#include <stdio.h>
#include <stdlib.h>
#include <unistd.h>
#include <fcntl.h>
#include <sys/stat.h>
#include <cstring>
#include <hpvm.h>
#include <tensorTypes.h>
#include <tensorUtils.h>
#include <config.h>

void var_0_node(void *t1, size_t bytes_t1, void *t2, size_t bytes_t2) {
  __hpvm__hint(hpvm::TENSOR_TARGET);
  __hpvm__attributes(2, t1, t2, 0);

  void *r = __hpvm__tensor_convolution(t1, t2, 1, 1, 1, 1);
  __hpvm__return(2, r, (size_t)0);
}

void var_1_node(void *t1, size_t bytes_t1, void *t2, size_t bytes_t2) {
  __hpvm__hint(hpvm::TENSOR_TARGET);
  __hpvm__attributes(2, t1, t2, 0);

  void *r = __hpvm__tensor_add(t1, t2);
  __hpvm__return(2, r, (size_t)0);
}

void var_2_node(void *t1, size_t bytes_t1) {
  __hpvm__hint(hpvm::TENSOR_TARGET);
  __hpvm__attributes(1, t1, 0);

  void *r = __hpvm__tensor_tanh(t1);
  __hpvm__return(2, r, (size_t)0);
}

void var_3_node(void *t1, size_t bytes_t1, void *t2, size_t bytes_t2) {
  __hpvm__hint(hpvm::TENSOR_TARGET);
  __hpvm__attributes(2, t1, t2, 0);

  void *r = __hpvm__tensor_convolution(t1, t2, 1, 1, 1, 1);
  __hpvm__return(2, r, (size_t)0);
}

void var_4_node(void *t1, size_t bytes_t1, void *t2, size_t bytes_t2) {
  __hpvm__hint(hpvm::TENSOR_TARGET);
  __hpvm__attributes(2, t1, t2, 0);

  void *r = __hpvm__tensor_add(t1, t2);
  __hpvm__return(2, r, (size_t)0);
}

void var_5_node(void *t1, size_t bytes_t1) {
  __hpvm__hint(hpvm::TENSOR_TARGET);
  __hpvm__attributes(1, t1, 0);

  void *r = __hpvm__tensor_tanh(t1);
  __hpvm__return(2, r, (size_t)0);
}

void var_6_node(void *t1, size_t bytes_t1) {
  __hpvm__hint(hpvm::TENSOR_TARGET);
  __hpvm__attributes(1, t1, 0);

  void *r = __hpvm__tensor_pool_max(t1, 2, 2, 0, 0, 2, 2);
  __hpvm__return(2, r, (size_t)0);
}

void var_7_node(void *t1, size_t bytes_t1, void *t2, size_t bytes_t2) {
  __hpvm__hint(hpvm::TENSOR_TARGET);
  __hpvm__attributes(2, t1, t2, 0);

  void *r = __hpvm__tensor_convolution(t1, t2, 1, 1, 1, 1);
  __hpvm__return(2, r, (size_t)0);
}

void var_8_node(void *t1, size_t bytes_t1, void *t2, size_t bytes_t2) {
  __hpvm__hint(hpvm::TENSOR_TARGET);
  __hpvm__attributes(2, t1, t2, 0);

  void *r = __hpvm__tensor_add(t1, t2);
  __hpvm__return(2, r, (size_t)0);
}

void var_9_node(void *t1, size_t bytes_t1) {
  __hpvm__hint(hpvm::TENSOR_TARGET);
  __hpvm__attributes(1, t1, 0);

  void *r = __hpvm__tensor_tanh(t1);
  __hpvm__return(2, r, (size_t)0);
}

void var_10_node(void *t1, size_t bytes_t1, void *t2, size_t bytes_t2) {
  __hpvm__hint(hpvm::TENSOR_TARGET);
  __hpvm__attributes(2, t1, t2, 0);

  void *r = __hpvm__tensor_convolution(t1, t2, 1, 1, 1, 1);
  __hpvm__return(2, r, (size_t)0);
}

