training_example_colab.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "accelerator": "GPU",
    "gpuClass": "standard"
  },
  "cells": [
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "1dWdVaAjTg_x",
        "outputId": "a4f45829-54d6-464d-c925-cd3509c64192"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Sun Mar 19 14:08:12 2023       \n",
            "+-----------------------------------------------------------------------------+\n",
            "| NVIDIA-SMI 525.85.12    Driver Version: 525.85.12    CUDA Version: 12.0     |\n",
            "|-------------------------------+----------------------+----------------------+\n",
            "| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |\n",
            "| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |\n",
            "|                               |                      |               MIG M. |\n",
            "|===============================+======================+======================|\n",
            "|   0  Tesla T4            Off  | 00000000:00:04.0 Off |                    0 |\n",
            "| N/A   67C    P0    29W /  70W |      0MiB / 15360MiB |      0%      Default |\n",
            "|                               |                      |                  N/A |\n",
            "+-------------------------------+----------------------+----------------------+\n",
            "                                                                               \n",
            "+-----------------------------------------------------------------------------+\n",
            "| Processes:                                                                  |\n",
            "|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |\n",
            "|        ID   ID                                                   Usage      |\n",
            "|=============================================================================|\n",
            "|  No running processes found                                                 |\n",
            "+-----------------------------------------------------------------------------+\n",
            "/content/relahash\n"
          ]
        }
      ],
      "source": [
        "!nvidia-smi\n",
        "!git clone -q https://github.com/thaiminhpv/relahash/\n",
        "%cd relahash"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!python main.py --ds cifar10 --nbit 64 --eval-interval 1 --beta 50 --device cuda:0"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "3Q-ZbSWCTwev",
        "outputId": "5ec4ce6c-1764-4519-a16a-eb6dd7a19616"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "{'R': 59000,\n",
            " 'arch': 'RelaHash',\n",
            " 'arch_kwargs': {'batchsize': 16,\n",
            "                 'device': 'cuda:0',\n",
            "                 'freeze_weight': False,\n",
            "                 'init_method': 'M',\n",
            "                 'nbit': 64,\n",
            "                 'nclass': 10,\n",
            "                 'pretrained': True},\n",
            " 'batch_size': 16,\n",
            " 'beta': 50.0,\n",
            " 'dataset': 'cifar10',\n",
            " 'dataset_kwargs': {'crop': 224,\n",
            "                    'evaluation_protocol': 1,\n",
            "                    'norm': 2,\n",
            "                    'reset': False,\n",
            "                    'resize': 224,\n",
            "                    'separate_multiclass': False},\n",
            " 'device': 'cuda:0',\n",
            " 'epochs': 100,\n",
            " 'eval_interval': 1,\n",
            " 'logdir': 'logs/RelaHash64_cifar10_1_100_0.0001_adam_/test_420_000',\n",
            " 'm': 0.5,\n",
            " 'multiclass': False,\n",
            " 'optim': 'adam',\n",
            " 'optim_kwargs': {'betas': (0.9, 0.999),\n",
            "                  'lr': 0.0001,\n",
            "                  'momentum': 0.9,\n",
            "                  'nesterov': False,\n",
            "                  'weight_decay': 0.0005},\n",
            " 'save_interval': 1,\n",
            " 'scheduler': 'step',\n",
            " 'scheduler_kwargs': {'gamma': 0.1, 'milestones': '0.5,0.75', 'step_size': 80},\n",
            " 'seed': 420,\n",
            " 'tag': 'test',\n",
            " 'wandb_enable': False}\n",
            "INFO 19-03-23 14:08:19: Creating Datasets\n",
            "Downloading https://www.cs.toronto.edu/~kriz/cifar-10-python.tar.gz to data/cifar10/cifar-10-python.tar.gz\n",
            "100% 170498071/170498071 [00:01<00:00, 90686524.53it/s]\n",
            "Extracting data/cifar10/cifar-10-python.tar.gz to data/cifar10\n",
            "Files already downloaded and verified\n",
            "Files already downloaded and verified\n",
            "Files already downloaded and verified\n",
            "Loading data/cifar10/0_1_test.txt\n",
            "Files already downloaded and verified\n",
            "Files already downloaded and verified\n",
            "Loading data/cifar10/0_1_database.txt\n",
            "INFO 19-03-23 14:08:29: Number of DB data: 59000\n",
            "INFO 19-03-23 14:08:29: Number of Train data: 5000\n",
            "/usr/local/lib/python3.9/dist-packages/torchvision/models/_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead.\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.9/dist-packages/torchvision/models/_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing `weights=AlexNet_Weights.IMAGENET1K_V1`. You can also use `weights=AlexNet_Weights.DEFAULT` to get the most up-to-date weights.\n",
            "  warnings.warn(msg)\n",
            "Downloading: \"https://download.pytorch.org/models/alexnet-owt-7be5be79.pth\" to /root/.cache/torch/hub/checkpoints/alexnet-owt-7be5be79.pth\n",
            "100% 233M/233M [00:02<00:00, 84.1MB/s]\n",
            "INFO 19-03-23 14:08:38: Doing for class 0\n",
            "INFO 19-03-23 14:08:38: Doing for class 1\n",
            "INFO 19-03-23 14:08:38: Doing for class 2\n",
            "INFO 19-03-23 14:08:38: Doing for class 3\n",
            "INFO 19-03-23 14:08:38: Max tried for 2, reducing distance constraint 0.6\n",
            "INFO 19-03-23 14:08:39: Max tried for 2, reducing distance constraint 0.59\n",
            "INFO 19-03-23 14:08:39: Max tried for 2, reducing distance constraint 0.58\n",
            "INFO 19-03-23 14:08:40: Max tried for 2, reducing distance constraint 0.57\n",
            "INFO 19-03-23 14:08:40: Max tried for 2, reducing distance constraint 0.5599999999999999\n",
            "INFO 19-03-23 14:08:40: Doing for class 4\n",
            "INFO 19-03-23 14:08:41: Max tried for 3, reducing distance constraint 0.5499999999999999\n",
            "INFO 19-03-23 14:08:41: Max tried for 3, reducing distance constraint 0.5399999999999999\n",
            "INFO 19-03-23 14:08:42: Max tried for 3, reducing distance constraint 0.5299999999999999\n",
            "INFO 19-03-23 14:08:42: Doing for class 5\n",
            "INFO 19-03-23 14:08:42: Doing for class 6\n",
            "INFO 19-03-23 14:08:43: Max tried for 5, reducing distance constraint 0.5199999999999999\n",
            "INFO 19-03-23 14:08:43: Max tried for 5, reducing distance constraint 0.5099999999999999\n",
            "INFO 19-03-23 14:08:43: Doing for class 7\n",
            "INFO 19-03-23 14:08:44: Max tried for 6, reducing distance constraint 0.4999999999999999\n",
            "INFO 19-03-23 14:08:44: Doing for class 8\n",
            "INFO 19-03-23 14:08:44: Doing for class 9\n",
            "RelaHash(\n",
            "  (backbone): AlexNet(\n",
            "    (features): Sequential(\n",
            "      (0): Conv2d(3, 64, kernel_size=(11, 11), stride=(4, 4), padding=(2, 2))\n",
            "      (1): ReLU(inplace=True)\n",
            "      (2): MaxPool2d(kernel_size=3, stride=2, padding=0, dilation=1, ceil_mode=False)\n",
            "      (3): Conv2d(64, 192, kernel_size=(5, 5), stride=(1, 1), padding=(2, 2))\n",
            "      (4): ReLU(inplace=True)\n",
            "      (5): MaxPool2d(kernel_size=3, stride=2, padding=0, dilation=1, ceil_mode=False)\n",
            "      (6): Conv2d(192, 384, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
            "      (7): ReLU(inplace=True)\n",
            "      (8): Conv2d(384, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
            "      (9): ReLU(inplace=True)\n",
            "      (10): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
            "      (11): ReLU(inplace=True)\n",
            "      (12): MaxPool2d(kernel_size=3, stride=2, padding=0, dilation=1, ceil_mode=False)\n",
            "    )\n",
            "    (avgpool): AdaptiveAvgPool2d(output_size=(6, 6))\n",
            "    (fc): Sequential(\n",
            "      (0): Dropout(p=0.5, inplace=False)\n",
            "      (1): Linear(in_features=9216, out_features=4096, bias=True)\n",
            "      (2): ReLU(inplace=True)\n",
            "      (3): Dropout(p=0.5, inplace=False)\n",
            "      (4): Linear(in_features=4096, out_features=4096, bias=True)\n",
            "      (5): ReLU(inplace=True)\n",
            "    )\n",
            "    (classifier): Linear(in_features=4096, out_features=1000, bias=True)\n",
            "  )\n",
            "  (hash_fc): Sequential(\n",
