luozachary / drl-rec Goto Github PK

drl-rec-master/pre_process_data.py这个文件中的错误：
list(map(lambda t: list(np.array(t.split(','), dtype=np.float64)), row[org].split('|')))
AttributeError: ("'int' object has no attribute 'split'", 'occurred at index 0')

在我的电脑上运行出现这样的问题。

I've got this error on "simulator.py", line 20,

init_state = np.array(self.data['state_float'].sample(1).values[0]).reshape((1, 12, 30))
ValueError: cannot reshape array of size 1 into shape (1,12,30)

can you help me?

I'm trying to use the sample data to train the model but I get the following error:

  File "build_estimator.py", line 11, in <module>
    from replay_buffer import RelayBuffer
  File "/.../drl-rec/replay_buffer.py", line 7, in <module>
    from simulator import data
  File "/.../drl-rec/simulator.py", line 6, in <module>
    from pre_process_data import data
  File "/.../drl-rec/pre_process_data.py", line 94, in <module>
    data, recall_data = process_data("train.csv", "embed.csv")
  File "/.../drl-rec/pre_process_data.py", line 29, in process_data
    ], axis=1
  File "/.../anaconda2/envs/tensorflow/lib/python3.7/site-packages/pandas/core/frame.py", line 6487, in apply
    return op.get_result()
  File "/.../envs/tensorflow/lib/python3.7/site-packages/pandas/core/apply.py", line 151, in get_result
    return self.apply_standard()
  File "/.../anaconda2/envs/tensorflow/lib/python3.7/site-packages/pandas/core/apply.py", line 257, in apply_standard
    self.apply_series_generator()
  File "/.../anaconda2/envs/tensorflow/lib/python3.7/site-packages/pandas/core/apply.py", line 286, in apply_series_generator
    results[i] = self.f(v)
  File "/.../drl-rec/pre_process_data.py", line 27, in <lambda>
    list(map(lambda t: list(np.array(t.split(','), dtype=np.float64)), row[org].split('|')))
AttributeError: ("'int' object has no attribute 'split'", 'occurred at index 0')

I found that in the README the elements are separated with ',' but in the sample data they are separated with '|'. I don't know if that is the problem, I think that it could also be that I'm using different versions of the dependencies. It would be nice if you could provide a requirements file with that information.

would you please offer me some training data？

gene_action产生的是id，怎么可以reshape成[a_dim,]传入critic网络的不应该是action对应的权重吗

您好，为什么我在结合数据集训练过程中，reward是越来越高的，但是critic网络的loss却越来越大

Thanks for your work , and I have downloaded this project and plan to run it on my computer. However, I failed in tf12 and tf13. So what is the version of tf in this project, or is there any mistakes of my operations?

Is this a complete implementation of the paper (Deep Reinforcement Learning for List-wise Recommendations)?

Traceback (most recent call last):
File "build_estimator.py", line 398, in
main(args_)
File "build_estimator.py", line 358, in main
env = Simulator()
File "/dockerdata/danielgxu/sucai_paoma/drl-rec-master/simulator.py", line 15, in init
self.init_state = self.reset()
File "/dockerdata/danielgxu/sucai_paoma/drl-rec-master/simulator.py", line 20, in reset
init_state = np.array(self.data['state_float'].sample(1).values[0]).reshape((1, 12, 30))
ValueError: cannot reshape array of size 11 into shape (1,12,30)

"train.csv"还有"embed.csv"里面的数据格式具体是怎样的呢？能截图一下吗？

Is the training data format as follows:

Recall data format and what about the embedding dimension ?

请问能提供work的数据样例吗，谢谢

您好，这写代码是drl for list-wise recommendation 的代码吗？ 最终能跑出结果吗