Draft: [onert-micro] Bring up SparseCrossEntropy Loss

onert-micro/onert-micro/include/OMConfig.h

@@ -41,6 +41,8 @@ enum OMMetrics
   MAE_METRICS,
   CROSS_ENTROPY_METRICS,
   ACCURACY,
+  SPARSE_CROSS_ENTROPY_METRICS,
+  SPARSE_CROSS_ENTROPY_ACCURACY,
 };
 
 /*
@@ -50,6 +52,7 @@ enum OMLoss
 {
   BINARY_CROSS_ENTROPY,
   CROSS_ENTROPY,
+  SPARSE_CROSS_ENTROPY,
   MSE,
   MAE,
 };

onert-micro/onert-micro/include/train/losses_functions/SparseCrossEntropy.h

@@ -0,0 +1,44 @@
+
+/*
+ * Copyright (c) 2024 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.
+ */
+
+#ifndef ONERT_MICRO_TRAIN_LOSSES_FUNCTIONS_SPARSE_CROSS_ENTROPY_H
+#define ONERT_MICRO_TRAIN_LOSSES_FUNCTIONS_SPARSE_CROSS_ENTROPY_H
+
+#include "OMStatus.h"
+
+#include <cstdint>
+
+namespace onert_micro
+{
+namespace train
+{
+namespace losses_functions
+{
+
+// Cross Entropy
+struct SparseCrossEntropy
+{
+  // Calculate sparse cross entropy error backpropagation between calculated and target data
+  static void calculateErrorBackpropagation(const uint32_t flat_size, const float *calculated_data,
+                                            const float *target_data, float *output_grad);
+};
+
+} // namespace losses_functions
+} // namespace train
+} // namespace onert_micro
+
+#endif // ONERT_MICRO_TRAIN_LOSSES_FUNCTIONS_SPARSE_CROSS_ENTROPY_H

onert-micro/onert-micro/include/train/metrics/SparseCrossEntropy.h

@@ -0,0 +1,43 @@
+
+/*
+ * Copyright (c) 2024 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.
+ */
+
+#ifndef ONERT_MICRO_TRAIN_METRICS_SPARSE_CROSS_ENTROPY_H
+#define ONERT_MICRO_TRAIN_METRICS_SPARSE_CROSS_ENTROPY_H
+
+#include "OMStatus.h"
+
+#include <cstdint>
+
+namespace onert_micro
+{
+namespace train
+{
+namespace metrics
+{
+
+struct SparseCrossEntropy
+{
+  // Calculate sparse cross entropy metric between calculated and target data
+  static float calculateValue(const uint32_t flat_size, const float *calculated_data,
+                              const float *target_data);
+};
+
+} // namespace metrics
+} // namespace train
+} // namespace onert_micro
+
+#endif // ONERT_MICRO_TRAIN_METRICS_SPARSE_CROSS_ENTROPY_H

onert-micro/onert-micro/include/train/metrics/SparseCrossEntropyAccuracy.h

@@ -0,0 +1,43 @@
+/*
+ * Copyright (c) 2024 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.
+ */
+
+#ifndef ONERT_MICRO_TRAIN_METRICS_SPARSE_CROSS_ENTROPY_ACCURACY_H
+#define ONERT_MICRO_TRAIN_METRICS_SPARSE_CROSS_ENTROPY_ACCURACY_H
+
+#include "OMStatus.h"
+
+#include <cstdint>
+
+namespace onert_micro
+{
+namespace train
+{
+namespace metrics
+{
+
+// Accuracy metric
+struct SparseCrossEntropyAccuracy
+{
+  // Calculate accuracy metric between calculated and target data
+  static float calculateValue(const uint32_t flat_size, const float *calculated_data,
+                              const float *target_data);
+};
+
+} // namespace metrics
+} // namespace train
+} // namespace onert_micro
+
+#endif // ONERT_MICRO_TRAIN_METRICS_SPARSE_CROSS_ENTROPY_ACCURACY_H

onert-micro/onert-micro/include/train/tests/OMTestUtils.h

@@ -40,7 +40,13 @@ OMStatus train(OMTrainingInterpreter &train_interpreter, OMConfig &config,
   const uint32_t num_train_data_samples = test_base.getTrainNumSamples();
   const uint32_t batch_size = config.training_context.batch_size;
   const uint32_t input_size = train_interpreter.getInputSizeAt(0);
-  const uint32_t target_size = train_interpreter.getOutputSizeAt(0);
+  uint32_t target_size = train_interpreter.getOutputSizeAt(0);
+
+  // TODO: Need to revisit this to make getOuputSize can get proper output number 
+  // when 'all' target number and output numbers are different
+  if (config.training_context.loss == SPARSE_CROSS_ENTROPY)
+    target_size = 1;
+
   for (uint32_t e = 0; e < training_epochs; ++e)
   {
     config.training_context.num_epoch = e + 1;
@@ -92,7 +98,13 @@ OMStatus evaluate(OMTrainingInterpreter &train_interpreter, OMConfig &config,
   const uint32_t num_test_data_samples = test_base.getTestNumSamples();
   const uint32_t batch_size = 1;
   const uint32_t input_size = train_interpreter.getInputSizeAt(0);
-  const uint32_t target_size = train_interpreter.getOutputSizeAt(0);
+  uint32_t target_size = train_interpreter.getOutputSizeAt(0);
+
+  // TODO: Need to revisit this to make getOuputSize can get proper output number 
+  // when 'all' target number and output numbers are different
+  if (config.training_context.loss == SPARSE_CROSS_ENTROPY)
+    target_size = 1;
+
   for (int i = 0; i < num_test_data_samples; ++i)
   {
     // Read current input and target data