val sparseConditionalAccumulator : ?name:string -> shape:Tensorflow.Node.Dim.t list -> ?container:string -> ?shared_name:string -> ?control_inputs:Node.p list -> unit -> [ `string ] Node.t
val sparseDenseCwiseAdd : ?name:string -> ?control_inputs:Node.p list -> [ `int64 ] Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [ `int64 ] Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t
val sparseDenseCwiseDiv : ?name:string -> ?control_inputs:Node.p list -> [ `int64 ] Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [ `int64 ] Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t
val sparseDenseCwiseMul : ?name:string -> ?control_inputs:Node.p list -> [ `int64 ] Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [ `int64 ] Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t
val sparseFillEmptyRows : ?name:string -> ?control_inputs:Node.p list -> [ `int64 ] Node.t -> 't Node.t -> [ `int64 ] Node.t -> 't Node.t -> [ `int64 ] Node.t * 't Node.t * [ `bool ] Node.t * [ `int64 ] Node.t
val sparseFillEmptyRowsGrad : ?name:string -> ?control_inputs:Node.p list -> [ `int64 ] Node.t -> 't Node.t -> 't Node.t * 't Node.t
val sparseMatMul : ?name:string -> ?transpose_a:bool -> ?transpose_b:bool -> ?a_is_sparse:bool -> ?b_is_sparse:bool -> ?control_inputs:Node.p list -> [< `float ] as 'ta Node.t -> [< `float ] as 'tb Node.t -> [ `float ] Node.t
val sparseReduceMax : ?name:string -> ?keep_dims:bool -> ?control_inputs:Node.p list -> [ `int64 ] Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [ `int64 ] Node.t -> [ `int32 ] Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t
val sparseReduceMaxSparse : ?name:string -> ?keep_dims:bool -> ?control_inputs:Node.p list -> [ `int64 ] Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [ `int64 ] Node.t -> [ `int32 ] Node.t -> [ `int64 ] Node.t * [< `float | `double | `int32 | `int64 ] as 't Node.t * [ `int64 ] Node.t
val sparseReduceSum : ?name:string -> ?keep_dims:bool -> ?control_inputs:Node.p list -> [ `int64 ] Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [ `int64 ] Node.t -> [ `int32 ] Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t
val sparseReduceSumSparse : ?name:string -> ?keep_dims:bool -> ?control_inputs:Node.p list -> [ `int64 ] Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [ `int64 ] Node.t -> [ `int32 ] Node.t -> [ `int64 ] Node.t * [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t * [ `int64 ] Node.t
val sparseReorder : ?name:string -> ?control_inputs:Node.p list -> [ `int64 ] Node.t -> 't Node.t -> [ `int64 ] Node.t -> [ `int64 ] Node.t * 't Node.t
val sparseReshape : ?name:string -> ?control_inputs:Node.p list -> [ `int64 ] Node.t -> [ `int64 ] Node.t -> [ `int64 ] Node.t -> [ `int64 ] Node.t * [ `int64 ] Node.t
val sparseSegmentMean : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double ] as 't Node.t -> [< `int32 | `int64 ] as 'tidx Node.t -> [ `int32 ] Node.t -> [< `float | `double ] as 't Node.t
val sparseSegmentMeanGrad : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double ] as 't Node.t -> [< `int32 | `int64 ] as 'tidx Node.t -> [ `int32 ] Node.t -> [ `int32 ] Node.t -> [< `float | `double ] as 't Node.t
val sparseSegmentMeanWithNumSegments : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double ] as 't Node.t -> [< `int32 | `int64 ] as 'tidx Node.t -> [ `int32 ] Node.t -> [< `int32 | `int64 ] as 'tnumsegments Node.t -> [< `float | `double ] as 't Node.t
val sparseSegmentSqrtN : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double ] as 't Node.t -> [< `int32 | `int64 ] as 'tidx Node.t -> [ `int32 ] Node.t -> [< `float | `double ] as 't Node.t
val sparseSegmentSqrtNGrad : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double ] as 't Node.t -> [< `int32 | `int64 ] as 'tidx Node.t -> [ `int32 ] Node.t -> [ `int32 ] Node.t -> [< `float | `double ] as 't Node.t
val sparseSegmentSqrtNWithNumSegments : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double ] as 't Node.t -> [< `int32 | `int64 ] as 'tidx Node.t -> [ `int32 ] Node.t -> [< `int32 | `int64 ] as 'tnumsegments Node.t -> [< `float | `double ] as 't Node.t
