tinygrad/test/test_assign.py

68 lines
2.1 KiB
Python

#!/usr/bin/env python
import unittest
import numpy as np
from tinygrad.tensor import Tensor
from tinygrad.lazy import LAZY
from tinygrad.ops import GlobalCounters
from tinygrad.graph import nm
N = 200 # has to be bigger than the cache to fail
class TestAssign(unittest.TestCase):
def test_simple_assignment(self):
a = Tensor(np.arange(N*N, dtype=np.float32)).reshape(N,N)
b = Tensor(np.arange(N*N, dtype=np.float32)).reshape(N,N)
a.realize()
b.realize()
ba1 = a.lazydata.realized
bb1 = b.lazydata.realized
a += b
a.realize()
ba2 = a.lazydata.realized
if LAZY: assert ba1 == ba2 and ba1 != bb1
np.testing.assert_allclose(a.numpy(), (np.arange(N*N)*2).reshape((N,N)))
def test_permuted_assignment(self):
a = Tensor(np.arange(N*N, dtype=np.float32)).reshape(N,N)
b = Tensor(np.arange(N*N, dtype=np.float32)).reshape(N,N)
a.realize()
b.realize()
ba1 = a.lazydata.realized
bb1 = b.lazydata.realized
a = a.permute(1,0)
a += b
a.realize()
ba2 = a.lazydata.realized
assert ba1 != ba2 and ba1 != bb1
np.testing.assert_allclose(a.numpy(), np.arange(N*N).reshape((N,N)) + np.arange(N*N).reshape((N,N)).transpose(1,0))
def test_post_permuted_assignment(self):
a = Tensor(np.arange(N*N, dtype=np.float32)).reshape(N,N)
b = Tensor(np.arange(N*N, dtype=np.float32)).reshape(N,N)
a.realize()
b.realize()
#GlobalCounters.cache = []
ba1 = a.lazydata.realized
bb1 = b.lazydata.realized
a.assign(a.permute(1,0) + b) # this should not work!
a.realize()
ba2 = a.lazydata.realized
# NOTE: don't test that it's assigned
#assert ba1 == ba2 and ba1 != bb1
"""
if len(GlobalCounters.cache):
runner, args = GlobalCounters.cache[0]
b0, b1, b2 = args
print(nm(b0), id(b0.cl))
print(nm(b1), id(b1.cl))
print(nm(b2), id(b2.cl))
"""
np.testing.assert_allclose(a.numpy(), np.arange(N*N).reshape((N,N)) + np.arange(N*N).reshape((N,N)).transpose(1,0))
# TODO: is there a way to sneak in a permute such that it returns the wrong answer?
if __name__ == "__main__":
unittest.main()