results missing, ValueError: Input

[maciejkos]

This can be hard to figure out since I can't share the data. I am running it in Google Colab.

automl_grid_search(csv_path='/content/CLT_all_tasks_trial_level.csv', target_field='correctResp', model_name='tpu', tpu_address = tpu_address)

Solving a binary_classification problem, maximizing accuracy using tensorflow.

Modeling with field specifications:
Subject: categorical
Finished: categorical
TrainingDay: categorical
Condition: categorical
CondPrev: categorical
TaskNumber: categorical
TaskId: categorical
TrialNumber: numeric
PresentationStimulus: numeric
StimTime: numeric
RespToTime: numeric
RT: numeric
SubjResp: categorical
OutcomeInt: categorical
TaskOutcomeInt: categorical
StimDim1: categorical
StimDim2: categorical
StimDim3: categorical
StimDim4: categorical
IntendedRule: categorical
Background: categorical
StimDimWord1: categorical
StimDimWord2: categorical
StimDimWord3: categorical
StimDimWord4: categorical
ExpResp: categorical
DistinctDays: categorical
out: categorical
StimType: categorical
0% 0/100 [00:00<?, ?trial/s]
0% 0/20 [00:00<?, ?epoch/s]
---------------------------------------------------------------------------
IndexError                                Traceback (most recent call last)
<ipython-input-16-ca69e1157d4e> in <module>()
      2                    target_field='correctResp',
      3                    model_name='tpu',
----> 4                    tpu_address = tpu_address)

/usr/local/lib/python3.6/dist-packages/automl_gs/automl_gs.py in automl_grid_search(csv_path, target_field, target_metric, framework, model_name, context, num_trials, split, num_epochs, col_types, gpu, tpu_address)
     92                     header=(best_result is None))
     93 
---> 94         train_results = results.tail(1).to_dict('records')[0]
     95 
     96         # If the target metric improves, save the new hps/files,

IndexError: list index out of range

Here is the log.

Apr 3, 2019, 5:31:44 PM | WARNING | ValueError: Input contains NaN, infinity or a value too large for dtype('float32').
-- | -- | --
Apr 3, 2019, 5:31:44 PM | WARNING | raise ValueError(msg_err.format(type_err, X.dtype))
Apr 3, 2019, 5:31:44 PM | WARNING | File "/usr/local/lib/python3.6/dist-packages/sklearn/utils/validation.py", line 56, in _assert_all_finite
Apr 3, 2019, 5:31:44 PM | WARNING | allow_nan=force_all_finite == 'allow-nan')
Apr 3, 2019, 5:31:44 PM | WARNING | File "/usr/local/lib/python3.6/dist-packages/sklearn/utils/validation.py", line 573, in check_array
Apr 3, 2019, 5:31:44 PM | WARNING | y_pred = check_array(y_pred, ensure_2d=False)
Apr 3, 2019, 5:31:44 PM | WARNING | File "/usr/local/lib/python3.6/dist-packages/sklearn/metrics/classification.py", line 1763, in log_loss
Apr 3, 2019, 5:31:44 PM | WARNING | logloss = log_loss(y_true, y_pred)
Apr 3, 2019, 5:31:44 PM | WARNING | File "/content/tpu_train/pipeline.py", line 1126, in on_epoch_end
Apr 3, 2019, 5:31:44 PM | WARNING | callback.on_epoch_end(epoch, logs)
Apr 3, 2019, 5:31:44 PM | WARNING | File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/callbacks.py", line 251, in on_epoch_end
Apr 3, 2019, 5:31:44 PM | WARNING | callbacks.on_epoch_end(epoch, epoch_logs)
Apr 3, 2019, 5:31:44 PM | WARNING | File "/usr/local/lib/python3.6/dist-packages/tensorflow/contrib/tpu/python/tpu/keras_support.py", line 1734, in _pipeline_fit_loop
Apr 3, 2019, 5:31:44 PM | WARNING | validation_steps=validation_steps)
Apr 3, 2019, 5:31:44 PM | WARNING | File "/usr/local/lib/python3.6/dist-packages/tensorflow/contrib/tpu/python/tpu/keras_support.py", line 1633, in _pipeline_fit
Apr 3, 2019, 5:31:44 PM | WARNING | steps_per_epoch, validation_steps, **kwargs)
Apr 3, 2019, 5:31:44 PM | WARNING | File "/usr/local/lib/python3.6/dist-packages/tensorflow/contrib/tpu/python/tpu/keras_support.py", line 1532, in fit
Apr 3, 2019, 5:31:44 PM | WARNING | batch_size=64 * 8)
Apr 3, 2019, 5:31:44 PM | WARNING | File "/content/tpu_train/pipeline.py", line 1095, in model_train
Apr 3, 2019, 5:31:44 PM | WARNING | model_train(df, encoders, args, model)
Apr 3, 2019, 5:31:44 PM | WARNING | File "model.py", line 69, in <module>
Apr 3, 2019, 5:31:44 PM | WARNING | Traceback (most recent call last):

AFAIK, the largest number in the dataset is 12007245.

