search

keras-team / autokeras

AutoML library for deep learning
http://autokeras.com/
Apache License 2.0
9.16k stars 1.4k forks source link

MNIST example fails with a BUS ERROR #118

Closed RomanKoshkin closed 5 years ago

RomanKoshkin commented 6 years ago

Bug Description

When I try to run the example code on the MNIST dataset, ` import autokeras as ak

from keras.datasets import mnist (X_train, Y_train), (X_test, Y_test) = mnist.load_data() X_train = X_train.reshape(X_train.shape + (1,)) X_test = X_test.reshape(X_test.shape + (1,)) clf = ak.ImageClassifier(verbose=True, augment=False) clf.fit(X_train, Y_train) `

it starts but fails with the following following error:

Initializing search. Initialization finished. Training model 0 Traceback (most recent call last): File "", line 1, in File "/opt/conda/lib/python3.6/multiprocessing/spawn.py", line 105, in spawn_main exitcode = _main(fd) File "/opt/conda/lib/python3.6/multiprocessing/spawn.py", line 114, in _main prepare(preparation_data) File "/opt/conda/lib/python3.6/multiprocessing/spawn.py", line 225, in prepare _fixup_main_from_path(data['init_main_from_path']) File "/opt/conda/lib/python3.6/multiprocessing/spawn.py", line 277, in _fixup_main_from_path run_name="__mp_main") File "/opt/conda/lib/python3.6/runpy.py", line 263, in run_path pkg_name=pkg_name, script_name=fname) File "/opt/conda/lib/python3.6/runpy.py", line 96, in _run_module_code mod_name, mod_spec, pkg_name, script_name) File "/opt/conda/lib/python3.6/runpy.py", line 85, in _run_code exec(code, run_globals) File "/home/amplifier/asdf.py", line 9, in clf.fit(X_train, Y_train) File "/opt/conda/lib/python3.6/site-packages/autokeras/image_supervised.py", line 238, in fit run_searcher_once(train_data, test_data, self.path, int(time_remain)) File "/opt/conda/lib/python3.6/site-packages/autokeras/image_supervised.py", line 41, in run_searcher_once searcher.search(train_data, test_data, timeout) File "/opt/conda/lib/python3.6/site-packages/autokeras/search.py", line 165, in search pool = multiprocessing.Pool(1) File "/opt/conda/lib/python3.6/multiprocessing/context.py", line 119, in Pool context=self.get_context()) File "/opt/conda/lib/python3.6/multiprocessing/pool.py", line 174, in init self._repopulate_pool() File "/opt/conda/lib/python3.6/multiprocessing/pool.py", line 239, in _repopulate_pool w.start() File "/opt/conda/lib/python3.6/multiprocessing/process.py", line 105, in start self._popen = self._Popen(self) File "/opt/conda/lib/python3.6/multiprocessing/context.py", line 284, in _Popen return Popen(process_obj) File "/opt/conda/lib/python3.6/multiprocessing/popen_spawn_posix.py", line 32, in init super().init(process_obj) File "/opt/conda/lib/python3.6/multiprocessing/popen_fork.py", line 19, in init__ self._launch(process_obj) File "/opt/conda/lib/python3.6/multiprocessing/popen_spawn_posix.py", line 42, in _launch prep_data = spawn.get_preparation_data(process_obj._name) File "/opt/conda/lib/python3.6/multiprocessing/spawn.py", line 143, in get_preparation_data _check_not_importing_main() File "/opt/conda/lib/python3.6/multiprocessing/spawn.py", line 136, in _check_not_importing_main is not going to be frozen to produce an executable.''') RuntimeError: An attempt has been made to start a new process before the current process has finished its bootstrapping phase.

    This probably means that you are not using fork to start your
    child processes and you have forgotten to use the proper idiom
    in the main module:

        if __name__ == '__main__':
            freeze_support()
            ...

    The "freeze_support()" line can be omitted if the program
    is not going to be frozen to produce an executable.