val sparseSegmentSum : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [< `int32 | `int64 ] as 'tidx Node.t -> [ `int32 ] Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t
val sparseSegmentSumWithNumSegments : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [< `int32 | `int64 ] as 'tidx Node.t -> [ `int32 ] Node.t -> [< `int32 | `int64 ] as 'tnumsegments Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t
val sparseSlice : ?name:string -> ?control_inputs:Node.p list -> [ `int64 ] Node.t -> 't Node.t -> [ `int64 ] Node.t -> [ `int64 ] Node.t -> [ `int64 ] Node.t -> [ `int64 ] Node.t * 't Node.t * [ `int64 ] Node.t
val sparseSliceGrad : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [ `int64 ] Node.t -> [ `int64 ] Node.t -> [ `int64 ] Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t
val sparseSoftmax : ?name:string -> ?control_inputs:Node.p list -> [ `int64 ] Node.t -> [< `float | `double ] as 't Node.t -> [ `int64 ] Node.t -> [< `float | `double ] as 't Node.t
val sparseSoftmaxCrossEntropyWithLogits : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double ] as 't Node.t -> [< `int32 | `int64 ] as 'tlabels Node.t -> [< `float | `double ] as 't Node.t * [< `float | `double ] as 't Node.t
val sparseSparseMaximum : ?name:string -> ?control_inputs:Node.p list -> [ `int64 ] Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [ `int64 ] Node.t -> [ `int64 ] Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [ `int64 ] Node.t -> [ `int64 ] Node.t * [< `float | `double | `int32 | `int64 ] as 't Node.t
val sparseSparseMinimum : ?name:string -> ?control_inputs:Node.p list -> [ `int64 ] Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [ `int64 ] Node.t -> [ `int64 ] Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [ `int64 ] Node.t -> [ `int64 ] Node.t * [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t
val sparseTensorDenseAdd : ?name:string -> ?control_inputs:Node.p list -> [< `int32 | `int64 ] as 'tindices Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `int32 | `int64 ] as 'tindices Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t
val sparseTensorDenseMatMul : ?name:string -> ?adjoint_a:bool -> ?adjoint_b:bool -> ?control_inputs:Node.p list -> [< `int32 | `int64 ] as 'tindices Node.t -> 't Node.t -> [ `int64 ] Node.t -> 't Node.t -> 't Node.t
val sparseTensorSliceDataset : ?name:string -> ?control_inputs:Node.p list -> [ `int64 ] Node.t -> 'tvalues Node.t -> [ `int64 ] Node.t -> [ `variant ] Node.t
val sparseToDense : ?name:string -> ?validate_indices:bool -> ?control_inputs:Node.p list -> [< `int32 | `int64 ] as 'tindices Node.t -> [< `int32 | `int64 ] as 'tindices Node.t -> 't Node.t -> 't Node.t -> 't Node.t
val sparseToSparseSetOperation : ?name:string -> set_operation:string -> ?validate_indices:bool -> ?control_inputs:Node.p list -> [ `int64 ] Node.t -> [< `int32 | `int64 | `string ] as 't Node.t -> [ `int64 ] Node.t -> [ `int64 ] Node.t -> [< `int32 | `int64 | `string ] as 't Node.t -> [ `int64 ] Node.t -> [ `int64 ] Node.t * [< `int32 | `int64 | `string ] as 't Node.t * [ `int64 ] Node.t
val split : ?name:string -> num_split:int -> ?control_inputs:Node.p list -> [ `int32 ] Node.t -> 't Node.t -> 't Node.t list
val splitV : ?name:string -> num_split:int -> ?control_inputs:Node.p list -> 't Node.t -> [< `int32 | `int64 ] as 'tlen Node.t -> [ `int32 ] Node.t -> 't Node.t list
val sqlDataset : ?name:string -> output_types:Tensorflow.Node.Type.p list -> output_shapes:Tensorflow.Node.Dim.t list list -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `string ] Node.t -> [ `string ] Node.t -> [ `variant ] Node.t
val sqrt : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `complex64 ] as 't Node.t -> [< `float | `double | `complex64 ] as 't Node.t
val sqrtGrad : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `complex64 ] as 't Node.t -> [< `float | `double | `complex64 ] as 't Node.t -> [< `float | `double | `complex64 ] as 't Node.t
