blob: d6ea77ad158b08dae7df5f5b6bfbc636bf895bbf [file] [log] [blame]
import sys
import torch
from torch.testing._internal.inductor_utils import GPU_TYPE
def first_arg(x, y):
return x[y]
def second_arg(x, y):
return x[:, y]
def same_pm_one(x, y):
return x[y + 1, y - 1]
def same_pp_one(x, y):
return x[y + 1, y + 1]
def store(x, y, z):
x[y + 1, y + 1] = z
if __name__ == "__main__":
_, fn_name, dims, dyn_shape, one_size = sys.argv
assert fn_name in ("first_arg", "second_arg", "same_pm_one", "same_pp_one", "store")
assert one_size in ("True", "False")
one_size = one_size == "True"
assert dims in ("2", "3")
shape_x = [3, 2, 4] if dims == "3" else [3, 2]
if one_size:
assert (
fn_name == "first_arg"
), "only first_arg can be tested for a special case of 1-size tensor"
shape_x[0] = 1
assert dyn_shape in ("True", "False")
dynamic_shapes = dyn_shape == "True"
x = torch.randn(shape_x, device=GPU_TYPE)
y = torch.arange(4, device=GPU_TYPE)
fn = vars()[fn_name]
fn = torch.compile(dynamic=dynamic_shapes)(fn)
if fn_name == "store":
shape = (y.numel(),) + x.shape[2:]
z = torch.randn(shape, device=GPU_TYPE)
fn(x, y, z)
else:
fn(x, y)