            "    (0): Linear(in_features=4096, out_features=64, bias=False)\n",
            "    (1): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
            "  )\n",
            "  (relative_similarity): RelativeSimilarity(\n",
            "    nbit=64, n_class=10\n",
            "    (relative_pos): RelativePosition()\n",
            "  )\n",
            ")\n",
            "INFO 19-03-23 14:08:45: Total Bit: 64\n",
            "INFO 19-03-23 14:08:45: Training Start\n",
            "INFO 19-03-23 14:08:45: Epoch [1/100]\n",
            "Training: 100% 312/312 [00:27<00:00, 11.41it/s, Train_loss=21.8, A(CE)=0.687, A(CB)=0.679]\n",
            "\n",
            "Test: 100% 63/63 [00:02<00:00, 29.94it/s, Eval_loss=19.4, A(CE)=0.816, A(CB)=0.819]\n",
            "\n",
            "Test: 100% 3688/3688 [01:52<00:00, 32.78it/s, Eval_loss=19.6, A(CE)=0.799, A(CB)=0.802]\n",
            "\n",
            "Distance [1844/1844] (1.25s)\n",
            "Sorting (2.58s)\n",
            "Query [1000/1000] (4.72s)\n",
            "INFO 19-03-23 14:11:15: Total time usage for calculating mAP: 8.77s\n",
            "INFO 19-03-23 14:11:15: mAP: 0.708623\n",
            "INFO 19-03-23 14:11:16: Epoch [2/100]\n",
            "Training: 100% 312/312 [00:23<00:00, 13.35it/s, Train_loss=18.5, A(CE)=0.839, A(CB)=0.836]\n",
            "\n",
            "Test: 100% 63/63 [00:01<00:00, 32.78it/s, Eval_loss=18.2, A(CE)=0.845, A(CB)=0.852]\n",
            "\n",
            "Test: 100% 3688/3688 [01:53<00:00, 32.59it/s, Eval_loss=18.4, A(CE)=0.833, A(CB)=0.837]\n",
            "\n",
            "\n",
            "Sorting (2.50s)\n",
            "Query [1000/1000] (5.49s)\n",
            "INFO 19-03-23 14:13:43: Total time usage for calculating mAP: 9.05s\n",
            "INFO 19-03-23 14:13:43: mAP: 0.777886\n",
            "INFO 19-03-23 14:13:44: Epoch [3/100]\n",
            "Training: 100% 312/312 [00:24<00:00, 12.59it/s, Train_loss=17.5, A(CE)=0.889, A(CB)=0.886]\n",
            "\n",
            "Test: 100% 63/63 [00:01<00:00, 33.40it/s, Eval_loss=17.8, A(CE)=0.847, A(CB)=0.856]\n",
            "\n",
            "Test: 100% 3688/3688 [01:54<00:00, 32.35it/s, Eval_loss=17.9, A(CE)=0.844, A(CB)=0.849]\n",
            "\n",
            "Distance [1844/1844] (0.82s)\n",
            "Sorting (2.49s)\n",
            "Query [1000/1000] (4.68s)\n",
            "INFO 19-03-23 14:16:13: Total time usage for calculating mAP: 8.19s\n",
            "INFO 19-03-23 14:16:13: mAP: 0.791908\n",
            "INFO 19-03-23 14:16:13: Epoch [4/100]\n",
            "Training: 100% 312/312 [00:23<00:00, 13.13it/s, Train_loss=16.9, A(CE)=0.921, A(CB)=0.921]\n",
            "\n",
            "Test: 100% 63/63 [00:01<00:00, 32.73it/s, Eval_loss=17.6, A(CE)=0.856, A(CB)=0.856]\n",
            "\n",
            "Test: 100% 3688/3688 [01:53<00:00, 32.36it/s, Eval_loss=17.7, A(CE)=0.854, A(CB)=0.859]\n",
            "\n",
            "\n",
            "Sorting (3.13s)\n",
            "Query [1000/1000] (4.65s)\n",
            "INFO 19-03-23 14:18:41: Total time usage for calculating mAP: 8.80s\n",
            "INFO 19-03-23 14:18:42: mAP: 0.804459\n",
            "INFO 19-03-23 14:18:42: Epoch [5/100]\n",
            "Training: 100% 312/312 [00:24<00:00, 12.56it/s, Train_loss=16.4, A(CE)=0.948, A(CB)=0.946]\n",
            "\n",
            "Test: 100% 63/63 [00:01<00:00, 32.92it/s, Eval_loss=17.4, A(CE)=0.878, A(CB)=0.883]\n",
            "\n",
            "Test: 100% 3688/3688 [01:53<00:00, 32.60it/s, Eval_loss=17.5, A(CE)=0.864, A(CB)=0.868]\n",
            "\n",
            "Distance [1844/1844] (0.76s)\n",
            "Sorting (2.37s)\n",
            "Query [1000/1000] (5.45s)\n",
            "INFO 19-03-23 14:21:11: Total time usage for calculating mAP: 8.78s\n",
            "INFO 19-03-23 14:21:11: mAP: 0.823301\n",
            "INFO 19-03-23 14:21:11: Epoch [6/100]\n",
            "Training: 100% 312/312 [00:24<00:00, 12.55it/s, Train_loss=16, A(CE)=0.965, A(CB)=0.963]\n",
            "\n",
            "Test: 100% 63/63 [00:02<00:00, 30.78it/s, Eval_loss=17.3, A(CE)=0.862, A(CB)=0.867]\n",
            "\n",
            "Test: 100% 3688/3688 [01:54<00:00, 32.35it/s, Eval_loss=17.4, A(CE)=0.863, A(CB)=0.868]\n",
            "\n",
            "\n",
            "Sorting (2.40s)\n",
            "Query [1000/1000] (4.60s)\n",
            "INFO 19-03-23 14:23:40: Total time usage for calculating mAP: 8.04s\n",
            "INFO 19-03-23 14:23:40: mAP: 0.818966\n",
            "INFO 19-03-23 14:23:40: Epoch [7/100]\n",
            "Training: 100% 312/312 [00:21<00:00, 14.54it/s, Train_loss=15.7, A(CE)=0.979, A(CB)=0.979]\n",
            "\n",
            "Test: 100% 63/63 [00:01<00:00, 32.44it/s, Eval_loss=17.2, A(CE)=0.876, A(CB)=0.89]\n",
            "\n",
            "Test: 100% 3688/3688 [01:54<00:00, 32.18it/s, Eval_loss=17.3, A(CE)=0.869, A(CB)=0.873]\n",
            "\n",
            "Distance [1844/1844] (0.81s)\n",
            "Sorting (2.26s)\n",
            "Query [1000/1000] (5.35s)\n",
            "INFO 19-03-23 14:26:07: Total time usage for calculating mAP: 8.63s\n",
            "INFO 19-03-23 14:26:07: mAP: 0.833163\n",
            "INFO 19-03-23 14:26:07: Epoch [8/100]\n",
            "Training: 100% 312/312 [00:24<00:00, 12.81it/s, Train_loss=15.4, A(CE)=0.991, A(CB)=0.991]\n",
            "\n",
            "Test: 100% 63/63 [00:01<00:00, 32.75it/s, Eval_loss=17.2, A(CE)=0.884, A(CB)=0.879]\n",
            "\n",
            "Test: 100% 3688/3688 [01:52<00:00, 32.80it/s, Eval_loss=17.3, A(CE)=0.868, A(CB)=0.872]\n",
            "\n",
            "\n",
            "Sorting (2.27s)\n",
            "Query [1000/1000] (4.55s)\n",
            "INFO 19-03-23 14:28:34: Total time usage for calculating mAP: 7.84s\n",
            "INFO 19-03-23 14:28:34: mAP: 0.827822\n",
            "INFO 19-03-23 14:28:34: Epoch [9/100]\n",
            "Training: 100% 312/312 [00:21<00:00, 14.21it/s, Train_loss=15.2, A(CE)=0.995, A(CB)=0.996]\n",
            "\n",
            "Test: 100% 63/63 [00:01<00:00, 33.05it/s, Eval_loss=17.2, A(CE)=0.873, A(CB)=0.879]\n",
            "\n",
            "Test: 100% 3688/3688 [01:52<00:00, 32.85it/s, Eval_loss=17.2, A(CE)=0.872, A(CB)=0.876]\n",
            "\n",
            "\n",
            "Sorting (2.23s)\n",
            "Query [1000/1000] (5.11s)\n",
            "INFO 19-03-23 14:30:58: Total time usage for calculating mAP: 8.33s\n",
            "INFO 19-03-23 14:30:58: mAP: 0.829105\n",
            "INFO 19-03-23 14:30:58: Epoch [10/100]\n",
            "Training: 100% 312/312 [00:20<00:00, 15.16it/s, Train_loss=15.1, A(CE)=0.998, A(CB)=0.998]\n",
            "\n",
            "Test: 100% 63/63 [00:01<00:00, 33.00it/s, Eval_loss=17.1, A(CE)=0.879, A(CB)=0.88]\n",
            "\n",
            "Test: 100% 3688/3688 [01:52<00:00, 32.77it/s, Eval_loss=17.2, A(CE)=0.873, A(CB)=0.877]\n",
            "\n",
            "\n",
            "Sorting (2.20s)\n",
            "Query [1000/1000] (5.19s)\n",
            "INFO 19-03-23 14:33:22: Total time usage for calculating mAP: 8.40s\n",
            "INFO 19-03-23 14:33:22: mAP: 0.833056\n",
            "INFO 19-03-23 14:33:22: Epoch [11/100]\n",
            "Training: 100% 312/312 [00:21<00:00, 14.57it/s, Train_loss=15, A(CE)=0.999, A(CB)=0.999]\n",
            "\n",
            "Test: 100% 63/63 [00:02<00:00, 23.72it/s, Eval_loss=17.1, A(CE)=0.888, A(CB)=0.888]\n",
            "\n",
            "Test: 100% 3688/3688 [01:51<00:00, 33.06it/s, Eval_loss=17.2, A(CE)=0.874, A(CB)=0.878]\n",
            "\n",
            "\n",
            "Sorting (2.44s)\n",
            "Query [1000/1000] (4.51s)\n",
            "INFO 19-03-23 14:35:46: Total time usage for calculating mAP: 8.27s\n",
            "INFO 19-03-23 14:35:46: mAP: 0.836779\n",
            "INFO 19-03-23 14:35:46: Epoch [12/100]\n",
            "Training: 100% 312/312 [00:23<00:00, 13.29it/s, Train_loss=14.9, A(CE)=0.999, A(CB)=0.999]\n",
            "\n",
            "Test: 100% 63/63 [00:01<00:00, 34.03it/s, Eval_loss=17.1, A(CE)=0.873, A(CB)=0.883]\n",
            "\n",
            "Test: 100% 3688/3688 [01:51<00:00, 33.06it/s, Eval_loss=17.2, A(CE)=0.872, A(CB)=0.877]\n",
            "\n",
            "Distance [1844/1844] (0.79s)\n",
            "Sorting (2.22s)\n",
            "Query [1000/1000] (4.70s)\n",
            "INFO 19-03-23 14:38:11: Total time usage for calculating mAP: 7.91s\n",
            "INFO 19-03-23 14:38:11: mAP: 0.831531\n",
            "INFO 19-03-23 14:38:11: Epoch [13/100]\n",
            "Training: 100% 312/312 [00:21<00:00, 14.75it/s, Train_loss=14.8, A(CE)=0.999, A(CB)=0.999]\n",
            "\n",
            "Test: 100% 63/63 [00:01<00:00, 33.79it/s, Eval_loss=17.1, A(CE)=0.882, A(CB)=0.883]\n",
            "\n",
            "Test: 100% 3688/3688 [01:51<00:00, 33.18it/s, Eval_loss=17.1, A(CE)=0.875, A(CB)=0.878]\n",
            "\n",
            "Distance [1844/1844] (0.82s)\n",
            "Sorting (2.20s)\n",
            "Query [1000/1000] (5.18s)\n",
            "INFO 19-03-23 14:40:34: Total time usage for calculating mAP: 8.40s\n",
            "INFO 19-03-23 14:40:34: mAP: 0.832003\n",
            "INFO 19-03-23 14:40:34: Epoch [14/100]\n",
            "Training: 100% 312/312 [00:20<00:00, 15.04it/s, Train_loss=14.7, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:02<00:00, 30.21it/s, Eval_loss=17.1, A(CE)=0.883, A(CB)=0.885]\n",