/opt/conda/lib/python3.6/multiprocessing/semaphore_tracker.py:143: UserWarning: semaphore_tracker: There appear to be 4 leaked semaphores to clean up at shutdown len(cache))

Setup Details

packages in environment at /opt/conda:

#

Name Version Build Channel

absl-py 0.2.2 alembic 0.9.9 py_0 conda-forge appdirs 1.4.3 py36h28b3542_0 anaconda arxiv 0.2.2 asn1crypto 0.24.0 py36_0 anaconda astor 0.7.1 async_generator 1.9 0 conda-forge atari-py 0.1.1 atomicwrites 1.1.5 py36_0 anaconda attrs 18.1.0 py36_0 anaconda audioread 2.1.5 py36_0 conda-forge autokeras 0.2.5 automat 0.7.0 py36_0 anaconda backcall 0.1.0 py_0 conda-forge binutils_impl_linux-64 2.28.1 had2808c_3 anaconda binutils_linux-64 7.2.0 had2808c_27 anaconda bkcharts 0.2 py36_0 anaconda blas 1.0 mkl anaconda bleach 2.1.3 py36_0 anaconda bleach 1.5.0 bokeh 0.13.0 py36_0 anaconda boto 2.48.0 py36_1 anaconda boto3 1.7.45 py36_0 anaconda botocore 1.10.45 py36_0 anaconda Box2D-kengz 2.3.3 bz2file 0.98 py36_1 anaconda bzip2 1.0.6 h14c3975_5 anaconda ca-certificates 2018.4.16 0 conda-forge cairo 1.14.12 h77bcde2_0 defaults catboost 0.9.1.1 py36_1 conda-forge certifi 2018.4.16 py36_0 conda-forge cffi 1.11.5 py36h9745a5d_0 anaconda chardet 3.0.4 py36_0 conda-forge click 6.7 py36_0 anaconda cloudpickle 0.5.3 py36_0 anaconda colorama 0.3.9 conda 4.5.5 py36_0 conda-forge conda-env 2.6.0 0 conda-forge configurable-http-proxy 3.1.0 node8_1 conda-forge constantly 15.1.0 py36h28b3542_0 anaconda cryptography 2.2.2 py36h14c3975_0 anaconda cuda90 1.0 h6433d27_0 pytorch cudatoolkit 9.0 h13b8566_0 anaconda curl 7.60.0 0 conda-forge cycler 0.10.0 py36_0 anaconda Cython 0.28.4 dask-core 0.18.1 py36_0 anaconda dbus 1.13.0 h3a4f0e9_0 conda-forge decorator 4.3.0 py36_0 anaconda dill 0.2.8.2 py36_0 anaconda docutils 0.14 py36_0 anaconda entrypoints 0.2.3 py36_2 anaconda enum34 1.1.6 expat 2.2.5 he0dffb1_0 anaconda fastcache 1.0.2 py36h14c3975_2 anaconda feedparser 5.2.1 ffmpeg 2.8.6 hf82bc7d_7 conda-forge flatbuffers 2015.12.22.1 fontconfig 2.13.0 h074f895_2 conda-forge freetype 2.8.1 0 conda-forge funcsigs 1.0.2 py36_0 anaconda future 0.16.0 py36_1 anaconda gast 0.2.0 gcc_impl_linux-64 7.2.0 habb00fd_3 anaconda gcc_linux-64 7.2.0 h550dcbe_27 anaconda glfw 1.7.0 glib 2.53.6 h5d9569c_2 defaults gmp 6.1.2 hfc679d8_0 conda-forge gmpy2 2.0.8 py36h10f8cd9_2 anaconda graphite2 1.3.11 hfc679d8_0 conda-forge grpcio 1.13.0 gsl 2.1 2 conda-forge gst-plugins-base 1.12.4 h33fb286_0 defaults gstreamer 1.12.4 hb53b477_0 defaults gxx_impl_linux-64 7.2.0 hdf63c60_3 anaconda gxx_linux-64 7.2.0 h550dcbe_27 anaconda gym 0.10.5 h5py 2.8.0 py36h8d01980_0 anaconda harfbuzz 1.7.6 hc5b324e_0 defaults hdf5 1.10.2 hba1933b_1 anaconda html5lib 0.9999999 html5lib 1.0.1 py36_0 anaconda hyperas 0.4 hyperlink 18.0.0 py36_0 anaconda hyperopt 0.1 icu 58.2 h9c2bf20_1 anaconda idna 2.7 py36_0 anaconda