9c7833faf9
* Vegetarian Filet o Fish model * fix.. atc.. * test cluster_speed_limit * fix.. cluster_speed_limit.. 2 * fix.. clusterspeedlimit3 * cruise speed to roadlimit speed * fix.. * fix.. eng * deltaUp/Down for lanechange * fix.. atc desire... * fix.. * ff * ff * fix.. * fix.. eng * fix engsound * Update desire_helper.py * fix.. connect... * fix curve_min speed * Revert "fix curve_min speed" This reverts commit fcc9c2eb14eb3504abef3e420db93e8882e56f37. * Reapply "fix curve_min speed" This reverts commit 2d2bba476c58a7b4e13bac3c3ad0e4694c95515d. * fix.. auto speed up.. roadlimit * fix.. atc auto lanechange... * Update desire_helper.py * Update cruise.py * debug atc... * fix.. waze alert offset.. * fix.. * test atc.. * fix.. * fix.. atc * atc test.. * fix.. atc * fix.. atc2 * fix.. atc3 * KerryGold Model. latsmooth_sec = 0.0 * lat smooth seconds 0.13 * fix comment * fix.. auto cruise, and speed unit * change lanemode switching. * erase mazda lkas button.
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['GPU'] = '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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