egnn_autoencoding.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "hrjmbVb-MSMW"
      },
      "source": [
        "# Imports"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "d6aKrI1ZvroP",
        "outputId": "76a0802e-43ee-4df0-da89-5e02dfd8834f"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Mounted at /content/drive\n",
            "/content/drive/.shortcut-targets-by-id/1cPQ2fA-SRAPng-aTI1P8QDLacE-wxHcy/lattices\n",
            "data  data2  _debug  LatentLattice  results\n"
          ]
        }
      ],
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')\n",
        "\n",
        "# set current directory\n",
        "# this should be the Google Drive folder where your file(s) are located\n",
        "%cd /content/drive/MyDrive/lattices\n",
        "\n",
        "## verify current directory\n",
        "!ls /content/drive/MyDrive/lattices\n",
        "\n",
        "# choose where you want your project files to be saved\n",
        "project_folder = \"/content/drive/MyDrive/lattices\""
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ATTwPCpMEv0N",
        "outputId": "7bf1f8a4-0b79-493f-8d0f-3c91dcdd6ca9"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "2.2.1+cu121\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m10.9/10.9 MB\u001b[0m \u001b[31m83.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m5.0/5.0 MB\u001b[0m \u001b[31m45.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n",
            "  Getting requirements to build wheel ... \u001b[?25l\u001b[?25hdone\n",
            "  Preparing metadata (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
            "  Building wheel for torch-geometric (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n"
          ]
        }
      ],
      "source": [
        "import os\n",
        "import torch\n",
        "os.environ['TORCH'] = torch.__version__\n",
        "print(torch.__version__)\n",
        "\n",
        "! pip install -q torch-scatter -f https://data.pyg.org/whl/torch-${TORCH}.html\n",
        "! pip install -q torch-sparse -f https://data.pyg.org/whl/torch-${TORCH}.html\n",
        "! pip install -q git+https://github.com/pyg-team/pytorch_geometric.git"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "K_n6xyRoD0JZ",
        "outputId": "b424727f-83c4-41a5-eb36-3b0314b6e24f"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Collecting lattpy\n",
            "  Downloading lattpy-0.7.7-py3-none-any.whl (79 kB)\n",
            "\u001b[?25l     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m0.0/79.2 kB\u001b[0m \u001b[31m?\u001b[0m eta \u001b[36m-:--:--\u001b[0m\r\u001b[2K     \u001b[91m━━━━━━━━━━━━━━━\u001b[0m\u001b[91m╸\u001b[0m\u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m30.7/79.2 kB\u001b[0m \u001b[31m1.4 MB/s\u001b[0m eta \u001b[36m0:00:01\u001b[0m\r\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m79.2/79.2 kB\u001b[0m \u001b[31m1.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: setuptools>=60.0.0 in /usr/local/lib/python3.10/dist-packages (from lattpy) (67.7.2)\n",
            "Collecting setuptools-scm[toml]>=4 (from lattpy)\n",
            "  Downloading setuptools_scm-8.1.0-py3-none-any.whl (43 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m43.7/43.7 kB\u001b[0m \u001b[31m3.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: numpy>=1.20.3 in /usr/local/lib/python3.10/dist-packages (from lattpy) (1.25.2)\n",
            "Requirement already satisfied: scipy>=1.7.1 in /usr/local/lib/python3.10/dist-packages (from lattpy) (1.11.4)\n",
            "Requirement already satisfied: matplotlib>=3.0.0 in /usr/local/lib/python3.10/dist-packages (from lattpy) (3.7.1)\n",
            "Requirement already satisfied: pytest>=6.2.5 in /usr/local/lib/python3.10/dist-packages (from lattpy) (7.4.4)\n",
            "Collecting hypothesis>=6.0.0 (from lattpy)\n",
            "  Downloading hypothesis-6.100.6-py3-none-any.whl (460 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m460.8/460.8 kB\u001b[0m \u001b[31m5.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: colorcet>=2.0.0 in /usr/local/lib/python3.10/dist-packages (from lattpy) (3.1.0)\n",
