FPFH descriptor and Deep Learning Using Tensorflow

Hi guys, I'm sorry for the inconvenience. I would like to understand how to use open3D codes with tensorflow. Can anybody help me? An example below:
```
def fpfh(vector):
lf = []
x,bat=vector
for LF in range(bat):
Cloud=x[LF]
pcd = o3d.geometry.PointCloud()
pcd.points = o3d.utility.Vector3dVector(Cloud)
#np.asarray(pcd.points)
voxel_size = 0.05 # means 5cm for the dataset
radius_normal = voxel_size * 2
pcd.estimate_normals(o3d.geometry.KDTreeSearchParamHybrid(radius=radius_normal, max_nn=30))
radius_feature = voxel_size * 5
pcd_fpfh = o3d.pipelines.registration.compute_fpfh_feature(pcd,o3d.geometry.KDTreeSearchParamHybrid(radius=radius_feature, max_nn=100))
localfeature = pcd_fpfh.data
localfeature = StandardScaler().fit_transform(localfeature)
localfeature = localfeature.T
lf.append(localfeature)
xlf=np.array(lf)
return xlf