TDSL (neural_nets_lib.Ocannl_tensor.Operation.DSL

val grad_spec : Tensor.grad_spec

val term : ?init_data:??? -> ?fetch_op:??? -> Tensor.op_fun

val number : ?label:??? -> ?axis_basis:??? -> Base.float -> Tensor.t

val bits : ?label:??? -> ?axis_basis:??? -> Base.int64 -> Tensor.t

val ndarray : Base.float Base.array -> Tensor.op_fun

val threefry4x32 : 
  ?spec:??? ->
  Tensor.t ->
  Tensor.t ->
  ?label:??? ->
  ?batch_dims:??? ->
  ?batch_axes:??? ->
  ?input_dims:??? ->
  ?output_dims:??? ->
  ?input_axes:??? ->
  ?output_axes:??? ->
  ?deduced:??? ->
  unit ->
  Tensor.t

val uint4x32_to_prec_uniform : 
  Tensor.t ->
  ?label:??? ->
  ?top_down_prec:??? ->
  ?batch_dims:??? ->
  ?batch_axes:??? ->
  ?input_dims:??? ->
  ?output_dims:??? ->
  ?input_axes:??? ->
  ?output_axes:??? ->
  ?deduced:??? ->
  unit ->
  Tensor.t

val uint4x32_to_prec_uniform1 : 
  Tensor.t ->
  ?label:??? ->
  ?top_down_prec:??? ->
  ?batch_dims:??? ->
  ?batch_axes:??? ->
  ?input_dims:??? ->
  ?output_dims:??? ->
  ?input_axes:??? ->
  ?output_axes:??? ->
  ?deduced:??? ->
  unit ->
  Tensor.t

val embed_self_id : ?label:??? -> unit -> Tensor.t

val default_param_init : 
  (unit ->
    ?label:??? ->
    ?top_down_prec:??? ->
    ?batch_dims:??? ->
    ?batch_axes:??? ->
    ?input_dims:??? ->
    ?output_dims:??? ->
    ?input_axes:??? ->
    ?output_axes:??? ->
    ?deduced:??? ->
    unit ->
    Tensor.t)
    Base.ref

val param : 
  ?value:??? ->
  ?values:??? ->
  ?param_init:??? ->
  Base.string ->
  ?more_label:??? ->
  Tensor.param_op_fun

val einsum : 
  ?capture_dims:??? ->
  Base.string ->
  Tensor.t ->
  Tensor.t ->
  Tensor.op_fun

val outer_sum : 
  ?capture_dims:??? ->
  Base.string ->
  Tensor.t ->
  Tensor.t ->
  Tensor.op_fun

val einsum1 : ?capture_dims:??? -> Base.string -> Tensor.t -> Tensor.op_fun

val einmax1 : 
  ?capture_dims:??? ->
  ?nonoverlapping:??? ->
  Base.string ->
  Tensor.t ->
  Tensor.op_fun

val tropical : 
  ?capture_dims:??? ->
  ?nonoverlapping:??? ->
  Base.string ->
  Tensor.t ->
  Tensor.t ->
  Tensor.op_fun

val concat_sum : 
  ?capture_dims:??? ->
  ?negated:??? ->
  Base.string ->
  Tensor.t Base.Array.t ->
  Tensor.op_fun

val concat : 
  ?capture_dims:??? ->
  ?negated:??? ->
  Base.string ->
  Tensor.t Base.Array.t ->
  Tensor.op_fun

val stack : stack_axis -> Tensor.t Base.Array.t -> Tensor.op_fun

val offsets : Tensor.op_fun

val range : ?label:??? -> ?axis_basis:??? -> Base__Int.t -> Tensor.t

val range_of_shape : 
  ?label:??? ->
  ?batch_dims:??? ->
  ?input_dims:??? ->
  ?output_dims:??? ->
  ?batch_axes:??? ->
  ?input_axes:??? ->
  ?output_axes:??? ->
  unit ->
  Tensor.t