imageio 2.3.0 py36_0 anaconda incremental 17.5.0 py36_0 anaconda intel-openmp 2018.0.3 0 anaconda ipykernel 4.8.2 py36_0 anaconda ipython 6.4.0 py36_1 anaconda ipython_genutils 0.2.0 py36_0 anaconda ipyvolume 0.4.6 ipywebrtc 0.3.0 ipywidgets 7.2.1 py36_0 anaconda isodate 0.6.0 py36_0 anaconda isort 4.3.4 jbig 2.1 hdba287a_0 anaconda jedi 0.12.0 py36_1 anaconda jinja2 2.10 py36_0 anaconda jmespath 0.9.3 py36_0 anaconda joblib 0.12 py36_0 anaconda jpeg 9c h470a237_0 conda-forge jsonschema 2.6.0 py36_0 anaconda jupyter 1.0.0 py36_4 anaconda jupyter-tensorboard 0.1.6 jupyter_client 5.2.3 py36_0 anaconda jupyter_console 5.2.0 py36_1 anaconda jupyter_contrib_core 0.3.3 py_2 conda-forge jupyter_contrib_nbextensions 0.5.0 py36_0 conda-forge jupyter_core 4.4.0 py36_0 anaconda jupyter_highlight_selected_word 0.2.0 py36_0 conda-forge jupyter_latex_envs 1.4.4 py36_0 conda-forge jupyter_nbextensions_configurator 0.4.0 py36_0 conda-forge jupyterhub 0.9.1 py36_0 conda-forge jupyterlab 0.32.1 py36_0 conda-forge jupyterlab_launcher 0.10.5 py36_0 conda-forge jupyterthemes 0.19.1 keepalive 0.5 py_1 conda-forge Keras 2.2.2 Keras-Applications 1.0.4 Keras-Preprocessing 1.0.2 kiwisolver 1.0.1 py36hf484d3e_0 anaconda krb5 1.14.6 0 conda-forge lesscpy 0.13.0 libcurl 7.60.0 h1ad7b7a_0 anaconda libedit 3.1.20170329 h6b74fdf_2 anaconda libffi 3.2.1 hd88cf55_4 anaconda libgcc 7.2.0 h69d50b8_2 anaconda libgcc-ng 7.2.0 hdf63c60_3 defaults libgfortran 3.0.0 1 anaconda libgfortran-ng 7.2.0 hdf63c60_3 anaconda libgpuarray 0.7.6 h14c3975_0 anaconda libiconv 1.15 h63c8f33_5 anaconda libpng 1.6.34 hb9fc6fc_0 anaconda librosa 0.6.1 py_1 conda-forge libsodium 1.0.16 h1bed415_0 anaconda libssh2 1.8.0 h9cfc8f7_4 anaconda libstdcxx-ng 7.2.0 hdf63c60_3 defaults libtiff 4.0.9 he85c1e1_1 anaconda libuuid 1.0.3 h1bed415_2 anaconda libxcb 1.13 h1bed415_1 anaconda libxml2 2.9.8 h26e45fe_1 anaconda libxslt 1.1.32 h1312cb7_0 anaconda lightfm 1.15 py36h7eb728f_0 conda-forge llvmlite 0.24.0 py36hdbcaa40_0 anaconda lxml 4.2.2 py36hf71bdeb_0 anaconda magma-cuda90 2.3.0 1 pytorch mako 1.0.7 py36_0 conda-forge Markdown 2.6.11 markupsafe 1.0 py36h14c3975_1 anaconda matlab-kernel 0.15.1 matlabengineforpython R2017b matlabengineforpython R2016a matlabengineforpython R2018a matplotlib 2.2.2 py36h0e671d2_1 defaults metakernel 0.20.14 mistune 0.8.3 py36h14c3975_1 anaconda mkl 2018.0.3 1 anaconda mkl-service 1.1.2 py36h651fb7a_4 anaconda mkl_fft 1.0.2 py36h651fb7a_0 anaconda mkl_random 1.0.1 py36h4414c95_1 anaconda mne 0.16.2 mock 2.0.0 py36_0 anaconda more-itertools 4.2.0 py36_0 anaconda mpc 1.1.0 h10f8cd9_1 anaconda mpfr 4.0.1 hdf1c602_3 anaconda mpmath 1.0.0 py36_2 anaconda mujoco-py 1.50.1.56 nbconvert 5.3.1 py36_0 anaconda nbformat 4.4.0 py36_0 anaconda nccl2 1.0 0 pytorch ncurses 6.1 hf484d3e_0 anaconda networkx 2.1 py36_0 anaconda nibabel 2.3.0 