using System;

using System.Collections.Generic;

using System.Runtime.InteropServices;

using System.Text;

using Tensorflow.Eager;

namespace Tensorflow.Gradients

{

public class Tape : DisposableObject

{

public int nesting_id { get; set; }

public Tape(bool persistent, bool watch_accessed_variables)

{

_handle = c_api.TFE_TapeSetNew(persistent, watch_accessed_variables);

}

public void watch(EagerTensor x)

{

c_api.TFE_TapeWatch(_handle, x.EagerTensorHandle);

}

public void pop_tape(Tape tape)

{

c_api.TFE_TapeSetRemove(tape);

}

public static void variable_accessed(ResourceVariable variable)

{

c_api.TFE_TapeVariableAccessed(variable);

}

public unsafe ResourceVariable[] watched_variables()

{

BindingArray result = c_api.TFE_TapeWatchedVariables(_handle);

var variables = new ResourceVariable[result.length];

for (int i = 0; i < result.length; i++)

{

var handle = *((IntPtr*)result.array + i);

var tensor = c_api.ResourceVariable_Handle(handle);

variables[i] = new ResourceVariable(handle, tensor);

}

return variables;

}

public static bool IsDtypeTrainable(DataType dtype)

{

switch (dtype)

{

case DataType.DtHalf:

case DataType.DtBfloat16:

case DataType.DtFloat:

case DataType.DtDouble:

case DataType.DtComplex64:

case DataType.DtComplex128:

case DataType.DtResource:

case DataType.DtVariant:

return true;

default:

return false;

}

}

protected override void DisposeUnmanagedResources(IntPtr handle)

{

}

public static implicit operator IntPtr(Tape tape)

=> tape._handle;

}

}