            "Requirement already satisfied: attrs>=22.2.0 in /usr/local/lib/python3.10/dist-packages (from hypothesis>=6.0.0->lattpy) (23.2.0)\n",
            "Requirement already satisfied: sortedcontainers<3.0.0,>=2.1.0 in /usr/local/lib/python3.10/dist-packages (from hypothesis>=6.0.0->lattpy) (2.4.0)\n",
            "Requirement already satisfied: exceptiongroup>=1.0.0 in /usr/local/lib/python3.10/dist-packages (from hypothesis>=6.0.0->lattpy) (1.2.1)\n",
            "Requirement already satisfied: contourpy>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=3.0.0->lattpy) (1.2.1)\n",
            "Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=3.0.0->lattpy) (0.12.1)\n",
            "Requirement already satisfied: fonttools>=4.22.0 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=3.0.0->lattpy) (4.51.0)\n",
            "Requirement already satisfied: kiwisolver>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=3.0.0->lattpy) (1.4.5)\n",
            "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=3.0.0->lattpy) (24.0)\n",
            "Requirement already satisfied: pillow>=6.2.0 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=3.0.0->lattpy) (9.4.0)\n",
            "Requirement already satisfied: pyparsing>=2.3.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=3.0.0->lattpy) (3.1.2)\n",
            "Requirement already satisfied: python-dateutil>=2.7 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=3.0.0->lattpy) (2.8.2)\n",
            "Requirement already satisfied: iniconfig in /usr/local/lib/python3.10/dist-packages (from pytest>=6.2.5->lattpy) (2.0.0)\n",
            "Requirement already satisfied: pluggy<2.0,>=0.12 in /usr/local/lib/python3.10/dist-packages (from pytest>=6.2.5->lattpy) (1.5.0)\n",
            "Requirement already satisfied: tomli>=1.0.0 in /usr/local/lib/python3.10/dist-packages (from pytest>=6.2.5->lattpy) (2.0.1)\n",
            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil>=2.7->matplotlib>=3.0.0->lattpy) (1.16.0)\n",
            "Installing collected packages: setuptools-scm, hypothesis, lattpy\n",
            "Successfully installed hypothesis-6.100.6 lattpy-0.7.7 setuptools-scm-8.1.0\n",
            "Requirement already satisfied: networkx in /usr/local/lib/python3.10/dist-packages (3.3)\n"
          ]
        }
      ],
      "source": [
        "! pip install lattpy\n",
        "! pip install networkx"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jBOqfJfyEHEF",
        "outputId": "1c716221-84df-431b-e531-8f2eba1c7f2a"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Cloning into 'LatentLattice'...\n",
            "remote: Enumerating objects: 29, done.\u001b[K\n",
            "remote: Counting objects: 100% (29/29), done.\u001b[K\n",
            "remote: Compressing objects: 100% (24/24), done.\u001b[K\n",
            "remote: Total 29 (delta 10), reused 15 (delta 4), pack-reused 0\u001b[K\n",
            "Receiving objects: 100% (29/29), 703.88 KiB | 6.07 MiB/s, done.\n",
            "Resolving deltas: 100% (10/10), done.\n"
          ]
        }
      ],
      "source": [
        "! git clone https://github.com/julballa/LatentLattice.git"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "U1-PSvV6MPrR"
      },
      "source": [
        "# Load and save dataset"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 452
        },
        "id": "Q24k44J6gmsH",
        "outputId": "3847acc2-d0d6-4db2-f7f5-d3b8ed6e3d64"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "from data_utils import simulate_ising, plot_grid\n",
        "\n",
        "# Parameters\n",
        "grid_size = 12\n",
        "temperature = 5.0\n",
        "steps = 500\n",
        "\n",
        "# Simulation\n",
        "final_grid = simulate_ising(grid_size, temperature, steps)\n",
        "\n",
        "# Plotting results\n",
        "plot_grid(final_grid)\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "8Y7-lVgaO-eb"