pyh24bf2e0_1 conda-forge nilearn 0.4.2 pyh24bf2e0_0 conda-forge ninja 1.8.2 py36h6bb024c_1 anaconda nipy 0.4.1 py36_1 conda-forge nipype 1.1.0 py36_0 conda-forge nitime 0.7 py36_1 conda-forge niwidgets 0.2.1 nodejs 8.11.3 hf484d3e_0 anaconda nose 1.3.7 py36_2 anaconda notebook 5.6.0 py36_0 anaconda numba 0.39.0 py36h04863e7_0 anaconda numpy 1.14.5 py36h1b885b7_4 anaconda numpy-base 1.14.5 py36hdbf6ddf_4 anaconda olefile 0.45.1 py36_0 anaconda opencv-python 3.4.1.15 openssl 1.0.2o 0 conda-forge packaging 17.1 py36_0 anaconda pamela 0.3.0 py36_0 conda-forge pandas 0.23.3 py36h04863e7_0 anaconda pandoc 2.2.1 0 conda-forge pandocfilters 1.4.2 py36_1 anaconda pango 1.40.14 hd50be51_1 conda-forge parso 0.3.0 py_0 conda-forge path.py 11.0.1 py36_0 anaconda patsy 0.5.0 py36_0 anaconda pbr 4.0.4 py36_0 anaconda pcre 8.39 0 conda-forge pexpect 4.6.0 py36_0 anaconda pickleshare 0.7.4 py36_0 anaconda pillow 5.2.0 py36_0 conda-forge pip 10.0.1 py36_0 anaconda pip 18.0 pixman 0.34.0 2 conda-forge plotly 2.7.0 py36_1 anaconda pluggy 0.6.0 py36_0 anaconda ply 3.11 prometheus_client 0.2.0 py36_0 anaconda prompt_toolkit 1.0.15 py36_0 anaconda protobuf 3.6.0 prov 1.5.0 py36_0 conda-forge psutil 5.4.6 py36h14c3975_0 anaconda ptyprocess 0.6.0 py36_0 anaconda py 1.5.4 py36_0 anaconda pyasn1 0.4.3 py36_0 anaconda pyasn1-modules 0.2.2 py36_0 anaconda pycosat 0.6.3 py36_0 conda-forge pycparser 2.18 py36_1 anaconda pycurl 7.43.0.2 py36hb7f436b_0 anaconda pydicom 1.1.0 py_0 conda-forge pydot 1.2.4 py36_0 anaconda pydotplus 2.0.2 py36_0 anaconda pyglet 1.3.2 pygments 2.2.0 py36_0 anaconda pygpu 0.7.6 py36h035aef0_0 anaconda pymatbridge 0.5.2 pymongo 3.7.1 PyOpenGL 3.1.0 pyopenssl 18.0.0 py36_0 anaconda pyparsing 2.2.0 py36_1 anaconda pyqt 5.9.2 py36h751905a_0 defaults pysocks 1.6.8 py36_1 conda-forge pytest 3.6.2 py36_0 anaconda python 3.6.6 hc3d631a_0 anaconda python-dateutil 2.7.3 py36_0 anaconda python-editor 1.0.3 py36_0 conda-forge python-oauth2 1.0.1 py36_0 conda-forge pytorch 0.4.0 py36_cuda9.0.176_cudnn7.1.2_1 [cuda90] pytorch pytz 2018.5 py36_0 anaconda pywavelets 0.5.2 py36h035aef0_2 anaconda pyyaml 3.12 py36h14c3975_1 anaconda pyzmq 17.0.0 py36h14c3975_3 anaconda qt 5.9.4 h4e5bff0_0 defaults qtconsole 4.3.1 py36_0 anaconda r-abind 1.4_5 r3.4.1_0 conda-forge r-acepack 1.4.1 r3.4.1_0 conda-forge r-assertthat 0.2.0 r3.4.1_0 conda-forge r-backports 1.1.2 r3.4.1_0 conda-forge r-base 3.4.1 hff14c37_5 conda-forge r-base64enc 0.1_3 r3.4.1_0 conda-forge r-bh 1.66.0_1 r3.4.1_0 conda-forge r-bindr 0.1.1 r3.4.1_0 conda-forge r-bindrcpp 0.2.2 r341h9d2a408_0 conda-forge r-bit 1.1_12 r3.4.1_0 conda-forge r-bit64 0.9_5 r3.4.1_0 conda-forge r-bitops 1.0_6 r3.4.1_0 conda-forge r-blob 1.1.1 r3.4.1_0 conda-forge r-boot 1.3_20 r3.4.1_0 conda-forge r-broom 0.5.0 r341_0 conda-forge r-car 2.1_4 r3.4.1_0 conda-forge r-caret 6.0_80 r341hc070d10_0 