1 files changed, 75 insertions, 0 deletions
diff --git a/runtime/neurun/backend/cpu/kernel/PadLayer.h b/runtime/neurun/backend/cpu/kernel/PadLayer.h
new file mode 100644
index 000000000..f4413a8ed
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+++ b/runtime/neurun/backend/cpu/kernel/PadLayer.h
@@ -0,0 +1,75 @@
+/*
+ * Copyright (c) 2019 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 __NEURUN_BACKEND_CPU_KERNEL_PADLAYER_H__
+#define __NEURUN_BACKEND_CPU_KERNEL_PADLAYER_H__
+
+#include <exec/IFunction.h>
+
+#include "OperationUtils.h"
+
+namespace neurun
+{
+namespace backend
+{
+namespace cpu
+{
+namespace kernel
+{
+
+// Note, this is pad with mode=`CONSTANT`: it doesn't support `REFLECT` and `SYMMETRIC`
+class PadLayer : public ::neurun::exec::IFunction
+{
+public:
+  PadLayer();
+
+public:
+  void padFloat32();
+
+  void padQuant8();
+
+  void configure(uint8_t *inputData, const TensorDescriptor inputDescr, uint8_t *outputData,
+                 const TensorDescriptor outputDescr, const int32_t *padData, int32_t padRank,
+                 uint8_t *constantValueData = nullptr);
+
+  void run();
+  void runSync()
+  {
+    // this abstract method is used just for profiling and called for
+    // backend::acl_common::AclFunction
+    run();
+  }
+
+private:
+  DataPtr _inputData;
+  DataPtr _outputData;
+
+  TensorDescriptor _inputDescr;
+  TensorDescriptor _outputDescr;
+
+  const int32_t *_padData;
+  int32_t _padRank;
+  DataPtr _constantValueData;
+
+  OperandType _inputType;
+};
+
+} // namespace kernel
+} // namespace cpu
+} // namespace backend
+} // namespace neurun
+
+#endif // __NEURUN_BACKEND_CPU_KERNEL_PADLAYER_H__