mirror of
https://github.com/tinygrad/tinygrad.git
synced 2026-01-14 17:38:06 -05:00
f5467cfedc
* runs one metal kernel * conv2d works * ops tests are passing * const folding * all ops work * pre commit always passes * torch works * working still * fix graph test * tests passing * image almost works * image conv works * most images * fix custom * fix assignment * fix compile enet * clean up comments * fix realize return value * include shapetracker in LB repr * copy should make a copy * reenable method cache * fix lna * dtypes in graph * forward only for IMAGE=2 * simple realize * getting close * fixup new api, it's good except the kernel count * back to 197 kernels * tests should pass * go to a real float * no type_on_cpu * fix the docs * put shapetracker back in it's proper place
69 lines
1.7 KiB
Python
69 lines
1.7 KiB
Python
import unittest
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import numpy as np
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from tinygrad.lazy import Device
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from tinygrad.tensor import Tensor
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from tinygrad.helpers import dtypes
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def multidevice_test(fxn):
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def ret(self):
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for device in Device._buffers:
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with self.subTest(device=device):
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try:
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Device[device]
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except Exception:
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print(f"WARNING: {device} test isn't running")
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continue
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fxn(self, device)
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return ret
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class TestExample(unittest.TestCase):
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@multidevice_test
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def test_convert_to_cpu(self, device):
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a = Tensor([[1,2],[3,4]], device=device)
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assert a.numpy().shape == (2,2)
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b = a.cpu()
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assert b.numpy().shape == (2,2)
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@multidevice_test
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def test_2_plus_3(self, device):
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a = Tensor([2], device=device)
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b = Tensor([3], device=device)
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result = a + b
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print(f"{a.numpy()} + {b.numpy()} = {result.numpy()}")
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assert result.numpy()[0] == 5.
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@multidevice_test
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def test_example_readme(self, device):
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x = Tensor.eye(3, device=device, requires_grad=True)
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y = Tensor([[2.0,0,-2.0]], device=device, requires_grad=True)
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z = y.matmul(x).sum()
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z.backward()
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x.grad.numpy() # dz/dx
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y.grad.numpy() # dz/dy
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assert x.grad.device == device
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assert y.grad.device == device
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@multidevice_test
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def test_example_matmul(self, device):
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try:
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Device[device]
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except Exception:
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print(f"WARNING: {device} test isn't running")
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return
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x = Tensor.eye(64, device=device, requires_grad=True)
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y = Tensor.eye(64, device=device, requires_grad=True)
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z = y.matmul(x).sum()
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z.backward()
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x.grad.numpy() # dz/dx
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y.grad.numpy() # dz/dy
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assert x.grad.device == device
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assert y.grad.device == device
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if __name__ == '__main__':
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unittest.main()
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