      },
      "source": [
        "# Train model"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "C86uyDsXQkCz",
        "outputId": "c0308235-2503-49b6-f884-2d3d8a559e3d"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Namespace(debug=True, mp_steps=3, emb_dim=32, layers=2, pooling=True, up_mlp=False, residual=True, noise=False, transpose=False, attn=False, loss='all', mode='train', lr_init=0.001, epochs=40, batch_size=32, edgeloss_weight=0.0, kl_weight=0, dataname='2d_square_lattice', num_workers=0, data_path='data/', working_dir='', suffix='', log_dir='', checkpoint_dir='trained_models', saved_model_dir=None)\n",
            "Training with 1 GPUs!\n",
            "\n",
            "# Params: 205090\n",
            "=====Epoch 1\n",
            "Training...\n",
            "Iteration:   0% 0/32 [00:00<?, ?it/s]/usr/local/lib/python3.10/dist-packages/torch_geometric/data/storage.py:450: UserWarning: Unable to accurately infer 'num_nodes' from the attribute set '{'edge_index'}'. Please explicitly set 'num_nodes' as an attribute of 'data' to suppress this warning\n",
            "  warnings.warn(\n",
            "loss_dist 2.008, loss_coords 1.219, loss_res 0.570, : 100% 32/32 [01:36<00:00,  3.01s/it]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:10<00:00,  1.43s/it]\n",
            "Epoch 1, valid_edge_mae: 1.99829, Train_mae: 1.21811, Validation_mae: 1.21688, Validation_rmsd: 2.84282, res_acc: 0.74, kl_x: 0.00, kl_h: 0.00, elapse: 106.57271\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 2.8428215876370113, epoch: 1\n",
            "Best validation rec acc so far: 0.7373611330986023, epoch: 1\n",
            "=====Epoch 2\n",
            "Training...\n",
            "loss_dist 1.982, loss_coords 1.205, loss_res 0.508, : 100% 32/32 [01:35<00:00,  3.00s/it]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:09<00:00,  1.41s/it]\n",
            "Epoch 2, valid_edge_mae: 1.98240, Train_mae: 1.20732, Validation_mae: 1.20783, Validation_rmsd: 2.83216, res_acc: 0.74, kl_x: 0.00, kl_h: 0.00, elapse: 105.92765\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 2.8321615600595886, epoch: 2\n",
            "Best validation rec acc so far: 0.7394791841506958, epoch: 2\n",
            "=====Epoch 3\n",
            "Training...\n",
            "loss_dist 1.917, loss_coords 1.200, loss_res 0.492, : 100% 32/32 [01:35<00:00,  2.99s/it]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:09<00:00,  1.38s/it]\n",
            "Epoch 3, valid_edge_mae: 1.93781, Train_mae: 1.20623, Validation_mae: 1.20361, Validation_rmsd: 2.82260, res_acc: 0.75, kl_x: 0.00, kl_h: 0.00, elapse: 105.25235\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 2.8226031508757528, epoch: 3\n",
            "Best validation rec acc so far: 0.746180534362793, epoch: 3\n",
            "=====Epoch 4\n",
            "Training...\n",
            "loss_dist 1.875, loss_coords 1.209, loss_res 0.533, : 100% 32/32 [01:35<00:00,  2.98s/it]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:10<00:00,  1.45s/it]\n",
            "Epoch 4, valid_edge_mae: 1.83648, Train_mae: 1.19510, Validation_mae: 1.19634, Validation_rmsd: 2.82418, res_acc: 0.75, kl_x: 0.00, kl_h: 0.00, elapse: 105.55909\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 2.8226031508757528, epoch: 3\n",
            "Best validation rec acc so far: 0.7517361044883728, epoch: 4\n",
            "=====Epoch 5\n",
            "Training...\n",
            "loss_dist 1.799, loss_coords 1.243, loss_res 0.467, : 100% 32/32 [01:34<00:00,  2.96s/it]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:09<00:00,  1.43s/it]\n",
            "Epoch 5, valid_edge_mae: 1.80015, Train_mae: 1.20847, Validation_mae: 1.21876, Validation_rmsd: 2.90762, res_acc: 0.76, kl_x: 0.00, kl_h: 0.00, elapse: 104.88898\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 2.8226031508757528, epoch: 3\n",
            "Best validation rec acc so far: 0.7596874833106995, epoch: 5\n",
            "=====Epoch 6\n",
