1 files changed, 106 insertions, 0 deletions
diff --git a/runtime/onert/core/src/interp/operations/Pad.cc b/runtime/onert/core/src/interp/operations/Pad.cc
new file mode 100644
index 000000000..d2e3627b4
--- /dev/null
+++ b/runtime/onert/core/src/interp/operations/Pad.cc
@@ -0,0 +1,106 @@
+/*
+ * 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.
+ */
+
+#include <cker/operation/Pad.h>
+
+#include "OperationUtil.h"
+
+#include "interp/Registration.h"
+#include "ir/operation/Pad.h"
+
+namespace onert
+{
+namespace interp
+{
+namespace
+{
+
+void preparePad(ExecEnv *env, const ir::Operation &node)
+{
+  const auto input_index = node.getInputs().at(ir::operation::Pad::INPUT);
+  const auto output_index = node.getOutputs().at(0);
+
+  const auto input_tensor = env->tensorAt(input_index);
+
+  const auto output_info = env->graph().operands().at(output_index).info();
+
+  // Check shape and type lhs is same with rhs
+  // TODO Util function to compare TensorInfo
+  if (output_info.total_size() == 0)
+  {
+    throw std::runtime_error{"Interp(Pad): NYI unspecified output shape"};
+  }
+  else
+  {
+    env->allocateIfNeeded(output_index, output_info);
+  }
+
+  const auto output_tensor = env->tensorAt(output_index);
+  if (input_tensor->data_type() != output_tensor->data_type())
+  {
+    throw std::runtime_error{"Interp(Pad): Invalid output type"};
+  }
+}
+
+void invoke(const ITensor *input_tensor, const ITensor *pad_tensor, const ITensor *output_tensor)
+{
+  const auto input_buffer = input_tensor->bufferRO();
+  const auto pad_buffer = pad_tensor->bufferRO();
+  auto output_buffer = output_tensor->buffer();
+
+  int32_t pad_rank = pad_tensor->dimension(0);
+
+  const auto cker_input_shape = convertShape(input_tensor->tensorInfo().shape());
+  const auto cker_output_shape = convertShape(output_tensor->tensorInfo().shape());
+  const float *input_ptr = reinterpret_cast<const float *>(input_buffer);
+  const int32_t *pad_ptr = reinterpret_cast<const int32_t *>(pad_buffer);
+  float *output_ptr = reinterpret_cast<float *>(output_buffer);
+
+  nnfw::cker::Pad(pad_ptr, pad_rank, cker_input_shape, input_ptr, cker_output_shape, output_ptr,
+                  nullptr);
+}
+
+void invokePad(const ExecEnv *env, const ir::Operation &node)
+{
+  const auto input_index = node.getInputs().at(ir::operation::Pad::INPUT);
+  const auto pad_index = node.getInputs().at(ir::operation::Pad::PAD);
+  const auto output_index = node.getOutputs().at(0);
+
+  const auto input_tensor = env->tensorAt(input_index);
+  const auto pad_tensor = env->tensorAt(pad_index);
+  const auto output_tensor = env->tensorAt(output_index);
+
+  const auto data_type = input_tensor->data_type();
+
+  if (data_type == ir::DataType::FLOAT32)
+  {
+    invoke(input_tensor, pad_tensor, output_tensor);
+  }
+  else
+  {
+    throw std::runtime_error{"Interp(Pad): NYI - Unsupported data type"};
+  }
+}
+} // namespace
+
+OpKernel *getPad()
+{
+  static OpKernel kernel = {preparePad, invokePad};
+  return &kernel;
+}
+
+} // namespace interp
+} // namespace onert