            "\n",
            "Test: 100% 3688/3688 [01:48<00:00, 33.88it/s, Eval_loss=17.1, A(CE)=0.874, A(CB)=0.878]\n",
            "\n",
            "Distance [1844/1844] (0.80s)\n",
            "Sorting (2.17s)\n",
            "Query [1000/1000] (5.15s)\n",
            "INFO 19-03-23 14:42:54: Total time usage for calculating mAP: 8.33s\n",
            "INFO 19-03-23 14:42:54: mAP: 0.837290\n",
            "INFO 19-03-23 14:42:55: Epoch [15/100]\n",
            "Training: 100% 312/312 [00:23<00:00, 13.15it/s, Train_loss=14.7, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:02<00:00, 28.03it/s, Eval_loss=17.1, A(CE)=0.876, A(CB)=0.882]\n",
            "\n",
            "Test: 100% 3688/3688 [01:47<00:00, 34.17it/s, Eval_loss=17.1, A(CE)=0.874, A(CB)=0.878]\n",
            "\n",
            "\n",
            "Sorting (2.23s)\n",
            "Query [1000/1000] (5.02s)\n",
            "INFO 19-03-23 14:45:17: Total time usage for calculating mAP: 8.22s\n",
            "INFO 19-03-23 14:45:17: mAP: 0.832633\n",
            "INFO 19-03-23 14:45:17: Epoch [16/100]\n",
            "Training: 100% 312/312 [00:20<00:00, 15.11it/s, Train_loss=14.7, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:02<00:00, 23.76it/s, Eval_loss=17, A(CE)=0.877, A(CB)=0.883]\n",
            "\n",
            "Test: 100% 3688/3688 [01:49<00:00, 33.77it/s, Eval_loss=17.1, A(CE)=0.873, A(CB)=0.877]\n",
            "\n",
            "\n",
            "Sorting (3.04s)\n",
            "Query [1000/1000] (4.40s)\n",
            "INFO 19-03-23 14:47:38: Total time usage for calculating mAP: 8.39s\n",
            "INFO 19-03-23 14:47:38: mAP: 0.835753\n",
            "INFO 19-03-23 14:47:38: Epoch [17/100]\n",
            "Training: 100% 312/312 [00:21<00:00, 14.28it/s, Train_loss=14.7, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:01<00:00, 33.76it/s, Eval_loss=17, A(CE)=0.883, A(CB)=0.886]\n",
            "\n",
            "Test: 100% 3688/3688 [01:49<00:00, 33.60it/s, Eval_loss=17.1, A(CE)=0.876, A(CB)=0.879]\n",
            "\n",
            "Distance [1844/1844] (1.05s)\n",
            "Sorting (2.35s)\n",
            "Query [1000/1000] (4.44s)\n",
            "INFO 19-03-23 14:49:59: Total time usage for calculating mAP: 8.09s\n",
            "INFO 19-03-23 14:50:00: mAP: 0.836045\n",
            "INFO 19-03-23 14:50:00: Epoch [18/100]\n",
            "Training: 100% 312/312 [00:21<00:00, 14.64it/s, Train_loss=14.6, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:01<00:00, 34.20it/s, Eval_loss=17, A(CE)=0.887, A(CB)=0.887]\n",
            "\n",
            "Test: 100% 3688/3688 [01:47<00:00, 34.26it/s, Eval_loss=17, A(CE)=0.876, A(CB)=0.88]\n",
            "\n",
            "Distance [1844/1844] (0.70s)\n",
            "Sorting (2.92s)\n",
            "Query [1000/1000] (4.35s)\n",
            "INFO 19-03-23 14:52:19: Total time usage for calculating mAP: 8.22s\n",
            "INFO 19-03-23 14:52:19: mAP: 0.837440\n",
            "INFO 19-03-23 14:52:19: Epoch [19/100]\n",
            "Training: 100% 312/312 [00:23<00:00, 13.08it/s, Train_loss=14.6, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:01<00:00, 34.60it/s, Eval_loss=17, A(CE)=0.88, A(CB)=0.882]\n",
            "\n",
            "Test: 100% 3688/3688 [01:49<00:00, 33.82it/s, Eval_loss=17, A(CE)=0.875, A(CB)=0.879]\n",
            "\n",
            "\n",
            "Sorting (2.39s)\n",
            "Query [1000/1000] (4.40s)\n",
            "INFO 19-03-23 14:54:41: Total time usage for calculating mAP: 7.72s\n",
            "INFO 19-03-23 14:54:41: mAP: 0.835371\n",
            "INFO 19-03-23 14:54:41: Epoch [20/100]\n",
            "Training: 100% 312/312 [00:21<00:00, 14.50it/s, Train_loss=14.6, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:01<00:00, 34.52it/s, Eval_loss=16.9, A(CE)=0.88, A(CB)=0.881]\n",
            "\n",
            "Test: 100% 3688/3688 [01:49<00:00, 33.64it/s, Eval_loss=17, A(CE)=0.876, A(CB)=0.88]\n",
            "\n",
            "Distance [1844/1844] (0.73s)\n",
            "Sorting (2.14s)\n",
            "Query [1000/1000] (4.42s)\n",
            "INFO 19-03-23 14:57:02: Total time usage for calculating mAP: 7.50s\n",
            "INFO 19-03-23 14:57:02: mAP: 0.834698\n",
            "INFO 19-03-23 14:57:02: Epoch [21/100]\n",
            "Training: 100% 312/312 [00:21<00:00, 14.42it/s, Train_loss=14.6, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:01<00:00, 34.15it/s, Eval_loss=16.9, A(CE)=0.886, A(CB)=0.89]\n",
            "\n",
            "Test: 100% 3688/3688 [01:49<00:00, 33.74it/s, Eval_loss=17, A(CE)=0.876, A(CB)=0.879]\n",
            "\n",
            "Distance [1844/1844] (0.74s)\n",
            "Sorting (2.29s)\n",
            "Query [1000/1000] (4.36s)\n",
            "INFO 19-03-23 14:59:22: Total time usage for calculating mAP: 7.59s\n",
            "INFO 19-03-23 14:59:22: mAP: 0.837890\n",
            "INFO 19-03-23 14:59:23: Epoch [22/100]\n",
            "Training: 100% 312/312 [00:23<00:00, 13.31it/s, Train_loss=14.6, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:02<00:00, 30.38it/s, Eval_loss=16.9, A(CE)=0.883, A(CB)=0.887]\n",
            "\n",
            "Test: 100% 3688/3688 [01:56<00:00, 31.71it/s, Eval_loss=17, A(CE)=0.876, A(CB)=0.88]\n",
            "\n",
            "\n",
            "Sorting (2.80s)\n",
            "Query [1000/1000] (4.58s)\n",
            "INFO 19-03-23 15:01:53: Total time usage for calculating mAP: 8.54s\n",
            "INFO 19-03-23 15:01:53: mAP: 0.835008\n",
            "INFO 19-03-23 15:01:53: Epoch [23/100]\n",
            "Training: 100% 312/312 [00:22<00:00, 13.86it/s, Train_loss=14.6, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:01<00:00, 32.17it/s, Eval_loss=16.9, A(CE)=0.888, A(CB)=0.894]\n",
            "\n",
            "Test: 100% 3688/3688 [01:55<00:00, 32.00it/s, Eval_loss=16.9, A(CE)=0.878, A(CB)=0.882]\n",
            "\n",
            "Distance [1844/1844] (0.79s)\n",
            "Sorting (2.10s)\n",
            "Query [1000/1000] (5.17s)\n",
            "INFO 19-03-23 15:04:21: Total time usage for calculating mAP: 8.26s\n",
            "INFO 19-03-23 15:04:21: mAP: 0.840103\n",
            "INFO 19-03-23 15:04:21: Epoch [24/100]\n",
            "Training: 100% 312/312 [00:24<00:00, 12.97it/s, Train_loss=14.6, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:02<00:00, 25.04it/s, Eval_loss=16.9, A(CE)=0.887, A(CB)=0.888]\n",
            "\n",
            "Test: 100% 3688/3688 [01:54<00:00, 32.10it/s, Eval_loss=17, A(CE)=0.876, A(CB)=0.879]\n",
            "\n",
            "Distance [1844/1844] (0.80s)\n",
            "Sorting (2.14s)\n",
            "Query [1000/1000] (4.45s)\n",
            "INFO 19-03-23 15:06:50: Total time usage for calculating mAP: 7.60s\n",
            "INFO 19-03-23 15:06:50: mAP: 0.834339\n",
            "INFO 19-03-23 15:06:50: Epoch [25/100]\n",
            "Training: 100% 312/312 [00:21<00:00, 14.60it/s, Train_loss=14.6, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:01<00:00, 32.83it/s, Eval_loss=16.8, A(CE)=0.891, A(CB)=0.893]\n",
            "\n",
            "Test: 100% 3688/3688 [01:54<00:00, 32.32it/s, Eval_loss=16.9, A(CE)=0.877, A(CB)=0.881]\n",
            "\n",
            "\n",
            "Sorting (2.14s)\n",
            "Query [1000/1000] (5.18s)\n",
            "INFO 19-03-23 15:09:16: Total time usage for calculating mAP: 8.33s\n",
            "INFO 19-03-23 15:09:16: mAP: 0.841783\n",
            "INFO 19-03-23 15:09:16: Epoch [26/100]\n",
            "Training: 100% 312/312 [00:23<00:00, 13.15it/s, Train_loss=14.6, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:02<00:00, 26.81it/s, Eval_loss=16.8, A(CE)=0.879, A(CB)=0.885]\n",
            "\n",
            "Test: 100% 3688/3688 [01:51<00:00, 33.17it/s, Eval_loss=16.9, A(CE)=0.877, A(CB)=0.88]\n",
            "\n",
            "\n",
            "Sorting (2.65s)\n",
            "Query [1000/1000] (4.46s)\n",
            "INFO 19-03-23 15:11:42: Total time usage for calculating mAP: 8.27s\n",
            "INFO 19-03-23 15:11:42: mAP: 0.832584\n",
            "INFO 19-03-23 15:11:42: Epoch [27/100]\n",
            "Training: 100% 312/312 [00:21<00:00, 14.32it/s, Train_loss=14.6, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:01<00:00, 33.36it/s, Eval_loss=16.8, A(CE)=0.883, A(CB)=0.889]\n",
            "\n",
            "Test: 100% 3688/3688 [01:53<00:00, 32.59it/s, Eval_loss=16.8, A(CE)=0.878, A(CB)=0.882]\n",
            "\n",
            "Distance [1844/1844] (0.81s)\n",
            "Sorting (2.14s)\n",
            "Query [1000/1000] (4.48s)\n",
            "INFO 19-03-23 15:14:07: Total time usage for calculating mAP: 7.63s\n",
            "INFO 19-03-23 15:14:07: mAP: 0.836178\n",
            "INFO 19-03-23 15:14:07: Epoch [28/100]\n",
            "Training: 100% 312/312 [00:21<00:00, 14.41it/s, Train_loss=14.6, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:01<00:00, 33.59it/s, Eval_loss=16.8, A(CE)=0.889, A(CB)=0.894]\n",
            "\n",
            "Test: 100% 3688/3688 [01:52<00:00, 32.83it/s, Eval_loss=16.9, A(CE)=0.879, A(CB)=0.882]\n",
            "\n",
            "Distance [1844/1844] (0.81s)\n",
            "Sorting (2.07s)\n",
            "Query [1000/1000] (4.92s)\n",