Thanks for the help!

[tayiorbeii]

I've actually seen a similar problem, and I am currently preparing an example to share (watch as it works this time!)

[tayiorbeii]

Here's a gist with train and test files.

I ran the following command to target the result column:

automl_gs train.csv result --model_name broken_example --framework xgboost --num_trials 100

then with test.csv in the broken_example_xgboost folder, run this command to check:

python3 model.py -d test.csv -m predict

Output is as follows:

error_example/broken_example_xgboost_20190404_233918 » python3 model.py -d test_pdb.csv -m predict
Traceback (most recent call last):
  File "model.py", line 55, in <module>
    predictions = model_predict(df, model, encoders)
  File "error_example/broken_example_xgboost_20190404_233918/pipeline.py", line 341, in model_predict
    data_enc = process_data(df, encoders, process_target=False)
  File "error_example/broken_example_xgboost_20190404_233918/pipeline.py", line 275, in process_data
    col4_enc = encoders['col4_encoder'].transform(col4_enc)
  File "/usr/local/lib/python3.7/site-packages/sklearn/preprocessing/label.py", line 467, in transform
    sparse_output=self.sparse_output)
  File "/usr/local/lib/python3.7/site-packages/sklearn/preprocessing/label.py", line 581, in label_binarize
    y = check_array(y, accept_sparse='csr', ensure_2d=False, dtype=None)
  File "/usr/local/lib/python3.7/site-packages/sklearn/utils/validation.py", line 573, in check_array
    allow_nan=force_all_finite == 'allow-nan')
  File "/usr/local/lib/python3.7/site-packages/sklearn/utils/validation.py", line 56, in _assert_all_finite
    raise ValueError(msg_err.format(type_err, X.dtype))
ValueError: Input contains NaN, infinity or a value too large for dtype('float64').

I've poked around at it a bit, but I don't really know what I'm doing.

I hope this helps though, and I appreciate your work on this project!

[tayiorbeii]

Adding this line before each encoder transform call in pipeline.py is helping, but annoying to do manually:

whatever_enc = whatever_enc[~np.isnan(whatever_enc)]

...but different errors are good to see!

EDIT: Found some luck by adjusting the training target to "true/false" strings instead of 0/1... not sure if this is a fluke.

EDIT AGAIN: this error can happen if you have a blank entry somewhere in your data. Open your csv file in your favorite editor and search for ,, and either delete the line or fill the cell or a third thing.

[mahesh1amour]

