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Commit 1610268e authored by Alykhan Tejani's avatar Alykhan Tejani
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use integer division in tests for array slicing + various PEP-8 fixes

parent 6c7733f0
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test/test_transforms.py
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import torch import torch
import torchvision.transforms as transforms import torchvision.transforms as transforms
import torchvision.datasets as datasets
import numpy as np
import unittest import unittest
import random import random
class Tester(unittest.TestCase): class Tester(unittest.TestCase):
def test_crop(self): def test_crop(self):
height = random.randint(10, 32) * 2 height = random.randint(10, 32) * 2
width = random.randint(10, 32) * 2 width = random.randint(10, 32) * 2
oheight = random.randint(5, (height - 2) / 2) * 2 oheight = random.randint(5, (height - 2) / 2) * 2
owidth = random.randint(5, (width - 2) / 2) * 2 owidth = random.randint(5, (width - 2) / 2) * 2
img = torch.ones(3, height, width) img = torch.ones(3, height, width)
oh1 = (height - oheight) / 2 oh1 = (height - oheight) // 2
ow1 = (width - owidth) / 2 ow1 = (width - owidth) // 2
imgnarrow = img[:, oh1 :oh1 + oheight, ow1 :ow1 + owidth] imgnarrow = img[:, oh1:oh1 + oheight, ow1:ow1 + owidth]
imgnarrow.fill_(0) imgnarrow.fill_(0)
result = transforms.Compose([ result = transforms.Compose([
transforms.ToPILImage(), transforms.ToPILImage(),
...@@ -23,7 +22,7 @@ class Tester(unittest.TestCase): ...@@ -23,7 +22,7 @@ class Tester(unittest.TestCase):
transforms.ToTensor(), transforms.ToTensor(),
])(img) ])(img)
assert result.sum() == 0, "height: " + str(height) + " width: " \ assert result.sum() == 0, "height: " + str(height) + " width: " \
+ str( width) + " oheight: " + str(oheight) + " owidth: " + str(owidth) + str(width) + " oheight: " + str(oheight) + " owidth: " + str(owidth)
oheight += 1 oheight += 1
owidth += 1 owidth += 1
result = transforms.Compose([ result = transforms.Compose([
...@@ -33,9 +32,9 @@ class Tester(unittest.TestCase): ...@@ -33,9 +32,9 @@ class Tester(unittest.TestCase):
])(img) ])(img)
sum1 = result.sum() sum1 = result.sum()
assert sum1 > 1, "height: " + str(height) + " width: " \ assert sum1 > 1, "height: " + str(height) + " width: " \
+ str( width) + " oheight: " + str(oheight) + " owidth: " + str(owidth) + str(width) + " oheight: " + str(oheight) + " owidth: " + str(owidth)
oheight += 1 oheight += 1
owidth += 1 owidth += 1
result = transforms.Compose([ result = transforms.Compose([
transforms.ToPILImage(), transforms.ToPILImage(),
transforms.CenterCrop((oheight, owidth)), transforms.CenterCrop((oheight, owidth)),
...@@ -43,15 +42,15 @@ class Tester(unittest.TestCase): ...@@ -43,15 +42,15 @@ class Tester(unittest.TestCase):
])(img) ])(img)
sum2 = result.sum() sum2 = result.sum()
assert sum2 > 0, "height: " + str(height) + " width: " \ assert sum2 > 0, "height: " + str(height) + " width: " \
+ str( width) + " oheight: " + str(oheight) + " owidth: " + str(owidth) + str(width) + " oheight: " + str(oheight) + " owidth: " + str(owidth)
assert sum2 > sum1, "height: " + str(height) + " width: " \ assert sum2 > sum1, "height: " + str(height) + " width: " \
+ str( width) + " oheight: " + str(oheight) + " owidth: " + str(owidth) + str(width) + " oheight: " + str(oheight) + " owidth: " + str(owidth)
def test_scale(self): def test_scale(self):
height = random.randint(24, 32) * 2 height = random.randint(24, 32) * 2
width = random.randint(24, 32) * 2 width = random.randint(24, 32) * 2
osize = random.randint(5, 12) * 2 osize = random.randint(5, 12) * 2
img = torch.ones(3, height, width) img = torch.ones(3, height, width)
result = transforms.Compose([ result = transforms.Compose([
transforms.ToPILImage(), transforms.ToPILImage(),
...@@ -63,7 +62,7 @@ class Tester(unittest.TestCase): ...@@ -63,7 +62,7 @@ class Tester(unittest.TestCase):
# print result.size() # print result.size()
assert osize in result.size() assert osize in result.size()
if height < width: if height < width:
assert result.size(1) <= result.size(2) assert result.size(1) <= result.size(2)
elif width < height: elif width < height:
assert result.size(1) >= result.size(2) assert result.size(1) >= result.size(2)
...@@ -71,7 +70,7 @@ class Tester(unittest.TestCase): ...@@ -71,7 +70,7 @@ class Tester(unittest.TestCase):
height = random.randint(10, 32) * 2 height = random.randint(10, 32) * 2
width = random.randint(10, 32) * 2 width = random.randint(10, 32) * 2
oheight = random.randint(5, (height - 2) / 2) * 2 oheight = random.randint(5, (height - 2) / 2) * 2
owidth = random.randint(5, (width - 2) / 2) * 2 owidth = random.randint(5, (width - 2) / 2) * 2
img = torch.ones(3, height, width) img = torch.ones(3, height, width)
result = transforms.Compose([ result = transforms.Compose([
transforms.ToPILImage(), transforms.ToPILImage(),
...@@ -100,20 +99,20 @@ class Tester(unittest.TestCase): ...@@ -100,20 +99,20 @@ class Tester(unittest.TestCase):
transforms.Pad(padding), transforms.Pad(padding),
transforms.ToTensor(), transforms.ToTensor(),
])(img) ])(img)
assert result.size(1) == height + 2*padding assert result.size(1) == height + 2 * padding
assert result.size(2) == width + 2*padding assert result.size(2) == width + 2 * padding
def test_lambda(self): def test_lambda(self):
trans = transforms.Lambda(lambda x: x.add(10)) trans = transforms.Lambda(lambda x: x.add(10))
x = torch.randn(10) x = torch.randn(10)
y = trans(x) y = trans(x)
assert(y.equal(torch.add(x, 10))) assert (y.equal(torch.add(x, 10)))
trans = transforms.Lambda(lambda x: x.add_(10)) trans = transforms.Lambda(lambda x: x.add_(10))
x = torch.randn(10) x = torch.randn(10)
y = trans(x) y = trans(x)
assert(y.equal(x)) assert (y.equal(x))
if __name__ == '__main__': if __name__ == '__main__':
unittest.main() unittest.main()
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