            "INFO 19-03-23 15:16:31: Total time usage for calculating mAP: 8.01s\n",
            "INFO 19-03-23 15:16:31: mAP: 0.838124\n",
            "INFO 19-03-23 15:16:31: Epoch [29/100]\n",
            "Training: 100% 312/312 [00:21<00:00, 14.79it/s, Train_loss=14.6, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:01<00:00, 32.05it/s, Eval_loss=16.8, A(CE)=0.884, A(CB)=0.891]\n",
            "\n",
            "Test: 100% 3688/3688 [01:52<00:00, 32.73it/s, Eval_loss=16.9, A(CE)=0.877, A(CB)=0.881]\n",
            "\n",
            "\n",
            "Sorting (2.37s)\n",
            "Query [1000/1000] (4.95s)\n",
            "INFO 19-03-23 15:18:55: Total time usage for calculating mAP: 8.32s\n",
            "INFO 19-03-23 15:18:55: mAP: 0.838078\n",
            "INFO 19-03-23 15:18:55: Epoch [30/100]\n",
            "Training: 100% 312/312 [00:21<00:00, 14.68it/s, Train_loss=14.6, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:02<00:00, 27.56it/s, Eval_loss=16.7, A(CE)=0.887, A(CB)=0.89]\n",
            "\n",
            "Test: 100% 3688/3688 [01:51<00:00, 32.94it/s, Eval_loss=16.8, A(CE)=0.879, A(CB)=0.883]\n",
            "\n",
            "\n",
            "Sorting (2.30s)\n",
            "Query [1000/1000] (4.36s)\n",
            "INFO 19-03-23 15:21:18: Total time usage for calculating mAP: 7.94s\n",
            "INFO 19-03-23 15:21:18: mAP: 0.840078\n",
            "INFO 19-03-23 15:21:18: Epoch [31/100]\n",
            "Training: 100% 312/312 [00:21<00:00, 14.20it/s, Train_loss=14.6, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:01<00:00, 32.91it/s, Eval_loss=16.7, A(CE)=0.886, A(CB)=0.894]\n",
            "\n",
            "Test: 100% 3688/3688 [01:52<00:00, 32.73it/s, Eval_loss=16.8, A(CE)=0.879, A(CB)=0.883]\n",
            "\n",
            "Distance [1844/1844] (0.80s)\n",
            "Sorting (2.07s)\n",
            "Query [1000/1000] (4.46s)\n",
            "INFO 19-03-23 15:23:43: Total time usage for calculating mAP: 7.52s\n",
            "INFO 19-03-23 15:23:43: mAP: 0.839666\n",
            "INFO 19-03-23 15:23:43: Epoch [32/100]\n",
            "Training: 100% 312/312 [00:21<00:00, 14.49it/s, Train_loss=14.6, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:01<00:00, 33.34it/s, Eval_loss=16.7, A(CE)=0.893, A(CB)=0.895]\n",
            "\n",
            "Test: 100% 3688/3688 [01:52<00:00, 32.88it/s, Eval_loss=16.8, A(CE)=0.878, A(CB)=0.882]\n",
            "\n",
            "\n",
            "Sorting (2.16s)\n",
            "Query [1000/1000] (4.89s)\n",
            "INFO 19-03-23 15:26:06: Total time usage for calculating mAP: 8.10s\n",
            "INFO 19-03-23 15:26:06: mAP: 0.840906\n",
            "INFO 19-03-23 15:26:06: Epoch [33/100]\n",
            "Training: 100% 312/312 [00:21<00:00, 14.66it/s, Train_loss=14.6, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:01<00:00, 33.03it/s, Eval_loss=16.7, A(CE)=0.888, A(CB)=0.889]\n",
            "\n",
            "Test: 100% 3688/3688 [01:52<00:00, 32.67it/s, Eval_loss=16.8, A(CE)=0.88, A(CB)=0.883]\n",
            "\n",
            "\n",
            "Sorting (2.27s)\n",
            "Query [1000/1000] (5.22s)\n",
            "INFO 19-03-23 15:28:31: Total time usage for calculating mAP: 8.45s\n",
            "INFO 19-03-23 15:28:31: mAP: 0.840305\n",
            "INFO 19-03-23 15:28:31: Epoch [34/100]\n",
            "Training: 100% 312/312 [00:21<00:00, 14.34it/s, Train_loss=14.6, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:02<00:00, 27.97it/s, Eval_loss=16.7, A(CE)=0.893, A(CB)=0.898]\n",
            "\n",
            "Test: 100% 3688/3688 [01:52<00:00, 32.78it/s, Eval_loss=16.7, A(CE)=0.88, A(CB)=0.885]\n",
            "\n",
            "\n",
            "Sorting (2.11s)\n",
            "Query [1000/1000] (4.54s)\n",
            "INFO 19-03-23 15:30:56: Total time usage for calculating mAP: 7.92s\n",
            "INFO 19-03-23 15:30:56: mAP: 0.840784\n",
            "INFO 19-03-23 15:30:56: Epoch [35/100]\n",
            "Training: 100% 312/312 [00:21<00:00, 14.27it/s, Train_loss=14.5, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:01<00:00, 33.54it/s, Eval_loss=16.6, A(CE)=0.886, A(CB)=0.889]\n",
            "\n",
            "Test: 100% 3688/3688 [01:53<00:00, 32.56it/s, Eval_loss=16.7, A(CE)=0.88, A(CB)=0.884]\n",
            "\n",
            "Distance [1844/1844] (0.83s)\n",
            "Sorting (2.08s)\n",
            "Query [1000/1000] (4.54s)\n",
            "INFO 19-03-23 15:33:20: Total time usage for calculating mAP: 7.66s\n",
            "INFO 19-03-23 15:33:20: mAP: 0.835839\n",
            "INFO 19-03-23 15:33:20: Epoch [36/100]\n",
            "Training: 100% 312/312 [00:21<00:00, 14.75it/s, Train_loss=14.6, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:01<00:00, 32.33it/s, Eval_loss=16.7, A(CE)=0.883, A(CB)=0.885]\n",
            "\n",
            "Test: 100% 3688/3688 [01:53<00:00, 32.51it/s, Eval_loss=16.8, A(CE)=0.879, A(CB)=0.883]\n",
            "\n",
            "\n",
            "Sorting (2.05s)\n",
            "Query [1000/1000] (5.29s)\n",
            "INFO 19-03-23 15:35:45: Total time usage for calculating mAP: 8.37s\n",
            "INFO 19-03-23 15:35:45: mAP: 0.834267\n",
            "INFO 19-03-23 15:35:45: Epoch [37/100]\n",
            "Training: 100% 312/312 [00:20<00:00, 14.89it/s, Train_loss=14.6, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:03<00:00, 20.16it/s, Eval_loss=16.6, A(CE)=0.885, A(CB)=0.893]\n",
            "\n",
            "Test: 100% 3688/3688 [01:51<00:00, 33.07it/s, Eval_loss=16.7, A(CE)=0.879, A(CB)=0.884]\n",
            "\n",
            "\n",
            "Sorting (2.83s)\n",
            "Query [1000/1000] (4.50s)\n",
            "INFO 19-03-23 15:38:09: Total time usage for calculating mAP: 8.33s\n",
            "INFO 19-03-23 15:38:09: mAP: 0.838308\n",
            "INFO 19-03-23 15:38:09: Epoch [38/100]\n",
            "Training: 100% 312/312 [00:21<00:00, 14.31it/s, Train_loss=14.6, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:01<00:00, 33.55it/s, Eval_loss=16.6, A(CE)=0.883, A(CB)=0.892]\n",
            "\n",
            "Test: 100% 3688/3688 [01:53<00:00, 32.64it/s, Eval_loss=16.7, A(CE)=0.879, A(CB)=0.883]\n",
            "\n",
            "\n",
            "Sorting (2.07s)\n",
            "Query [1000/1000] (4.39s)\n",
            "INFO 19-03-23 15:40:34: Total time usage for calculating mAP: 7.43s\n",
            "INFO 19-03-23 15:40:34: mAP: 0.838965\n",
            "INFO 19-03-23 15:40:34: Epoch [39/100]\n",
            "Training: 100% 312/312 [00:21<00:00, 14.32it/s, Train_loss=14.6, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:01<00:00, 33.36it/s, Eval_loss=16.6, A(CE)=0.889, A(CB)=0.89]\n",
            "\n",
            "Test: 100% 3688/3688 [01:52<00:00, 32.74it/s, Eval_loss=16.7, A(CE)=0.88, A(CB)=0.884]\n",
            "\n",
            "Distance [1844/1844] (0.81s)\n",
            "Sorting (2.05s)\n",
            "Query [1000/1000] (4.69s)\n",
            "INFO 19-03-23 15:42:58: Total time usage for calculating mAP: 7.75s\n",
            "INFO 19-03-23 15:42:58: mAP: 0.840594\n",
            "INFO 19-03-23 15:42:58: Epoch [40/100]\n",
            "Training: 100% 312/312 [00:20<00:00, 15.01it/s, Train_loss=14.6, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:01<00:00, 33.68it/s, Eval_loss=16.6, A(CE)=0.891, A(CB)=0.896]\n",
            "\n",
            "Test: 100% 3688/3688 [01:52<00:00, 32.69it/s, Eval_loss=16.7, A(CE)=0.88, A(CB)=0.884]\n",
            "\n",
            "Distance [1844/1844] (0.80s)\n",
            "Sorting (2.01s)\n",
            "Query [1000/1000] (5.15s)\n",
            "INFO 19-03-23 15:45:22: Total time usage for calculating mAP: 8.17s\n",
            "INFO 19-03-23 15:45:22: mAP: 0.835949\n",
            "INFO 19-03-23 15:45:22: Epoch [41/100]\n",
            "Training: 100% 312/312 [00:21<00:00, 14.53it/s, Train_loss=14.5, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:02<00:00, 22.70it/s, Eval_loss=16.6, A(CE)=0.897, A(CB)=0.899]\n",
            "\n",
            "Test: 100% 3688/3688 [01:50<00:00, 33.30it/s, Eval_loss=16.7, A(CE)=0.881, A(CB)=0.884]\n",
            "\n",
            "\n",
            "Sorting (2.75s)\n",
            "Query [1000/1000] (4.45s)\n",
            "INFO 19-03-23 15:47:45: Total time usage for calculating mAP: 8.18s\n",
            "INFO 19-03-23 15:47:45: mAP: 0.842555\n",
            "INFO 19-03-23 15:47:46: Epoch [42/100]\n",
            "Training: 100% 312/312 [00:24<00:00, 12.96it/s, Train_loss=14.6, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:01<00:00, 33.66it/s, Eval_loss=16.6, A(CE)=0.895, A(CB)=0.902]\n",
            "\n",
            "Test: 100% 3688/3688 [01:51<00:00, 33.05it/s, Eval_loss=16.7, A(CE)=0.882, A(CB)=0.885]\n",
            "\n",
            "\n",
            "Sorting (2.07s)\n",
            "Query [1000/1000] (4.43s)\n",
            "INFO 19-03-23 15:50:11: Total time usage for calculating mAP: 7.51s\n",
            "INFO 19-03-23 15:50:11: mAP: 0.843667\n",
            "INFO 19-03-23 15:50:11: Epoch [43/100]\n",
            "Training: 100% 312/312 [00:23<00:00, 13.34it/s, Train_loss=14.5, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:01<00:00, 33.87it/s, Eval_loss=16.6, A(CE)=0.895, A(CB)=0.898]\n",
            "\n",