I'm also facing error like

mahesh@mahesh-HP-EliteBook-840-G1:$ pip3 install automl_gs
Collecting automl_gs
Downloading https://files.pythonhosted.org/packages/c4/51/27833a08fe4f83711b09836ddd9128e275a6900c47e0e5782112ed611484/automl_gs-0.2.1.tar.gz
Collecting pandas (from automl_gs)
Cache entry deserialization failed, entry ignored
Using cached https://files.pythonhosted.org/packages/19/74/e50234bc82c553fecdbd566d8650801e3fe2d6d8c8d940638e3d8a7c5522/pandas-0.24.2-cp36-cp36m-manylinux1_x86_64.whl
Collecting scikit-learn (from automl_gs)
Using cached https://files.pythonhosted.org/packages/5e/82/c0de5839d613b82bddd088599ac0bbfbbbcbd8ca470680658352d2c435bd/scikit_learn-0.20.3-cp36-cp36m-manylinux1_x86_64.whl
Collecting autopep8 (from automl_gs)
Collecting tqdm (from automl_gs)
Using cached https://files.pythonhosted.org/packages/6c/4b/c38b5144cf167c4f52288517436ccafefe9dc01b8d1c190e18a6b154cd4a/tqdm-4.31.1-py2.py3-none-any.whl
Collecting jinja2>=2.8 (from automl_gs)
Cache entry deserialization failed, entry ignored
Downloading https://files.pythonhosted.org/packages/1d/e7/fd8b501e7a6dfe492a433deb7b9d833d39ca74916fa8bc63dd1a4947a671/Jinja2-2.10.1-py2.py3-none-any.whl (124kB)
100% |████████████████████████████████| 133kB 436kB/s
Collecting pyyaml (from automl_gs)
Cache entry deserialization failed, entry ignored
Downloading https://files.pythonhosted.org/packages/9f/2c/9417b5c774792634834e730932745bc09a7d36754ca00acf1ccd1ac2594d/PyYAML-5.1.tar.gz (274kB)
100% |████████████████████████████████| 276kB 4.6MB/s
Collecting numpy>=1.12.0 (from pandas->automl_gs)
Cache entry deserialization failed, entry ignored
Using cached https://files.pythonhosted.org/packages/35/d5/4f8410ac303e690144f0a0603c4b8fd3b986feb2749c435f7cdbb288f17e/numpy-1.16.2-cp36-cp36m-manylinux1_x86_64.whl
Collecting python-dateutil>=2.5.0 (from pandas->automl_gs)
Cache entry deserialization failed, entry ignored
Using cached https://files.pythonhosted.org/packages/41/17/c62faccbfbd163c7f57f3844689e3a78bae1f403648a6afb1d0866d87fbb/python_dateutil-2.8.0-py2.py3-none-any.whl
Collecting pytz>=2011k (from pandas->automl_gs)
Cache entry deserialization failed, entry ignored
Using cached https://files.pythonhosted.org/packages/61/28/1d3920e4d1d50b19bc5d24398a7cd85cc7b9a75a490570d5a30c57622d34/pytz-2018.9-py2.py3-none-any.whl
Collecting scipy>=0.13.3 (from scikit-learn->automl_gs)
Using cached https://files.pythonhosted.org/packages/7f/5f/c48860704092933bf1c4c1574a8de1ffd16bf4fde8bab190d747598844b2/scipy-1.2.1-cp36-cp36m-manylinux1_x86_64.whl
Collecting pycodestyle>=2.4.0 (from autopep8->automl_gs)
Using cached https://files.pythonhosted.org/packages/0e/0c/04a353e104d2f324f8ee5f4b32012618c1c86dd79e52a433b64fceed511b/pycodestyle-2.5.0-py2.py3-none-any.whl
Collecting MarkupSafe>=0.23 (from jinja2>=2.8->automl_gs)
Cache entry deserialization failed, entry ignored
Using cached https://files.pythonhosted.org/packages/b2/5f/23e0023be6bb885d00ffbefad2942bc51a620328ee910f64abe5a8d18dd1/MarkupSafe-1.1.1-cp36-cp36m-manylinux1_x86_64.whl
Collecting six>=1.5 (from python-dateutil>=2.5.0->pandas->automl_gs)
Cache entry deserialization failed, entry ignored
Using cached https://files.pythonhosted.org/packages/73/fb/00a976f728d0d1fecfe898238ce23f502a721c0ac0ecfedb80e0d88c64e9/six-1.12.0-py2.py3-none-any.whl
Building wheels for collected packages: automl-gs, pyyaml
Running setup.py bdist_wheel for automl-gs ... done
Stored in directory: /home/mahesh/.cache/pip/wheels/2d/5e/f0/deffbd0fcc4afd6b065366dded7b9c8cd1b7c02f6b39c24552
Running setup.py bdist_wheel for pyyaml ... done
Stored in directory: /home/mahesh/.cache/pip/wheels/ad/56/bc/1522f864feb2a358ea6f1a92b4798d69ac783a28e80567a18b
Successfully built automl-gs pyyaml
Installing collected packages: numpy, six, python-dateutil, pytz, pandas, scipy, scikit-learn, pycodestyle, autopep8, tqdm, MarkupSafe, jinja2, pyyaml, automl-gs
Successfully installed MarkupSafe-1.1.1 automl-gs-0.2.1 autopep8-1.4.3 jinja2-2.10.1 numpy-1.16.2 pandas-0.24.2 pycodestyle-2.5.0 python-dateutil-2.8.0 pytz-2018.9 pyyaml-5.1 scikit-learn-0.20.3 scipy-1.2.1 six-1.12.0 tqdm-4.31.1
mahesh@mahesh-HP-EliteBook-840-G1:$ from automl_gs import automl_grid_search
from: can't read /var/mail/automl_gs
mahesh@mahesh-HP-EliteBook-840-G1:~$ python3

automl_grid_search('/home/mahesh/Documents/Projects/DataX/Venv_programs/Data/Housing.csv','price')
Solving a regression problem, minimizing mse using tensorflow.

