Questions about JNSKR source code
liulu1998 opened this issue · 5 comments
-
What's the meaning of
max_user_piandmax_relation_piin JNSKR ? -
What's the meaning of
pos_num_randpos_num_uin JNSKR ?
Line 85 in c9c2bca
Line 105 in c9c2bca
- It seems that the way calculating Attention Weight in your code is NOT the same as Equ. (11)
Lines 62 to 65 in c9c2bca
I'm working on a project about knowledge-enhanced RS and deeply interested in your work.
Thanks for your time and patience, looking forward to your reply.
Hi, thank you for your interest in our work!
为了说的清楚点，也节省时间，我直接用中文解答一下吧，
1、max_user_pi，是对于每个商品，最多的交互用户的数量；max_relation_pi是对于每个商品最多的交互关系数量。因为tensorflow中的输入需要是一个对齐的tensor, 所以我们输入的每个训练batch的shape为 [batch_size, max_user_pi]，对于数量不足的商品，我们用“self.n_users”补齐。
2、因为我们的输入tensor是补齐的，所以首先用 tf.cast(tf.not_equal(self.input_iu, self.n_users)操作来所补得“self.n_users”置为0，这样就不会被更新计算到。
3、这两种计算attention的方法基本上没啥区别，可以互换。
@chenchongthu
谢谢你的回复！我懂了。
我又有一个问题： L2 正则化 是否要计算 H_i ？ 此处并没有计算 H_i 的范数 ↓
Line 130 in c9c2bca
H_i 在此处定义的 ↓
Line 50 in c9c2bca
一般情况下大家不对预测层进行L2约束，所以加不加都可以，我们在这篇文章中基本上是用dropout来防止过拟合的，所以L2在这个工作里影响不大
你好，我想问一下，我在把Main_JNSKR.py代码里的数据集路径从amazon-book改到yelp2018的时候会报错。
`Traceback (most recent call last):
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py", line 1334, in _do_call
return fn(*args)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py", line 1319, in _run_fn
options, feed_dict, fetch_list, target_list, run_metadata)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py", line 1407, in _call_tf_sessionrun
run_metadata)
tensorflow.python.framework.errors_impl.InvalidArgumentError: indices[32] = 45920 is not in [0, 45920)
[[{{node embedding_lookup_9}} = GatherV2[Taxis=DT_INT32, Tindices=DT_INT32, Tparams=DT_FLOAT, _device="/job:localhost/replica:0/task:0/device:CPU:0"](uidWg/read, _arg_users_0_1, embedding_lookup_9/axis)]]
[[{{node embedding_lookup_7/_109}} = _Recvclient_terminated=false, recv_device="/job:localhost/replica:0/task:0/device:GPU:0", send_device="/job:localhost/replica:0/task:0/device:CPU:0", send_device_incarnation=1, tensor_name="edge_23_embedding_lookup_7", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/device:GPU:0"]]
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "Main_JNSKR.py", line 143, in
ret = test(sess, model, users_to_test, item_test)
File "/home/JNSKR/Model/utility/our_test.py", line 148, in test
rate_batch = model.eval(sess, feed_dict=feed_dict)
File "/home/JNSKR/Model/JNSKR.py", line 141, in eval
batch_predictions = sess.run(self.batch_predictions, feed_dict)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py", line 929, in run
run_metadata_ptr)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py", line 1152, in _run
feed_dict_tensor, options, run_metadata)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py", line 1328, in _do_run
run_metadata)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py", line 1348, in _do_call
raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.InvalidArgumentError: indices[32] = 45920 is not in [0, 45920)
[[node embedding_lookup_9 (defined at /home/JNSKR/Model/JNSKR.py:156) = GatherV2[Taxis=DT_INT32, Tindices=DT_INT32, Tparams=DT_FLOAT, _device="/job:localhost/replica:0/task:0/device:CPU:0"](uidWg/read, _arg_users_0_1, embedding_lookup_9/axis)]]
[[{{node embedding_lookup_7/_109}} = _Recvclient_terminated=false, recv_device="/job:localhost/replica:0/task:0/device:GPU:0", send_device="/job:localhost/replica:0/task:0/device:CPU:0", send_device_incarnation=1, tensor_name="edge_23_embedding_lookup_7", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/device:GPU:0"]]
Caused by op 'embedding_lookup_9', defined at:
File "Main_JNSKR.py", line 97, in
model._build_graph()
File "/home/JNSKR/Model/JNSKR.py", line 167, in _build_graph
self._creat_prediction()
File "/home/JNSKR/Model/JNSKR.py", line 156, in _creat_prediction
u_e = tf.nn.embedding_lookup(self.uid_W, self.users)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/ops/embedding_ops.py", line 313, in embedding_lookup
transform_fn=None)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/ops/embedding_ops.py", line 133, in _embedding_lookup_and_transform
result = _clip(array_ops.gather(params[0], ids, name=name),
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/ops/array_ops.py", line 2675, in gather
return gen_array_ops.gather_v2(params, indices, axis, name=name)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/ops/gen_array_ops.py", line 3332, in gather_v2
"GatherV2", params=params, indices=indices, axis=axis, name=name)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/op_def_library.py", line 787, in _apply_op_helper
op_def=op_def)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/util/deprecation.py", line 488, in new_func
return func(*args, **kwargs)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/ops.py", line 3274, in create_op
op_def=op_def)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/ops.py", line 1770, in init
self._traceback = tf_stack.extract_stack()
InvalidArgumentError (see above for traceback): indices[32] = 45920 is not in [0, 45920)
[[node embedding_lookup_9 (defined at /home/JNSKR/Model/JNSKR.py:156) = GatherV2[Taxis=DT_INT32, Tindices=DT_INT32, Tparams=DT_FLOAT, _device="/job:localhost/replica:0/task:0/device:CPU:0"](uidWg/read, _arg_users_0_1, embedding_lookup_9/axis)]]
[[{{node embedding_lookup_7/_109}} = _Recvclient_terminated=false, recv_device="/job:localhost/replica:0/task:0/device:GPU:0", send_device="/job:localhost/replica:0/task:0/device:CPU:0", send_device_incarnation=1, tensor_name="edge_23_embedding_lookup_7", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/device:GPU:0"]]`
请问更换数据集跑实验是不是还有其他地方需要改动呢？不好意思我现在对TensorFlow的使用还不是很熟悉。
你好，更换数据集需要更改两个地方，一个是Main_JNSKR.py代码里，另一个是utility下的parser.py里：
parser.add_argument('--dataset', nargs='?', default='amazon-book',
help='Choose a dataset from {yelp2018, last-fm, amazon-book}')