You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
53 lines
1.5 KiB
53 lines
1.5 KiB
1 month ago
|
#!/usr/bin/env python
|
||
|
|
import os
|
||
|
|
import unittest
|
||
|
|
import numpy as np
|
||
|
|
if 'IMAGE' not in os.environ:
|
||
|
|
os.environ['IMAGE'] = '2'
|
||
|
|
os.environ['GPU'] = '1'
|
||
|
|
os.environ['OPT'] = '2'
|
||
|
|
from tinygrad.tensor import Tensor
|
||
|
|
from tinygrad.nn import Conv2d
|
||
|
|
Tensor.no_grad = True
|
||
|
|
|
||
|
|
class TestImage(unittest.TestCase):
|
||
|
|
def test_create_image(self):
|
||
|
|
t = Tensor.ones(128, 128, 1)
|
||
|
|
t = t.reshape(128, 32, 4) + 3
|
||
|
|
t.realize()
|
||
|
|
np.testing.assert_array_equal(t.numpy(), np.ones((128,32,4))*4)
|
||
|
|
|
||
|
|
def test_sum_image(self):
|
||
|
|
t1 = Tensor.ones(16, 16, 1).reshape(16, 4, 4) + 3
|
||
|
|
t1.realize()
|
||
|
|
t1 = t1.sum()
|
||
|
|
t1.realize()
|
||
|
|
assert t1.numpy() == 16*4*4*4, f"got {t1.numpy()}"
|
||
|
|
|
||
|
|
def test_add_image(self):
|
||
|
|
t1 = Tensor.ones(16, 16, 1).reshape(16, 4, 4) + 3
|
||
|
|
t2 = Tensor.ones(16, 16, 1).reshape(16, 4, 4) + 4
|
||
|
|
t1.realize()
|
||
|
|
t2.realize()
|
||
|
|
t3 = t1 + t2
|
||
|
|
t3.realize()
|
||
|
|
np.testing.assert_array_equal(t3.numpy(), np.ones((16,4,4))*9)
|
||
|
|
|
||
|
|
def test_padded_conv(self):
|
||
|
|
bs, in_chans, out_chans = 1,12,32
|
||
|
|
tiny_conv = Conv2d(in_chans, out_chans, 3, bias=None, padding=1)
|
||
|
|
tiny_dat = Tensor.ones(bs, 12, 64, 128)
|
||
|
|
tiny_conv(tiny_dat).realize()
|
||
|
|
|
||
|
|
def test_op_conv(self):
|
||
|
|
bs, in_chans, out_chans = 1,12,32
|
||
|
|
tiny_conv = Conv2d(in_chans, out_chans, 3, bias=None, padding=1)
|
||
|
|
tiny_dconv = Conv2d(out_chans, out_chans, 1, bias=None, padding=0)
|
||
|
|
tiny_dat = Tensor.ones(bs, 12, 64, 128)
|
||
|
|
p2 = tiny_conv(tiny_dat).relu()
|
||
|
|
p2 = tiny_dconv(p2)
|
||
|
|
p2.realize()
|
||
|
|
|
||
|
|
if __name__ == '__main__':
|
||
|
|
unittest.main()
|