TensorFlow.NET/src/TensorFlowNET.Core/Training/Trackable.cs at master · BOYMMM/TensorFlow.NET · GitHub

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/*****************************************************************************

Licensed under the Apache License, Version 2.0 (the "License");

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

You may obtain a copy of the License at

http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software

distributed under the License is distributed on an "AS IS" BASIS,

WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.

See the License for the specific language governing permissions and

limitations under the License.

******************************************************************************/

using System;

namespace Tensorflow.Train

{

public abstract class Trackable

{

protected int _self_update_uid;

/// <summary>

/// Restore-on-create for a variable be saved with this `Checkpointable`.

/// </summary>

/// <returns></returns>

protected virtual VariableV1 _add_variable_with_custom_getter(string name,

int[] shape,

TF_DataType dtype = TF_DataType.TF_FLOAT,

IInitializer initializer = null,

Func<string, int[], TF_DataType, IInitializer, bool, VariableV1> getter = null,

bool overwrite = false,

bool trainable = false)

{

var checkpoint_initializer = true;

var new_variable = getter(name, shape, dtype, initializer, trainable);

// If we set an initializer and the variable processed it, tracking will not

// assign again. It will add this variable to our dependencies, and if there

// is a non-trivial restoration queued, it will handle that. This also

// handles slot variables.

if (!overwrite || new_variable is RefVariable)

return _track_checkpointable(new_variable, name: name,

overwrite: overwrite);

else

return new_variable;

}

/// <summary>

/// Pop and load any deferred checkpoint restores into `trackable`.

/// </summary>

/// <param name="name"></param>

/// <param name="trackable"></param>

protected void _handle_deferred_dependencies(string name, VariableV1 trackable)

{

_maybe_initialize_trackable();

// TODO

}

protected VariableV1 _track_checkpointable(VariableV1 checkpointable, string name, bool overwrite = false)

{

return checkpointable;

}

/// <summary>

/// Initialize dependency management.

/// </summary>

protected void _maybe_initialize_trackable()

{

// _self_unconditional_checkpoint_dependencies = []

_self_update_uid = -1;

}

TensorFlow.NET/src/TensorFlowNET.Core/Training/Trackable.cs at master · BOYMMM/TensorFlow.NET · GitHub

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