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redshells's Issues

tf.Session is deprecated.

warning now comes out.

W1022 09:22:52.705346 4633392576 deprecation_wrapper.py:119] From python3.6/site-packages/redshells-0.1.7-py3.6.egg/redshells/model/early_stopping.py:19: The name tf.Session is deprecated. Please use tf.compat.v1.Session instead.

Pipeline between Train and Optimize task are not connected

Hi,

Thanks for presenting examples of important tasks in machine learning, OptimizeTask and TrainTask.
I want to know how I can all task by running only TrainTask in below code.

https://github.com/yamasakih/redshells/blob/feature/add-thunderbolt-example/examples/thunderbolt_example.py

This code is based on the following site.
https://github.com/vaaaaanquish/gokart_redshells_thunderbolt_example/blob/master/Example.ipynb

When I ran TrainTask, gokart raised below error.

[2019-11-12 22:08:40,934][WARNING](worker.py:658) Will not run sample.TrainXGBoostModel(n_estimators=50, test_size=0.2) or any dependencies due to error in complete() method:
Traceback (most recent call last):
  File "/Users/yamasakih/anaconda3/envs/gokart/lib/python3.7/site-packages/luigi/worker.py", line 409, in check_complete
    is_complete = task.complete()
  File "/Users/yamasakih/anaconda3/envs/gokart/lib/python3.7/site-packages/gokart/task.py", line 69, in complete
    is_completed = all([t.exists() for t in luigi.task.flatten(self.output())])
  File "thunderbolt_example.py", line 104, in output
    return self.make_target('TrainXGBoostModel.pkl')
  File "/Users/yamasakih/anaconda3/envs/gokart/lib/python3.7/site-packages/gokart/task.py", line 102, in make_target
    unique_id = self.make_unique_id() if use_unique_id else None
  File "/Users/yamasakih/anaconda3/envs/gokart/lib/python3.7/site-packages/gokart/task.py", line 182, in make_unique_id
    self.task_unique_id = self.task_unique_id or self._make_hash_id()
  File "/Users/yamasakih/anaconda3/envs/gokart/lib/python3.7/site-packages/gokart/task.py", line 191, in _make_hash_id
    dependencies = [_to_str_params(task) for task in luigi.task.flatten(self.requires())]
  File "thunderbolt_example.py", line 93, in requires
    param = self.clone(OptimizeXGBoostModel).load()
  File "/Users/yamasakih/anaconda3/envs/gokart/lib/python3.7/site-packages/gokart/task.py", line 146, in load
    return _load(self._get_input_targets(target))
  File "/Users/yamasakih/anaconda3/envs/gokart/lib/python3.7/site-packages/gokart/task.py", line 144, in _load
    return targets.load()
  File "/Users/yamasakih/anaconda3/envs/gokart/lib/python3.7/site-packages/gokart/target.py", line 58, in load
    with self._target.open('r') as f:
  File "/Users/yamasakih/anaconda3/envs/gokart/lib/python3.7/site-packages/luigi/local_target.py", line 165, in open
    fileobj = FileWrapper(io.BufferedReader(io.FileIO(self.path, mode)))
FileNotFoundError: [Errno 2] No such file or directory: './resources/model/OptimizeXGBoostModel_c3153844698935b3eb1eb42d91e218fb.pkl'

So, I have to run OptimizeTask, and next run TrainTask. It takes a little time :(

I'd like you to tell me if better coding works. Thank you in advance!

Use default user index

When flag with_user_embedding is False, using default user index would be better rather than using index zero.

Return of TravisCI

Because change GitHub rate structure, we need to go back to TravisCI from GitHub Actions.

_人人人人人人人人人人人_
> Deadline is 11/13. <
 ̄Y^Y^Y^Y^Y^Y^Y^Y^YY^ ̄

Indexing scipy.csr_matrix with numpy.ndarray not supported in scipy==1.3.1

matrix[user_indices, item_indices] in graph_convolutional_matrix_completion.py L.404 returns error in scipy==1.3.1, since indexing with numpy.ndarray is not possible.

Possible Solution

  • matrix[len(user_indices), len(item_indices)]
    or
  • specific scipy version as scipy==1.2.1 at redshells/setup.py

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