            "Training...\n",
            "loss_dist 1.947, loss_coords 1.254, loss_res 0.438, : 100% 32/32 [01:35<00:00,  2.99s/it]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:10<00:00,  1.45s/it]\n",
            "Epoch 6, valid_edge_mae: 2.00495, Train_mae: 1.22586, Validation_mae: 1.29149, Validation_rmsd: 3.02001, res_acc: 0.78, kl_x: 0.00, kl_h: 0.00, elapse: 105.88434\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 2.8226031508757528, epoch: 3\n",
            "Best validation rec acc so far: 0.777256965637207, epoch: 6\n",
            "=====Epoch 7\n",
            "Training...\n",
            "loss_dist 1.741, loss_coords 1.277, loss_res 0.470, : 100% 32/32 [01:35<00:00,  2.97s/it]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:10<00:00,  1.43s/it]\n",
            "Epoch 7, valid_edge_mae: 1.73208, Train_mae: 1.27395, Validation_mae: 1.24836, Validation_rmsd: 3.12994, res_acc: 0.78, kl_x: 0.00, kl_h: 0.00, elapse: 105.07565\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 2.8226031508757528, epoch: 3\n",
            "Best validation rec acc so far: 0.7776041626930237, epoch: 7\n",
            "=====Epoch 8\n",
            "Training...\n",
            "loss_dist 1.680, loss_coords 1.214, loss_res 0.427, : 100% 32/32 [01:35<00:00,  2.98s/it]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:11<00:00,  1.60s/it]\n",
            "Epoch 8, valid_edge_mae: 1.65939, Train_mae: 1.23060, Validation_mae: 1.21636, Validation_rmsd: 3.13000, res_acc: 0.78, kl_x: 0.00, kl_h: 0.00, elapse: 106.72819\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 2.8226031508757528, epoch: 3\n",
            "Best validation rec acc so far: 0.7832291722297668, epoch: 8\n",
            "=====Epoch 9\n",
            "Training...\n",
            "loss_dist 1.720, loss_coords 1.192, loss_res 0.422, : 100% 32/32 [01:34<00:00,  2.96s/it]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:09<00:00,  1.39s/it]\n",
            "Epoch 9, valid_edge_mae: 1.69252, Train_mae: 1.21540, Validation_mae: 1.21075, Validation_rmsd: 3.08877, res_acc: 0.79, kl_x: 0.00, kl_h: 0.00, elapse: 104.50761\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 2.8226031508757528, epoch: 3\n",
            "Best validation rec acc so far: 0.785277783870697, epoch: 9\n",
            "=====Epoch 10\n",
            "Training...\n",
            "loss_dist 1.662, loss_coords 1.194, loss_res 0.398, : 100% 32/32 [01:35<00:00,  2.99s/it]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:10<00:00,  1.44s/it]\n",
            "Epoch 10, valid_edge_mae: 1.65505, Train_mae: 1.21334, Validation_mae: 1.19917, Validation_rmsd: 3.06592, res_acc: 0.80, kl_x: 0.00, kl_h: 0.00, elapse: 105.67116\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 2.8226031508757528, epoch: 3\n",
            "Best validation rec acc so far: 0.796423614025116, epoch: 10\n",
            "=====Epoch 11\n",
            "Training...\n",
            "loss_dist 1.690, loss_coords 1.233, loss_res 0.367, : 100% 32/32 [01:34<00:00,  2.96s/it]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:10<00:00,  1.50s/it]\n",
            "Epoch 11, valid_edge_mae: 1.68505, Train_mae: 1.21072, Validation_mae: 1.19907, Validation_rmsd: 3.03459, res_acc: 0.80, kl_x: 0.00, kl_h: 0.00, elapse: 105.32821\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 2.8226031508757528, epoch: 3\n",
            "Best validation rec acc so far: 0.8023263812065125, epoch: 11\n",
            "=====Epoch 12\n",
            "Training...\n",
            "loss_dist 1.657, loss_coords 1.184, loss_res 0.359, : 100% 32/32 [01:34<00:00,  2.96s/it]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:09<00:00,  1.35s/it]\n",
            "Epoch 12, valid_edge_mae: 1.62267, Train_mae: 1.19264, Validation_mae: 1.17874, Validation_rmsd: 3.00658, res_acc: 0.81, kl_x: 0.00, kl_h: 0.00, elapse: 104.34875\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 2.8226031508757528, epoch: 3\n",
            "Best validation rec acc so far: 0.8103819489479065, epoch: 12\n",