val square : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 | `complex64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 | `complex64 ] as 't Node.t
val squaredDifference : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 | `complex64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 | `complex64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 | `complex64 ] as 't Node.t
val squeeze : ?name:string -> ?squeeze_dims:int list -> ?control_inputs:Node.p list -> 't Node.t -> 't Node.t
val stack : ?name:string -> ?stack_name:string -> ?control_inputs:Node.p list -> unit -> [ `string ] Node.t
val stackClose : ?name:string -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `unit ] Node.t
val stackPop : ?name:string -> type_:'elem_type Tensorflow.Node.Type.t -> ?control_inputs:Node.p list -> [ `string ] Node.t -> 'elem_type Node.t
val stackPush : ?name:string -> ?swap_memory:bool -> ?control_inputs:Node.p list -> [ `string ] Node.t -> 't Node.t -> 't Node.t
val stageClear : ?name:string -> ?capacity:int -> ?memory_limit:int -> dtypes:Tensorflow.Node.Type.p list -> ?container:string -> ?shared_name:string -> ?control_inputs:Node.p list -> unit -> [ `unit ] Node.t
val stageSize : ?name:string -> ?capacity:int -> ?memory_limit:int -> dtypes:Tensorflow.Node.Type.p list -> ?container:string -> ?shared_name:string -> ?control_inputs:Node.p list -> unit -> [ `int32 ] Node.t
val statelessMultinomial : ?name:string -> type_:[< `int32 | `int64 ] as 'output_dtype Tensorflow.Node.Type.t -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [ `int32 ] Node.t -> [< `int32 | `int64 ] as 'tseed Node.t -> [< `int32 | `int64 ] as 'output_dtype Node.t
val statelessRandomNormal : ?name:string -> type_:[< `float | `double ] as 'dtype Tensorflow.Node.Type.t -> ?control_inputs:Node.p list -> [< `int32 | `int64 ] as 't Node.t -> [< `int32 | `int64 ] as 'tseed Node.t -> [< `float | `double ] as 'dtype Node.t
val statelessRandomUniform : ?name:string -> type_:[< `float | `double ] as 'dtype Tensorflow.Node.Type.t -> ?control_inputs:Node.p list -> [< `int32 | `int64 ] as 't Node.t -> [< `int32 | `int64 ] as 'tseed Node.t -> [< `float | `double ] as 'dtype Node.t
val statelessTruncatedNormal : ?name:string -> type_:[< `float | `double ] as 'dtype Tensorflow.Node.Type.t -> ?control_inputs:Node.p list -> [< `int32 | `int64 ] as 't Node.t -> [< `int32 | `int64 ] as 'tseed Node.t -> [< `float | `double ] as 'dtype Node.t
val stopGradient : ?name:string -> ?control_inputs:Node.p list -> 't Node.t -> 't Node.t
val stridedSlice : ?name:string -> ?begin_mask:int -> ?end_mask:int -> ?ellipsis_mask:int -> ?new_axis_mask:int -> ?shrink_axis_mask:int -> ?control_inputs:Node.p list -> 't Node.t -> [< `int32 | `int64 ] as 'index Node.t -> [< `int32 | `int64 ] as 'index Node.t -> [< `int32 | `int64 ] as 'index Node.t -> 't Node.t
val stridedSliceAssign : ?name:string -> ?begin_mask:int -> ?end_mask:int -> ?ellipsis_mask:int -> ?new_axis_mask:int -> ?shrink_axis_mask:int -> ?control_inputs:Node.p list -> 't Node.t -> [< `int32 | `int64 ] as 'index Node.t -> [< `int32 | `int64 ] as 'index Node.t -> [< `int32 | `int64 ] as 'index Node.t -> 't Node.t -> 't Node.t
val stridedSliceGrad : ?name:string -> ?begin_mask:int -> ?end_mask:int -> ?ellipsis_mask:int -> ?new_axis_mask:int -> ?shrink_axis_mask:int -> ?control_inputs:Node.p list -> [< `int32 | `int64 ] as 'index Node.t -> [< `int32 | `int64 ] as 'index Node.t -> [< `int32 | `int64 ] as 'index Node.t -> [< `int32 | `int64 ] as 'index Node.t -> 't Node.t -> 't Node.t
val stringJoin : ?name:string -> ?separator:string -> ?control_inputs:Node.p list -> [ `string ] Node.t list -> [ `string ] Node.t
val stringSplit : ?name:string -> ?skip_empty:bool -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `string ] Node.t -> [ `int64 ] Node.t * [ `string ] Node.t * [ `int64 ] Node.t
val stringSplitV2 : ?name:string -> ?maxsplit:int -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `string ] Node.t -> [ `int64 ] Node.t * [ `string ] Node.t * [ `int64 ] Node.t
