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https://github.com/firestar5683/StarPilot.git
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firestar5683
22a8575199
Keep official openpilot ancestry and dependency licenses. Store resources directly in Git, remove LFS setup requirements, and leave the downloadable big model outside the source tree.
53 lines
1.9 KiB
Python
53 lines
1.9 KiB
Python
#!/usr/bin/env python
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import unittest, os
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import torch
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import numpy as np
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from tinygrad.helpers import DEV
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from tinygrad.tensor import Tensor
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from tinygrad.device import Device
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from tinygrad.dtype import _from_torch_dtype, _to_torch_dtype
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MOCKGPU = DEV.interface.startswith("MOCK")
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@unittest.skipIf(Device.DEFAULT not in ["METAL", "CUDA"] or MOCKGPU, f"no support on {Device.DEFAULT}")
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class TestInterop(unittest.TestCase):
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def setUp(self):
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if Device.DEFAULT == "CUDA": self.torch_device = "cuda"
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elif Device.DEFAULT == "METAL": self.torch_device = "mps"
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def test_torch_interop(self):
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inp = torch.rand(2, 2, 3, device=torch.device(self.torch_device))
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if self.torch_device == "mps": torch.mps.synchronize()
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else: torch.cuda.synchronize()
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tg_data = Tensor.from_blob(inp.data_ptr(), inp.shape, dtype=_from_torch_dtype(inp.dtype))
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tg_out = tg_data[:, :, 0] * 0.2989 + tg_data[:, :, 1] * 0.5870 + tg_data[:, :, 2] * 0.1140
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tg_res = tg_out.numpy()
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if self.torch_device == "mps" and os.getenv("CI", "") != "":
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# MPS backend out of memory: https://discuss.pytorch.org/t/mps-back-end-out-of-memory-on-github-action/189773
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# Calculate expected value on cpu.
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inp = inp.cpu()
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torch_out = inp[:, :, 0] * 0.2989 + inp[:, :, 1] * 0.5870 + inp[:, :, 2] * 0.1140
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np.testing.assert_allclose(tg_res, torch_out.cpu().numpy(), atol=1e-5, rtol=1e-5)
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def test_torch_interop_write(self):
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tg_data = Tensor.randn((4, 4), device=Device.DEFAULT)
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out = torch.empty(4, 4, device=torch.device(self.torch_device), dtype=_to_torch_dtype(tg_data.dtype))
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tg_out = Tensor.from_blob(out.data_ptr(), out.shape, dtype=_from_torch_dtype(out.dtype))
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tg_out.assign(tg_data).realize()
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Device[Device.DEFAULT].synchronize()
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torch_out_np = out.cpu().numpy()
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np.testing.assert_allclose(tg_data.numpy(), torch_out_np, atol=1e-5, rtol=1e-5)
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if __name__ == '__main__':
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unittest.main()
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