            "=====Epoch 13\n",
            "Training...\n",
            "loss_dist 1.591, loss_coords 1.203, loss_res 0.366, : 100% 32/32 [01:35<00:00,  2.97s/it]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:10<00:00,  1.43s/it]\n",
            "Epoch 13, valid_edge_mae: 1.59985, Train_mae: 1.19586, Validation_mae: 1.19330, Validation_rmsd: 3.03594, res_acc: 0.82, kl_x: 0.00, kl_h: 0.00, elapse: 105.25191\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 2.8226031508757528, epoch: 3\n",
            "Best validation rec acc so far: 0.8170833587646484, epoch: 13\n",
            "=====Epoch 14\n",
            "Training...\n",
            "loss_dist 1.625, loss_coords 1.212, loss_res 0.333, : 100% 32/32 [01:35<00:00,  2.98s/it]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:10<00:00,  1.45s/it]\n",
            "Epoch 14, valid_edge_mae: 1.63716, Train_mae: 1.19572, Validation_mae: 1.18762, Validation_rmsd: 3.06093, res_acc: 0.83, kl_x: 0.00, kl_h: 0.00, elapse: 105.39037\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 2.8226031508757528, epoch: 3\n",
            "Best validation rec acc so far: 0.8294097185134888, epoch: 14\n",
            "=====Epoch 15\n",
            "Training...\n",
            "loss_dist 1.687, loss_coords 1.203, loss_res 0.318, : 100% 32/32 [01:35<00:00,  2.98s/it]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:09<00:00,  1.40s/it]\n",
            "Epoch 15, valid_edge_mae: 1.67437, Train_mae: 1.18629, Validation_mae: 1.19028, Validation_rmsd: 3.02463, res_acc: 0.82, kl_x: 0.00, kl_h: 0.00, elapse: 105.12443\n",
            "Best validation RMSD so far: 2.8226031508757528, epoch: 3\n",
            "Best validation rec acc so far: 0.8294097185134888, epoch: 14\n",
            "=====Epoch 16\n",
            "Training...\n",
            "loss_dist 1.716, loss_coords 1.186, loss_res 0.317, : 100% 32/32 [01:35<00:00,  2.98s/it]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:10<00:00,  1.50s/it]\n",
            "Epoch 16, valid_edge_mae: 1.74850, Train_mae: 1.18416, Validation_mae: 1.19412, Validation_rmsd: 2.97653, res_acc: 0.84, kl_x: 0.00, kl_h: 0.00, elapse: 106.01708\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 2.8226031508757528, epoch: 3\n",
            "Best validation rec acc so far: 0.8434722423553467, epoch: 16\n",
            "=====Epoch 17\n",
            "Training...\n",
            "loss_dist 1.666, loss_coords 1.161, loss_res 0.306, : 100% 32/32 [01:34<00:00,  2.96s/it]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:10<00:00,  1.46s/it]\n",
            "Epoch 17, valid_edge_mae: 1.68060, Train_mae: 1.18380, Validation_mae: 1.16260, Validation_rmsd: 2.94046, res_acc: 0.84, kl_x: 0.00, kl_h: 0.00, elapse: 104.90770\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 2.8226031508757528, epoch: 3\n",
            "Best validation rec acc so far: 0.84354168176651, epoch: 17\n",
            "=====Epoch 18\n",
            "Training...\n",
            "loss_dist 1.660, loss_coords 1.186, loss_res 0.263, : 100% 32/32 [01:35<00:00,  2.99s/it]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:10<00:00,  1.45s/it]\n",
            "Epoch 18, valid_edge_mae: 1.67261, Train_mae: 1.17957, Validation_mae: 1.17091, Validation_rmsd: 2.96103, res_acc: 0.86, kl_x: 0.00, kl_h: 0.00, elapse: 105.72422\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 2.8226031508757528, epoch: 3\n",
            "Best validation rec acc so far: 0.8648263812065125, epoch: 18\n",
            "=====Epoch 19\n",
            "Training...\n",
            "loss_dist 1.654, loss_coords 1.157, loss_res 0.242, : 100% 32/32 [01:35<00:00,  2.97s/it]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:09<00:00,  1.37s/it]\n",
            "Epoch 19, valid_edge_mae: 1.63859, Train_mae: 1.17865, Validation_mae: 1.17357, Validation_rmsd: 2.95894, res_acc: 0.87, kl_x: 0.00, kl_h: 0.00, elapse: 104.66864\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 2.8226031508757528, epoch: 3\n",
            "Best validation rec acc so far: 0.8715277910232544, epoch: 19\n",
