def test_maxpool(self):
"""
Test maximum pooling layer.
"""
mp = layers.MaxPool((3, 3), (2, 2))
o = mp(torch.randn(1, 2, 32, 64))
self.assertEqual(o.shape, (1, 2, 15, 31))
def build_maxpool(self, input: Tuple[int, int, int, int], block: str) -> Union[Tuple[None, None, None], Tuple[Tuple[int, int, int, int], str, Callable]]:
"""
Builds a maxpool layer.
"""
pattern = re.compile(r'(?P<type>Mp)(?P<name>{\w+})?(\d+),(\d+)(?:,(\d+),(\d+))?')
m = pattern.match(block)
if not m:
return None, None, None
kernel_size = (int(m.group(3)), int(m.group(4)))
stride = (kernel_size[0] if not m.group(5) else int(m.group(5)),
kernel_size[1] if not m.group(6) else int(m.group(6)))
fn = layers.MaxPool(kernel_size, stride)
logger.debug('{}\t\tmaxpool\tkernel {} x {} stride {} x {}'.format(self.idx+1, kernel_size[0], kernel_size[1], stride[0], stride[1]))
return fn.get_shape(input), self.get_layer_name(m.group('type'), m.group('name')), fn
def build_maxpool(
self, input: Tuple[int, int, int, int], blocks: List[str], idx: int
) -> Union[Tuple[None, None, None], Tuple[Tuple[int, int, int, int], str,
Callable]]:
"""
Builds a maxpool layer.
"""
pattern = re.compile(
r'(?P<type>Mp)(?P<name>{\w+})?(\d+),(\d+)(?:,(\d+),(\d+))?')
m = pattern.match(blocks[idx])
if not m:
return None, None, None
kernel_size = (int(m.group(3)), int(m.group(4)))
stride = (kernel_size[0] if not m.group(5) else int(m.group(5)),
kernel_size[1] if not m.group(6) else int(m.group(6)))
fn = layers.MaxPool(kernel_size, stride)
self.idx += 1
logger.debug(
f'{self.idx}\t\tmaxpool\tkernel {kernel_size[0]} x {kernel_size[1]} stride {stride[0]} x {stride[1]}'
)
return fn.get_shape(input), [
VGSLBlock(blocks[idx], m.group('type'), m.group('name'), self.idx)
], fn