1 files changed, 104 insertions, 0 deletions
diff --git a/compiler/luci-interpreter/src/kernels/BatchToSpaceND.cpp b/compiler/luci-interpreter/src/kernels/BatchToSpaceND.cpp
new file mode 100644
index 000000000..591fcc00a
--- /dev/null
+++ b/compiler/luci-interpreter/src/kernels/BatchToSpaceND.cpp
@@ -0,0 +1,104 @@
+/*
+ * Copyright (c) 2021 Samsung Electronics Co., Ltd. All Rights Reserved
+ * Copyright 2019 The TensorFlow 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.
+ */
+
+#include "kernels/BatchToSpaceND.h"
+#include "kernels/Utils.h"
+
+#include <tensorflow/lite/kernels/internal/optimized/optimized_ops.h>
+
+#include <stdexcept>
+
+namespace luci_interpreter
+{
+
+namespace kernels
+{
+
+namespace
+{
+const int kInputMinDimensionNum = 3;
+const int kInputMaxDimensionNum = 4;
+} // namespace
+
+BatchToSpaceND::BatchToSpaceND(const Tensor *input, const Tensor *block_shape, const Tensor *crops,
+                               Tensor *output)
+  : Kernel({input, block_shape, crops}, {output})
+{
+}
+
+void BatchToSpaceND::configure()
+{
+
+  const auto *block_shape_data = block_shape()->data<int32_t>();
+  const auto *crops_data = crops()->data<int32_t>();
+  LUCI_INTERPRETER_CHECK(input()->shape().num_dims() >= kInputMinDimensionNum);
+  LUCI_INTERPRETER_CHECK(input()->shape().num_dims() <= kInputMaxDimensionNum);
+  LUCI_INTERPRETER_CHECK(input()->element_type() == output()->element_type());
+
+  int spatial_dims_num = input()->shape().num_dims() - 2;
+
+  LUCI_INTERPRETER_CHECK(block_shape()->shape().num_dims() == 1);
+  LUCI_INTERPRETER_CHECK(block_shape()->shape().dim(0) == spatial_dims_num);
+
+  LUCI_INTERPRETER_CHECK(crops()->shape().num_dims() == 2);
+  LUCI_INTERPRETER_CHECK(crops()->shape().dim(0) == spatial_dims_num);
+  LUCI_INTERPRETER_CHECK(crops()->shape().dim(1) == 2);
+  for (int i = 0; i < spatial_dims_num * 2; ++i)
+  {
+    LUCI_INTERPRETER_CHECK(crops_data[i] >= 0);
+  }
+
+  Shape output_shape = Shape(input()->shape().num_dims());
+  int output_batch_size = input()->shape().dim(0);
+  for (int i = 0; i < spatial_dims_num; ++i)
+  {
+    LUCI_INTERPRETER_CHECK(output_batch_size % block_shape_data[i] == 0);
+    output_batch_size = output_batch_size / block_shape_data[i];
+    output_shape.dim(i + 1) =
+      input()->shape().dim(i + 1) * block_shape_data[i] - crops_data[i * 2] - crops_data[i * 2 + 1];
+  }
+
+  output_shape.dim(0) = output_batch_size;
+  output_shape.dim(input()->shape().num_dims() - 1) =
+    input()->shape().dim(input()->shape().num_dims() - 1);
+  output()->resize(output_shape);
+}
+
+void BatchToSpaceND::execute() const
+{
+  switch (input()->element_type())
+  {
+    case DataType::FLOAT32:
+      tflite::optimized_ops::BatchToSpaceND(
+        getTensorShape(input()), getTensorData<float>(input()), getTensorShape(block_shape()),
+        getTensorData<int32_t>(block_shape()), getTensorShape(crops()),
+        getTensorData<int32_t>(crops()), getTensorShape(output()), getTensorData<float>(output()));
+      break;
+    case DataType::U8:
+      tflite::optimized_ops::BatchToSpaceND(
+        getTensorShape(input()), getTensorData<uint8_t>(input()), getTensorShape(block_shape()),
+        getTensorData<int32_t>(block_shape()), getTensorShape(crops()),
+        getTensorData<int32_t>(crops()), getTensorShape(output()),
+        getTensorData<uint8_t>(output()));
+      break;
+    default:
+      throw std::runtime_error("Unsupported type.");
+  }
+}
+
+} // namespace kernels
+} // namespace luci_interpreter