(model, valid_set, time_steps, beam_search=True, num_beams=5)
return prediction, groundtruth
Get model outputs for displaying.
Get model outputs for displaying.
Get model outputs for displaying .
def get_predictions(model, valid_set, time_steps, beam_search=True, num_beams=5):
    """
    Get model outputs for displaying.
    """
    shape = (valid_set.nbatches, model.be.bsz, time_steps)
    if beam_search:
        ypred = model.get_outputs_beam(valid_set, num_beams=num_beams)
        prediction = ypred.reshape(shape).transpose(1, 0, 2)
    else:
        ypred = model.get_outputs(valid_set)
        prediction = ypred.argmax(2).reshape(shape).transpose(1, 0, 2)

    groundtruth = valid_set.X[:, :valid_set.nbatches, ::-1]
    prediction = prediction[:, :, ::-1].flatten()
    groundtruth = groundtruth[:, :, ::-1].flatten()

    return prediction, groundtruth
def get_predictions ( model , valid_set , time_steps , beam_search = True , num_beams = 5 ) : shape = ( valid_set . nbatches , model . be . bsz , time_steps ) if beam_search : ypred = model . get_outputs_beam ( valid_set , num_beams = num_beams ) prediction = ypred . reshape ( shape ) . transpose ( 1 , 0 , 2 ) else : ypred = model . get_outputs ( valid_set ) prediction = ypred . argmax ( 2 ) . reshape ( shape ) . transpose ( 1 , 0 , 2 ) groundtruth = valid_set . X [ : , : valid_set . nbatches , : : - 1 ] prediction = prediction [ : , : , : : - 1 ] . flatten ( ) groundtruth = groundtruth [ : , : , : : - 1 ] . flatten ( ) return prediction , groundtruth