[tflchef] Introduce TFliteImport (#2355)

* [tflchef] Introduce TFliteImport

This will introduce TFliteImport class that provides needed information from tflite::Model to build recipe

Signed-off-by: SaeHie Park <saehie.park@samsung.com>
* add brief

diff --git a/contrib/tflchef/tflite/src/TFliteImport.cpp b/contrib/tflchef/tflite/src/TFliteImport.cpp
new file mode 100644 (file)
index 0000000..2e5ef50
--- /dev/null
+++ b/contrib/tflchef/tflite/src/TFliteImport.cpp
@@ -0,0 +1,145 @@
+/*
+ * Copyright (c) 2018 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 "TFliteImport.h"
+
+#include "Convert.h"
+
+#include <sstream>
+
+namespace tflchef
+{
+
+const char *kEmptyTensorName = "(noname)";
+
+const char *tensor_type(const tflite::Tensor *tensor)
+{
+  return tflite::EnumNameTensorType(tensor->type());
+}
+
+const char *tensor_name(const tflite::Tensor *tensor)
+{
+  auto name = tensor->name();
+  if (name)
+    return name->c_str();
+  return kEmptyTensorName;
+}
+
+bool is_valid(const tflite::OperatorCode *opcode)
+{
+  tflite::BuiltinOperator code = opcode->builtin_code();
+  return (tflite::BuiltinOperator_MIN <= code && code <= tflite::BuiltinOperator_MAX);
+}
+
+bool is_custom(const tflite::OperatorCode *opcode)
+{
+  tflite::BuiltinOperator code = opcode->builtin_code();
+  return (code == tflite::BuiltinOperator_CUSTOM);
+}
+
+TFliteImport::TFliteImport(const tflite::Model *model)
+{
+  _subgraphs = model->subgraphs();
+  _buffers = model->buffers();
+
+  auto opcodes = model->operator_codes();
+  for (const ::tflite::OperatorCode *opcode : *opcodes)
+  {
+    _op_codes.push_back(opcode);
+  }
+}
+
+bool TFliteImport::select_sub_graph(uint32_t sgindex)
+{
+  _tensors = nullptr;
+  _operators = nullptr;
+  _inputs.clear();
+  _outputs.clear();
+
+  if (_subgraphs->Length() <= sgindex)
+  {
+    assert(false);
+    return false;
+  }
+
+  const tflite::SubGraph *subgraph = (*_subgraphs)[sgindex];
+
+  _tensors = subgraph->tensors();
+  _operators = subgraph->operators();
+
+  _inputs = FlatBufferIntArrayToVector(subgraph->inputs());
+  _outputs = FlatBufferIntArrayToVector(subgraph->outputs());
+
+  return true;
+}
+
+tflite::BuiltinOperator TFliteImport::builtin_code(const tflite::Operator *op) const
+{
+  uint32_t index = op->opcode_index();
+  assert(index < _op_codes.size());
+  const tflite::OperatorCode *opcode = _op_codes.at(index);
+
+  return opcode->builtin_code();
+}
+
+std::string TFliteImport::opcode_name(const tflite::Operator *op) const
+{
+  uint32_t index = op->opcode_index();
+  assert(index < _op_codes.size());
+  const tflite::OperatorCode *opcode = _op_codes.at(index);
+
+  if (!is_valid(opcode))
+  {
+    std::ostringstream oss;
+    oss << "(invalid: " << index << ")";
+    return oss.str();
+  }
+
+  if (is_custom(opcode))
+  {
+    if (!opcode->custom_code())
+      return "(invalid custom)";
+
+    return opcode->custom_code()->c_str();
+  }
+
+  tflite::BuiltinOperator code = opcode->builtin_code();
+  return EnumNameBuiltinOperator(code);
+}
+
+size_t TFliteImport::buffer_info(const tflite::Tensor *tensor, const uint8_t **buff_data)
+{
+  *buff_data = nullptr;
+
+  if (tensor->buffer() == 0)
+    return 0;
+
+  if (auto *buffer = (*_buffers)[tensor->buffer()])
+  {
+    if (auto *array = buffer->data())
+    {
+      if (size_t size = array->size())
+      {
+        *buff_data = reinterpret_cast<const uint8_t *>(array->data());
+        return size;
+      }
+    }
+  }
+
+  return 0;
+}
+
+} // namespace tflchef