            "Test: 100% 3688/3688 [01:53<00:00, 32.48it/s, Eval_loss=16.6, A(CE)=0.882, A(CB)=0.886]\n",
            "\n",
            "Distance [1844/1844] (0.84s)\n",
            "Sorting (2.10s)\n",
            "Query [1000/1000] (5.40s)\n",
            "INFO 19-03-23 15:52:38: Total time usage for calculating mAP: 8.54s\n",
            "INFO 19-03-23 15:52:38: mAP: 0.844174\n",
            "INFO 19-03-23 15:52:39: Epoch [44/100]\n",
            "Training: 100% 312/312 [00:24<00:00, 12.55it/s, Train_loss=14.6, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:01<00:00, 33.49it/s, Eval_loss=16.6, A(CE)=0.882, A(CB)=0.894]\n",
            "\n",
            "Test: 100% 3688/3688 [01:53<00:00, 32.62it/s, Eval_loss=16.7, A(CE)=0.881, A(CB)=0.885]\n",
            "\n",
            "Distance [1844/1844] (0.82s)\n",
            "Sorting (2.08s)\n",
            "Query [1000/1000] (4.40s)\n",
            "INFO 19-03-23 15:55:06: Total time usage for calculating mAP: 7.51s\n",
            "INFO 19-03-23 15:55:06: mAP: 0.839159\n",
            "INFO 19-03-23 15:55:06: Epoch [45/100]\n",
            "Training: 100% 312/312 [00:21<00:00, 14.54it/s, Train_loss=14.6, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:01<00:00, 33.00it/s, Eval_loss=16.6, A(CE)=0.898, A(CB)=0.904]\n",
            "\n",
            "Test: 100% 3688/3688 [01:53<00:00, 32.38it/s, Eval_loss=16.7, A(CE)=0.88, A(CB)=0.884]\n",
            "\n",
            "\n",
            "Sorting (2.12s)\n",
            "Query [1000/1000] (5.18s)\n",
            "INFO 19-03-23 15:57:32: Total time usage for calculating mAP: 8.31s\n",
            "INFO 19-03-23 15:57:32: mAP: 0.844452\n",
            "INFO 19-03-23 15:57:32: Epoch [46/100]\n",
            "Training: 100% 312/312 [00:24<00:00, 12.87it/s, Train_loss=14.5, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:02<00:00, 31.07it/s, Eval_loss=16.5, A(CE)=0.894, A(CB)=0.894]\n",
            "\n",
            "Test: 100% 3688/3688 [01:52<00:00, 32.75it/s, Eval_loss=16.6, A(CE)=0.881, A(CB)=0.884]\n",
            "\n",
            "\n",
            "Sorting (2.12s)\n",
            "Query [1000/1000] (4.47s)\n",
            "INFO 19-03-23 15:59:59: Total time usage for calculating mAP: 7.81s\n",
            "INFO 19-03-23 15:59:59: mAP: 0.839296\n",
            "INFO 19-03-23 15:59:59: Epoch [47/100]\n",
            "Training: 100% 312/312 [00:22<00:00, 14.11it/s, Train_loss=14.6, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:01<00:00, 32.24it/s, Eval_loss=16.6, A(CE)=0.894, A(CB)=0.9]\n",
            "\n",
            "Test: 100% 3688/3688 [01:53<00:00, 32.49it/s, Eval_loss=16.7, A(CE)=0.881, A(CB)=0.885]\n",
            "\n",
            "\n",
            "Sorting (2.06s)\n",
            "Query [1000/1000] (4.56s)\n",
            "INFO 19-03-23 16:02:24: Total time usage for calculating mAP: 7.62s\n",
            "INFO 19-03-23 16:02:24: mAP: 0.843317\n",
            "INFO 19-03-23 16:02:24: Epoch [48/100]\n",
            "Training: 100% 312/312 [00:21<00:00, 14.43it/s, Train_loss=14.6, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:01<00:00, 33.11it/s, Eval_loss=16.5, A(CE)=0.897, A(CB)=0.902]\n",
            "\n",
            "Test: 100% 3688/3688 [01:53<00:00, 32.48it/s, Eval_loss=16.6, A(CE)=0.883, A(CB)=0.887]\n",
            "\n",
            "\n",
            "Sorting (2.11s)\n",
            "Query [1000/1000] (5.06s)\n",
            "INFO 19-03-23 16:04:50: Total time usage for calculating mAP: 8.21s\n",
            "INFO 19-03-23 16:04:50: mAP: 0.844282\n",
            "INFO 19-03-23 16:04:50: Epoch [49/100]\n",
            "Training: 100% 312/312 [00:21<00:00, 14.20it/s, Train_loss=14.6, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:02<00:00, 28.33it/s, Eval_loss=16.5, A(CE)=0.886, A(CB)=0.891]\n",
            "\n",
            "Test: 100% 3688/3688 [01:53<00:00, 32.50it/s, Eval_loss=16.6, A(CE)=0.881, A(CB)=0.885]\n",
            "\n",
            "\n",
            "Sorting (2.05s)\n",
            "Query [1000/1000] (4.48s)\n",
            "INFO 19-03-23 16:07:15: Total time usage for calculating mAP: 7.65s\n",
            "INFO 19-03-23 16:07:15: mAP: 0.839636\n",
            "INFO 19-03-23 16:07:15: Epoch [50/100]\n",
            "Training: 100% 312/312 [00:22<00:00, 14.11it/s, Train_loss=14.6, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:01<00:00, 33.17it/s, Eval_loss=16.5, A(CE)=0.893, A(CB)=0.896]\n",
            "\n",
            "Test: 100% 3688/3688 [01:54<00:00, 32.15it/s, Eval_loss=16.6, A(CE)=0.884, A(CB)=0.887]\n",
            "\n",
            "\n",
            "Sorting (2.04s)\n",
            "Query [1000/1000] (5.22s)\n",
            "INFO 19-03-23 16:09:42: Total time usage for calculating mAP: 8.30s\n",
            "INFO 19-03-23 16:09:42: mAP: 0.842350\n",
            "INFO 19-03-23 16:09:42: Epoch [51/100]\n",
            "Training: 100% 312/312 [00:20<00:00, 14.87it/s, Train_loss=14.6, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:02<00:00, 24.54it/s, Eval_loss=16.6, A(CE)=0.891, A(CB)=0.893]\n",
            "\n",
            "Test: 100% 3688/3688 [01:56<00:00, 31.72it/s, Eval_loss=16.7, A(CE)=0.881, A(CB)=0.884]\n",
            "\n",
            "\n",
            "Sorting (2.13s)\n",
            "Query [1000/1000] (4.57s)\n",
            "INFO 19-03-23 16:12:10: Total time usage for calculating mAP: 7.83s\n",
            "INFO 19-03-23 16:12:10: mAP: 0.836764\n",
            "INFO 19-03-23 16:12:10: Epoch [52/100]\n",
            "Training: 100% 312/312 [00:22<00:00, 14.02it/s, Train_loss=14.6, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:01<00:00, 32.54it/s, Eval_loss=16.5, A(CE)=0.89, A(CB)=0.891]\n",
            "\n",
            "Test: 100% 3688/3688 [01:55<00:00, 31.89it/s, Eval_loss=16.6, A(CE)=0.881, A(CB)=0.885]\n",
            "\n",
            "Distance [1844/1844] (0.86s)\n",
            "Sorting (2.12s)\n",
            "Query [1000/1000] (5.35s)\n",
            "INFO 19-03-23 16:14:38: Total time usage for calculating mAP: 8.54s\n",
            "INFO 19-03-23 16:14:38: mAP: 0.838874\n",
            "INFO 19-03-23 16:14:38: Epoch [53/100]\n",
            "Training: 100% 312/312 [00:22<00:00, 14.05it/s, Train_loss=14.5, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:02<00:00, 26.46it/s, Eval_loss=16.4, A(CE)=0.893, A(CB)=0.898]\n",
            "\n",
            "Test: 100% 3688/3688 [01:55<00:00, 31.88it/s, Eval_loss=16.6, A(CE)=0.881, A(CB)=0.885]\n",
            "\n",
            "\n",
            "Sorting (2.07s)\n",
            "Query [1000/1000] (4.49s)\n",
            "INFO 19-03-23 16:17:06: Total time usage for calculating mAP: 7.57s\n",
            "INFO 19-03-23 16:17:06: mAP: 0.843417\n",
            "INFO 19-03-23 16:17:06: Epoch [54/100]\n",
            "Training: 100% 312/312 [00:21<00:00, 14.38it/s, Train_loss=14.6, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:01<00:00, 32.70it/s, Eval_loss=16.4, A(CE)=0.895, A(CB)=0.898]\n",
            "\n",
            "Test: 100% 3688/3688 [01:55<00:00, 31.93it/s, Eval_loss=16.5, A(CE)=0.884, A(CB)=0.887]\n",
            "\n",
            "Distance [1844/1844] (0.85s)\n",
            "Sorting (2.07s)\n",
            "Query [1000/1000] (5.25s)\n",
            "INFO 19-03-23 16:19:34: Total time usage for calculating mAP: 8.39s\n",
            "INFO 19-03-23 16:19:34: mAP: 0.841133\n",
            "INFO 19-03-23 16:19:34: Epoch [55/100]\n",
            "Training: 100% 312/312 [00:21<00:00, 14.50it/s, Train_loss=14.6, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:02<00:00, 24.40it/s, Eval_loss=16.4, A(CE)=0.896, A(CB)=0.896]\n",
            "\n",
            "Test: 100% 3688/3688 [02:01<00:00, 30.43it/s, Eval_loss=16.6, A(CE)=0.881, A(CB)=0.884]\n",
            "\n",
            "Distance [1844/1844] (0.88s)\n",
            "Sorting (2.19s)\n",
            "Query [1000/1000] (5.66s)\n",
            "INFO 19-03-23 16:22:08: Total time usage for calculating mAP: 8.95s\n",
            "INFO 19-03-23 16:22:08: mAP: 0.841508\n",
            "INFO 19-03-23 16:22:08: Epoch [56/100]\n",
            "Training: 100% 312/312 [00:23<00:00, 13.34it/s, Train_loss=14.5, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:02<00:00, 25.69it/s, Eval_loss=16.5, A(CE)=0.891, A(CB)=0.889]\n",
            "\n",
            "Test: 100% 3688/3688 [02:02<00:00, 30.03it/s, Eval_loss=16.6, A(CE)=0.881, A(CB)=0.884]\n",
            "\n",
            "\n",
            "Sorting (2.07s)\n",
            "Query [1000/1000] (5.35s)\n",
            "INFO 19-03-23 16:24:45: Total time usage for calculating mAP: 8.47s\n",
            "INFO 19-03-23 16:24:45: mAP: 0.835112\n",
            "INFO 19-03-23 16:24:45: Epoch [57/100]\n",
            "Training: 100% 312/312 [00:21<00:00, 14.24it/s, Train_loss=14.6, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:02<00:00, 25.59it/s, Eval_loss=16.5, A(CE)=0.891, A(CB)=0.898]\n",
            "\n",
            "Test: 100% 3688/3688 [01:57<00:00, 31.39it/s, Eval_loss=16.6, A(CE)=0.882, A(CB)=0.885]\n",
            "\n",
            "\n",
            "Sorting (2.12s)\n",
            "Query [1000/1000] (4.44s)\n",
            "INFO 19-03-23 16:27:15: Total time usage for calculating mAP: 7.59s\n",
            "INFO 19-03-23 16:27:15: mAP: 0.840069\n",
            "INFO 19-03-23 16:27:15: Epoch [58/100]\n",
