本文整理了Java中water.fvec.Frame.byteSize()方法的一些代码示例，展示了Frame.byteSize()的具体用法。这些代码示例主要来源于Github/Stackoverflow/Maven等平台，是从一些精选项目中提取出来的代码，具有较强的参考意义，能在一定程度帮忙到你。Frame.byteSize()方法的具体详情如下：
包路径：water.fvec.Frame
类名称：Frame
方法名：byteSize

Frame.byteSize介绍

暂无

代码示例

代码示例来源：origin: h2oai/h2o-3

@Override protected int nModelsInParallel() {
 if (!_parms._parallelize_cross_validation || _parms._max_runtime_secs != 0) return 1; //user demands serial building (or we need to honor the time constraints for all CV models equally)
 if (_train.byteSize() < 1e6) return _parms._nfolds; //for small data, parallelize over CV models
 return 1;
}

代码示例来源：origin: h2oai/h2o-3

@Override protected int nModelsInParallel() {
 if (!_parms._parallelize_cross_validation || _parms._max_runtime_secs != 0) return 1; //user demands serial building (or we need to honor the time constraints for all CV models equally)
 if (_train.byteSize() < 1e6) return _parms._nfolds; //for small data, parallelize over CV models
 return 2; //GBM always has some serial work, so it's fine to build two models at once
}

代码示例来源：origin: h2oai/h2o-2

public long length() {
 if (isFrame()) {
  return ((Frame)get()).byteSize();
 }
 return _max;
}

代码示例来源：origin: h2oai/h2o-2

check += v.nChunks();
assert(total_chunk_count == check);
assert(total_chunk_byte_size == _fr.byteSize());

代码示例来源：origin: h2oai/h2o-2

@Override protected Boolean defaultValue() {
  // Can we allocate ALL of the dataset locally?
  long bs = fr().byteSize();
  if( !MemoryManager.tryReserveTaskMem(bs) ) return false;
  // Also, do we have enough chunks to run it well globally?
  if( fr().anyVec().nChunks() >= 2*H2O.CLOUD.size() ) return false;
  // Less than 2 chunks per node, and fits locally... default to local-only
  return true;
 }
}

代码示例来源：origin: h2oai/h2o-2

@Override protected Response serve() {
 if( src_key == null ) return RequestServer._http404.serve();
 numRows = src_key.numRows();
 numCols = src_key.numCols();
 Futures fs = new Futures();
 for( int i=0; i<numCols; i++ )
  src_key.vecs()[i].rollupStats(fs);
 fs.blockForPending();
 byteSize = src_key.byteSize();
 cols = new ColSummary[numCols];
 for( int i=0; i<cols.length; i++ )
  cols[i] = new ColSummary(src_key._names[i],src_key.vecs()[i]);
 return Response.done(this);
}

代码示例来源：origin: h2oai/h2o-2

private boolean canLoadAll(final Frame fr, ChunkAllocInfo cai) {
 int nchks = fr.anyVec().nChunks();
 long localBytes = 0l;
 for (int i = 0; i < nchks; ++i) {
  Key k = fr.anyVec().chunkKey(i);
  if (k.home()) {
   localBytes += fr.anyVec().chunkForChunkIdx(i).byteSize();
  }
 }
 long memForNonLocal = fr.byteSize() - localBytes;
 // Also must add in the RF internal data structure overhead
 memForNonLocal += fr.numRows() * fr.numCols();
 for(int i = 0; i < H2O.CLOUD._memary.length; i++) {
  HeartBeat hb = H2O.CLOUD._memary[i]._heartbeat;
  long nodeFreeMemory = (long)(hb.get_max_mem() * 0.8); // * OVERHEAD_MAGIC;
  Log.debug(Log.Tag.Sys.RANDF, i + ": computed available mem: " + PrettyPrint.bytes(nodeFreeMemory));
  Log.debug(Log.Tag.Sys.RANDF, i + ": remote chunks require: " + PrettyPrint.bytes(memForNonLocal));
  if (nodeFreeMemory - memForNonLocal <= 0 || (nodeFreeMemory <= TWO_HUNDRED_MB && memForNonLocal >= ONE_FIFTY_MB)) {
   Log.info("Node free memory raw: "+nodeFreeMemory);
   cai.node = H2O.CLOUD._memary[i];
   cai.availableMemory = nodeFreeMemory;
   cai.requiredMemory = memForNonLocal;
   return false;
  }
 }
 return true;
}