val stringStrip : ?name:string -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `string ] Node.t
val stringToHashBucket : ?name:string -> num_buckets:int -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `int64 ] Node.t
val stringToHashBucketFast : ?name:string -> num_buckets:int -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `int64 ] Node.t
val stringToHashBucketStrong : ?name:string -> num_buckets:int -> key:int list -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `int64 ] Node.t
val stringToNumber : ?name:string -> type_: [< `float | `double | `int32 | `int64 ] as 'out_type Tensorflow.Node.Type.t -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [< `float | `double | `int32 | `int64 ] as 'out_type Node.t
val sub : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 | `complex64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 | `complex64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 | `complex64 ] as 't Node.t
val substr : ?name:string -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [< `int32 | `int64 ] as 't Node.t -> [< `int32 | `int64 ] as 't Node.t -> [ `string ] Node.t
val sum : ?name:string -> ?keep_dims:bool -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `int32 | `int64 ] as 'tidx Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t
val svd : ?name:string -> ?compute_uv:bool -> ?full_matrices:bool -> ?control_inputs:Node.p list -> [< `double | `float | `complex64 ] as 't Node.t -> [< `double | `float | `complex64 ] as 't Node.t * [< `double | `float | `complex64 ] as 't Node.t * [< `double | `float | `complex64 ] as 't Node.t
val switch : ?name:string -> ?control_inputs:Node.p list -> 't Node.t -> [ `bool ] Node.t -> 't Node.t * 't Node.t
val tFRecordDataset : ?name:string -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `string ] Node.t -> [ `int64 ] Node.t -> [ `variant ] Node.t
val tFRecordReader : ?name:string -> ?container:string -> ?shared_name:string -> ?compression_type:string -> ?control_inputs:Node.p list -> unit -> [ `string ] Node.t
val takeDataset : ?name:string -> output_types:Tensorflow.Node.Type.p list -> output_shapes:Tensorflow.Node.Dim.t list list -> ?control_inputs:Node.p list -> [ `variant ] Node.t -> [ `int64 ] Node.t -> [ `variant ] Node.t
val takeManySparseFromTensorsMap : ?name:string -> type_1:'dtype Tensorflow.Node.Type.t -> ?container:string -> ?shared_name:string -> ?control_inputs:Node.p list -> [ `int64 ] Node.t -> [ `int64 ] Node.t * 'dtype Node.t * [ `int64 ] Node.t
val tan : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 | `complex64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 | `complex64 ] as 't Node.t
val tanh : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `complex64 ] as 't Node.t -> [< `float | `double | `complex64 ] as 't Node.t
val tanhGrad : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `complex64 ] as 't Node.t -> [< `float | `double | `complex64 ] as 't Node.t -> [< `float | `double | `complex64 ] as 't Node.t
val temporaryVariable : ?name:string -> type_:'dtype Tensorflow.Node.Type.t -> shape:Tensorflow.Node.Dim.t list -> ?var_name:string -> ?control_inputs:Node.p list -> unit -> 'dtype Node.t
val tensorArray : ?name:string -> ?dynamic_size:bool -> ?clear_after_read:bool -> ?tensor_array_name:string -> ?element_shape:Tensorflow.Node.Dim.t list -> ?control_inputs:Node.p list -> [ `int32 ] Node.t -> [ `string ] Node.t
val tensorArrayClose : ?name:string -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `unit ] Node.t
val tensorArrayCloseV2 : ?name:string -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `unit ] Node.t
val tensorArrayConcat : ?name:string -> type_:'dtype Tensorflow.Node.Type.t -> ?element_shape_except0:Tensorflow.Node.Dim.t list -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `float ] Node.t -> 'dtype Node.t * [ `int64 ] Node.t