            "Training: 100% 312/312 [00:21<00:00, 14.56it/s, Train_loss=14.5, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:01<00:00, 33.12it/s, Eval_loss=16.4, A(CE)=0.896, A(CB)=0.902]\n",
            "\n",
            "Test: 100% 3688/3688 [01:55<00:00, 32.06it/s, Eval_loss=16.5, A(CE)=0.884, A(CB)=0.888]\n",
            "\n",
            "Distance [1844/1844] (0.81s)\n",
            "Sorting (2.10s)\n",
            "Query [1000/1000] (5.27s)\n",
            "INFO 19-03-23 16:29:42: Total time usage for calculating mAP: 8.39s\n",
            "INFO 19-03-23 16:29:42: mAP: 0.844311\n",
            "INFO 19-03-23 16:29:42: Epoch [59/100]\n",
            "Training: 100% 312/312 [00:20<00:00, 14.97it/s, Train_loss=14.6, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:02<00:00, 21.43it/s, Eval_loss=16.4, A(CE)=0.895, A(CB)=0.895]\n",
            "\n",
            "Test: 100% 3688/3688 [01:54<00:00, 32.20it/s, Eval_loss=16.6, A(CE)=0.881, A(CB)=0.885]\n",
            "\n",
            "Distance [1844/1844] (1.07s)\n",
            "Sorting (2.06s)\n",
            "Query [1000/1000] (4.45s)\n",
            "INFO 19-03-23 16:32:08: Total time usage for calculating mAP: 7.80s\n",
            "INFO 19-03-23 16:32:08: mAP: 0.841570\n",
            "INFO 19-03-23 16:32:08: Epoch [60/100]\n",
            "Training: 100% 312/312 [00:22<00:00, 13.94it/s, Train_loss=14.5, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:01<00:00, 33.39it/s, Eval_loss=16.4, A(CE)=0.894, A(CB)=0.898]\n",
            "\n",
            "Test: 100% 3688/3688 [01:55<00:00, 32.06it/s, Eval_loss=16.5, A(CE)=0.884, A(CB)=0.887]\n",
            "\n",
            "\n",
            "Sorting (2.04s)\n",
            "Query [1000/1000] (5.21s)\n",
            "INFO 19-03-23 16:34:36: Total time usage for calculating mAP: 8.26s\n",
            "INFO 19-03-23 16:34:36: mAP: 0.841642\n",
            "INFO 19-03-23 16:34:36: Epoch [61/100]\n",
            "Training: 100% 312/312 [00:21<00:00, 14.71it/s, Train_loss=14.6, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:02<00:00, 30.17it/s, Eval_loss=16.4, A(CE)=0.891, A(CB)=0.894]\n",
            "\n",
            "Test: 100% 3688/3688 [01:55<00:00, 31.80it/s, Eval_loss=16.5, A(CE)=0.882, A(CB)=0.886]\n",
            "\n",
            "\n",
            "Sorting (2.49s)\n",
            "Query [1000/1000] (4.56s)\n",
            "INFO 19-03-23 16:37:03: Total time usage for calculating mAP: 8.41s\n",
            "INFO 19-03-23 16:37:03: mAP: 0.836321\n",
            "INFO 19-03-23 16:37:03: Epoch [62/100]\n",
            "Training: 100% 312/312 [00:22<00:00, 13.81it/s, Train_loss=14.6, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:02<00:00, 31.17it/s, Eval_loss=16.5, A(CE)=0.895, A(CB)=0.898]\n",
            "\n",
            "Test: 100% 3688/3688 [01:58<00:00, 31.07it/s, Eval_loss=16.6, A(CE)=0.884, A(CB)=0.887]\n",
            "\n",
            "\n",
            "Sorting (2.10s)\n",
            "Query [1000/1000] (5.41s)\n",
            "INFO 19-03-23 16:39:35: Total time usage for calculating mAP: 8.56s\n",
            "INFO 19-03-23 16:39:35: mAP: 0.842179\n",
            "INFO 19-03-23 16:39:35: Epoch [63/100]\n",
            "Training: 100% 312/312 [00:22<00:00, 13.98it/s, Train_loss=14.5, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:02<00:00, 26.58it/s, Eval_loss=16.5, A(CE)=0.887, A(CB)=0.89]\n",
            "\n",
            "Test: 100% 3688/3688 [01:52<00:00, 32.82it/s, Eval_loss=16.5, A(CE)=0.882, A(CB)=0.886]\n",
            "\n",
            "\n",
            "Sorting (2.02s)\n",
            "Query [1000/1000] (4.42s)\n",
            "INFO 19-03-23 16:42:00: Total time usage for calculating mAP: 7.71s\n",
            "INFO 19-03-23 16:42:00: mAP: 0.837508\n",
            "INFO 19-03-23 16:42:00: Epoch [64/100]\n",
            "Training: 100% 312/312 [00:21<00:00, 14.28it/s, Train_loss=14.5, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:01<00:00, 33.64it/s, Eval_loss=16.4, A(CE)=0.891, A(CB)=0.897]\n",
            "\n",
            "Test: 100% 3688/3688 [01:52<00:00, 32.77it/s, Eval_loss=16.5, A(CE)=0.884, A(CB)=0.887]\n",
            "\n",
            "\n",
            "Sorting (2.09s)\n",
            "Query [1000/1000] (4.52s)\n",
            "INFO 19-03-23 16:44:24: Total time usage for calculating mAP: 7.65s\n",
            "INFO 19-03-23 16:44:24: mAP: 0.841442\n",
            "INFO 19-03-23 16:44:24: Epoch [65/100]\n",
            "Training: 100% 312/312 [00:21<00:00, 14.49it/s, Train_loss=14.6, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:01<00:00, 32.84it/s, Eval_loss=16.4, A(CE)=0.904, A(CB)=0.902]\n",
            "\n",
            "Test: 100% 3688/3688 [01:53<00:00, 32.51it/s, Eval_loss=16.5, A(CE)=0.883, A(CB)=0.887]\n",
            "\n",
            "\n",
            "Sorting (2.04s)\n",
            "Query [1000/1000] (5.30s)\n",
            "INFO 19-03-23 16:46:50: Total time usage for calculating mAP: 8.37s\n",
            "INFO 19-03-23 16:46:50: mAP: 0.838103\n",
            "INFO 19-03-23 16:46:50: Epoch [66/100]\n",
            "Training: 100% 312/312 [00:20<00:00, 15.08it/s, Train_loss=14.6, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:02<00:00, 28.54it/s, Eval_loss=16.4, A(CE)=0.892, A(CB)=0.899]\n",
            "\n",
            "Test: 100% 3688/3688 [01:54<00:00, 32.11it/s, Eval_loss=16.5, A(CE)=0.882, A(CB)=0.887]\n",
            "\n",
            "\n",
            "Sorting (2.40s)\n",
            "Query [1000/1000] (4.92s)\n",
            "INFO 19-03-23 16:49:16: Total time usage for calculating mAP: 8.63s\n",
            "INFO 19-03-23 16:49:16: mAP: 0.842225\n",
            "INFO 19-03-23 16:49:16: Epoch [67/100]\n",
            "Training: 100% 312/312 [00:22<00:00, 14.04it/s, Train_loss=14.5, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:01<00:00, 32.67it/s, Eval_loss=16.3, A(CE)=0.895, A(CB)=0.897]\n",
            "\n",
            "Test: 100% 3688/3688 [01:56<00:00, 31.77it/s, Eval_loss=16.5, A(CE)=0.883, A(CB)=0.886]\n",
            "\n",
            "\n",
            "Sorting (2.02s)\n",
            "Query [1000/1000] (5.13s)\n",
            "INFO 19-03-23 16:51:44: Total time usage for calculating mAP: 8.17s\n",
            "INFO 19-03-23 16:51:44: mAP: 0.841589\n",
            "INFO 19-03-23 16:51:44: Epoch [68/100]\n",
            "Training: 100% 312/312 [00:21<00:00, 14.80it/s, Train_loss=14.5, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:02<00:00, 22.21it/s, Eval_loss=16.4, A(CE)=0.889, A(CB)=0.891]\n",
            "\n",
            "Test: 100% 3688/3688 [01:53<00:00, 32.41it/s, Eval_loss=16.5, A(CE)=0.882, A(CB)=0.886]\n",
            "\n",
            "\n",
            "Sorting (2.63s)\n",
            "Query [1000/1000] (4.48s)\n",
            "INFO 19-03-23 16:54:10: Total time usage for calculating mAP: 8.26s\n",
            "INFO 19-03-23 16:54:10: mAP: 0.838653\n",
            "INFO 19-03-23 16:54:10: Epoch [69/100]\n",
            "Training: 100% 312/312 [00:22<00:00, 14.12it/s, Train_loss=14.5, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:01<00:00, 32.59it/s, Eval_loss=16.4, A(CE)=0.895, A(CB)=0.895]\n",
            "\n",
            "Test: 100% 3688/3688 [01:53<00:00, 32.36it/s, Eval_loss=16.5, A(CE)=0.882, A(CB)=0.887]\n",
            "\n",
            "\n",
            "Sorting (2.05s)\n",
            "Query [1000/1000] (4.50s)\n",
            "INFO 19-03-23 16:56:36: Total time usage for calculating mAP: 7.60s\n",
            "INFO 19-03-23 16:56:36: mAP: 0.839031\n",
            "INFO 19-03-23 16:56:36: Epoch [70/100]\n",
            "Training: 100% 312/312 [00:21<00:00, 14.42it/s, Train_loss=14.5, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:01<00:00, 32.62it/s, Eval_loss=16.4, A(CE)=0.889, A(CB)=0.895]\n",
            "\n",
            "Test: 100% 3688/3688 [01:53<00:00, 32.36it/s, Eval_loss=16.6, A(CE)=0.881, A(CB)=0.885]\n",
            "\n",
            "\n",
            "Sorting (2.05s)\n",
            "Query [1000/1000] (5.26s)\n",
            "INFO 19-03-23 16:59:02: Total time usage for calculating mAP: 8.38s\n",
            "INFO 19-03-23 16:59:02: mAP: 0.839775\n",
            "INFO 19-03-23 16:59:02: Epoch [71/100]\n",
            "Training: 100% 312/312 [00:21<00:00, 14.78it/s, Train_loss=14.5, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:02<00:00, 28.42it/s, Eval_loss=16.3, A(CE)=0.901, A(CB)=0.905]\n",
            "\n",
            "Test: 100% 3688/3688 [01:54<00:00, 32.20it/s, Eval_loss=16.5, A(CE)=0.884, A(CB)=0.888]\n",
            "\n",
            "Distance [1844/1844] (0.87s)\n",
            "Sorting (2.69s)\n",
            "Query [1000/1000] (4.45s)\n",
            "INFO 19-03-23 17:01:28: Total time usage for calculating mAP: 8.27s\n",
            "INFO 19-03-23 17:01:28: mAP: 0.844539\n",
            "INFO 19-03-23 17:01:29: Epoch [72/100]\n",
            "Training: 100% 312/312 [00:24<00:00, 12.83it/s, Train_loss=14.6, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:01<00:00, 32.60it/s, Eval_loss=16.4, A(CE)=0.891, A(CB)=0.895]\n",
            "\n",
            "Test: 100% 3688/3688 [01:55<00:00, 32.05it/s, Eval_loss=16.5, A(CE)=0.882, A(CB)=0.886]\n",
            "\n",
            "Distance [1844/1844] (0.84s)\n",
            "Sorting (2.11s)\n",
            "Query [1000/1000] (5.34s)\n",
            "INFO 19-03-23 17:03:59: Total time usage for calculating mAP: 8.50s\n",
