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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.
52 lines
1.5 KiB
Python
52 lines
1.5 KiB
Python
#!/usr/bin/env python
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import os
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import unittest
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import numpy as np
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if 'IMAGE' not in os.environ:
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os.environ['IMAGE'] = '2'
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os.environ['CL'] = '1'
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os.environ['OPT'] = '2'
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from tinygrad.tensor import Tensor
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from tinygrad.nn import Conv2d
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class TestImage(unittest.TestCase):
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def test_create_image(self):
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t = Tensor.ones(128, 128, 1)
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t = t.reshape(128, 32, 4) + 3
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t.realize()
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np.testing.assert_array_equal(t.numpy(), np.ones((128,32,4))*4)
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def test_sum_image(self):
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t1 = Tensor.ones(16, 16, 1).reshape(16, 4, 4) + 3
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t1.realize()
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t1 = t1.sum()
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t1.realize()
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assert t1.numpy() == 16*4*4*4, f"got {t1.numpy()}"
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def test_add_image(self):
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t1 = Tensor.ones(16, 16, 1).reshape(16, 4, 4) + 3
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t2 = Tensor.ones(16, 16, 1).reshape(16, 4, 4) + 4
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t1.realize()
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t2.realize()
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t3 = t1 + t2
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t3.realize()
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np.testing.assert_array_equal(t3.numpy(), np.ones((16,4,4))*9)
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def test_padded_conv(self):
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bs, in_chans, out_chans = 1,12,32
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tiny_conv = Conv2d(in_chans, out_chans, 3, bias=None, padding=1)
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tiny_dat = Tensor.ones(bs, 12, 64, 128)
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tiny_conv(tiny_dat).realize()
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def test_op_conv(self):
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bs, in_chans, out_chans = 1,12,32
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tiny_conv = Conv2d(in_chans, out_chans, 3, bias=None, padding=1)
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tiny_dconv = Conv2d(out_chans, out_chans, 1, bias=None, padding=0)
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tiny_dat = Tensor.ones(bs, 12, 64, 128)
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p2 = tiny_conv(tiny_dat).relu()
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p2 = tiny_dconv(p2)
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p2.realize()
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if __name__ == '__main__':
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unittest.main()
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