代码示例来源：origin: h2oai/h2o-3

dl.error("_class_sampling_factors", "class_sampling_factors requires balance_classes to be enabled.");
if (_replicate_training_data && null != train() && train().byteSize() > 0.9*H2O.CLOUD.free_mem()/H2O.CLOUD.size() && H2O.CLOUD.size() > 1) {
 dl.error("_replicate_training_data", "Compressed training dataset takes more than 90% of avg. free available memory per node (" + 0.9*H2O.CLOUD.free_mem()/H2O.CLOUD.size() + "), cannot run with replicate_training_data.");

代码示例来源：origin: h2oai/h2o-3

bytes = train.numRows() * model.model_info()._width * model.model_info()._height * model.model_info()._channels * 4;
} else {
 bytes = train.byteSize();

代码示例来源：origin: ai.h2o/h2o-algos

@Override protected int nModelsInParallel() {
 if (!_parms._parallelize_cross_validation || _parms._max_runtime_secs != 0) return 1; //user demands serial building (or we need to honor the time constraints for all CV models equally)
 if (_train.byteSize() < 1e6) return _parms._nfolds; //for small data, parallelize over CV models
 return 1;
}

代码示例来源：origin: ai.h2o/h2o-algos

@Override protected int nModelsInParallel() {
 if (!_parms._parallelize_cross_validation || _parms._max_runtime_secs != 0) return 1; //user demands serial building (or we need to honor the time constraints for all CV models equally)
 if (_train.byteSize() < 1e6) return _parms._nfolds; //for small data, parallelize over CV models
 return 2; //GBM always has some serial work, so it's fine to build two models at once
}

代码示例来源：origin: h2oai/h2o-3

dl.error("_class_sampling_factors", "class_sampling_factors requires balance_classes to be enabled.");
if (_replicate_training_data && null != train() && train().byteSize() > 0.9*H2O.CLOUD.free_mem()/H2O.CLOUD.size() && H2O.CLOUD.size() > 1) {
 dl.error("_replicate_training_data", "Compressed training dataset takes more than 90% of avg. free available memory per node (" + 0.9*H2O.CLOUD.free_mem()/H2O.CLOUD.size() + "), cannot run with replicate_training_data.");

代码示例来源：origin: ai.h2o/h2o-algos

dl.error("_class_sampling_factors", "class_sampling_factors requires balance_classes to be enabled.");
if (_replicate_training_data && null != train() && train().byteSize() > 0.9*H2O.CLOUD.free_mem()/H2O.CLOUD.size() && H2O.CLOUD.size() > 1) {
 dl.error("_replicate_training_data", "Compressed training dataset takes more than 90% of avg. free available memory per node (" + 0.9*H2O.CLOUD.free_mem()/H2O.CLOUD.size() + "), cannot run with replicate_training_data.");

代码示例来源：origin: ai.h2o/h2o-algos

bytes = train.numRows() * model.model_info()._width * model.model_info()._height * model.model_info()._channels * 4;
} else {
 bytes = train.byteSize();

代码示例来源：origin: ai.h2o/h2o-algos

dl.error("_class_sampling_factors", "class_sampling_factors requires balance_classes to be enabled.");
if (_replicate_training_data && null != train() && train().byteSize() > 0.9*H2O.CLOUD.free_mem()/H2O.CLOUD.size() && H2O.CLOUD.size() > 1) {
 dl.error("_replicate_training_data", "Compressed training dataset takes more than 90% of avg. free available memory per node (" + 0.9*H2O.CLOUD.free_mem()/H2O.CLOUD.size() + "), cannot run with replicate_training_data.");