val tensorArrayConcatV2 : ?name:string -> type_:'dtype Tensorflow.Node.Type.t -> ?element_shape_except0:Tensorflow.Node.Dim.t list -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `float ] Node.t -> 'dtype Node.t * [ `int64 ] Node.t
val tensorArrayGather : ?name:string -> type_:'dtype Tensorflow.Node.Type.t -> ?element_shape:Tensorflow.Node.Dim.t list -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `int32 ] Node.t -> [ `float ] Node.t -> 'dtype Node.t
val tensorArrayGatherV2 : ?name:string -> type_:'dtype Tensorflow.Node.Type.t -> ?element_shape:Tensorflow.Node.Dim.t list -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `int32 ] Node.t -> [ `float ] Node.t -> 'dtype Node.t
val tensorArrayGrad : ?name:string -> source:string -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `float ] Node.t -> [ `string ] Node.t
val tensorArrayGradV2 : ?name:string -> source:string -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `float ] Node.t -> [ `string ] Node.t
val tensorArrayPack : ?name:string -> type_:'dtype Tensorflow.Node.Type.t -> ?element_shape:Tensorflow.Node.Dim.t list -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `float ] Node.t -> 'dtype Node.t
val tensorArrayRead : ?name:string -> type_:'dtype Tensorflow.Node.Type.t -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `int32 ] Node.t -> [ `float ] Node.t -> 'dtype Node.t
val tensorArrayReadV2 : ?name:string -> type_:'dtype Tensorflow.Node.Type.t -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `int32 ] Node.t -> [ `float ] Node.t -> 'dtype Node.t
val tensorArrayScatter : ?name:string -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `int32 ] Node.t -> 't Node.t -> [ `float ] Node.t -> [ `float ] Node.t
val tensorArrayScatterV2 : ?name:string -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `int32 ] Node.t -> 't Node.t -> [ `float ] Node.t -> [ `float ] Node.t
val tensorArraySize : ?name:string -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `float ] Node.t -> [ `int32 ] Node.t
val tensorArraySizeV2 : ?name:string -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `float ] Node.t -> [ `int32 ] Node.t
val tensorArraySplit : ?name:string -> ?control_inputs:Node.p list -> [ `string ] Node.t -> 't Node.t -> [ `int64 ] Node.t -> [ `float ] Node.t -> [ `float ] Node.t
val tensorArraySplitV2 : ?name:string -> ?control_inputs:Node.p list -> [ `string ] Node.t -> 't Node.t -> [ `int64 ] Node.t -> [ `float ] Node.t -> [ `float ] Node.t
val tensorArrayUnpack : ?name:string -> ?control_inputs:Node.p list -> [ `string ] Node.t -> 't Node.t -> [ `float ] Node.t -> [ `float ] Node.t
val tensorArrayV2 : ?name:string -> ?element_shape:Tensorflow.Node.Dim.t list -> ?dynamic_size:bool -> ?clear_after_read:bool -> ?tensor_array_name:string -> ?control_inputs:Node.p list -> [ `int32 ] Node.t -> [ `string ] Node.t
val tensorArrayWrite : ?name:string -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `int32 ] Node.t -> 't Node.t -> [ `float ] Node.t -> [ `float ] Node.t
val tensorArrayWriteV2 : ?name:string -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `int32 ] Node.t -> 't Node.t -> [ `float ] Node.t -> [ `float ] Node.t
val tensorListConcatLists : ?name:string -> ?control_inputs:Node.p list -> [ `variant ] Node.t -> [ `variant ] Node.t -> [ `variant ] Node.t
val tensorListElementShape : ?name:string -> type_:[< `int32 | `int64 ] as 'shape_type Tensorflow.Node.Type.t -> ?control_inputs:Node.p list -> [ `variant ] Node.t -> [< `int32 | `int64 ] as 'shape_type Node.t
val tensorListFromTensor : ?name:string -> ?control_inputs:Node.p list -> 'element_dtype Node.t -> [< `int32 | `int64 ] as 'shape_type Node.t -> [ `variant ] Node.t
val tensorListGetItem : ?name:string -> type_:'element_dtype Tensorflow.Node.Type.t -> ?control_inputs:Node.p list -> [ `variant ] Node.t -> [ `int32 ] Node.t -> 'element_dtype Node.t
val tensorListLength : ?name:string -> ?control_inputs:Node.p list -> [ `variant ] Node.t -> [ `int32 ] Node.t
