tinygrad/test/test_gc.py

66 lines
1.9 KiB
Python

#!/usr/bin/env python
import gc
import unittest
import numpy as np
from tinygrad.device import Buffer
from tinygrad.engine.realize import run_schedule
from tinygrad.tensor import Tensor
def tensors_allocated():
return sum([isinstance(x, Tensor) for x in gc.get_objects()])
def bufs_allocated():
return sum([isinstance(x, Buffer) for x in gc.get_objects()])
class TestGC(unittest.TestCase):
def test_gc(self):
Tensor.manual_seed(0)
a = Tensor.rand(4, 4, requires_grad=True)
b = Tensor.zeros(4, 4, requires_grad=True)
(a*b).mean().backward()
assert (tensors_allocated() > 0)
del a,b
assert (tensors_allocated() == 1) # one for Tensor._device_rng_counters
def test_gc_complex(self):
Tensor.manual_seed(0)
a = Tensor(np.zeros((4, 4), dtype=np.float32), requires_grad=True)
b = Tensor.rand(4, 4, requires_grad=True)
assert (tensors_allocated() == 4)
(a*b).mean().backward()
assert (tensors_allocated() == 5)
del b
assert (tensors_allocated() == 3)
b = Tensor(np.zeros((4, 4), dtype=np.float32), requires_grad=True)
print(tensors_allocated())
(a*b).mean().backward()
print(tensors_allocated())
assert (tensors_allocated() == 5)
del b
assert (tensors_allocated() == 3)
def test_schedule_gc(self):
init = bufs_allocated()
x = Tensor.ones(256).contiguous().realize()
y = Tensor.ones(5, 5).contiguous()
y.schedule()
del x
del y
self.assertEqual(bufs_allocated()-init, 0)
def test_schedule_gc_with_inputs(self):
init = bufs_allocated()
x = Tensor.ones(256).contiguous().realize()
y = x+Tensor.ones(256).contiguous()
ys = y.schedule()
del x
run_schedule(ys)
np.testing.assert_equal(y.numpy(), np.full((256,), 2))
self.assertEqual(bufs_allocated()-init, 1)
del y
self.assertEqual(bufs_allocated()-init, 0)
if __name__ == '__main__':
unittest.main()