/* Copyright 2017 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 "tensorflow/lite/c/c_api_internal.h"
#ifndef TF_LITE_STATIC_MEMORY
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#endif  // TF_LITE_STATIC_MEMORY

int TfLiteIntArrayGetSizeInBytes(int size) {
  static TfLiteIntArray dummy;
  return sizeof(dummy) + sizeof(dummy.data[0]) * size;
}

int TfLiteIntArrayEqual(const TfLiteIntArray* a, const TfLiteIntArray* b) {
  if (a == b) return 1;
  if (a == NULL || b == NULL) return 0;
  return TfLiteIntArrayEqualsArray(a, b->size, b->data);
}

int TfLiteIntArrayEqualsArray(const TfLiteIntArray* a, int b_size,
                              const int b_data[]) {
  if (a == NULL) return (b_size == 0);
  if (a->size != b_size) return 0;
  int i = 0;
  for (; i < a->size; i++)
    if (a->data[i] != b_data[i]) return 0;
  return 1;
}

#ifndef TF_LITE_STATIC_MEMORY

TfLiteIntArray* TfLiteIntArrayCreate(int size) {
  TfLiteIntArray* ret =
      (TfLiteIntArray*)malloc(TfLiteIntArrayGetSizeInBytes(size));
  ret->size = size;
  return ret;
}

void TfLiteIntArrayPrint(const char* s, TfLiteIntArray* a) {
  printf("%s: length=%d [", s, a->size);
  if (a->size) printf("%d", a->data[0]);
  int i = 1;
  for (; i < a->size; i++) {
    printf(" %d", a->data[i]);
  }
  printf("]\n");
}

TfLiteIntArray* TfLiteIntArrayCopy(const TfLiteIntArray* src) {
  if (!src) return NULL;
  TfLiteIntArray* ret = TfLiteIntArrayCreate(src->size);
  if (ret) {
    memcpy(ret->data, src->data, src->size * sizeof(int));
  }
  return ret;
}

void TfLiteIntArrayFree(TfLiteIntArray* a) { free(a); }

int TfLiteFloatArrayGetSizeInBytes(int size) {
  static TfLiteFloatArray dummy;
  return sizeof(dummy) + sizeof(dummy.data[0]) * size;
}

TfLiteFloatArray* TfLiteFloatArrayCreate(int size) {
  TfLiteFloatArray* ret =
      (TfLiteFloatArray*)malloc(TfLiteFloatArrayGetSizeInBytes(size));
  ret->size = size;
  return ret;
}

void TfLiteFloatArrayFree(TfLiteFloatArray* a) { free(a); }

void TfLiteTensorDataFree(TfLiteTensor* t) {
  if (t->allocation_type == kTfLiteDynamic && t->data.raw) {
    free(t->data.raw);
  }
  t->data.raw = NULL;
}

void TfLiteQuantizationFree(TfLiteQuantization* quantization) {
  if (quantization->type == kTfLiteAffineQuantization) {
    TfLiteAffineQuantization* q_params =
        (TfLiteAffineQuantization*)(quantization->params);
    if (q_params->scale) {
      TfLiteFloatArrayFree(q_params->scale);
      q_params->scale = NULL;
    }
    if (q_params->zero_point) {
      TfLiteIntArrayFree(q_params->zero_point);
      q_params->zero_point = NULL;
    }
    free(q_params);
  }
  quantization->params = NULL;
  quantization->type = kTfLiteNoQuantization;
}

void TfLiteTensorFree(TfLiteTensor* t) {
  TfLiteTensorDataFree(t);
  if (t->dims) TfLiteIntArrayFree(t->dims);
  t->dims = NULL;

  TfLiteQuantizationFree(&t->quantization);
}

void TfLiteTensorReset(TfLiteType type, const char* name, TfLiteIntArray* dims,
                       TfLiteQuantizationParams quantization, char* buffer,
                       size_t size, TfLiteAllocationType allocation_type,
                       const void* allocation, bool is_variable,
                       TfLiteTensor* tensor) {
  TfLiteTensorFree(tensor);
  tensor->type = type;
  tensor->name = name;
  tensor->dims = dims;
  tensor->params = quantization;
  tensor->data.raw = buffer;
  tensor->bytes = size;
  tensor->allocation_type = allocation_type;
  tensor->allocation = allocation;
  tensor->is_variable = is_variable;

  tensor->quantization.type = kTfLiteNoQuantization;
  tensor->quantization.params = NULL;
}

void TfLiteTensorRealloc(size_t num_bytes, TfLiteTensor* tensor) {
  if (tensor->allocation_type != kTfLiteDynamic) {
    return;
  }
  if (!tensor->data.raw) {
    tensor->data.raw = malloc(num_bytes);
  } else if (num_bytes > tensor->bytes) {
    tensor->data.raw = realloc(tensor->data.raw, num_bytes);
  }
  tensor->bytes = num_bytes;
}
#endif  // TF_LITE_STATIC_MEMORY

const char* TfLiteTypeGetName(TfLiteType type) {
  switch (type) {
    case kTfLiteNoType:
      return "NOTYPE";
    case kTfLiteFloat32:
      return "FLOAT32";
    case kTfLiteInt16:
      return "INT16";
    case kTfLiteInt32:
      return "INT32";
    case kTfLiteUInt8:
      return "UINT8";
    case kTfLiteInt8:
      return "INT8";
    case kTfLiteInt64:
      return "INT64";
    case kTfLiteBool:
      return "BOOL";
    case kTfLiteComplex64:
      return "COMPLEX64";
    case kTfLiteString:
      return "STRING";
    case kTfLiteFloat16:
      return "FLOAT16";
  }
  return "Unknown type";
}

TfLiteDelegate TfLiteDelegateCreate() {
  TfLiteDelegate d = {
      .data_ = NULL,
      .Prepare = NULL,
      .CopyFromBufferHandle = NULL,
      .CopyToBufferHandle = NULL,
      .FreeBufferHandle = NULL,
      .flags = kTfLiteDelegateFlagsNone,
  };
  return d;
}