val stop_gradient : ?spec:??? -> ?capture_dims:??? -> Tensor.t -> Tensor.op_fun

val reshape : 
  l:Base.string ->
  ?b:??? ->
  ?i:??? ->
  ?o:??? ->
  Ir.Ndarray.t ->
  ?fetch_op:??? ->
  ?top_down_prec:??? ->
  ?batch_axes:??? ->
  ?input_axes:??? ->
  ?output_axes:??? ->
  ?deduced:??? ->
  Base.unit ->
  Tensor.t

val wrap : 
  l:Base.string ->
  ?prec:??? ->
  ?b:??? ->
  ?i:??? ->
  ?o:??? ->
  Ir.Ndarray.t ->
  ?fetch_op:??? ->
  ?top_down_prec:??? ->
  ?batch_axes:??? ->
  ?input_axes:??? ->
  ?output_axes:??? ->
  ?deduced:??? ->
  Base.unit ->
  Tensor.t

val wrap_padded : 
  l:Base.string ->
  ?b:??? ->
  ?i:??? ->
  ?o:??? ->
  padding:Ir.Ops.axis_padding Base.array ->
  padded_value:Base.float ->
  Ir.Ndarray.t ->
  ?fetch_op:??? ->
  ?top_down_prec:??? ->
  ?batch_axes:??? ->
  ?input_axes:??? ->
  ?output_axes:??? ->
  ?deduced:??? ->
  Base.unit ->
  Tensor.t

val rebatch : 
  l:Base.string ->
  Ir.Ndarray.t ->
  ?fetch_op:??? ->
  ?top_down_prec:??? ->
  ?batch_dims:??? ->
  ?batch_axes:??? ->
  ?deduced:??? ->
  Base.unit ->
  Tensor.t

val init : 
  l:Base.string ->
  prec:Ir.Ops.prec ->
  ?b:??? ->
  ?i:??? ->
  ?o:??? ->
  f:(Base.int Base.array -> Base.float) ->
  ?fetch_op:??? ->
  ?top_down_prec:??? ->
  ?batch_axes:??? ->
  ?input_axes:??? ->
  ?output_axes:??? ->
  ?deduced:??? ->
  Base.unit ->
  Tensor.t

val uniform : 
  unit ->
  ?label:??? ->
  ?top_down_prec:??? ->
  ?batch_dims:??? ->
  ?batch_axes:??? ->
  ?input_dims:??? ->
  ?output_dims:??? ->
  ?input_axes:??? ->
  ?output_axes:??? ->
  ?deduced:??? ->
  unit ->
  Tensor.t

val reshape_param : 
  l:Base.string ->
  ?i:??? ->
  ?o:??? ->
  Ir.Ndarray.t ->
  ?more_label:??? ->
  ?input_axes:??? ->
  ?output_axes:??? ->
  ?deduced:??? ->
  Base.unit ->
  Tensor.t

val wrap_param : 
  l:Base.string ->
  ?i:??? ->
  ?o:??? ->
  Ir.Ndarray.t ->
  ?more_label:??? ->
  ?input_axes:??? ->
  ?output_axes:??? ->
  ?deduced:??? ->
  Base.unit ->
  Tensor.t

val matmul : Tensor.t -> Tensor.t -> Tensor.op_fun

val pointmul : 
  ?spec:??? ->
  ?capture_dims:??? ->
  Tensor.t ->
  Tensor.t ->
  Tensor.op_fun

val add : 
  ?spec:??? ->
  ?capture_dims:??? ->
  Tensor.t ->
  Tensor.t ->
  Tensor.op_fun

val pointpow : 
  ?spec:??? ->
  ?capture_dims:??? ->
  Base.float ->
  Tensor.t ->
  Tensor.op_fun

val relu : ?spec:??? -> ?capture_dims:??? -> Tensor.t -> Tensor.op_fun

val sat01 : ?spec:??? -> ?capture_dims:??? -> Tensor.t -> Tensor.op_fun

val fma : Tensor.t -> Tensor.t -> Tensor.t -> Tensor.op_fun

val number_int : ?label:??? -> ?axis_basis:??? -> int -> Tensor.t

val embed_symbol : ?label:??? -> Ir.Indexing.static_symbol -> Tensor.t

val embed_dim : ?label:??? -> Shape.delayed_var_ref -> Tensor.t

val sub : 
  ?spec:??? ->
  ?capture_dims:??? ->
  Tensor.t ->
  Tensor.t ->
  Tensor.op_fun