val tensorListPopBack : ?name:string -> type_1:'element_dtype Tensorflow.Node.Type.t -> ?control_inputs:Node.p list -> [ `variant ] Node.t -> [ `variant ] Node.t * 'element_dtype Node.t
val tensorListPushBack : ?name:string -> ?control_inputs:Node.p list -> [ `variant ] Node.t -> 'element_dtype Node.t -> [ `variant ] Node.t
val tensorListPushBackBatch : ?name:string -> ?control_inputs:Node.p list -> [ `variant ] Node.t -> 'element_dtype Node.t -> [ `variant ] Node.t
val tensorListReserve : ?name:string -> ?control_inputs:Node.p list -> [< `int32 | `int64 ] as 'shape_type Node.t -> [ `int32 ] Node.t -> [ `variant ] Node.t
val tensorListSetItem : ?name:string -> ?control_inputs:Node.p list -> [ `variant ] Node.t -> [ `int32 ] Node.t -> 'element_dtype Node.t -> [ `variant ] Node.t
val tensorListStack : ?name:string -> type_:'element_dtype Tensorflow.Node.Type.t -> ?num_elements:int -> ?control_inputs:Node.p list -> [ `variant ] Node.t -> 'element_dtype Node.t
val tensorSummary : ?name:string -> ?description:string -> ?display_name:string -> ?control_inputs:Node.p list -> 't Node.t -> [ `string ] Node.t
val tensorSummaryV2 : ?name:string -> ?control_inputs:Node.p list -> [ `string ] Node.t -> 't Node.t -> [ `string ] Node.t -> [ `string ] Node.t
val textLineDataset : ?name:string -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `string ] Node.t -> [ `int64 ] Node.t -> [ `variant ] Node.t
val textLineReader : ?name:string -> ?skip_header_lines:int -> ?container:string -> ?shared_name:string -> ?control_inputs:Node.p list -> unit -> [ `string ] Node.t
val threadUnsafeUnigramCandidateSampler : ?name:string -> num_true:int -> num_sampled:int -> unique:bool -> range_max:int -> ?seed:int -> ?seed2:int -> ?control_inputs:Node.p list -> [ `int64 ] Node.t -> [ `int64 ] Node.t * [ `float ] Node.t * [ `float ] Node.t
val tile : ?name:string -> ?control_inputs:Node.p list -> 't Node.t -> [< `int32 | `int64 ] as 'tmultiples Node.t -> 't Node.t
val tileGrad : ?name:string -> ?control_inputs:Node.p list -> 't Node.t -> [ `int32 ] Node.t -> 't Node.t
val timestamp : ?name:string -> ?control_inputs:Node.p list -> unit -> [ `double ] Node.t
val topK : ?name:string -> k:int -> ?sorted:bool -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t * [ `int32 ] Node.t
val topKV2 : ?name:string -> ?sorted:bool -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [ `int32 ] Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t * [ `int32 ] Node.t
val transpose : ?name:string -> ?control_inputs:Node.p list -> 't Node.t -> [< `int32 | `int64 ] as 'tperm Node.t -> 't Node.t
val truncateDiv : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 | `complex64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 | `complex64 ] as 't Node.t -> [< `float | `double | `int32 | `int64 | `complex64 ] as 't Node.t
val truncateMod : ?name:string -> ?control_inputs:Node.p list -> [< `int32 | `int64 | `float | `double ] as 't Node.t -> [< `int32 | `int64 | `float | `double ] as 't Node.t -> [< `int32 | `int64 | `float | `double ] as 't Node.t
val truncatedNormal : ?name:string -> type_:[< `float | `double ] as 'dtype Tensorflow.Node.Type.t -> ?seed:int -> ?seed2:int -> ?control_inputs:Node.p list -> [< `int32 | `int64 ] as 't Node.t -> [< `float | `double ] as 'dtype Node.t
val tryRpc : ?name:string -> ?protocol:string -> ?fail_fast:bool -> ?timeout_in_ms:int -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `string ] Node.t -> [ `string ] Node.t -> [ `string ] Node.t * [ `int32 ] Node.t * [ `string ] Node.t
val unbatch : ?name:string -> timeout_micros:int -> ?container:string -> ?shared_name:string -> ?control_inputs:Node.p list -> 't Node.t -> [ `int64 ] Node.t -> [ `int64 ] Node.t -> 't Node.t
val unbatchDataset : ?name:string -> output_types:Tensorflow.Node.Type.p list -> output_shapes:Tensorflow.Node.Dim.t list list -> ?control_inputs:Node.p list -> [ `variant ] Node.t -> [ `variant ] Node.t
val unbatchGrad : ?name:string -> ?container:string -> ?shared_name:string -> ?control_inputs:Node.p list -> 't Node.t -> [ `int64 ] Node.t -> 't Node.t -> [ `int64 ] Node.t -> 't Node.t
