--- /dev/null
+/*
+ * Copyright (c) 2022 Samsung Electronics Co., Ltd 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 System.Runtime.InteropServices;
+using Tizen.MachineLearning.Train;
+
+internal static partial class Interop
+{
+ internal static partial class Layer
+ {
+ /* int ml_train_layer_create(ml_train_layer_h *layer, ml_train_layer_type_e type) */
+ [DllImport(Libraries.Nntrainer, EntryPoint = "ml_train_layer_create")]
+ public static extern NNTrainerError Create(out IntPtr layerHandle, NNTrainerLayerType type);
+
+ /* int ml_train_layer_destroy(ml_train_layer_h layer) */
+ [DllImport(Libraries.Nntrainer, EntryPoint = "ml_train_layer_destroy")]
+ public static extern NNTrainerError Destroy(IntPtr layerHandle);
+ }
+}
\ No newline at end of file
IniWithBin = 2
}
+ /// <summary>
+ /// Enumeration for the neural network layer type of NNTrainer.
+ /// </summary>
+ /// <since_tizen> 10 </since_tizen>
+ public enum NNTrainerLayerType
+ {
+ /// <summary>
+ /// Input Layer
+ /// </summary>
+ Input = 0,
+ /// <summary>
+ /// Fully Connected Layer
+ /// </summary>
+ FC = 1,
+ /// <summary>
+ /// Batch Normalization Layer
+ /// </summary>
+ BN = 2,
+ /// <summary>
+ /// Convolution 2D Layer
+ /// </summary>
+ Conv2D = 3,
+ /// <summary>
+ /// Pooling 2D Layer
+ /// </summary>
+ Pooling2D= 4,
+ /// <summary>
+ /// Flatten Layer
+ /// </summary>
+ Flatten = 5,
+ /// <summary>
+ /// Activation Layer
+ /// </summary>
+ Activation = 6,
+ /// <summary>
+ /// Addition Layer
+ /// </summary>
+ Addition = 7,
+ /// <summary>
+ /// Concat Layer
+ /// </summary>
+ Concat = 8,
+ /// <summary>
+ /// MultiOut Layer
+ /// </summary>
+ MultiOut = 9,
+ /// <summary>
+ /// Embedding Layer
+ /// </summary>
+ Embedding = 10,
+ /// <summary>
+ /// RNN Layer
+ /// </summary>
+ RNN = 11,
+ /// <summary>
+ /// LSTM Layer
+ /// </summary>
+ LSTM = 12,
+ /// <summary>
+ /// Split Layer
+ /// </summary>
+ Split = 13,
+ /// <summary>
+ /// GRU Layer
+ /// </summary>
+ GRU = 14,
+ /// <summary>
+ /// Permute Layer
+ /// </summary>
+ Permute = 15,
+ /// <summary>
+ /// Dropout Layer
+ /// </summary>
+ Dropout = 16,
+ /// <summary>
+ /// Backbone using NNStreamer
+ /// </summary>
+ BackboneNNStreamer = 17,
+ /// <summary>
+ /// Centroid KNN Layer
+ /// </summary>
+ CentroidKNN = 18,
+ /// <summary>
+ /// Convolution 1D Layer
+ /// </summary>
+ Conv1D = 19,
+ /// <summary>
+ /// LSTM Cell Layer
+ /// </summary>
+ LSTMCell = 20,
+ /// <summary>
+ /// GRU Cell Layer
+ /// </summary>
+ GRUCell = 21,
+ /// <summary>
+ /// RNN Cell Layer
+ /// </summary>
+ RNNCell = 22,
+ /// <summary>
+ /// ZoneoutLSTM Cell Layer
+ /// </summary>
+ ZoneoutLSTMCell = 23,
+ /// <summary>
+ /// Preprocess flip Layer
+ /// </summary>
+ PreprocessFlip = 300,
+ /// <summary>
+ /// Preprocess translate Layer
+ /// </summary>
+ PreprocessTranslate = 301,
+ /// <summary>
+ /// Preprocess L2Normalization Layer
+ /// </summary>
+ PreprocessL2Norm = 302,
+ /// <summary>
+ /// Mean Squared Error Loss Layer
+ /// </summary>
+ LoseMSE = 500,
+ /// <summary>
+ /// Cross Entropy with Sigmoid Loss Layer
+ /// </summary>
+ LossCrossEntropySigmoid = 501,
+ /// <summary>
+ /// Cross Entropy with Softmax Loss Layer
+ /// </summary>
+ LossCrossEntropySoftmax = 502,
+ /// <summary>
+ /// Unknown
+ /// </summary>
+ Unknown = 999
+ }
+
internal static class NNTrainer
{
--- /dev/null
+/*
+* Copyright (c) 2022 Samsung Electronics Co., Ltd. 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 static Interop;
+using System;
+using System.IO;
+
+namespace Tizen.MachineLearning.Train
+{
+ /// <summary>
+ /// Creates a neural network layer.
+ /// </summary>
+ /// <remarks>
+ /// Use this function to create neural network layer.
+ /// If the function succeeds, layer must be released using Destroy(), if not added to a model.
+ /// If added to a model, layer is available until the model is released.
+ /// </remarks>
+ /// <since_tizen> 10 </since_tizen>
+ public class Layer: IDisposable
+ {
+ private IntPtr handle = IntPtr.Zero;
+ private bool disposed = false;
+
+ /// <summary>
+ /// Creates a neural network layer.
+ /// </summary>
+ /// <param name="type">The nntrainer layer type.</param>
+ /// <since_tizen> 10 </since_tizen>
+ public Layer(NNTrainerLayerType type)
+ {
+ NNTrainerError ret = Interop.Layer.Create(out handle, type);
+ NNTrainer.CheckException(ret, "Failed to create model instance");
+ }
+ /// <summary>
+ /// Frees the neural network layer.
+ /// </summary>
+ /// <since_tizen> 10 </since_tizen>
+ /// <remarks>
+ /// Use this function to destroy neural network layer. Fails if layer is owned by a model.
+ /// </remarks>
+ ~Layer()
+ {
+ Dispose(false);
+ }
+
+ /// <summary>
+ /// Releases any unmanaged resources used by this object.
+ /// </summary>
+ /// <since_tizen> 10 </since_tizen>
+ public void Dispose()
+ {
+ Dispose(true);
+ GC.SuppressFinalize(this);
+ }
+
+ /// <summary>
+ /// Releases any unmanaged resources used by this object including opened handle.
+ /// </summary>
+ /// <param name="disposing">If true, disposes any disposable objects. If false, does not dispose disposable objects.</param>
+ /// <since_tizen> 10 </since_tizen>
+ protected virtual void Dispose(bool disposing)
+ {
+ if (disposed)
+ return;
+ if (disposing)
+ {
+ // release managed object
+ }
+ // release unmanaged object
+ if (handle != IntPtr.Zero)
+ {
+ // Destroy the neural network layer.
+ NNTrainerError ret = Interop.Layer.Destroy(handle);
+ NNTrainer.CheckException(ret, "Failed to destroy layer instance");
+
+ handle = IntPtr.Zero;
+ }
+ disposed = true;
+ }
+ }
+}
projects / platform / core / csapi / tizenfx.git / commitdiff