            "INFO 19-03-23 17:03:59: mAP: 0.838980\n",
            "INFO 19-03-23 17:03:59: Epoch [73/100]\n",
            "Training: 100% 312/312 [00:20<00:00, 14.89it/s, Train_loss=14.6, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:02<00:00, 24.51it/s, Eval_loss=16.3, A(CE)=0.893, A(CB)=0.898]\n",
            "\n",
            "Test: 100% 3688/3688 [01:54<00:00, 32.20it/s, Eval_loss=16.5, A(CE)=0.883, A(CB)=0.887]\n",
            "\n",
            "\n",
            "Sorting (2.32s)\n",
            "Query [1000/1000] (4.52s)\n",
            "INFO 19-03-23 17:06:25: Total time usage for calculating mAP: 8.14s\n",
            "INFO 19-03-23 17:06:25: mAP: 0.841705\n",
            "INFO 19-03-23 17:06:25: Epoch [74/100]\n",
            "Training: 100% 312/312 [00:21<00:00, 14.19it/s, Train_loss=14.6, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:01<00:00, 32.90it/s, Eval_loss=16.3, A(CE)=0.89, A(CB)=0.891]\n",
            "\n",
            "Test: 100% 3688/3688 [01:54<00:00, 32.13it/s, Eval_loss=16.5, A(CE)=0.882, A(CB)=0.886]\n",
            "\n",
            "\n",
            "Sorting (2.02s)\n",
            "Query [1000/1000] (4.58s)\n",
            "INFO 19-03-23 17:08:51: Total time usage for calculating mAP: 7.63s\n",
            "INFO 19-03-23 17:08:51: mAP: 0.839810\n",
            "INFO 19-03-23 17:08:51: Epoch [75/100]\n",
            "Training: 100% 312/312 [00:21<00:00, 14.59it/s, Train_loss=14.5, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:01<00:00, 31.71it/s, Eval_loss=16.3, A(CE)=0.89, A(CB)=0.893]\n",
            "\n",
            "Test: 100% 3688/3688 [01:55<00:00, 31.98it/s, Eval_loss=16.5, A(CE)=0.884, A(CB)=0.887]\n",
            "\n",
            "\n",
            "Sorting (2.03s)\n",
            "Query [1000/1000] (5.10s)\n",
            "INFO 19-03-23 17:11:18: Total time usage for calculating mAP: 8.15s\n",
            "INFO 19-03-23 17:11:18: mAP: 0.834859\n",
            "INFO 19-03-23 17:11:18: Epoch [76/100]\n",
            "Training: 100% 312/312 [00:21<00:00, 14.73it/s, Train_loss=14.5, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:02<00:00, 23.47it/s, Eval_loss=16.3, A(CE)=0.893, A(CB)=0.895]\n",
            "\n",
            "Test: 100% 3688/3688 [01:55<00:00, 32.02it/s, Eval_loss=16.4, A(CE)=0.883, A(CB)=0.887]\n",
            "\n",
            "Distance [1844/1844] (0.81s)\n",
            "Sorting (2.01s)\n",
            "Query [1000/1000] (4.35s)\n",
            "INFO 19-03-23 17:13:45: Total time usage for calculating mAP: 7.38s\n",
            "INFO 19-03-23 17:13:45: mAP: 0.838304\n",
            "INFO 19-03-23 17:13:45: Epoch [77/100]\n",
            "Training: 100% 312/312 [00:22<00:00, 14.06it/s, Train_loss=14.5, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:01<00:00, 31.92it/s, Eval_loss=16.3, A(CE)=0.895, A(CB)=0.898]\n",
            "\n",
            "Test: 100% 3688/3688 [01:55<00:00, 32.04it/s, Eval_loss=16.4, A(CE)=0.884, A(CB)=0.888]\n",
            "\n",
            "Distance [1844/1844] (0.83s)\n",
            "Sorting (1.98s)\n",
            "Query [1000/1000] (5.20s)\n",
            "INFO 19-03-23 17:16:12: Total time usage for calculating mAP: 8.22s\n",
            "INFO 19-03-23 17:16:12: mAP: 0.839982\n",
            "INFO 19-03-23 17:16:12: Epoch [78/100]\n",
            "Training: 100% 312/312 [00:21<00:00, 14.64it/s, Train_loss=14.5, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:02<00:00, 22.91it/s, Eval_loss=16.3, A(CE)=0.892, A(CB)=0.893]\n",
            "\n",
            "Test: 100% 3688/3688 [01:54<00:00, 32.09it/s, Eval_loss=16.4, A(CE)=0.885, A(CB)=0.888]\n",
            "\n",
            "\n",
            "Sorting (2.06s)\n",
            "Query [1000/1000] (4.52s)\n",
            "INFO 19-03-23 17:18:39: Total time usage for calculating mAP: 7.92s\n",
            "INFO 19-03-23 17:18:39: mAP: 0.836067\n",
            "INFO 19-03-23 17:18:39: Epoch [79/100]\n",
            "Training: 100% 312/312 [00:22<00:00, 14.08it/s, Train_loss=14.5, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:01<00:00, 32.78it/s, Eval_loss=16.4, A(CE)=0.894, A(CB)=0.895]\n",
            "\n",
            "Test: 100% 3688/3688 [01:56<00:00, 31.77it/s, Eval_loss=16.5, A(CE)=0.883, A(CB)=0.886]\n",
            "\n",
            "\n",
            "Sorting (2.07s)\n",
            "Query [1000/1000] (5.25s)\n",
            "INFO 19-03-23 17:21:08: Total time usage for calculating mAP: 8.35s\n",
            "INFO 19-03-23 17:21:08: mAP: 0.841748\n",
            "INFO 19-03-23 17:21:08: Epoch [80/100]\n",
            "Training: 100% 312/312 [00:20<00:00, 15.24it/s, Train_loss=14.5, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:01<00:00, 33.12it/s, Eval_loss=16.4, A(CE)=0.888, A(CB)=0.893]\n",
            "\n",
            "Test: 100% 3688/3688 [01:52<00:00, 32.79it/s, Eval_loss=16.5, A(CE)=0.88, A(CB)=0.884]\n",
            "\n",
            "\n",
            "Sorting (2.00s)\n",
            "Query [1000/1000] (5.22s)\n",
            "INFO 19-03-23 17:23:31: Total time usage for calculating mAP: 8.28s\n",
            "INFO 19-03-23 17:23:31: mAP: 0.836330\n",
            "INFO 19-03-23 17:23:31: Epoch [81/100]\n",
            "Training: 100% 312/312 [00:20<00:00, 15.05it/s, Train_loss=14.5, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:02<00:00, 22.84it/s, Eval_loss=16.3, A(CE)=0.898, A(CB)=0.906]\n",
            "\n",
            "Test: 100% 3688/3688 [01:51<00:00, 33.14it/s, Eval_loss=16.5, A(CE)=0.885, A(CB)=0.889]\n",
            "\n",
            "Distance [1844/1844] (0.72s)\n",
            "Sorting (2.71s)\n",
            "Query [1000/1000] (4.46s)\n",
            "INFO 19-03-23 17:25:54: Total time usage for calculating mAP: 8.09s\n",
            "INFO 19-03-23 17:25:54: mAP: 0.845224\n",
            "INFO 19-03-23 17:25:55: Epoch [82/100]\n",
            "Training: 100% 312/312 [00:24<00:00, 12.85it/s, Train_loss=14.5, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:01<00:00, 31.81it/s, Eval_loss=16.3, A(CE)=0.897, A(CB)=0.903]\n",
            "\n",
            "Test: 100% 3688/3688 [01:53<00:00, 32.41it/s, Eval_loss=16.4, A(CE)=0.886, A(CB)=0.889]\n",
            "\n",
            "Distance [1844/1844] (0.81s)\n",
            "Sorting (1.96s)\n",
            "Query [1000/1000] (4.96s)\n",
            "INFO 19-03-23 17:28:23: Total time usage for calculating mAP: 7.93s\n",
            "INFO 19-03-23 17:28:23: mAP: 0.844393\n",
            "INFO 19-03-23 17:28:23: Epoch [83/100]\n",
            "Training: 100% 312/312 [00:21<00:00, 14.85it/s, Train_loss=14.5, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:01<00:00, 33.91it/s, Eval_loss=16.3, A(CE)=0.897, A(CB)=0.9]\n",
            "\n",
            "Test: 100% 3688/3688 [01:52<00:00, 32.86it/s, Eval_loss=16.4, A(CE)=0.885, A(CB)=0.889]\n",
            "\n",
            "Distance [1844/1844] (0.81s)\n",
            "Sorting (1.96s)\n",
            "Query [1000/1000] (5.17s)\n",
            "INFO 19-03-23 17:30:46: Total time usage for calculating mAP: 8.14s\n",
            "INFO 19-03-23 17:30:46: mAP: 0.841908\n",
            "INFO 19-03-23 17:30:46: Epoch [84/100]\n",
            "Training: 100% 312/312 [00:21<00:00, 14.69it/s, Train_loss=14.5, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:02<00:00, 22.96it/s, Eval_loss=16.2, A(CE)=0.898, A(CB)=0.904]\n",
            "\n",
            "Test: 100% 3688/3688 [01:51<00:00, 33.13it/s, Eval_loss=16.4, A(CE)=0.885, A(CB)=0.89]\n",
            "\n",
            "\n",
            "Sorting (2.66s)\n",
            "Query [1000/1000] (4.37s)\n",
            "INFO 19-03-23 17:33:10: Total time usage for calculating mAP: 8.09s\n",
            "INFO 19-03-23 17:33:10: mAP: 0.846231\n",
            "INFO 19-03-23 17:33:10: Epoch [85/100]\n",
            "Training: 100% 312/312 [00:24<00:00, 12.95it/s, Train_loss=14.5, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:01<00:00, 33.09it/s, Eval_loss=16.3, A(CE)=0.898, A(CB)=0.904]\n",
            "\n",
            "Test: 100% 3688/3688 [01:51<00:00, 33.02it/s, Eval_loss=16.4, A(CE)=0.886, A(CB)=0.889]\n",
            "\n",
            "\n",
            "Sorting (2.03s)\n",
            "Query [1000/1000] (4.35s)\n",
            "INFO 19-03-23 17:35:35: Total time usage for calculating mAP: 7.34s\n",
            "INFO 19-03-23 17:35:35: mAP: 0.843072\n",
            "INFO 19-03-23 17:35:35: Epoch [86/100]\n",
            "Training: 100% 312/312 [00:21<00:00, 14.58it/s, Train_loss=14.5, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:01<00:00, 33.34it/s, Eval_loss=16.3, A(CE)=0.897, A(CB)=0.902]\n",
            "\n",
            "Test: 100% 3688/3688 [01:51<00:00, 33.04it/s, Eval_loss=16.4, A(CE)=0.886, A(CB)=0.889]\n",
            "\n",
            "\n",
            "Sorting (1.98s)\n",
            "Query [1000/1000] (4.38s)\n",
            "INFO 19-03-23 17:37:58: Total time usage for calculating mAP: 7.36s\n",
            "INFO 19-03-23 17:37:58: mAP: 0.841389\n",
            "INFO 19-03-23 17:37:58: Epoch [87/100]\n",
            "Training: 100% 312/312 [00:21<00:00, 14.64it/s, Train_loss=14.5, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:01<00:00, 33.14it/s, Eval_loss=16.3, A(CE)=0.901, A(CB)=0.903]\n",
            "\n",
            "Test: 100% 3688/3688 [01:52<00:00, 32.90it/s, Eval_loss=16.4, A(CE)=0.885, A(CB)=0.889]\n",
