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you may not use this file except in compliance with the License.

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using Tensorflow.NumPy;

namespace Tensorflow

{

/// <summary>

/// A variable maintains state in the graph across calls to `run()`. You add a

/// variable to the graph by constructing an instance of the class `Variable`.

///

/// The `Variable()` constructor requires an initial value for the variable,

/// which can be a `Tensor` of any type and shape. The initial value defines the

/// type and shape of the variable. After construction, the type and shape of

/// the variable are fixed. The value can be changed using one of the assign methods.

/// https://tensorflow.org/guide/variables

/// </summary>

public interface IVariableV1

{

string UniqueId { get; }

string Name { get; }

/// <summary>

/// Handle is ref type

/// </summary>

Tensor Handle { get; }

string Device { get; }

Operation Initializer { get; }

Operation Op { get; }

/// <summary>

/// GraphElement is a copy of Handle

/// </summary>

Tensor GraphElement { get; }

Graph Graph { get; }

TF_DataType dtype { get; }

Shape shape { get; }

bool Trainable { get; }

Tensor assign_add<T>(T delta, bool use_locking = false, string name = null, bool read_value = true);

Tensor assign_sub<T>(T delta, bool use_locking = false, string name = null, bool read_value = true);

IVariableV1 assign_sub_lazy_load(Tensor delta, string name = null);

Tensor assign<T>(T value, bool use_locking = false, string name = null, bool read_value = true);

IVariableV1 assign_lazy_load(Tensor value, string name = null);

Tensor AsTensor(TF_DataType dtype = TF_DataType.DtInvalid, string name = null, bool as_ref = false);

NDArray numpy();

}

}