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46 lines
1.2 KiB
Python
46 lines
1.2 KiB
Python
#!/usr/bin/env python
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import gc
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import unittest
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from tinygrad.tensor import Tensor, GPU, ANE, Device
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def tensors_allocated():
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return sum([isinstance(x, Tensor) for x in gc.get_objects()])
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class TestGC(unittest.TestCase):
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device = Device.CPU
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def test_gc(self):
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a = Tensor.zeros(4,4, device=self.device)
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b = Tensor.zeros(4,4, device=self.device)
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(a*b).mean().backward()
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assert(tensors_allocated() > 0)
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del a,b
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assert(tensors_allocated() == 0)
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def test_gc_complex(self):
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a = Tensor.zeros(4,4, device=self.device)
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b = Tensor.zeros(4,4, device=self.device)
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assert(tensors_allocated() == 2)
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(a*b).mean().backward()
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assert(tensors_allocated() == 4)
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del b
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assert(tensors_allocated() == 2)
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b = Tensor.zeros(4,4, device=self.device)
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print(tensors_allocated())
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(a*b).mean().backward()
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print(tensors_allocated())
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assert(tensors_allocated() == 4)
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del b
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assert(tensors_allocated() == 2)
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@unittest.skipUnless(GPU, "Requires GPU")
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class TestGCGPU(TestGC):
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device = Device.GPU
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@unittest.skipUnless(ANE, "Requires ANE")
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class TestGCANE(TestGC):
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device=Device.ANE
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if __name__ == '__main__':
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unittest.main()
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