I have tried to run "neptune send experiment_manager.py --environment keras-2.0-gpu-py3 --worker gcp-gpu-medium --config neptune_config.yaml -- train_evaluate_predict_pipeline --pipeline_name glove_lstm"

but got lots of package installation issues. I tried to comment out some in requirements.txt, but seems they are so many. Any solution for this? Or I just missed something in configuration? Thanks.

Hi, I was able to run all models locally (run_end_to_end.sh) but weren't able to run catboost on top of the models.

TypeError: fit() missing 1 required positional argument: 'validation_data'

It looks like I am missing something. Is it possible to reproduce your pipeline without loading data from the cloud?

When I run command "neptune login" I got nothing but "Unable to access auth server. Login url is incorrect" Is there anything wrong with the server?

Found bugs:

1. missing "," in the end of line 28 in file "pipeline_config.py".
2. missing "import nltk" in file "/steps/preprocessing.py".

Error:

1. FileNotFoundError 30.2639 | /usr/local/lib/python3.6/dist-packages/h5py/init.py:36: FutureWarning: Conversion of the second argument of issubdtype from float to np.floating is deprecated. In future, it will be treated as np.float64 == np.dtype(float).type. 30.26557 | from ._conv import register_converters as register_converters 30.417965 | Using TensorFlow backend. 35.018845 | Traceback (most recent call last): 35.019116 | File "/usr/local/lib/python3.6/dist-packages/deepsense/neptune/job_wrapper.py", line 113, in 35.019273 | execute() 35.019429 | File "/usr/local/lib/python3.6/dist-packages/deepsense/neptune/job_wrapper.py", line 109, in execute 35.019568 | execfile(job_filepath, job_globals) 35.019697 | File "/usr/local/lib/python3.6/dist-packages/past/builtins/misc.py", line 82, in execfile 35.019829 | exec(code, myglobals, mylocals) 35.019959 | File "main.py", line 12, in 35.020092 | from pipelines import PIPELINES 35.020226 | File "/neptune/pipelines.py", line 8, in 35.020365 | from steps.preprocessing import XYSplit, TextCleaner, TfidfVectorizer, WordListFilter, Normalizer, TextCounter,
   35.020523 | File "/neptune/steps/preprocessing.py", line 24, in 35.020654 | with open('../external_data/apostrophes.json', 'r') as f: 35.020784 | FileNotFoundError: [Errno 2] No such file or directory: '../external_data/apostrophes.json'

 After I copy the data from that file into the code as following, another error pops up. #with open('../external_data/apostrophes.json', 'r') as f: # APPO = json.load(f) APPO = { "arent": "are not", ..., "well": "will" }