void var_11_node(void *t1, size_t bytes_t1, void *t2, size_t bytes_t2) {
  __hpvm__hint(hpvm::TENSOR_TARGET);
  __hpvm__attributes(2, t1, t2, 0);

  void *r = __hpvm__tensor_add(t1, t2);
  __hpvm__return(2, r, (size_t)0);
}

void var_12_node(void *t1, size_t bytes_t1) {
  __hpvm__hint(hpvm::TENSOR_TARGET);
  __hpvm__attributes(1, t1, 0);

  void *r = __hpvm__tensor_tanh(t1);
  __hpvm__return(2, r, (size_t)0);
}

void var_13_node(void *t1, size_t bytes_t1) {
  __hpvm__hint(hpvm::TENSOR_TARGET);
  __hpvm__attributes(1, t1, 0);

  void *r = __hpvm__tensor_pool_max(t1, 2, 2, 0, 0, 2, 2);
  __hpvm__return(2, r, (size_t)0);
}

void var_14_node(void *t1, size_t bytes_t1, void *t2, size_t bytes_t2) {
  __hpvm__hint(hpvm::TENSOR_TARGET);
  __hpvm__attributes(2, t1, t2, 0);

  void *r = __hpvm__tensor_convolution(t1, t2, 1, 1, 1, 1);
  __hpvm__return(2, r, (size_t)0);
}

void var_15_node(void *t1, size_t bytes_t1, void *t2, size_t bytes_t2) {
  __hpvm__hint(hpvm::TENSOR_TARGET);
  __hpvm__attributes(2, t1, t2, 0);

  void *r = __hpvm__tensor_add(t1, t2);
  __hpvm__return(2, r, (size_t)0);
}

void var_16_node(void *t1, size_t bytes_t1) {
  __hpvm__hint(hpvm::TENSOR_TARGET);
  __hpvm__attributes(1, t1, 0);

  void *r = __hpvm__tensor_tanh(t1);
  __hpvm__return(2, r, (size_t)0);
}

void var_17_node(void *t1, size_t bytes_t1, void *t2, size_t bytes_t2) {
  __hpvm__hint(hpvm::TENSOR_TARGET);
  __hpvm__attributes(2, t1, t2, 0);

  void *r = __hpvm__tensor_convolution(t1, t2, 1, 1, 1, 1);
  __hpvm__return(2, r, (size_t)0);
}

void var_18_node(void *t1, size_t bytes_t1, void *t2, size_t bytes_t2) {
  __hpvm__hint(hpvm::TENSOR_TARGET);
  __hpvm__attributes(2, t1, t2, 0);

  void *r = __hpvm__tensor_add(t1, t2);
  __hpvm__return(2, r, (size_t)0);
}

void var_19_node(void *t1, size_t bytes_t1) {
  __hpvm__hint(hpvm::TENSOR_TARGET);
  __hpvm__attributes(1, t1, 0);

  void *r = __hpvm__tensor_tanh(t1);
  __hpvm__return(2, r, (size_t)0);
}

void var_20_node(void *t1, size_t bytes_t1) {
  __hpvm__hint(hpvm::TENSOR_TARGET);
  __hpvm__attributes(1, t1, 0);

  void *r = __hpvm__tensor_pool_max(t1, 2, 2, 0, 0, 2, 2);
  __hpvm__return(2, r, (size_t)0);
}

void var_21_node(void *t1, size_t bytes_t1, void *t2, size_t bytes_t2) {
  __hpvm__hint(hpvm::TENSOR_TARGET);
  __hpvm__attributes(2, t1, t2, 0);

  void *r = __hpvm__tensor_mul(t1, t2);
  __hpvm__return(2, r, (size_t)0);
}

void var_22_node(void *t1, size_t bytes_t1, void *t2, size_t bytes_t2) {
  __hpvm__hint(hpvm::TENSOR_TARGET);
  __hpvm__attributes(2, t1, t2, 0);

  void *r = __hpvm__tensor_add(t1, t2);
  __hpvm__return(2, r, (size_t)0);
}

void var_23_node(void *t1, size_t bytes_t1) {
  __hpvm__hint(hpvm::CUDNN_TARGET);
  __hpvm__attributes(1, t1, 0);