            "\n",
            "\n",
            "Sorting (1.97s)\n",
            "Query [1000/1000] (5.10s)\n",
            "INFO 19-03-23 17:40:21: Total time usage for calculating mAP: 8.09s\n",
            "INFO 19-03-23 17:40:21: mAP: 0.843889\n",
            "INFO 19-03-23 17:40:21: Epoch [88/100]\n",
            "Training: 100% 312/312 [00:20<00:00, 14.87it/s, Train_loss=14.5, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:01<00:00, 31.69it/s, Eval_loss=16.3, A(CE)=0.895, A(CB)=0.898]\n",
            "\n",
            "Test: 100% 3688/3688 [01:52<00:00, 32.72it/s, Eval_loss=16.4, A(CE)=0.885, A(CB)=0.889]\n",
            "\n",
            "\n",
            "Sorting (2.41s)\n",
            "Query [1000/1000] (4.79s)\n",
            "INFO 19-03-23 17:42:45: Total time usage for calculating mAP: 8.21s\n",
            "INFO 19-03-23 17:42:45: mAP: 0.844099\n",
            "INFO 19-03-23 17:42:45: Epoch [89/100]\n",
            "Training: 100% 312/312 [00:22<00:00, 13.95it/s, Train_loss=14.5, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:02<00:00, 30.80it/s, Eval_loss=16.3, A(CE)=0.895, A(CB)=0.899]\n",
            "\n",
            "Test: 100% 3688/3688 [02:03<00:00, 29.80it/s, Eval_loss=16.5, A(CE)=0.884, A(CB)=0.888]\n",
            "\n",
            "\n",
            "Sorting (2.84s)\n",
            "Query [1000/1000] (4.62s)\n",
            "INFO 19-03-23 17:45:22: Total time usage for calculating mAP: 8.55s\n",
            "INFO 19-03-23 17:45:22: mAP: 0.840647\n",
            "INFO 19-03-23 17:45:22: Epoch [90/100]\n",
            "Training: 100% 312/312 [00:23<00:00, 13.37it/s, Train_loss=14.5, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:02<00:00, 29.55it/s, Eval_loss=16.3, A(CE)=0.897, A(CB)=0.903]\n",
            "\n",
            "Test: 100% 3688/3688 [02:02<00:00, 30.01it/s, Eval_loss=16.4, A(CE)=0.886, A(CB)=0.889]\n",
            "\n",
            "\n",
            "Sorting (2.91s)\n",
            "Query [1000/1000] (4.84s)\n",
            "INFO 19-03-23 17:47:59: Total time usage for calculating mAP: 8.81s\n",
            "INFO 19-03-23 17:47:59: mAP: 0.843010\n",
            "INFO 19-03-23 17:47:59: Epoch [91/100]\n",
            "Training: 100% 312/312 [00:22<00:00, 13.73it/s, Train_loss=14.5, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:02<00:00, 31.04it/s, Eval_loss=16.3, A(CE)=0.9, A(CB)=0.903]\n",
            "\n",
            "Test: 100% 3688/3688 [01:52<00:00, 32.76it/s, Eval_loss=16.4, A(CE)=0.886, A(CB)=0.89]\n",
            "\n",
            "Distance [1844/1844] (0.79s)\n",
            "Sorting (1.95s)\n",
            "Query [1000/1000] (4.40s)\n",
            "INFO 19-03-23 17:50:24: Total time usage for calculating mAP: 7.34s\n",
            "INFO 19-03-23 17:50:24: mAP: 0.843516\n",
            "INFO 19-03-23 17:50:24: Epoch [92/100]\n",
            "Training: 100% 312/312 [00:21<00:00, 14.45it/s, Train_loss=14.5, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:01<00:00, 33.36it/s, Eval_loss=16.3, A(CE)=0.899, A(CB)=0.9]\n",
            "\n",
            "Test: 100% 3688/3688 [01:52<00:00, 32.88it/s, Eval_loss=16.4, A(CE)=0.886, A(CB)=0.889]\n",
            "\n",
            "Distance [1844/1844] (0.83s)\n",
            "Sorting (1.98s)\n",
            "Query [1000/1000] (4.36s)\n",
            "INFO 19-03-23 17:52:47: Total time usage for calculating mAP: 7.38s\n",
            "INFO 19-03-23 17:52:47: mAP: 0.841761\n",
            "INFO 19-03-23 17:52:47: Epoch [93/100]\n",
            "Training: 100% 312/312 [00:20<00:00, 15.05it/s, Train_loss=14.5, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:01<00:00, 33.80it/s, Eval_loss=16.3, A(CE)=0.894, A(CB)=0.905]\n",
            "\n",
            "Test: 100% 3688/3688 [01:51<00:00, 32.97it/s, Eval_loss=16.4, A(CE)=0.885, A(CB)=0.888]\n",
            "\n",
            "\n",
            "Sorting (1.98s)\n",
            "Query [1000/1000] (4.92s)\n",
            "INFO 19-03-23 17:55:10: Total time usage for calculating mAP: 7.89s\n",
            "INFO 19-03-23 17:55:10: mAP: 0.844075\n",
            "INFO 19-03-23 17:55:10: Epoch [94/100]\n",
            "Training: 100% 312/312 [00:21<00:00, 14.81it/s, Train_loss=14.5, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:01<00:00, 33.53it/s, Eval_loss=16.4, A(CE)=0.898, A(CB)=0.901]\n",
            "\n",
            "Test: 100% 3688/3688 [01:52<00:00, 32.81it/s, Eval_loss=16.5, A(CE)=0.886, A(CB)=0.889]\n",
            "\n",
            "\n",
            "Sorting (2.06s)\n",
            "Query [1000/1000] (5.08s)\n",
            "INFO 19-03-23 17:57:34: Total time usage for calculating mAP: 8.08s\n",
            "INFO 19-03-23 17:57:34: mAP: 0.847607\n",
            "INFO 19-03-23 17:57:34: Epoch [95/100]\n",
            "Training: 100% 312/312 [00:24<00:00, 12.93it/s, Train_loss=14.5, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:01<00:00, 33.27it/s, Eval_loss=16.3, A(CE)=0.898, A(CB)=0.899]\n",
            "\n",
            "Test: 100% 3688/3688 [01:51<00:00, 32.97it/s, Eval_loss=16.4, A(CE)=0.885, A(CB)=0.888]\n",
            "\n",
            "\n",
            "Sorting (2.07s)\n",
            "Query [1000/1000] (4.88s)\n",
            "INFO 19-03-23 18:00:00: Total time usage for calculating mAP: 8.23s\n",
            "INFO 19-03-23 18:00:00: mAP: 0.845806\n",
            "INFO 19-03-23 18:00:00: Epoch [96/100]\n",
            "Training: 100% 312/312 [00:22<00:00, 13.78it/s, Train_loss=14.5, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:01<00:00, 31.84it/s, Eval_loss=16.2, A(CE)=0.896, A(CB)=0.9]\n",
            "\n",
            "Test: 100% 3688/3688 [02:05<00:00, 29.50it/s, Eval_loss=16.4, A(CE)=0.886, A(CB)=0.888]\n",
            "\n",
            "\n",
            "Sorting (2.12s)\n",
            "Query [1000/1000] (4.63s)\n",
            "INFO 19-03-23 18:02:38: Total time usage for calculating mAP: 7.83s\n",
            "INFO 19-03-23 18:02:38: mAP: 0.841172\n",
            "INFO 19-03-23 18:02:38: Epoch [97/100]\n",
            "Training: 100% 312/312 [00:22<00:00, 14.07it/s, Train_loss=14.5, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:01<00:00, 31.94it/s, Eval_loss=16.3, A(CE)=0.895, A(CB)=0.902]\n",
            "\n",
            "Test: 100% 3688/3688 [02:05<00:00, 29.31it/s, Eval_loss=16.4, A(CE)=0.885, A(CB)=0.889]\n",
            "\n",
            "Distance [1844/1844] (0.86s)\n",
            "Sorting (2.04s)\n",
            "Query [1000/1000] (4.68s)\n",
            "INFO 19-03-23 18:05:16: Total time usage for calculating mAP: 7.79s\n",
            "INFO 19-03-23 18:05:16: mAP: 0.844143\n",
            "INFO 19-03-23 18:05:16: Epoch [98/100]\n",
            "Training: 100% 312/312 [00:22<00:00, 13.75it/s, Train_loss=14.5, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:01<00:00, 31.89it/s, Eval_loss=16.3, A(CE)=0.901, A(CB)=0.901]\n",
            "\n",
            "Test: 100% 3688/3688 [02:02<00:00, 30.12it/s, Eval_loss=16.4, A(CE)=0.886, A(CB)=0.889]\n",
            "\n",
            "\n",
            "Sorting (2.13s)\n",
            "Query [1000/1000] (4.90s)\n",
            "INFO 19-03-23 18:07:51: Total time usage for calculating mAP: 8.37s\n",
            "INFO 19-03-23 18:07:52: mAP: 0.842151\n",
            "INFO 19-03-23 18:07:52: Epoch [99/100]\n",
            "Training: 100% 312/312 [00:23<00:00, 13.45it/s, Train_loss=14.5, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:02<00:00, 31.14it/s, Eval_loss=16.4, A(CE)=0.897, A(CB)=0.9]\n",
            "\n",
            "Test: 100% 3688/3688 [02:04<00:00, 29.70it/s, Eval_loss=16.5, A(CE)=0.885, A(CB)=0.888]\n",
            "\n",
            "\n",
            "Sorting (2.19s)\n",
            "Query [1000/1000] (5.37s)\n",
            "INFO 19-03-23 18:10:30: Total time usage for calculating mAP: 8.62s\n",
            "INFO 19-03-23 18:10:30: mAP: 0.841401\n",
            "INFO 19-03-23 18:10:30: Epoch [100/100]\n",
            "Training: 100% 312/312 [00:23<00:00, 13.56it/s, Train_loss=14.5, A(CE)=1, A(CB)=1]\n",
            "\n",
            "Test: 100% 63/63 [00:02<00:00, 30.07it/s, Eval_loss=16.3, A(CE)=0.895, A(CB)=0.901]\n",
            "\n",
            "Test: 100% 3688/3688 [02:06<00:00, 29.17it/s, Eval_loss=16.4, A(CE)=0.885, A(CB)=0.889]\n",
            "\n",
            "Distance [1844/1844] (0.85s)\n",
            "Sorting (1.99s)\n",
            "Query [1000/1000] (4.74s)\n",
            "INFO 19-03-23 18:13:09: Total time usage for calculating mAP: 7.79s\n",
            "INFO 19-03-23 18:13:09: mAP: 0.838818\n",
            "INFO 19-03-23 18:13:09: Remaining Save Tasks: 3\n",
            "INFO 19-03-23 18:13:10: Doing: logs/RelaHash64_cifar10_1_100_0.0001_adam_/test_420_000/optims/ep100.pth\n",
            "INFO 19-03-23 18:13:11: Doing: logs/RelaHash64_cifar10_1_100_0.0001_adam_/test_420_000/models/last.pth\n",
            "INFO 19-03-23 18:13:13: Doing: logs/RelaHash64_cifar10_1_100_0.0001_adam_/test_420_000/optims/last.pth\n",
            "INFO 19-03-23 18:13:14: Training End at 2023-03-19 18:13:14\n",
            "INFO 19-03-23 18:13:14: Total time used: 4.08 hours\n",
            "INFO 19-03-23 18:13:14: Best mAP: 0.847607\n",
            "INFO 19-03-23 18:13:14: Done: logs/RelaHash64_cifar10_1_100_0.0001_adam_/test_420_000\n"
          ]
        }
      ]
    }
  ]
}