conda-forge r-cellranger 1.1.0 r3.4.1_0 conda-forge r-checkmate 1.8.5 r3.4.1_0 conda-forge r-class 7.3_14 r3.4.1_0 conda-forge r-cli 1.0.0 r3.4.1_0 conda-forge r-cluster 2.0.6 r3.4.1_0 conda-forge r-codetools 0.2_15 r3.4.1_0 conda-forge r-colorspace 1.3_2 r3.4.1_0 conda-forge r-combinat 0.0_8 r3.4.1_0 conda-forge r-crayon 1.3.4 r3.4.1_0 conda-forge r-crosstalk 1.0.0 r3.4.1_0 conda-forge r-curl 3.2 r3.4.1_0 conda-forge r-cvst 0.2_1 r3.4.1_0 conda-forge r-data.table 1.11.4 r341hc070d10_0 conda-forge r-dbi 1.0.0 r341_0 conda-forge r-dbplyr 1.2.1 r341_1 conda-forge r-ddalpha 1.3.4 r341_0 conda-forge r-deoptimr 1.0_8 r3.4.1_0 conda-forge r-devtools 1.13.6 r341_0 conda-forge r-dichromat 2.0_0 r3.4.1_0 conda-forge r-digest 0.6.15 r3.4.1_0 conda-forge r-dimred 0.1.0 r3.4.1_0 conda-forge r-dplyr 0.7.6 r341h9d2a408_0 conda-forge r-drr 0.0.3 r3.4.1_0 conda-forge r-evaluate 0.10.1 r3.4.1_0 conda-forge r-forcats 0.3.0 r3.4.1_0 conda-forge r-foreach 1.4.4 r3.4.1_0 conda-forge r-forecast 8.2 r3.4.1_0 conda-forge r-foreign 0.8_67 r3.4.1_0 conda-forge r-formula 1.2_1 r3.4.1_0 conda-forge r-fracdiff 1.4_2 r3.4.1_0 conda-forge r-gbm 2.1.3 r3.4.1_0 conda-forge r-geometry 0.3_6 r3.4.1_0 conda-forge r-ggjoy 0.4.1 r341_0 conda-forge r-ggplot2 3.0.0 r341h6115d3f_0 conda-forge r-ggridges 0.5.0 r3.4.1_0 conda-forge r-ggthemes 3.5.0 r341_0 conda-forge r-ggvis 0.4.3 r3.4.1_0 conda-forge r-git2r 0.21.0 r341h0c37787_0 conda-forge r-glmnet 2.0_5 r3.4.1_0 conda-forge r-glue 1.3.0 r341_0 conda-forge r-gower 0.1.2 r3.4.1_0 conda-forge r-gridextra 2.3 r3.4.1_0 conda-forge r-gsubfn 0.6_6 r3.4.1_0 conda-forge r-gtable 0.2.0 r3.4.1_0 conda-forge r-haven 1.1.2 r341_0 conda-forge r-hexbin 1.27.2 r3.4.1_0 conda-forge r-highr 0.7 r341_0 conda-forge r-hmisc 4.0_3 r3.4.1_0 conda-forge r-hms 0.3 r3.4.1_0 conda-forge r-htmltable 1.9 r3.4.1_0 conda-forge r-htmltools 0.3.6 r3.4.1_0 conda-forge r-htmlwidgets 1.0 r3.4.1_0 conda-forge r-httpuv 1.3.6.2 r3.4.1_0 conda-forge r-httr 1.3.1 r3.4.1_0 conda-forge r-ipred 0.9_6 r3.4.1_0 conda-forge r-irdisplay 0.4.4 r3.4.1_0 conda-forge r-irkernel 0.8.12 r341_0 conda-forge r-iterators 1.0.10 r341_0 conda-forge r-jsonlite 1.5 r3.4.1_0 conda-forge r-kernlab 0.9_25 r3.4.1_0 conda-forge r-kernsmooth 2.23_15 r3.4.1_0 conda-forge r-klar 0.6_12 r3.4.1_0 conda-forge r-knitr 1.20 r3.4.1_0 conda-forge r-labeling 0.3 r3.4.1_0 conda-forge r-lattice 0.20_34 r3.4.1_0 conda-forge r-latticeextra 0.6_28 r3.4.1_0 conda-forge r-lava 1.6.2 r341_0 conda-forge r-lazyeval 0.2.1 r3.4.1_0 conda-forge r-leaflet 2.0.1 r341_0 conda-forge r-leaps 3.0 r3.4.1_0 conda-forge r-lme4 1.1_13 r3.4.1_0 conda-forge r-lmertest 2.0_33 r3.4.1_0 conda-forge r-lmtest 0.9_35 r3.4.1_0 conda-forge r-lubridate 1.7.4 r3.4.1_0 conda-forge r-magic 1.5_6 r3.4.1_0 conda-forge r-magrittr 1.5 r3.4.1_0 conda-forge r-markdown 0.8 r3.4.1_1 conda-forge