  void *r = __hpvm__tensor_softmax(t1);
  __hpvm__return(2, r, (size_t)0);
}

void root(void *input, size_t input_bytes, void *conv2d_1_w,
          size_t conv2d_1_w_bytes, void *conv2d_1_b, size_t conv2d_1_b_bytes,
          void *conv2d_2_w, size_t conv2d_2_w_bytes, void *conv2d_2_b,
          size_t conv2d_2_b_bytes, void *conv2d_3_w, size_t conv2d_3_w_bytes,
          void *conv2d_3_b, size_t conv2d_3_b_bytes, void *conv2d_4_w,
          size_t conv2d_4_w_bytes, void *conv2d_4_b, size_t conv2d_4_b_bytes,
          void *conv2d_5_w, size_t conv2d_5_w_bytes, void *conv2d_5_b,
          size_t conv2d_5_b_bytes, void *conv2d_6_w, size_t conv2d_6_w_bytes,
          void *conv2d_6_b, size_t conv2d_6_b_bytes, void *dense_1_w,
          size_t dense_1_w_bytes, void *dense_1_b, size_t dense_1_b_bytes) {

  __hpvm__hint(hpvm::CPU_TARGET);
  __hpvm__attributes(15, input, conv2d_1_w, conv2d_1_b, conv2d_2_w, conv2d_2_b,
                     conv2d_3_w, conv2d_3_b, conv2d_4_w, conv2d_4_b, conv2d_5_w,
                     conv2d_5_b, conv2d_6_w, conv2d_6_b, dense_1_w, dense_1_b,
                     0);

  void *var_0 = __hpvm__createNodeND(0, var_0_node);

  __hpvm__bindIn(var_0, 0, 0, 0);
  __hpvm__bindIn(var_0, 1, 1, 0);
  __hpvm__bindIn(var_0, 2, 2, 0);
  __hpvm__bindIn(var_0, 3, 3, 0);

  void *var_1 = __hpvm__createNodeND(0, var_1_node);

  __hpvm__edge(var_0, var_1, 1, 0, 0, 0);
  __hpvm__edge(var_0, var_1, 1, 1, 1, 0);
  __hpvm__bindIn(var_1, 4, 2, 0);
  __hpvm__bindIn(var_1, 5, 3, 0);

  void *var_2 = __hpvm__createNodeND(0, var_2_node);

  __hpvm__edge(var_1, var_2, 1, 0, 0, 0);
  __hpvm__edge(var_1, var_2, 1, 1, 1, 0);

  void *var_3 = __hpvm__createNodeND(0, var_3_node);

  __hpvm__edge(var_2, var_3, 1, 0, 0, 0);
  __hpvm__edge(var_2, var_3, 1, 1, 1, 0);
  __hpvm__bindIn(var_3, 6, 2, 0);
  __hpvm__bindIn(var_3, 7, 3, 0);

  void *var_4 = __hpvm__createNodeND(0, var_4_node);

  __hpvm__edge(var_3, var_4, 1, 0, 0, 0);
  __hpvm__edge(var_3, var_4, 1, 1, 1, 0);
  __hpvm__bindIn(var_4, 8, 2, 0);
  __hpvm__bindIn(var_4, 9, 3, 0);

  void *var_5 = __hpvm__createNodeND(0, var_5_node);

  __hpvm__edge(var_4, var_5, 1, 0, 0, 0);
  __hpvm__edge(var_4, var_5, 1, 1, 1, 0);

  void *var_6 = __hpvm__createNodeND(0, var_6_node);

  __hpvm__edge(var_5, var_6, 1, 0, 0, 0);
  __hpvm__edge(var_5, var_6, 1, 1, 1, 0);

  void *var_7 = __hpvm__createNodeND(0, var_7_node);

  __hpvm__edge(var_6, var_7, 1, 0, 0, 0);
  __hpvm__edge(var_6, var_7, 1, 1, 1, 0);
  __hpvm__bindIn(var_7, 10, 2, 0);
  __hpvm__bindIn(var_7, 11, 3, 0);

  void *var_8 = __hpvm__createNodeND(0, var_8_node);

