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synced 2026-01-08 22:48:25 -05:00
bcf1518309
* Update all devices to be tested
ANE, CPU and OCL all now support all tests.
However tests are not currently passing on GPU and I cannot test on CPU.
Failing GPU test are not an issue caused by this update. Tests have not
been passing due to a missing "six" required installation.
OpenCL Tests have not been run since commit: 1a1c63a08b
devices have 3 types and are handle by a new DeviceTypes enum. (The goal
is to revert to Tensor.<type>, but this current setup allows for keyword
argument defaults: `device=DeviceType.CPU`)
All references to Tensor.GPU/CPU/ANE as been converted to the
corresponding `DeviceTypes` enum.
Refactor of the conversion code to allow for any device to any device
conversion.
* Add six dependency in requirements.txt
* Resolve failure to run tests
Move six into gpu required installs. Remove six from standard
installation.
* Remove repeated data conversion
* Refactor method names
Also reduce code with .to and .to_
* Dynamic device handlers
* Refactor DeviceTypes -> Device
* Add mem copy profiling back
* test_backward_pass_diamond_model passing
* Resolve Sum issue on GPU
* Revert batchnorm2d tests
* Update README with upadated API
* ANE testing with
* Last minute line gains
47 lines
1.2 KiB
Python
47 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, Device
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from .config import ANE
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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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