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BatchNorm2D -> BatchNorm2d (#558)

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* BatchNorm2D -> BatchNorm2d

* Fix typo
This commit is contained in:
Jacky Lee
2023-02-16 12:31:49 -08:00
committed by GitHub
parent 09315ef34f
commit e172f0087a
9 changed files with 34 additions and 35 deletions
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10
test/external_test_opt.py
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@@ -46,7 +46,7 @@ class TestOpt(unittest.TestCase):
# TODO: with Tensor.training
Tensor.training = True
img = Tensor.ones(1,32,4,4)
bn = nn.BatchNorm2D(32, track_running_stats=False)
bn = nn.BatchNorm2d(32, track_running_stats=False)
with CLCache():
img_bn = bn(img).realize()
print(img_bn)
@@ -73,7 +73,7 @@ class TestOpt(unittest.TestCase):
Tensor.training = True
img = Tensor.ones(1,3,4,4)
c1 = nn.Conv2d(3,32,3)
bn = nn.BatchNorm2D(32, track_running_stats=False)
bn = nn.BatchNorm2d(32, track_running_stats=False)
opt = optim.SGD(optim.get_parameters([c1, bn]))
with CLCache():
img_bn = bn(c1(img)).elu().sum()
@@ -86,7 +86,7 @@ class TestOpt(unittest.TestCase):
def test_fold_conv_batchnorm_notrain(self):
img = Tensor.ones(1,3,8,8)
c1 = nn.Conv2d(3,32,3)
bn = nn.BatchNorm2D(32, track_running_stats=False)
bn = nn.BatchNorm2d(32, track_running_stats=False)
# precache the bn
img_conv = bn(c1(img)).relu().realize()
with CLCache():
@@ -97,7 +97,7 @@ class TestOpt(unittest.TestCase):
Tensor.training = True
img = Tensor.ones(1,3,8,8)
c1 = nn.Conv2d(3,32,3)
bn = nn.BatchNorm2D(32, track_running_stats=False)
bn = nn.BatchNorm2d(32, track_running_stats=False)
with CLCache():
img_conv = bn(c1(img)).relu().realize()
print(img_conv)
@@ -132,4 +132,4 @@ class TestOpt(unittest.TestCase):
assert len(GlobalCounters.cache) == 2, "optimizer didn't fold conv/relu"
if __name__ == '__main__':
unittest.main()
unittest.main()