While trying to train a lenet model for multiclass classification using h2o deepwater using mxnet backed i am getting the following errors:
Loading H2O mxnet bindings.
Found CUDA_HOME or CUDA_PATH environment variable, trying to connect to GPU devices.
Loading CUDA library.
Loading mxnet library.
Loading H2O mxnet bindings.
Done loading H2O mxnet bindings.
Constructing model.
Done constructing model.
Building network.
mxnet data input shape: (32,100)
[10:40:16] /home/jenkins/slave_dir_from_mr-0xb1/workspace/deepwater-master/thirdparty/mxnet/dmlc-core/include/dmlc/logging.h:235: [10:40:16] src/operator/./convolution-inl.h:349: Check failed: (dshape.ndim()) == (4) Input data should be 4D in batch-num_filter-y-x
[10:40:16] src/symbol.cxx:189: Check failed: (MXSymbolInferShape(GetHandle(), keys.size(), keys.data(), arg_ind_ptr.data(), arg_shape_data.data(), &in_shape_size, &in_shape_ndim, &in_shape_data, &out_shape_size, &out_shape_ndim, &out_shape_data, &aux_shape_size, &aux_shape_ndim, &aux_shape_data, &complete)) == (0)
The details of my setup :
Ram : 12gb
Graphics card : Nvidia 920mx driver version : 384.90
Cuda : 8.0.61
cudnn : 6.0
R version : 3.4.3
H2o version : 3.15.0.393 & h2o-R package : 3.16.0.2
mxnet : 0.11.0
Train data size : 400mb (when converting to the h2o frame object it comes around 800mb)
Things i have done :
1.) Gave enough memory to java heap while running h2o cluster (java -Xmx9g -jar h2o.jar)
2.) Build the mxnet from source for gpu
3.) Monitored the gpu and system via nvidia-smi and system monitor. At no point do they eat up all the ram to show "out of memory" issue. I still will be having around 2-3gb free before the error shows up
4.) Have tried with tensorflow-gpu(build from source). Checking the pip list made sure that its installed but during model creation in R it gives the error :
Error: java.lang.RuntimeException: Unable to initialize the native Deep Learning backend: null
5.) The only method i got it the h2o deepwater to work with all the backend and gpu is through docker setup provided in the installation tutorials.
I wanted the same functionality in my laptop instead of using docker. Any help or advice will be greatly appreciated !
you don’t need to drop the response column from the test set, H2O will ignore it
I had this hunch, but I couldn't find this info anywhere. So, it's like the model I use would keep the response column name and, when I give it another data with this column, it would not use it?
At this point I'm able to run
make from h2o-flow project and the project is built in ../h2o-3/h2o-web/src/main/resources/www/flowso it looks to be present from the h2o-3 perspective but I'm still unable to see those changes in the browser.I have 'flow.js` modified and the server still replies with the old version of that script.
Followed the instructions on setting up the environment in Idea.
Have anyone faced this problem? Could you please help me with that.
h2o.import_file, try setting destination_frame as something different each time
I have been trying to import data via SQL in Flow - the JDBC server connection that I have is jdbc:sqlserver://eztw6l0aw7.database.windows.net:1433;database=<database>;user=<user>@eztw6l0aw7;password={your_password_here};encrypt=true;trustServerCertificate=false;hostNameInCertificate=*.database.windows.net;loginTimeout=30;
I have entered this into the connection URL and the table name and the user and pass in the appropriate fields and pressed "Import" but got nothing. I have tried the URL with deleting the database=, user= and password= fields out or in and neither works. I have no problem importing a CSV file
Task :h2o-web:installBowerPackages
bower h2o-flow#0.10.3 cached https://github.com/h2oai/h2o-flow.git#0.10.3
bower h2o-flow#0.10.3 validate 0.10.3 against https://github.com/h2oai/h2o-flow.git#0.10.3
bower h2o-flow#0.10.3 install h2o-flow#0.10.3
do you mean bower can install a package from a github repo only by its valid tag,and the bower.json is not required?
