internal static void TrainMultiDevice(Symbol symbol, Context[] ctx, string[] arg_names, string[] param_names, string[] aux_names, NDArrayDict arg_params, NDArrayDict aux_params, int begin_epoch, int end_epoch, int?epoch_size, Optimizer optimizer, KVStore kvstore, bool update_on_kvstore, DataIter train_data, DataIter eval_data = null, EvalMetric eval_metric = null, IEpochEndCallback epoch_end_callback = null, IBatchEndCallback batch_end_callback = null, int[] work_load_list = null, Monitor monitor = null, IEvalEndCallback eval_end_callback = null, IEvalBatchEndCallback eval_batch_end_callback = null, Func <int, Symbol> sym_gen = null)
{
var executor_manager = new DataParallelExecutorManager(symbol: symbol,
ctx: ctx,
train_data: train_data,
arg_names: arg_names,
param_names: param_names,
aux_names: aux_names,
work_load_list: work_load_list,
sym_gen: sym_gen);
if (monitor != null)
{
executor_manager.InstallMonitor(monitor);
}
executor_manager.SetParams(arg_params, aux_params);
Updater updater = null;
if (!update_on_kvstore)
{
updater = Optimizer.GetUpdater(optimizer);
}
else
{
kvstore.SetOptimizer(optimizer);
}
if (kvstore != null)
{
InitializeKVStore(kvstore: kvstore,
param_arrays: new List <NDArrayList>()
{
executor_manager.ParamArrays
},
arg_params: arg_params,
param_names: executor_manager.param_names,
update_on_kvstore: update_on_kvstore);
}
train_data.Reset();
for (int epoch = begin_epoch; epoch < end_epoch; epoch++)
{
var tic = DateTime.Now;
eval_metric.Reset();
int nbatch = 0;
while (true)
{
bool do_reset = true;
while (!train_data.End())
{
var data_batch = train_data.Next();
executor_manager.LoadDataBatch(data_batch);
if (monitor != null)
{
monitor.Tic();
}
executor_manager.Forward(true);
executor_manager.Backward();
if (update_on_kvstore)
{
if (kvstore.Type.Contains("nccl"))
{
UpdateParamsOnKVStoreNCCL(new List <NDArrayList>()
{
executor_manager.ParamArrays
}, new List <NDArrayList>()
{
executor_manager.GradArrays
}, kvstore, executor_manager.param_names);
}
else
{
UpdateParamsOnKVStore(new List <NDArrayList>()
{
executor_manager.ParamArrays
}, new List <NDArrayList>()
{
executor_manager.GradArrays
}, kvstore, executor_manager.param_names);
}
}
else
{
UpdateParams(new List <NDArrayList>()
{
executor_manager.ParamArrays
}, new List <NDArrayList>()
{
executor_manager.GradArrays
}, updater, ctx.Length, kvstore, executor_manager.param_names);
}
if (monitor != null)
{
monitor.TocPrint();
}
executor_manager.UpdateMetric(eval_metric, data_batch.Label);
nbatch++;
if (batch_end_callback != null)
{
MultipleCallbacks(batch_end_callback, epoch, nbatch, eval_metric);
}
if (epoch_size.HasValue && nbatch >= epoch_size.Value)
{
do_reset = false;
break;
}
}
if (do_reset)
{
Logger.Info($"Epoch[{epoch}] Resetting Data Iterator");
train_data.Reset();
}
if (epoch_size.HasValue)
{
if (nbatch >= epoch_size.Value)
{
break;
}
else
{
break;
}
}
}
var toc = DateTime.Now;
Logger.Info($"Epoch[{epoch}] Time cost={(toc - tic).TotalSeconds}");
if (epoch_end_callback != null || epoch + 1 == end_epoch)
{
executor_manager.CopyTo(arg_params, aux_params);
}
MultipleCallbacks(epoch_end_callback, epoch, symbol, arg_params, aux_params);
if (eval_data != null)
{
eval_metric.Reset();
eval_data.Reset();
int total_num_batch = 0;
int i = 0;
while (!eval_data.End())
{
var eval_batch = eval_data.Next();
executor_manager.LoadDataBatch(eval_batch);
executor_manager.Forward();
executor_manager.UpdateMetric(eval_metric, eval_batch.Label);
if (eval_batch_end_callback != null)
{
MultipleCallbacks(eval_batch_end_callback, epoch, i, eval_metric);
}
total_num_batch++;
}
if (eval_end_callback != null)
{
MultipleCallbacks(eval_end_callback, epoch, eval_metric);
}
}
}
}
