/* Copyright 2022 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 <stddef.h>

#include <cstring>

#include "tensorflow/lite/c/builtin_op_data.h"
#include "tensorflow/lite/c/common.h"
#include "tensorflow/lite/kernels/internal/compatibility.h"
#include "tensorflow/lite/kernels/kernel_util.h"
#include "tensorflow/lite/micro/kernels/kernel_util.h"
#include "tensorflow/lite/micro/memory_helpers.h"
#include "tensorflow/lite/micro/micro_context.h"
#include "tensorflow/lite/micro/micro_graph.h"
#include "tensorflow/lite/micro/micro_utils.h"

namespace tflite {

namespace {

struct OpData {
  int cond_subgraph_index;
  int body_subgraph_index;
};

void* WhileInit(TfLiteContext* context, const char* buffer, size_t length) {
  TFLITE_DCHECK(context->AllocatePersistentBuffer != nullptr);
  return context->AllocatePersistentBuffer(context, sizeof(OpData));
}

TfLiteStatus WhilePrepare(TfLiteContext* context, TfLiteNode* node) {
  OpData* op_data = reinterpret_cast<OpData*>(node->user_data);
  const auto* params =
      reinterpret_cast<const TfLiteWhileParams*>(node->builtin_data);

  op_data->cond_subgraph_index = params->cond_subgraph_index;
  op_data->body_subgraph_index = params->body_subgraph_index;

  // The first input is the condition.
  tflite::MicroContext* micro_context = tflite::GetMicroContext(context);

  size_t num_inputs = node->inputs->size;
  size_t num_outputs = node->outputs->size;

  MicroGraph& graph_info = micro_context->graph();

  TF_LITE_ENSURE(context,
                 op_data->cond_subgraph_index < graph_info.NumSubgraphs());
  TF_LITE_ENSURE(context,
                 op_data->body_subgraph_index < graph_info.NumSubgraphs());

  TF_LITE_ENSURE_EQ(context, num_inputs,
                    graph_info.NumSubgraphInputs(op_data->cond_subgraph_index));
  TF_LITE_ENSURE_EQ(context, num_inputs,
                    graph_info.NumSubgraphInputs(op_data->body_subgraph_index));
  TF_LITE_ENSURE_EQ(context, num_inputs, num_outputs);
  TF_LITE_ENSURE_EQ(
      context, num_outputs,
      graph_info.NumSubgraphOutputs(op_data->body_subgraph_index));

  return kTfLiteOk;
}

TfLiteStatus WhileEval(TfLiteContext* context, TfLiteNode* node) {
  const OpData* op_data = reinterpret_cast<OpData*>(node->user_data);

  tflite::MicroContext* micro_context = tflite::GetMicroContext(context);
  MicroGraph* graph_info = &micro_context->graph();

  TF_LITE_ENSURE_OK(context,
                    tflite::micro::CopyOpInputsToSubgraphInputs(
                        context, node, graph_info, op_data->cond_subgraph_index,
                        /*first_tensor_idx=*/0));

  // Preserve the op inputs by copying to op outputs, prior to invoking
  // a subgraph which could invalidate the memory of one or more op inputs.
  // This is possible when using the output of the DECODE operator as input to
  // the WHILE op, in the presence of alternate decompression memory.
  TF_LITE_ENSURE_OK(context,
                    tflite::micro::CopyOpInputsToOpOutputs(context, node));

  TF_LITE_ENSURE_OK(context,
                    graph_info->InvokeSubgraph(op_data->cond_subgraph_index));

  TfLiteEvalTensor* cond_subgraph_output = graph_info->GetSubgraphOutput(
      op_data->cond_subgraph_index, /*tensor_idx=*/0);
  bool cond_value = cond_subgraph_output->data.b[0];

  while (cond_value == true) {
    // Copy output of this iteration back to the body input.
    TF_LITE_ENSURE_OK(
        context, tflite::micro::CopyOpOutputsToSubgraphInputs(
                     context, node, graph_info, op_data->body_subgraph_index));
    TF_LITE_ENSURE_OK(context,
                      graph_info->InvokeSubgraph(op_data->body_subgraph_index));

    TF_LITE_ENSURE_OK(
        context, tflite::micro::CopySubgraphOutputsToOpOutputs(
                     context, node, graph_info, op_data->body_subgraph_index));
    TF_LITE_ENSURE_OK(
        context, tflite::micro::CopyOpOutputsToSubgraphInputs(
                     context, node, graph_info, op_data->cond_subgraph_index));
    TF_LITE_ENSURE_OK(context,
                      graph_info->InvokeSubgraph(op_data->cond_subgraph_index));

    cond_subgraph_output = graph_info->GetSubgraphOutput(
        op_data->cond_subgraph_index, /*tensor_idx=*/0);
    cond_value = cond_subgraph_output->data.b[0];
  }

  return kTfLiteOk;
}

}  // namespace.

TFLMRegistration Register_WHILE() {
  return tflite::micro::RegisterOp(WhileInit, WhilePrepare, WhileEval);
}

}  // namespace tflite