def test_downsample(self):
self.assertEqual([10, 16, 16, 3],
infer.downsample([10, 32, 32, 3], [2, 2],
spatial_begin=infer.spatial_begin(
infer.Format.NHWC)))
self.assertEqual([10, 16, 8],
infer.downsample([10, 32, 32], [2, 4],
format=infer.Format.NHWC))
self.assertEqual([10, 3, 8, 16],
infer.downsample([10, 3, 32, 32], [4, 2],
format=infer.Format.NCHW))
def test_upsample(self):
self.assertEqual([10, 64, 64, 3],
infer.upsample([10, 32, 32, 3], [2, 2],
spatial_begin=infer.spatial_begin(
infer.Format.NHWC)))
self.assertEqual([10, 64, 128],
infer.upsample([10, 32, 32], [2, 4],
format=infer.Format.NHWC))
self.assertEqual([10, 3, 128, 64],
infer.upsample([10, 3, 32, 32], [4, 2],
format=infer.Format.NCHW))
def test_resize(self):
self.assertEqual([10, 16, 64, 3],
infer.resize([10, 32, 32, 3], [16, 64],
spatial_begin=infer.spatial_begin(
infer.Format.NHWC)))
self.assertEqual([10, 16, 64],
infer.resize([10, 32, 32], [16, 64],
format=infer.Format.NHWC))
self.assertEqual([10, 3, 16, 64],
infer.resize([10, 3, 32, 32], [16, 64],
format=infer.Format.NCHW))
def test_conv(self):
self.assertEqual([10, 30, 30, 16], infer.conv(input=[10, 32, 32, 3],
filter=[3, 3],
padding=infer.Padding.VALID,
stride=[1, 1],
dilation=[1, 1],
groups=1,
spatial_begin=infer.spatial_begin(infer.Format.NHWC),
channel_axis=infer.channel_axis(infer.Format.NHWC),
output_channels=16))
self.assertEqual([10, 16, 30, 30], infer.conv(input=[10, 3, 32, 32],
filter=[3, 3],
padding=[(0, 0), (0, 0)],
stride=[1, 1],
dilation=[1, 1],
groups=1,
spatial_begin=infer.spatial_begin(infer.Format.NCHW),
channel_axis=infer.channel_axis(infer.Format.NCHW),
output_channels=16))
self.assertEqual([10, 3, 32, 32], infer.conv(input=[10, 16, 30, 30],
filter=[3, 3],
padding=[(0, 0), (0, 0)],
stride=[1, 1],
dilation=[1, 1],
groups=1,
format=infer.Format.NCHW,
output_channels=3,
deconv=True))
self.assertEqual([10, 3, 32, 32], infer.conv(input=[10, 16, 32, 32],
filter=[3, 3],
padding=infer.Padding.SAME_UPPER,
stride=[1, 1],
dilation=[1, 1],
groups=1,
format=infer.Format.NCHW,
output_channels=3))
self.assertEqual([10, 6, 32, 32], infer.conv(input=[10, 3, 32, 32],
filter=[3, 3],
padding=infer.Padding.SAME_LOWER,
stride=[1, 1],
dilation=[1, 1],
groups=0,
format=infer.Format.NCHW,
output_channels=6))
self.assertEqual([10, 16, 32, 32], infer.conv(input=[10, 3, 32, 32],
filter=[3, 3],
padding=infer.Padding.SAME_UPPER,
stride=[1, 1],
dilation=[1, 1],
groups=1,
format=infer.Format.NCHW,
output_channels=16,
deconv=True))
self.assertEqual([10, 16, 64, 64], infer.conv(input=[10, 3, 32, 32],
filter=[3, 3],
padding=infer.Padding.SAME_UPPER,
stride=[2, 2],
dilation=[1, 1],
groups=1,
format=infer.Format.NCHW,
output_channels=16,
deconv=True))
self.assertEqual([10, 16, 65, 65], infer.conv(input=[10, 3, 32, 32],
filter=[3, 3],
padding=infer.Padding.SAME_UPPER,
stride=[2, 2],
dilation=[1, 1],
groups=1,
format=infer.Format.NCHW,
output_channels=16,
output_padding=[(0, 1), (0, 1)],
deconv=True))