val pointdiv : 
  ?spec:??? ->
  ?capture_dims:??? ->
  Tensor.t ->
  Tensor.t ->
  Tensor.op_fun

val slice : Idx.static_symbol -> Tensor.t -> Tensor.op_fun

val exp : ?spec:??? -> ?capture_dims:??? -> Tensor.t -> Tensor.op_fun

val log : ?spec:??? -> ?capture_dims:??? -> Tensor.t -> Tensor.op_fun

val log2 : ?spec:??? -> ?capture_dims:??? -> Tensor.t -> Tensor.op_fun

val sin : ?spec:??? -> ?capture_dims:??? -> Tensor.t -> Tensor.op_fun

val cos : ?spec:??? -> ?capture_dims:??? -> Tensor.t -> Tensor.op_fun

val neg : ?spec:??? -> ?capture_dims:??? -> Tensor.t -> Tensor.op_fun

val cast : ?spec:??? -> ?capture_dims:??? -> Tensor.t -> Tensor.op_fun

val stretch : 
  ?spec:??? ->
  ?capture_dims:??? ->
  Tensor.t ->
  ?label:??? ->
  ?top_down_prec:??? ->
  ?batch_dims:??? ->
  ?batch_axes:??? ->
  ?input_dims:??? ->
  ?output_dims:??? ->
  ?input_axes:??? ->
  ?output_axes:??? ->
  ?deduced:??? ->
  unit ->
  Tensor.t

val sqrt : ?spec:??? -> ?capture_dims:??? -> Tensor.t -> Tensor.op_fun

val recip : ?spec:??? -> ?capture_dims:??? -> Tensor.t -> Tensor.op_fun

val recip_sqrt : ?spec:??? -> ?capture_dims:??? -> Tensor.t -> Tensor.op_fun

val tanh : ?spec:??? -> ?capture_dims:??? -> Tensor.t -> Tensor.op_fun

val where : 
  ?spec:??? ->
  ?capture_dims:??? ->
  Tensor.t ->
  Tensor.t ->
  Tensor.t ->
  Tensor.op_fun

val not : ?spec:??? -> ?capture_dims:??? -> Tensor.t -> Tensor.op_fun

val lt : 
  ?spec:??? ->
  ?capture_dims:??? ->
  Tensor.t ->
  Tensor.t ->
  Tensor.op_fun

val le : 
  ?spec:??? ->
  ?capture_dims:??? ->
  Tensor.t ->
  Tensor.t ->
  Tensor.op_fun

val eq : 
  ?spec:??? ->
  ?capture_dims:??? ->
  Tensor.t ->
  Tensor.t ->
  Tensor.op_fun

val ne : 
  ?spec:??? ->
  ?capture_dims:??? ->
  Tensor.t ->
  Tensor.t ->
  Tensor.op_fun

val uniform_at : 
  Tensor.t ->
  ?label:??? ->
  ?top_down_prec:??? ->
  ?batch_dims:??? ->
  ?batch_axes:??? ->
  ?input_dims:??? ->
  ?output_dims:??? ->
  ?input_axes:??? ->
  ?output_axes:??? ->
  ?deduced:??? ->
  unit ->
  Tensor.t

val uniform1 : 
  unit ->
  ?label:??? ->
  ?top_down_prec:??? ->
  ?batch_dims:??? ->
  ?batch_axes:??? ->
  ?input_dims:??? ->
  ?output_dims:??? ->
  ?input_axes:??? ->
  ?output_axes:??? ->
  ?deduced:??? ->
  unit ->
  Tensor.t

val uniform_at1 : 
  Tensor.t ->
  ?label:??? ->
  ?top_down_prec:??? ->
  ?batch_dims:??? ->
  ?batch_axes:??? ->
  ?input_dims:??? ->
  ?output_dims:??? ->
  ?input_axes:??? ->
  ?output_axes:??? ->
  ?deduced:??? ->
  unit ->
  Tensor.t

val interleave : Tensor.t -> Tensor.t -> Tensor.op_fun

val deinterleave_even : Tensor.t -> Tensor.op_fun

val deinterleave_odd : Tensor.t -> Tensor.op_fun

module O : sig ... end