def _test_fuse_conv(self,
conv_args,
bn_args,
relu_args,
bn_class,
input_size,
device="cpu"):
cbr = bb.ConvBNRelu(
3,
6,
kernel_size=3,
padding=1,
conv_args=conv_args,
bn_args=bn_args,
relu_args=relu_args,
).to(device)
for _ in range(3):
inputs = torch.rand(input_size).to(device)
cbr(inputs)
cbr.eval()
fused = fuse_utils.fuse_convbnrelu(cbr, inplace=False)
self.assertTrue(_find_modules(cbr, bn_class))
self.assertFalse(_find_modules(fused, bn_class))
run_and_compare(cbr, fused, input_size, device)
def test_conv_bn_relu_upsample_empty_input(self):
op = bb.ConvBNRelu(4, 4, stride=-2, kernel_size=3, padding=1)
input_size = [0, 4, 4, 4]
inputs = torch.rand(input_size)
output = op(inputs)
self.assertEqual(output.shape, torch.Size([0, 4, 8, 8]))
def __init__(self, in_channels, out_channels, *,
check_out_channels, **kwargs):
super().__init__()
assert kwargs["width_divisor"] == WIDTH_DIVISOR
self.check_out_channels = check_out_channels
self.conv = basic_blocks.ConvBNRelu(in_channels, out_channels,
**kwargs)
def test_conv_bn_relu_upsample(self):
# currently empty batch for dw conv is not supported
op = bb.ConvBNRelu(4, 4, stride=-2, kernel_size=3, padding=1)
input_size = [1, 4, 4, 4]
inputs = torch.rand(input_size)
output = op(inputs)
self.assertEqual(output.shape, torch.Size([1, 4, 8, 8]))
def test_conv_bn_relu_empty_input(self):
# currently empty batch for dw conv is not supported
op = bb.ConvBNRelu(4, 4, stride=2, kernel_size=3, padding=1, groups=4)
input_size = [0, 4, 4, 4]
inputs = torch.rand(input_size)
output = op(inputs)
self.assertEqual(output.shape, torch.Size([0, 4, 2, 2]))
input_size = [2, 4, 4, 4]
inputs = torch.rand(input_size)
output = op(inputs)
self.assertEqual(output.shape, torch.Size([2, 4, 2, 2]))
def test_fuse_convbnrelu(self):
cbr = bb.ConvBNRelu(3,
6,
kernel_size=3,
padding=1,
bn_args="bn",
relu_args="relu").eval()
fused = fuse_utils.fuse_convbnrelu(cbr, inplace=False)
self.assertTrue(_find_modules(cbr, torch.nn.BatchNorm2d))
self.assertFalse(_find_modules(fused, torch.nn.BatchNorm2d))
input_size = [2, 3, 7, 7]
run_and_compare(cbr, fused, input_size)
def __init__(self):
super().__init__()
cbr = bb.ConvBNRelu(3, 6, kernel_size=3, bn_args="bn")
self.cbr = cbr
self.cbr_list = [cbr]
