def __call__(self, h_img, pcd):
B = h_img.shape[0]
# conv1
h_img = F.relu(self.conv1_img(h_img))
h_pcd = F.relu(self.conv1_pcd(pcd))
feat1 = F.concat((h_pcd, h_img), axis=1)
# conv2
h_img = F.relu(self.conv2_img(h_img))
h_pcd = F.relu(self.conv2_pcd(h_pcd))
feat2 = F.concat((h_pcd, h_img), axis=1)
# conv3, conv4
feat3 = F.concat((feat1, feat2), axis=1)
h = F.relu(self.conv3(feat3))
h = F.relu(self.conv4(h))
h = F.average_pooling_1d(h, self.n_point)
h = h.reshape((B, 1024))
return h
def __call__(self, h_rgb, pcd):
B, _, n_point = h_rgb.shape
# conv1
h_rgb = F.relu(self.conv1_rgb(h_rgb))
h_pcd = F.relu(self.conv1_pcd(pcd))
feat1 = F.concat((h_rgb, h_pcd), axis=1)
# conv2
h_rgb = F.relu(self.conv2_rgb(h_rgb))
h_pcd = F.relu(self.conv2_pcd(h_pcd))
feat2 = F.concat((h_rgb, h_pcd), axis=1)
# conv3, conv4
h = F.relu(self.conv3(feat2))
h = F.relu(self.conv4(h))
h = F.average_pooling_1d(h, n_point)
h = h.reshape((B, 1024, 1))
feat3 = F.repeat(h, n_point, axis=2)
feat = F.concat((feat1, feat2, feat3), axis=1)
return feat
def test_average_pooling_1d_invalid(self):
(x, ksize) = self._get_data(2)
with self.assertRaises(ValueError):
functions.average_pooling_1d(x, ksize)
def test_average_pooling_1d(self):
(x, ksize) = self._get_data(1)
testing.assert_allclose(
functions.average_pooling_nd(x, ksize).data,
functions.average_pooling_1d(x, ksize).data)
def test_average_pooling_1d_invalid(self):
(x, ksize) = self._get_data(2)
with pytest.raises(ValueError):
functions.average_pooling_1d(x, ksize)
def test_average_pooling_1d(self):
(x, ksize) = self._get_data(1)
testing.assert_allclose(
functions.average_pooling_nd(x, ksize).array,
functions.average_pooling_1d(x, ksize).array)