diff --git a/contrib/tflchef/tflite/src/TFliteImport.h b/contrib/tflchef/tflite/src/TFliteImport.h
new file mode 100644 (file)
index 0000000..a6ce62f
--- /dev/null
+++ b/contrib/tflchef/tflite/src/TFliteImport.h
@@ -0,0 +1,100 @@
+/*
+ * Copyright (c) 2018 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 __TFLITE_IMPORT_H__
+#define __TFLITE_IMPORT_H__
+
+#include <tflite_generated.h>
+
+#include <tflchef.pb.h>
+
+#include <map>
+#include <vector>
+
+namespace tflchef
+{
+
+using TFliteSubGraphs_t = flatbuffers::Vector<flatbuffers::Offset<tflite::SubGraph>>;
+using TFliteTensors_t = flatbuffers::Vector<flatbuffers::Offset<tflite::Tensor>>;
+using TFliteBuffers_t = flatbuffers::Vector<flatbuffers::Offset<tflite::Buffer>>;
+using TFliteOperators_t = flatbuffers::Vector<flatbuffers::Offset<tflite::Operator>>;
+
+const char *tensor_type(const tflite::Tensor *tensor);
+const char *tensor_name(const tflite::Tensor *tensor);
+bool is_valid(const tflite::OperatorCode *opcode);
+bool is_custom(const tflite::OperatorCode *opcode);
+
+/**
+ * @brief Loads TF lite file and provides helpers to access attributes
+ */
+class TFliteImport
+{
+public:
+  TFliteImport(const tflite::Model *model);
+
+  TFliteImport() = delete;
+
+public:
+  bool select_sub_graph(uint32_t subgraph);
+
+public:
+  const TFliteBuffers_t *buffers() { return _buffers; }
+  const TFliteTensors_t *tensors() { return _tensors; }
+  const TFliteOperators_t *operators() { return _operators; }
+  const std::vector<uint32_t> &inputs() const { return _inputs; }
+  const std::vector<uint32_t> &outputs() const { return _outputs; }
+
+  uint32_t num_subgraph() const { return _subgraphs->Length(); }
+
+  tflite::BuiltinOperator builtin_code(const tflite::Operator *op) const;
+  std::string opcode_name(const tflite::Operator *op) const;
+  size_t buffer_info(const tflite::Tensor *tensor, const uint8_t **buff_data);
+
+  /**
+   * @brief This will record the tensor by index, if it needs filler option,
+   *        such as kernel, bias.
+   */
+  void set_tensor_filler(uint32_t tensor_index) { _tensor_filler[tensor_index] = true; }
+
+  /**
+   * @brief This will return true if the tensor by index, needs a filler option.
+   */
+  bool get_tensor_filler(uint32_t tensor_index)
+  {
+    auto it = _tensor_filler.find(tensor_index);
+    if (it != _tensor_filler.end())
+    {
+      return it->second;
+    }
+    return false;
+  }
+
+private:
+  const TFliteSubGraphs_t *_subgraphs;
+  const TFliteBuffers_t *_buffers;
+  const TFliteTensors_t *_tensors;
+  const TFliteOperators_t *_operators;
+
+  std::vector<const tflite::OperatorCode *> _op_codes;
+  std::vector<uint32_t> _inputs;
+  std::vector<uint32_t> _outputs;
+
+  std::map<uint32_t, bool> _tensor_filler;
+};
+
+} // namespace tflchef
+
+#endif // __TFLITE_IMPORT_H__