def f(*idxs):
idxs = list(idxs)
sm = lengths[0]
load = tensors[0].load(idxs)
for length, tensor in list(zip(lengths, tensors))[1:]:
new_idxs = idxs[:]
new_idxs[dim] -= to_expr(sm)
load = te.ifThenElse(idxs[dim] < to_expr(sm), load,
tensor.load(new_idxs))
return load
def f(*idxs):
val = args[0].load(idxs)
return te.ifThenElse(
val < to_expr(args[1]), to_expr(args[1]),
te.ifThenElse(val > to_expr(args[2]), to_expr(args[2]), val))
def compute(idxs):
load = inputs[0].as_buf().load(idxs)
return te.ifThenElse(te.ExprHandle.isnan(load),
te.ExprHandle.float(0.), load)