r-mass 7.3_50 r341hc070d10_0 conda-forge r-matrix 1.2_14 r3.4.1_0 conda-forge r-matrixmodels 0.4_1 r3.4.1_0 conda-forge r-memoise 1.1.0 r3.4.1_0 conda-forge r-mgcv 1.8_24 r341_0 conda-forge r-mime 0.5 r3.4.1_0 conda-forge r-minqa 1.2.4 r3.4.1_0 conda-forge r-mnormt 1.5_5 r3.4.1_0 conda-forge r-modelmetrics 1.1.0 r3.4.1_0 conda-forge r-modelr 0.1.2 r341_0 conda-forge r-munsell 0.5.0 r341_0 conda-forge r-nlme 3.1_131 r3.4.1_0 conda-forge r-nloptr 1.0.4 r3.4.1_1 conda-forge r-nnet 7.3_12 r3.4.1_0 conda-forge r-numderiv 2016.8_1 r3.4.1_0 conda-forge r-nycflights13 1.0.0 r341_0 conda-forge r-openssl 1.0.1 r3.4.1_0 conda-forge r-openxlsx 4.0.17 r3.4.1_0 conda-forge r-pbdzmq 0.3_2 r3.4.1_0 conda-forge r-pbkrtest 0.4_7 r3.4.1_0 conda-forge r-pillar 1.2.2 r341h6115d3f_1 conda-forge r-pkgconfig 2.0.1 r3.4.1_0 conda-forge r-plogr 0.2.0 r341h6115d3f_0 conda-forge r-plotly 4.7.1 r3.4.1_0 conda-forge r-pls 2.6_0 r3.4.1_0 conda-forge r-plyr 1.8.4 r3.4.1_0 conda-forge r-png 0.1_7 r3.4.1_0 conda-forge r-prettyunits 1.0.2 r3.4.1_0 conda-forge r-proc 1.9.1 r3.4.1_0 conda-forge r-prodlim 2018.04.18 r3.4.1_0 conda-forge r-proto 1.0.0 r3.4.1_0 conda-forge r-psych 1.8.4 r341_0 conda-forge r-purrr 0.2.4 r3.4.1_0 conda-forge r-quadprog 1.5_5 r3.4.1_0 conda-forge r-quantreg 5.33 r3.4.1_0 conda-forge r-r6 2.2.2 r3.4.1_0 conda-forge r-randomforest 4.6_12 r3.4.1_0 conda-forge r-raster 2.6_7 r3.4.1_0 conda-forge r-rcolorbrewer 1.1_2 r3.4.1_0 conda-forge r-rcpp 0.12.17 r341h9d2a408_0 conda-forge r-rcpparmadillo 0.8.500.0 r3.4.1_0 conda-forge r-rcppeigen 0.3.3.4.0 r3.4.1_0 conda-forge r-rcpproll 0.2.2 r3.4.1_0 conda-forge r-rcurl 1.95_4.11 r341ha4d7672_0 conda-forge r-readr 1.1.1 r3.4.1_0 conda-forge r-readxl 1.1.0 r341_0 conda-forge r-recipes 0.1.3 r341_0 conda-forge r-rematch 1.0.1 r3.4.1_0 conda-forge r-repr 0.15 r341_0 conda-forge r-reshape2 1.4.3 r3.4.1_0 conda-forge r-rio 0.5.10 r3.4.1_0 conda-forge r-rlang 0.2.1 r341_0 conda-forge r-rmarkdown 1.10 r341h6115d3f_0 conda-forge r-robustbase 0.92_7 r3.4.1_0 conda-forge r-rodbc 1.3_14 r3.4.1_0 conda-forge r-rpart 4.1_13 r3.4.1_0 conda-forge r-rprojroot 1.3_2 r3.4.1_0 conda-forge r-rsqlite 2.0 r3.4.1_0 conda-forge r-rstudioapi 0.7 r3.4.1_0 conda-forge r-rvest 0.3.2 r3.4.1_0 conda-forge r-scales 0.5.0 r3.4.1_0 conda-forge r-selectr 0.3_1 r3.4.1_0 conda-forge r-sfsmisc 1.1_1 r3.4.1_0 conda-forge r-shiny 1.0.5 r3.4.1_0 conda-forge r-sourcetools 0.1.6 r3.4.1_0 conda-forge r-sp 1.2_7 r341h470a237_1 conda-forge r-sparsem 1.77 r3.4.1_0 conda-forge r-squarem 2017.10_1 r3.4.1_0 conda-forge r-stringi 1.2.3 r341_0 conda-forge r-stringr 1.3.1 r341_0 conda-forge r-survival 2.42_6 r341_0 conda-forge r-tibble 1.4.2 r3.4.1_0 conda-forge r-tidyr 0.8.1 r341_0 conda-forge r-tidyselect 0.2.4 r3.4.1_0 conda-forge r-tidyverse 1.1.1 r3.4.1_0 conda-forge r-timedate 3012.100 r3.4.1_0 conda-forge r-tinytex 