  __hpvm__edge(var_7, var_8, 1, 0, 0, 0);
  __hpvm__edge(var_7, var_8, 1, 1, 1, 0);
  __hpvm__bindIn(var_8, 12, 2, 0);
  __hpvm__bindIn(var_8, 13, 3, 0);

  void *var_9 = __hpvm__createNodeND(0, var_9_node);

  __hpvm__edge(var_8, var_9, 1, 0, 0, 0);
  __hpvm__edge(var_8, var_9, 1, 1, 1, 0);

  void *var_10 = __hpvm__createNodeND(0, var_10_node);

  __hpvm__edge(var_9, var_10, 1, 0, 0, 0);
  __hpvm__edge(var_9, var_10, 1, 1, 1, 0);
  __hpvm__bindIn(var_10, 14, 2, 0);
  __hpvm__bindIn(var_10, 15, 3, 0);

  void *var_11 = __hpvm__createNodeND(0, var_11_node);

  __hpvm__edge(var_10, var_11, 1, 0, 0, 0);
  __hpvm__edge(var_10, var_11, 1, 1, 1, 0);
  __hpvm__bindIn(var_11, 16, 2, 0);
  __hpvm__bindIn(var_11, 17, 3, 0);

  void *var_12 = __hpvm__createNodeND(0, var_12_node);

  __hpvm__edge(var_11, var_12, 1, 0, 0, 0);
  __hpvm__edge(var_11, var_12, 1, 1, 1, 0);

  void *var_13 = __hpvm__createNodeND(0, var_13_node);

  __hpvm__edge(var_12, var_13, 1, 0, 0, 0);
  __hpvm__edge(var_12, var_13, 1, 1, 1, 0);

  void *var_14 = __hpvm__createNodeND(0, var_14_node);

  __hpvm__edge(var_13, var_14, 1, 0, 0, 0);
  __hpvm__edge(var_13, var_14, 1, 1, 1, 0);
  __hpvm__bindIn(var_14, 18, 2, 0);
  __hpvm__bindIn(var_14, 19, 3, 0);

  void *var_15 = __hpvm__createNodeND(0, var_15_node);

  __hpvm__edge(var_14, var_15, 1, 0, 0, 0);
  __hpvm__edge(var_14, var_15, 1, 1, 1, 0);
  __hpvm__bindIn(var_15, 20, 2, 0);
  __hpvm__bindIn(var_15, 21, 3, 0);

  void *var_16 = __hpvm__createNodeND(0, var_16_node);

  __hpvm__edge(var_15, var_16, 1, 0, 0, 0);
  __hpvm__edge(var_15, var_16, 1, 1, 1, 0);

  void *var_17 = __hpvm__createNodeND(0, var_17_node);

  __hpvm__edge(var_16, var_17, 1, 0, 0, 0);
  __hpvm__edge(var_16, var_17, 1, 1, 1, 0);
  __hpvm__bindIn(var_17, 22, 2, 0);
  __hpvm__bindIn(var_17, 23, 3, 0);

  void *var_18 = __hpvm__createNodeND(0, var_18_node);

  __hpvm__edge(var_17, var_18, 1, 0, 0, 0);
  __hpvm__edge(var_17, var_18, 1, 1, 1, 0);
  __hpvm__bindIn(var_18, 24, 2, 0);
  __hpvm__bindIn(var_18, 25, 3, 0);

  void *var_19 = __hpvm__createNodeND(0, var_19_node);

  __hpvm__edge(var_18, var_19, 1, 0, 0, 0);
  __hpvm__edge(var_18, var_19, 1, 1, 1, 0);

  void *var_20 = __hpvm__createNodeND(0, var_20_node);

  __hpvm__edge(var_19, var_20, 1, 0, 0, 0);
  __hpvm__edge(var_19, var_20, 1, 1, 1, 0);

  void *var_21 = __hpvm__createNodeND(0, var_21_node);

  __hpvm__edge(var_20, var_21, 1, 0, 0, 0);
  __hpvm__edge(var_20, var_21, 1, 1, 1, 0);
  __hpvm__bindIn(var_21, 26, 2, 0);
  __hpvm__bindIn(var_21, 27, 3, 0);

  void *var_22 = __hpvm__createNodeND(0, var_22_node);

