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

Copyright 2018 The TensorFlow.NET Authors. All Rights Reserved.

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;

using Tensorflow.Operations.Initializers;

using static Tensorflow.Binding;

namespace Tensorflow.Train

{

public class SlotCreator

{

/// <summary>

/// Create a slot initialized to 0 with same shape as the primary object.

/// </summary>

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

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

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

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

/// <returns></returns>

public RefVariable create_zeros_slot(RefVariable primary, string name, TF_DataType dtype = TF_DataType.DtInvalid, bool colocate_with_primary = true)

{

if (dtype == TF_DataType.DtInvalid)

dtype = primary.dtype;

var slot_shape = primary.shape;

if (slot_shape.is_fully_defined())

{

var initializer = new Zeros();

return create_slot_with_initializer(

primary, initializer, slot_shape, dtype, name,

colocate_with_primary: colocate_with_primary);

}

else

{

throw new NotImplementedException("create_zeros_slot is not fully defined.");

}

}

/// <summary>

/// Creates a slot initialized using an `Initializer`.

/// </summary>

/// <returns></returns>

public RefVariable create_slot_with_initializer(RefVariable primary, IInitializer initializer, TensorShape shape,

TF_DataType dtype, string name, bool colocate_with_primary = true)

{

var validate_shape = shape.is_fully_defined();

var prefix = primary.op.name;

return tf_with(new variable_scope(string.Empty, prefix + "/" + name), delegate

{

return _create_slot_var(primary, initializer, "", validate_shape, shape, dtype);

});

}

/// <summary>

/// Helper function for creating a slot variable.

/// </summary>

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

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

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

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

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

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

/// <returns></returns>

private RefVariable _create_slot_var(VariableV1 primary, IInitializer val, string scope, bool validate_shape,

TensorShape shape, TF_DataType dtype)

{

bool use_resource = primary is ResourceVariable;

if (resource_variable_ops.is_resource_variable(primary))

use_resource = true;

var slot = tf.get_variable(

scope,

initializer: val,

trainable: false,

use_resource: use_resource,

shape: shape,

dtype: dtype,

validate_shape: validate_shape);

return slot;

}

}

}