[ https://issues.apache.org/jira/browse/MADLIB-1393?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Frank McQuillan closed MADLIB-1393. ----------------------------------- Resolution: Fixed https://github.com/apache/madlib/pull/462 > DL: Fit and evaluate changes for asymmetric cluster config > ---------------------------------------------------------- > > Key: MADLIB-1393 > URL: https://issues.apache.org/jira/browse/MADLIB-1393 > Project: Apache MADlib > Issue Type: New Feature > Components: Deep Learning > Reporter: Ekta Khanna > Priority: Major > Fix For: v1.17 > > > Single fit() > {code} > madlib_keras_fit( > source_table, > model, > model_arch_table, > model_arch_id, > compile_params, > fit_params, > num_iterations, > use_gpus, -- changed definition > validation_table, > metrics_compute_frequency, > warm_start, > name, > description > ) > {code} > {{use_gpus}} (optional) > BOOLEAN, *default*: FALSE (i.e., CPU). Determines whether GPUs are to be used > for training the neural network. Set to TRUE to use GPUs. > *Note* > This parameter must not conflict with how the distribution rules are set in > the preprocessor function. For example, if you set a distribution rule to > use certain segments on hosts that do not have GPUs attached, you will get an > error if you set {{use_gpus}} to TRUE. > Also, we have seen some memory related issues when segments share GPU > resources. For example, if you have 4 segments sharing 1 GPU, you may get > memory related errors. The recommended configuration is to have 1 GPU per > segment. > *Multi model fit()* > Same idea as above ^^^ for single model fit. > *Evaluate* > Same idea as above ^^^ for single model fit.. -- This message was sent by Atlassian Jira (v8.3.4#803005)