val uniformCandidateSampler : ?name:string -> num_true:int -> num_sampled:int -> unique:bool -> range_max:int -> ?seed:int -> ?seed2:int -> ?control_inputs:Node.p list -> [ `int64 ] Node.t -> [ `int64 ] Node.t * [ `float ] Node.t * [ `float ] Node.t
val unique : ?name:string -> type_1:[< `int32 | `int64 ] as 'out_idx Tensorflow.Node.Type.t -> ?control_inputs:Node.p list -> 't Node.t -> 't Node.t * [< `int32 | `int64 ] as 'out_idx Node.t
val uniqueV2 : ?name:string -> type_1:[< `int32 | `int64 ] as 'out_idx Tensorflow.Node.Type.t -> ?control_inputs:Node.p list -> 't Node.t -> [< `int32 | `int64 ] as 'taxis Node.t -> 't Node.t * [< `int32 | `int64 ] as 'out_idx Node.t
val uniqueWithCounts : ?name:string -> type_1:[< `int32 | `int64 ] as 'out_idx Tensorflow.Node.Type.t -> type_2:[< `int32 | `int64 ] as 'out_idx Tensorflow.Node.Type.t -> ?control_inputs:Node.p list -> 't Node.t -> 't Node.t * [< `int32 | `int64 ] as 'out_idx Node.t * [< `int32 | `int64 ] as 'out_idx Node.t
val uniqueWithCountsV2 : ?name:string -> type_1:[< `int32 | `int64 ] as 'out_idx Tensorflow.Node.Type.t -> type_2:[< `int32 | `int64 ] as 'out_idx Tensorflow.Node.Type.t -> ?control_inputs:Node.p list -> 't Node.t -> [< `int32 | `int64 ] as 'taxis Node.t -> 't Node.t * [< `int32 | `int64 ] as 'out_idx Node.t * [< `int32 | `int64 ] as 'out_idx Node.t
val unpack : ?name:string -> num:int -> ?axis:int -> ?control_inputs:Node.p list -> 't Node.t -> 't Node.t list
val unravelIndex : ?name:string -> ?control_inputs:Node.p list -> [< `int32 | `int64 ] as 'tidx Node.t -> [< `int32 | `int64 ] as 'tidx Node.t -> [< `int32 | `int64 ] as 'tidx Node.t
val unsortedSegmentMax : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [< `int32 | `int64 ] as 'tindices Node.t -> [< `int32 | `int64 ] as 'tnumsegments Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t
val unsortedSegmentMin : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `int64 ] as 't Node.t -> [< `int32 | `int64 ] as 'tindices Node.t -> [< `int32 | `int64 ] as 'tnumsegments Node.t -> [< `float | `double | `int32 | `int64 ] as 't Node.t
val unsortedSegmentProd : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `int32 | `int64 ] as 'tindices Node.t -> [< `int32 | `int64 ] as 'tnumsegments Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t
val unsortedSegmentSum : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t -> [< `int32 | `int64 ] as 'tindices Node.t -> [< `int32 | `int64 ] as 'tnumsegments Node.t -> [< `float | `double | `int32 | `complex64 | `int64 ] as 't Node.t
val variable : ?name:string -> type_:'dtype Tensorflow.Node.Type.t -> shape:Tensorflow.Node.Dim.t list -> ?container:string -> ?shared_name:string -> ?control_inputs:Node.p list -> unit -> 'dtype Node.t
val variableV2 : ?name:string -> type_:'dtype Tensorflow.Node.Type.t -> shape:Tensorflow.Node.Dim.t list -> ?container:string -> ?shared_name:string -> ?control_inputs:Node.p list -> unit -> 'dtype Node.t
val where : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double | `int32 | `complex64 | `int64 | `bool ] as 't Node.t -> [ `int64 ] Node.t
val wholeFileReader : ?name:string -> ?container:string -> ?shared_name:string -> ?control_inputs:Node.p list -> unit -> [ `string ] Node.t
val windowDataset : ?name:string -> output_types:Tensorflow.Node.Type.p list -> output_shapes:Tensorflow.Node.Dim.t list list -> ?control_inputs:Node.p list -> [ `variant ] Node.t -> [ `int64 ] Node.t -> [ `variant ] Node.t
val writeFile : ?name:string -> ?control_inputs:Node.p list -> [ `string ] Node.t -> [ `string ] Node.t -> [ `unit ] Node.t
val zerosLike : ?name:string -> ?control_inputs:Node.p list -> 't Node.t -> 't Node.t
val zeta : ?name:string -> ?control_inputs:Node.p list -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t -> [< `float | `double ] as 't Node.t
val zipDataset : ?name:string -> output_types:Tensorflow.Node.Type.p list -> output_shapes:Tensorflow.Node.Dim.t list list -> ?control_inputs:Node.p list -> [ `variant ] Node.t list -> [ `variant ] Node.t