  __hpvm__edge(var_21, var_22, 1, 0, 0, 0);
  __hpvm__edge(var_21, var_22, 1, 1, 1, 0);
  __hpvm__bindIn(var_22, 28, 2, 0);
  __hpvm__bindIn(var_22, 29, 3, 0);

  void *var_23 = __hpvm__createNodeND(0, var_23_node);

  __hpvm__edge(var_22, var_23, 1, 0, 0, 0);
  __hpvm__edge(var_22, var_23, 1, 1, 1, 0);

  __hpvm__bindOut(var_23, 0, 0, 0);
  __hpvm__bindOut(var_23, 1, 1, 0);
}

struct ret_t {
  void *tensor;
  size_t bytes;
};

typedef struct __attribute__((__packed__)) {
  void *input;
  size_t input_bytes;
  void *conv2d_1_w;
  size_t conv2d_1_w_bytes;
  void *conv2d_1_b;
  size_t conv2d_1_b_bytes;
  void *conv2d_2_w;
  size_t conv2d_2_w_bytes;
  void *conv2d_2_b;
  size_t conv2d_2_b_bytes;
  void *conv2d_3_w;
  size_t conv2d_3_w_bytes;
  void *conv2d_3_b;
  size_t conv2d_3_b_bytes;
  void *conv2d_4_w;
  size_t conv2d_4_w_bytes;
  void *conv2d_4_b;
  size_t conv2d_4_b_bytes;
  void *conv2d_5_w;
  size_t conv2d_5_w_bytes;
  void *conv2d_5_b;
  size_t conv2d_5_b_bytes;
  void *conv2d_6_w;
  size_t conv2d_6_w_bytes;
  void *conv2d_6_b;
  size_t conv2d_6_b_bytes;
  void *dense_1_w;
  size_t dense_1_w_bytes;
  void *dense_1_b;
  size_t dense_1_b_bytes;

  struct ret_t r;
} RootIn;

int main() {

  std::string dir_prefix = std::string(MODEL_PARAMS_DIR) + "/alexnet2_cifar10/";

  std::string labels_path = dir_prefix + std::string("labels.bin");
  std::string conv2d_1_w_path = dir_prefix + std::string("conv2d_1_w.bin");
  void *conv2d_1_w =
      readTrainedWeights(conv2d_1_w_path.c_str(), 0, 32, 3, 3, 3);
  std::string conv2d_1_b_path = dir_prefix + std::string("conv2d_1_b.bin");
  void *conv2d_1_b =
      readTrainedWeights(conv2d_1_b_path.c_str(), 0, 1, 32, 1, 1);
  std::string conv2d_2_w_path = dir_prefix + std::string("conv2d_2_w.bin");
  void *conv2d_2_w =
      readTrainedWeights(conv2d_2_w_path.c_str(), 0, 32, 32, 3, 3);
  std::string conv2d_2_b_path = dir_prefix + std::string("conv2d_2_b.bin");
  void *conv2d_2_b =
      readTrainedWeights(conv2d_2_b_path.c_str(), 0, 1, 32, 1, 1);
  std::string conv2d_3_w_path = dir_prefix + std::string("conv2d_3_w.bin");
  void *conv2d_3_w =
      readTrainedWeights(conv2d_3_w_path.c_str(), 0, 64, 32, 3, 3);
  std::string conv2d_3_b_path = dir_prefix + std::string("conv2d_3_b.bin");
  void *conv2d_3_b =
      readTrainedWeights(conv2d_3_b_path.c_str(), 0, 1, 64, 1, 1);
  std::string conv2d_4_w_path = dir_prefix + std::string("conv2d_4_w.bin");
  void *conv2d_4_w =
      readTrainedWeights(conv2d_4_w_path.c_str(), 0, 64, 64, 3, 3);
  std::string conv2d_4_b_path = dir_prefix + std::string("conv2d_4_b.bin");
  void *conv2d_4_b =
      readTrainedWeights(conv2d_4_b_path.c_str(), 0, 1, 64, 1, 1);
  std::string conv2d_5_w_path = dir_prefix + std::string("conv2d_5_w.bin");
  void *conv2d_5_w =
      readTrainedWeights(conv2d_5_w_path.c_str(), 0, 128, 64, 3, 3);
  std::string conv2d_5_b_path = dir_prefix + std::string("conv2d_5_b.bin");
  void *conv2d_5_b =
      readTrainedWeights(conv2d_5_b_path.c_str(), 0, 1, 128, 1, 1);
  std::string conv2d_6_w_path = dir_prefix + std::string("conv2d_6_w.bin");
  void *conv2d_6_w =
      readTrainedWeights(conv2d_6_w_path.c_str(), 0, 128, 128, 3, 3);
  std::string conv2d_6_b_path = dir_prefix + std::string("conv2d_6_b.bin");
  void *conv2d_6_b =
      readTrainedWeights(conv2d_6_b_path.c_str(), 0, 1, 128, 1, 1);
  std::string dense_1_w_path = dir_prefix + std::string("dense_1_w.bin");
  void *dense_1_w =
      readTrainedWeights(dense_1_w_path.c_str(), 0, 1, 1, 2048, 10);
  std::string dense_1_b_path = dir_prefix + std::string("dense_1_b.bin");
  void *dense_1_b = readTrainedWeights(dense_1_b_path.c_str(), 0, 1, 10, 1, 1);