2. TypeError 645.742938 Traceback (most recent call last): 645.743234 File "/usr/local/lib/python3.6/dist-packages/deepsense/neptune/job_wrapper.py", line 113, in 645.743377 execute() 645.74352 File "/usr/local/lib/python3.6/dist-packages/deepsense/neptune/job_wrapper.py", line 109, in execute 645.743696 execfile(job_filepath, job_globals) 645.743897 File "/usr/local/lib/python3.6/dist-packages/past/builtins/misc.py", line 82, in execfile 645.744034 exec_(code, myglobals, mylocals) 645.744164 File "main.py", line 382, in 645.744294 action() 645.744436 File "/usr/local/lib/python3.6/dist-packages/click/core.py", line 722, in call 645.744561 return self.main(*args, **kwargs) 645.744717 File "/usr/local/lib/python3.6/dist-packages/click/core.py", line 697, in main 645.744849 rv = self.invoke(ctx) 645.744996 File "/usr/local/lib/python3.6/dist-packages/click/core.py", line 1066, in invoke 645.745155 return _process_result(sub_ctx.command.invoke(sub_ctx)) 645.745335 File "/usr/local/lib/python3.6/dist-packages/click/core.py", line 895, in invoke 645.745471 return ctx.invoke(self.callback, **ctx.params) 645.745602 File "/usr/local/lib/python3.6/dist-packages/click/core.py", line 535, in invoke 645.745742 return callback(*args, **kwargs) 645.745871 File "main.py", line 129, in train_evaluate_predict_pipeline 645.746002 _train_pipeline(pipeline_name) 645.746266 File "main.py", line 68, in _train_pipeline 645.746432 _ = pipeline.fit_transform(data) 645.746566 File "/neptune/steps/base.py", line 71, in fit_transform 645.746704 step_inputs[input_step.name] = input_step.fit_transform(data) 645.746835 File "/neptune/steps/base.py", line 77, in fit_transform 645.746964 step_output_data = self._cached_fit_transform(step_inputs) 645.747093 File "/neptune/steps/base.py", line 91, in _cached_fit_transform 645.747223 step_output_data = self.transformer.fit_transform(**step_inputs) 645.747351 File "/neptune/steps/base.py", line 213, in fit_transform 645.747482 self.fit(*args, **kwargs) 645.747618 File "/neptune/models.py", line 54, in fit 645.747749 self.callbacks = self._create_callbacks(**self.callbacks_config) 645.747895 File "/neptune/models.py", line 30, in _create_callbacks 645.748021 neptune = NeptuneMonitor(**kwargs['neptune_monitor']) 645.748166 File "/neptune/steps/keras/callbacks.py", line 11, in init 645.748296 self.batch_loss_channel_name = get_correct_channel_name(self.ctx, 'Batch Log-loss training') 645.748426 File "/neptune/steps/keras/callbacks.py", line 38, in get_correct_channel_name 645.748554 channels_with_name = [channel for channel in ctx.job._channels if name in channel.name] 645.74869 File "/usr/local/lib/python3.6/dist-packages/deepsense/neptune/client_library/context_factory.py", line 91, in job 645.748819 , JobPropertyDeprecationWarning) 645.748948 File "/usr/local/lib/python3.6/dist-packages/deepsense/neptune/common/utils/neptune_warnings.py", line 52, in neptune_warn 645.749108 warnings.warn(message, warning_type) 645.749242 File "/usr/lib/python3.6/warnings.py", line 101, in _showwarnmsg 645.749421 _showwarnmsg_impl(msg) 645.749568 File "/usr/lib/python3.6/warnings.py", line 28, in _showwarnmsg_impl 645.749706 text = _formatwarnmsg(msg) 645.749838 File "/usr/lib/python3.6/warnings.py", line 116, in _formatwarnmsg 645.749987 msg.filename, msg.lineno, line=msg.line) 645.75013 TypeError: custom_formatwarning() got an unexpected keyword argument 'line'

How should I get it running successfully? I am running on Neptune using command "neptune send --environment keras-2.0-gpu-py3 --worker gcp-gpu-medium -- train_evaluate_predict_pipeline --pipeline_name glove_lstm". I've tried other pipeline, all fail :(

Hi,

I tried the notebook neptune_ensembling.ipynb on neptune, but I got this error message: ... ModuleNotFoundError: No module named 'seaborn'

I am not sure which combination of worker type, Python version and leading library I should use where this seaborn module is installed. Thanks.

How can I run this code on the local machine? Accordance with your wiki, file experiment_manager.py exists in the repo and I should use it. But I don't see it. Could you help me?

https://github.com/neptune-ml/kaggle-toxic-starter/wiki/Experimentation-guideline

Hi, how do we add a command line parameter to the select the GPU at run time, especially on amulti gpu machine? I tried adding

@action.command()

@click.option('-g', '--gpu', help='select gpu', default=1, required=true)
def select_gpu(gpu):
    os.environ["CUDA_VISIBLE_DEVICES"]=gpu

I tried to add a similar code block for train_evaluate_predict_pipeline and pass the gpu parameter but i keep getting invalid option during runtime. I know its not the package issue, but the documentation did not help either

When I tried to run $ neptune send experiment_manager.py --environment keras-2.0-gpu-py3 --worker gcp-gpu-medium --config neptune_config.yaml -- train_evaluate_predict_pipeline --pipeline_name glove_lstm, the experiment failed because it failed to import attrdict.

However, this lib is already written in the requirements, and I guess somehow the program failed to check the requirements?

The test data in /public folder is old and so the submission output is generated for old test data. The test data for this competition has been recently changed.

Bumps numpy from 1.21.0 to 1.22.0.

Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting @dependabot rebase.

Bumps ipython from 6.2.1 to 7.16.3.

Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting @dependabot rebase.

Hope to see your final solution to the problem......And thanks for providing the environment for running the models...it made a lot of difference in running massive stackers :)