Modeling with field specifications:
area: numeric
bedrooms: numeric
bathrooms: categorical
stories: categorical
mainroad: categorical
guestroom: categorical
basement: categorical
hotwaterheating: categorical
airconditioning: categorical
parking: categorical
prefarea: categorical
furnishingstatus: categorical
0%| | 0/100 [00:00<?, ?trial/sTraceback (most recent call last): | 0/20 [00:00<?, ?epoch/s]
File "model.py", line 49, in
build_encoders(df)
File "/home/mahesh/automl_train/pipeline.py", line 209, in build_encoders
mainroad_encoder.fit(mainroad_tf)
File "/home/mahesh/.local/lib/python3.6/site-packages/sklearn/preprocessing/label.py", line 413, in fit
self.classes_ = unique_labels(y)
File "/home/mahesh/.local/lib/python3.6/site-packages/sklearn/utils/multiclass.py", line 96, in unique_labels
raise ValueError("Unknown label type: %s" % repr(ys))
ValueError: Unknown label type: (array([nan, nan, 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes',
'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', nan,
'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes',
'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes',
'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes',
'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes',
'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes',
'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes',
'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes',
'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes',
'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes',
'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes',
'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes',
'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes',
'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes',
'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'no', 'yes', 'yes',
'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes',
'yes', 'yes', 'no', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes',
'yes', 'yes', 'yes', 'yes', 'yes', 'no', 'yes', 'yes', 'yes',
'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'no', 'yes', 'no',
'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'no', 'yes', 'yes',
'yes', 'yes', 'yes', 'yes', 'yes', 'no', 'yes', 'yes', 'yes', 'no',
'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes',
'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes',
'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes',
'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes',
'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes',
'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes',
'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'no', 'yes',
'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'no', 'yes', 'yes',
'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'no',
'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'no', 'yes', 'no',
'no', 'no', 'no', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes',
'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes',
'yes', 'yes', 'yes', 'yes', 'no', 'yes', 'yes', 'yes', 'yes',
'yes', 'yes', 'yes', 'no', 'yes', 'no', 'no', 'no', 'yes', 'yes',
'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes',
'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'no',
'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'no', 'no', 'yes',
'yes', 'yes', 'yes', 'yes', 'yes', 'no', 'yes', 'yes', 'yes', 'no',
'yes', 'yes', 'yes', 'no', 'yes', 'yes', 'yes', 'yes', 'no', 'yes',
'yes', 'yes', 'yes', 'yes', 'yes', 'no', 'yes', 'yes', 'yes',
'yes', 'yes', 'no', 'yes', 'yes', 'no', 'no', 'yes', 'yes', 'yes',
'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'no', 'yes', 'yes',
'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes',
'yes', 'yes', 'yes', 'no', 'yes', 'yes', 'no', 'yes', 'no', 'yes',
'no', 'yes', 'yes', 'yes', 'no', 'yes', 'yes', 'no', 'yes', 'yes',
'yes', 'yes', 'no', 'no', 'yes', 'yes', 'yes', 'no', 'no', 'yes',
'no', 'no', 'yes', 'no', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes',
'yes', 'no', 'yes', 'yes', 'yes', 'yes', 'no', 'yes', 'yes', 'yes',
'no', 'yes', 'yes', 'yes', 'no', 'yes', 'yes', 'yes', 'no', 'yes',
'yes', 'yes', 'no', 'no', 'no', 'no', 'no', 'yes', 'no', 'yes',
'yes', 'yes', 'yes', 'no', 'no', 'no', 'yes', 'yes', 'yes', 'yes',
'yes', 'yes', 'yes', 'no', 'yes', 'no', 'yes', 'yes', 'yes', 'yes',
'no', 'yes', 'yes', 'yes', 'no', 'no', 'yes', 'yes', 'no', 'yes',
'no', 'yes', 'yes', 'yes', 'yes', 'no', 'yes', 'yes', 'yes', 'yes',
'yes', 'no', 'no', 'yes', 'no', 'no', 'no', 'yes', 'yes', 'yes',
'no', 'yes', 'yes', 'no', 'yes', 'no', 'yes', 'no', 'yes'],
dtype=object),)
Traceback (most recent call last): | 0/20 [00:00<?, ?epoch/s]
File "", line 1, in
File "/home/mahesh/.local/lib/python3.6/site-packages/automl_gs/automl_gs.py", line 87, in automl_grid_search
"metadata", "results.csv"))
File "/home/mahesh/.local/lib/python3.6/site-packages/pandas/io/parsers.py", line 702, in parser_f
return _read(filepath_or_buffer, kwds)
File "/home/mahesh/.local/lib/python3.6/site-packages/pandas/io/parsers.py", line 429, in _read
parser = TextFileReader(filepath_or_buffer, **kwds)
File "/home/mahesh/.local/lib/python3.6/site-packages/pandas/io/parsers.py", line 895, in init
self._make_engine(self.engine)
File "/home/mahesh/.local/lib/python3.6/site-packages/pandas/io/parsers.py", line 1122, in _make_engine
self._engine = CParserWrapper(self.f, **self.options)
File "/home/mahesh/.local/lib/python3.6/site-packages/pandas/io/parsers.py", line 1853, in init
self._reader = parsers.TextReader(src, **kwds)
File "pandas/_libs/parsers.pyx", line 387, in pandas._libs.parsers.TextReader.cinit
File "pandas/_libs/parsers.pyx", line 705, in pandas._libs.parsers.TextReader._setup_parser_source
FileNotFoundError: [Errno 2] File b'automl_train/metadata/results.csv' does not exist: b'automl_train/metadata/results.csv'