0.5 r341h6115d3f_0 conda-forge r-tseries 0.10_40 r3.4.1_0 conda-forge r-utf8 1.1.3 r3.4.1_0 conda-forge r-uuid 0.1_2 r3.4.1_0 conda-forge r-viridis 0.5.1 r3.4.1_0 conda-forge r-viridislite 0.3.0 r3.4.1_0 conda-forge r-whisker 0.3_2 r3.4.1_0 conda-forge r-withr 2.1.1 r3.4.1_0 conda-forge r-xml2 1.2.0 r341_0 conda-forge r-xtable 1.8_2 r3.4.1_0 conda-forge r-yaml 2.1.19 r341_0 conda-forge r-zoo 1.8_2 r341hc070d10_0 conda-forge ray 0.5.0 rdflib 4.2.2 py36_0 conda-forge readline 7.0 ha6073c6_4 anaconda redis 2.10.6 requests 2.19.1 py36_0 anaconda resampy 0.2.1 py_1 conda-forge rise 5.3.0 py36_0 damianavila82 rpy2 2.9.4 py36r341h24bf2e0_0 conda-forge ruamel_yaml 0.15.40 py36h470a237_0 conda-forge s3transfer 0.1.13 py36_0 anaconda scikit-image 0.14.0 py36hf484d3e_1 anaconda scikit-learn 0.19.1 py36hedc7406_0 anaconda scipy 1.1.0 py36hc49cb51_0 anaconda seaborn 0.8.1 py36_0 anaconda send2trash 1.5.0 py_0 conda-forge service_identity 17.0.0 py36h28b3542_0 anaconda setuptools 39.1.0 setuptools 39.2.0 py36_0 anaconda simplegeneric 0.8.1 py36_2 anaconda simplejson 3.15.0 py36h14c3975_0 anaconda sip 4.19.8 py36hf484d3e_0 anaconda six 1.11.0 py36_1 anaconda smart_open 1.6.0 py36_0 anaconda sparqlwrapper 1.8.2 py36_0 conda-forge spotlight 0.1.5 py36_0 maciejkula sqlalchemy 1.2.8 py36h14c3975_0 anaconda sqlite 3.24.0 h84994c4_0 anaconda statsmodels 0.9.0 py36h035aef0_0 anaconda sympy 1.1.1 py36_0 anaconda tabulate 0.8.2 py36_0 anaconda tensorboard 1.8.0 tensorboardX 1.2 tensorflow 1.8.0 tensorflow-gpu 1.8.0 termcolor 1.1.0 terminado 0.8.1 py36_1 anaconda testpath 0.3.1 py36_0 anaconda theano 1.0.2 py36h6bb024c_0 anaconda tk 8.6.7 hc745277_3 anaconda toolz 0.9.0 py36_0 anaconda torch 0.4.1 torchvision 0.2.1 py36_1 pytorch tornado 5.0.2 py36h14c3975_0 anaconda tqdm 4.23.4 py36_0 anaconda traitlets 4.3.2 py36_0 anaconda traits 4.6.0 py36h14c3975_2 anaconda traittypes 0.2.1 twisted 17.5.0 py36_0 defaults tzlocal 1.5.1 py_0 conda-forge unixodbc 2.3.5 h09ba92c_1 conda-forge urllib3 1.23 py36_0 conda-forge wcwidth 0.1.7 py36_0 anaconda webencodings 0.5 py36_0 conda-forge Werkzeug 0.14.1 wheel 0.31.1 py36_0 anaconda widgetsnbextension 3.2.1 py36_0 anaconda x264 1!152.20180717 h470a237_0 conda-forge xorg-kbproto 1.0.7 h470a237_2 conda-forge xorg-libice 1.0.9 h470a237_3 conda-forge xorg-libsm 1.2.2 h470a237_3 conda-forge xorg-libx11 1.6.5 h470a237_1 conda-forge xorg-libxext 1.3.3 h470a237_3 conda-forge xorg-libxrender 0.9.10 h470a237_1 conda-forge xorg-renderproto 0.11.1 h470a237_2 conda-forge xorg-xextproto 7.3.0 h470a237_2 conda-forge xorg-xproto 7.0.31 h470a237_7 conda-forge xvfbwrapper 0.2.9 py36_0 conda-forge xz 5.2.4 h14c3975_4 anaconda yaml 0.1.7 had09818_2 anaconda yapf 0.22.0 zeromq 4.2.5 hf484d3e_0 anaconda zlib 1.2.11 ha838bed_2 anaconda zope 1.0 py36_0 anaconda zope.interface 4.5.0 py36h14c3975_0 anaconda

