static void Main(string[] args)
{
// boot .net core 10.5M.
var mm = new MemoryMonitor();
// warm up tensorflow.net 28.5M.
mm.WarmUp();
var cases = new MemoryTestingCases();
int batchSize = 1000;
// explaination of constant
mm.Execute(10, 100 * batchSize, cases.Constant2x3);
// 1 million float tensor 68M.
mm.Execute(10, 100 * batchSize, cases.Constant);
// 100K float variable 84M.
mm.Execute(10, 10 * batchSize, cases.Variable);
// 1 million math add 39M.
mm.Execute(10, 100 * batchSize, cases.MathAdd);
// 100K gradient 44M.
mm.Execute(10, 10 * batchSize, cases.Gradient);
// 95M
Console.WriteLine("Finished.");
Console.ReadLine();
}
static void Main(string[] args)
{
var diag = new Diagnostician();
// diag.Diagnose(@"D:\memory.txt");
// this class is used explor new features.
var exploring = new Exploring();
// exploring.Run();
// boot .net core 10.5M.
var mm = new MemoryMonitor();
// warm up tensorflow.net 37.3M.
mm.WarmUp();
BasicTest(mm);
KerasTest(mm);
FuncGraph(mm);
// 65M
Console.WriteLine("Finished.");
Console.ReadLine();
}
static void KerasTest(MemoryMonitor mm)
{
var keras = new MemoryKerasTest();
// +1M (10,50)
mm.Execute(10, 1, keras.Conv2DLayer);
mm.Execute(10, 50, keras.InputLayer);
mm.Execute(10, 10, keras.Prediction);
}
static void BasicTest(MemoryMonitor mm)
{
int batchSize = 1000;
var basic = new MemoryBasicTest();
// 1 million placeholder
/*tf.compat.v1.disable_eager_execution();
* mm.Execute(10, 100 * batchSize, basic.Placeholder);
* tf.enable_eager_execution();*/
// 1 million tensor
mm.Execute(10, 100 * batchSize, basic.Constant);
// explaination of constant
mm.Execute(10, 100 * batchSize, basic.Constant2x3);
mm.Execute(10, 100 * batchSize, basic.ConstantString);
// 100K float variable.
mm.Execute(10, batchSize, basic.Variable);
mm.Execute(10, batchSize, basic.VariableRead);
mm.Execute(10, batchSize, basic.VariableAssign);
// 1 million math.
mm.Execute(10, 100 * batchSize, basic.MathAdd);
// Conv2d in constant tensor
mm.Execute(10, batchSize, basic.Conv2DWithTensor);
// Conv2d in variable
mm.Execute(10, batchSize, basic.Conv2DWithVariable);
// 100K gradient 44M.
mm.Execute(10, 10 * batchSize, basic.Gradient);
// memory leak when increasing the epoch
mm.Execute(10, 10, basic.Dataset);
}
static void Main(string[] args)
{
// this class is used explor new features.
var exploring = new Exploring();
// exploring.Run();
// boot .net core 10.5M.
var mm = new MemoryMonitor();
// warm up tensorflow.net 37.3M.
mm.WarmUp();
var cases = new MemoryTestingCases();
int batchSize = 1000;
// 1 million tensor
mm.Execute(10, 100 * batchSize, cases.Constant);
// explaination of constant
mm.Execute(10, 100 * batchSize, cases.Constant2x3);
// +0M
mm.Execute(10, batchSize, cases.Conv2dWithTensor);
// 100K float variable 84M.
mm.Execute(10, batchSize, cases.Variable);
// +45M memory leak
mm.Execute(10, batchSize, cases.Conv2dWithVariable);
// 1 million math add 39M.
mm.Execute(10, 100 * batchSize, cases.MathAdd);
// 100K gradient 44M.
mm.Execute(10, 10 * batchSize, cases.Gradient);
// 95M
Console.WriteLine("Finished.");
Console.ReadLine();
}
static void FuncGraph(MemoryMonitor mm)
{
var func = new MemoryFuncGraphTest();
mm.Execute(10, 100, func.ConcreteFunction);
}