  // void* input = readTrainedWeights(input_path.c_str(), 0,10000,3,32,32);
  // uint8_t* labels = readLabels(labels_path.c_str(),10000);

  __hpvm__init();
  RootIn *args = static_cast<RootIn *>(malloc(sizeof(RootIn)));

  args->conv2d_1_w = conv2d_1_w;
  args->conv2d_1_w_bytes = 0;
  args->conv2d_1_b = conv2d_1_b;
  args->conv2d_1_b_bytes = 0;
  args->conv2d_2_w = conv2d_2_w;
  args->conv2d_2_w_bytes = 0;
  args->conv2d_2_b = conv2d_2_b;
  args->conv2d_2_b_bytes = 0;
  args->conv2d_3_w = conv2d_3_w;
  args->conv2d_3_w_bytes = 0;
  args->conv2d_3_b = conv2d_3_b;
  args->conv2d_3_b_bytes = 0;
  args->conv2d_4_w = conv2d_4_w;
  args->conv2d_4_w_bytes = 0;
  args->conv2d_4_b = conv2d_4_b;
  args->conv2d_4_b_bytes = 0;
  args->conv2d_5_w = conv2d_5_w;
  args->conv2d_5_w_bytes = 0;
  args->conv2d_5_b = conv2d_5_b;
  args->conv2d_5_b_bytes = 0;
  args->conv2d_6_w = conv2d_6_w;
  args->conv2d_6_w_bytes = 0;
  args->conv2d_6_b = conv2d_6_b;
  args->conv2d_6_b_bytes = 0;
  args->dense_1_w = dense_1_w;
  args->dense_1_w_bytes = 0;
  args->dense_1_b = dense_1_b;
  args->dense_1_b_bytes = 0;

  int batch_size = 250;
  int test_input_size = 5000;
  int batch_count = test_input_size / batch_size;

  std::string input_path = dir_prefix + std::string("input.bin");
  // void* input = create4DTensor(0,nchw,batch_size,3,32,32);

  startMemTracking();
  startProfiling();

  for (int j = 0; j < 1; j++) {
    for (int i = 0; i < batch_count; i++) {

      int start = i * batch_size;
      int end = (i + 1) * batch_size;

      // copyInputBatch(input_path.c_str(),start,end,3,32,32, input);

      void *input =
          readInputBatch(input_path.c_str(), 0, start, end, 3, 32, 32);

      args->input = input;
      args->input_bytes = 0;

      void *dfg = __hpvm__launch(0, root, (void *)args);

      __hpvm__wait(dfg);

      void *result = static_cast<RootIn *>(args)->r.tensor;
      hpvm_request_tensor(result, 0);

      llvm_hpvm_invokeRtControl(result, labels_path.c_str(), start, end);

      freeBatchMemory();
    }
  }

  stopProfiling();
  __hpvm__cleanup();

  return 0;
}