eagleoflqj commented 6 years ago

I think it's not an autokeras error. Try to put your code into if __name__=='__main__': like this

if __name__=='__main__':
    (X_train, Y_train), (X_test, Y_test) = mnist.load_data()
    X_train = X_train.reshape(X_train.shape + (1,))
    X_test = X_test.reshape(X_test.shape + (1,))
    clf = ak.ImageClassifier(verbose=True, augment=False)
    clf.fit(X_train, Y_train)
RomanKoshkin commented 6 years ago

Tried it. Still keep getting the error.

lsheiba commented 6 years ago

Having a similar problem:

Initializing search. [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17] [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43] Initialization finished. Training model 0 Bus error (core dumped) root@autokeras-v2-jupyter-56787d65fb-lbkpn:/notebooks# Using TensorFlow backend. /opt/conda/lib/python3.6/multiprocessing/semaphore_tracker.py:143: UserWarning: semaphore_tracker: There appear to be 4 leaked semaphores to clean up at shutdown len(cache))

ghost commented 6 years ago

I have the same issue. anyone has the answer?

RomanKoshkin commented 6 years ago

Any advice on how this could be done, please? You don't mean physical dismounting, do you?

RomanKoshkin commented 6 years ago

Here's what I get from nvidia-smi:

Fri Aug 31 10:03:59 2018 +-----------------------------------------------------------------------------+ | NVIDIA-SMI 396.54 Driver Version: 396.54 | |-------------------------------+----------------------+----------------------+ | GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC | | Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. | |===============================+======================+======================| | 0 GeForce GTX 108... Off | 00000000:05:00.0 On | N/A | | 21% 34C P8 18W / 250W | 1121MiB / 11170MiB | 0% Default | +-------------------------------+----------------------+----------------------+ | 1 GeForce GTX 108... Off | 00000000:06:00.0 Off | N/A | | 21% 33C P8 17W / 250W | 7012MiB / 11178MiB | 0% Default | +-------------------------------+----------------------+----------------------+ | 2 GeForce GTX 108... Off | 00000000:09:00.0 Off | N/A | | 21% 33C P8 16W / 250W | 1244MiB / 11178MiB | 0% Default | +-------------------------------+----------------------+----------------------+ | 3 GeForce GTX 108... Off | 00000000:0A:00.0 Off | N/A | | 21% 32C P8 18W / 250W | 227MiB / 11178MiB | 0% Default | +-------------------------------+----------------------+----------------------+

+-----------------------------------------------------------------------------+ | Processes: GPU Memory | | GPU PID Type Process name Usage | |=============================================================================| | 1 430 C /opt/conda/bin/python 6785MiB | +-----------------------------------------------------------------------------+

ghost commented 6 years ago

I figured it out for myself. The docker container I was using was 2G memory. I increased it to 16G and restarted the docker image by adding --shm-size 16G when running docker run. It solved my problems. Hope it helps.

xieqihui commented 6 years ago

I got the same issue. And I have 24 GB memory for my docker container to use. There is only one GTX 1080 GPU. My configuration has no problem running the Keras mnist example

yogurfrul commented 6 years ago

same with @Lincoln-Jiang
maybe the multiprocessing of searcher need more shm-size than default

hoangphzalora commented 6 years ago

I think @eagleoflqj comment is right but we need put code in the main function as follow.

import autokeras as ak

from keras.datasets import mnist
def main():
    (X_train, Y_train), (X_test, Y_test) = mnist.load_data()
    X_train = X_train.reshape(X_train.shape + (1,))
    X_test = X_test.reshape(X_test.shape + (1,))
    clf = ak.ImageClassifier(verbose=True, augment=False)
    clf.fit(X_train, Y_train)

if __name__ == "__main__":
    main()

Ref: https://stackoverflow.com/questions/24374288/where-to-put-freeze-support-in-a-python-script

nathanningbo commented 5 years ago

I figured it out for myself. The docker container I was using was 2G memory. I increased it to 16G and restarted the docker image by adding --shm-size 16G when running docker run. It solved my problems. Hope it helps.

It helps ! Thanks

Eton commented 5 years ago

Having a same problem

Is this error cause by #26 ?

haifeng-jin commented 5 years ago

Having a same problem

Is this error cause by #26 ?

That issue is already fixed, it won't cause a bus error. Were you using the latest version?

Thanks.

stale[bot] commented 5 years ago

This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.