base_layers.py中：embedding 的call
def call(self, inputs):
shape = inputs.shape
inputs = tf.reshape(inputs,[-1])
output_shape = shape.concatenate(self.dim)
output_shape = [d if d is not None else -1 for d in output_shape.as_list()] #//tensorshape->[,,] list
return tf.reshape(tf.nn.embedding_lookup(self.embeddings, inputs),output_shape)

**GraphSage-ShallowEncoder e

Description

Currently our unit tests are disorganized and each test creates example StellarGraph graphs in different or similar ways with no sharing of this code.

This issue is to improve the unit tests by making functions to create example graphs available to all unit tests by, for example, making them pytest fixtures at the top level of the tests (see https://docs.pytest.org/en/latest/

读了你的源码，关于这些矩阵names = ['x','y','tx','ty','allx','ally','adj']分别代表什么？
比如allx => the feature vectors of both labeled and unlabeled training docs/words，你的实验数据不都是有标签的嘛，为什么会有unlabeled training docs？
你在论文中说你的节点初始化为one-hot向量，而我在代码中看到你用word嵌入的平均作为doc嵌入输入，这是为什么？the one-hot labels of the labeled training docs又代表什么？
关于这些x,y,tx,ty等等，我比较难懂，请求您抽出时间为我解答，非常感谢

nowadays, docs with rarely interpretation is difficult to understand the algorithm,
Such as bayes rule sets and other Underdogs have little references.
If can provide a common introduce in interface level may be good for programmers
who have little information of algorithm to start

When following NFP's homo prediction tutorial, recieved the following error

ValueError: Object arrays cannot be loaded when allow_pickle=False

When ran the following code

from chainer.datasets import split_dataset_random
from chainer_chemistry import datasets as D
from chainer_chemistry.dataset.preprocessors import preprocess_method_dict
from chainer_chemistry.datasets import Nu

The README.md describes what KGCN is, but it does not describe how it will be beneficial for users.

We should have a use-case section describing the kind of problems in which KGCN makes sense as a solution.

I viewed the whole code and found that the code only use toy dummy data to train model. So I don't really understand how you use those data to train GCN model. Can you supply the code or instructions about how to use real-world data to train model?