include module type of Ops_manual
module Placeholder : sig ... end
type 't b = ?name:string -> 't Node.t -> 't Node.t -> 't Node.t
val (+) : [< `float | `double | `int32 | `int64 | `complex64 | `string ] b
val (-) : [< `float | `double | `int32 | `int64 | `complex64 ] b
val (/) : [< `float | `double | `int32 | `int64 | `complex64 ] b
val (*) : [< `float | `double | `int32 | `int64 | `complex64 ] b
val (*^) : [< `float | `double | `int32 | `complex64 ] b
val f_or_d : ?shape:int list -> type_:[< `float | `double ] as 'a Tensorflow.Node.Type.t -> float -> 'a Node.t
val f : ?shape:int list -> float -> [ `float ] Node.t
val d : ?shape:int list -> float -> [ `double ] Node.t
val cf : ?shape:int list -> float list -> [ `float ] Node.t
val cd : ?shape:int list -> float list -> [ `double ] Node.t
val ci32 : ?shape:int list -> int list -> [ `int32 ] Node.t
val ci64 : ?shape:int list -> int list -> [ `int64 ] Node.t
val const_float : ?name:string -> ?control_inputs:Node.p list -> ?shape:int list -> type_:[< `float | `double ] as 'dtype Tensorflow.Node.Type.t -> float list -> 'dtype Node.t
val const_int : ?name:string -> ?control_inputs:Node.p list -> ?shape:int list -> type_:[< `int32 | `int64 ] as 'dtype Tensorflow.Node.Type.t -> int list -> 'dtype Node.t
val const_string : ?name:string -> ?shape:int list -> string list -> [ `string ] Node.t
val const_string0 : ?name:string -> string -> [ `string ] Node.t
val scalar : ?empty_shape:unit -> type_:[< `float | `double ] as 'dtype Tensorflow.Node.Type.t -> float -> 'dtype Node.t
val four32 : [ `int32 ] Node.t
val three32 : [ `int32 ] Node.t
val two32 : [ `int32 ] Node.t
val one32 : [ `int32 ] Node.t
val zero32 : [ `int32 ] Node.t
type 'a reduce_fn = ?dims:int list -> [< `complex64 | `double | `float | `int32 | `int64 ] as 'a Node.t -> 'a Node.t
val reduce_sum : 'a reduce_fn
val reduce_min : 'a reduce_fn
val reduce_max : 'a reduce_fn
val reduce_mean : 'a reduce_fn
val reduce_prod : 'a reduce_fn
val reduce_all : ?dims:int list -> [ `bool ] Node.t -> [ `bool ] Node.t
val reduce_any : ?dims:int list -> [ `bool ] Node.t -> [ `bool ] Node.t
val save_ : ?name:string -> [ `string ] Node.t -> [ `string ] Node.t -> Node.p list -> [ `unit ] Node.t
val save : filename:string -> (string * Node.p) list -> [ `unit ] Node.t
val split2 : ?name:string -> [ `int32 ] Node.t -> 't Node.t -> 't Node.t * 't Node.t
val split3 : ?name:string -> [ `int32 ] Node.t -> 't Node.t -> 't Node.t * 't Node.t * 't Node.t
val split4 : ?name:string -> [ `int32 ] Node.t -> 't Node.t -> 't Node.t * 't Node.t * 't Node.t * 't Node.t
val range : [ `int32 ] Node.t -> [ `int32 ] Node.t
val placeholder : ?name:string -> type_:'a Tensorflow.Node.Type.t -> int list -> 'a Placeholder.t
val dropout : [< `float | `double ] as 'a Node.t -> keep_prob:'a Node.t -> 'a Node.t
val cast : ?name:string -> 'srcT Node.t -> type_:'dstT Tensorflow.Node.Type.t -> 'dstT Node.t
val count : 'a Node.t -> dims:int list -> [ `int32 ] Node.t
type 'a moments = {
  1. mean : 'a Node.t;
  2. variance : 'a Node.t;
}
val moments : [< `double | `float ] as 'a Node.t -> dims:int list -> 'a moments
val normalize : ?epsilon:float -> [< `double | `float ] as 'a Node.t -> 'a moments -> 'a Node.t
val cond_with_control_inputs : [ `bool ] Node.t -> if_true:(control_inputs:Node.p list -> 'a Node.t) -> if_false:(control_inputs:Node.p list -> 'a Node.t) -> 'a Node.t
val cond : [ `bool ] Node.t -> if_true:'a Node.t -> if_false:'a Node.t -> 'a Node.t
val shape32 : ?name:string -> ?control_inputs:Node.p list -> 't Node.t -> [ `int32 ] Node.t
val cross_entropy : ?epsilon:float -> ys:[< `double | `float ] as 'a Node.t -> y_hats:'a Node.t -> [ `sum | `mean ] -> 'a Node.t
val binary_cross_entropy : ?epsilon:float -> labels:[< `double | `float ] as 'a Node.t -> model_values:'a Node.t -> [ `sum | `mean ] -> 'a Node.t
val leaky_relu : [< `double | `float ] as 'a Node.t -> alpha:float -> 'a Node.t
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