def train

bendtorch-load@1.3.0.0 · main.bend:213

import Base
import bendtorch@1.3.0.0/main.bend as T

213def train(~P: Type, ~X: Type, ~Y: Type, ~S: Type, ~m: T.Layer<P, X, Y, S>, +path: String, tr: T.Train<P>) -> IO(T.Train<P>):
214  match tr:
215    case T.Train{p, g, T.NoMom{}, p1, p2, loss}:
216      train_read(~P, ~X, ~Y, ~S, ~m, path, T.Layer.count(P, X, Y, S, m), 1, 0, T.Train{p, g, T.NoMom{}, p1, p2, loss})
217    case T.Train{p, g, T.OneMom{mm}, p1, p2, loss}:
218      train_read(~P, ~X, ~Y, ~S, ~m, path, T.Layer.count(P, X, Y, S, m), 2, 0, T.Train{p, g, T.OneMom{mm}, p1, p2, loss})
219    case T.Train{p, g, T.TwoMom{mm, vv}, p1, p2, loss}:
220      train_read(~P, ~X, ~Y, ~S, ~m, path, T.Layer.count(P, X, Y, S, m), 3, 2, T.Train{p, g, T.TwoMom{mm, vv}, p1, p2, loss})
221    case T.Train{p, g, T.Packed{t}, p1, p2, loss}:
222      do IO<T.Train<P>>:
223        +n : U32 <- cells_of(path)
224        train_read(~P, ~X, ~Y, ~S, ~m, path, n, 1, 0, T.Train{p, g, T.Packed{t}, p1, p2, loss})