            "=====Epoch 20\n",
            "Training...\n",
            "loss_dist 1.608, loss_coords 1.189, loss_res 0.238, : 100% 32/32 [01:36<00:00,  3.00s/it]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:10<00:00,  1.45s/it]\n",
            "Epoch 20, valid_edge_mae: 1.63372, Train_mae: 1.19833, Validation_mae: 1.22154, Validation_rmsd: 3.08296, res_acc: 0.87, kl_x: 0.00, kl_h: 0.00, elapse: 106.23319\n",
            "Best validation RMSD so far: 2.8226031508757528, epoch: 3\n",
            "Best validation rec acc so far: 0.8715277910232544, epoch: 19\n",
            "=====Epoch 21\n",
            "Training...\n",
            "Iteration:   0% 0/32 [00:00<?, ?it/s]/content/drive/MyDrive/lattices/LatentLattice/train.py:135: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`). Consider using `matplotlib.pyplot.close()`.\n",
            "  fig = plt.figure()\n",
            "loss_dist 1.623, loss_coords 1.155, loss_res 0.236, : 100% 32/32 [01:35<00:00,  2.99s/it]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:10<00:00,  1.47s/it]\n",
            "Epoch 21, valid_edge_mae: 1.64378, Train_mae: 1.18972, Validation_mae: 1.18508, Validation_rmsd: 2.98746, res_acc: 0.90, kl_x: 0.00, kl_h: 0.00, elapse: 106.07506\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 2.8226031508757528, epoch: 3\n",
            "Best validation rec acc so far: 0.8952777981758118, epoch: 21\n",
            "=====Epoch 22\n",
            "Training...\n",
            "loss_dist 1.603, loss_coords 1.153, loss_res 0.216, : 100% 32/32 [01:36<00:00,  3.01s/it]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:09<00:00,  1.37s/it]\n",
            "Epoch 22, valid_edge_mae: 1.59461, Train_mae: 1.16565, Validation_mae: 1.12617, Validation_rmsd: 2.89390, res_acc: 0.89, kl_x: 0.00, kl_h: 0.00, elapse: 105.79012\n",
            "Best validation RMSD so far: 2.8226031508757528, epoch: 3\n",
            "Best validation rec acc so far: 0.8952777981758118, epoch: 21\n",
            "=====Epoch 23\n",
            "Training...\n",
            "loss_dist 1.596, loss_coords 1.107, loss_res 0.159, : 100% 32/32 [01:34<00:00,  2.96s/it]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:10<00:00,  1.50s/it]\n",
            "Epoch 23, valid_edge_mae: 1.62033, Train_mae: 1.14545, Validation_mae: 1.12535, Validation_rmsd: 2.88667, res_acc: 0.91, kl_x: 0.00, kl_h: 0.00, elapse: 105.35589\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 2.8226031508757528, epoch: 3\n",
            "Best validation rec acc so far: 0.9090971946716309, epoch: 23\n",
            "=====Epoch 24\n",
            "Training...\n",
            "loss_dist 1.586, loss_coords 1.120, loss_res 0.148, : 100% 32/32 [01:35<00:00,  2.98s/it]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:10<00:00,  1.44s/it]\n",
            "Epoch 24, valid_edge_mae: 1.61102, Train_mae: 1.15215, Validation_mae: 1.16591, Validation_rmsd: 2.92176, res_acc: 0.92, kl_x: 0.00, kl_h: 0.00, elapse: 105.49195\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 2.8226031508757528, epoch: 3\n",
            "Best validation rec acc so far: 0.9154860973358154, epoch: 24\n",
            "=====Epoch 25\n",
            "Training...\n",
            "loss_dist 1.708, loss_coords 1.161, loss_res 0.210, : 100% 32/32 [01:35<00:00,  2.98s/it]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:09<00:00,  1.40s/it]\n",
            "Epoch 25, valid_edge_mae: 1.68502, Train_mae: 1.14499, Validation_mae: 1.12494, Validation_rmsd: 2.84181, res_acc: 0.90, kl_x: 0.00, kl_h: 0.00, elapse: 105.20171\n",
            "Best validation RMSD so far: 2.8226031508757528, epoch: 3\n",
            "Best validation rec acc so far: 0.9154860973358154, epoch: 24\n",
            "=====Epoch 26\n",
            "Training...\n",
            "loss_dist 1.617, loss_coords 1.140, loss_res 0.141, : 100% 32/32 [01:35<00:00,  2.99s/it]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:09<00:00,  1.39s/it]\n",
            "Epoch 26, valid_edge_mae: 1.63008, Train_mae: 1.14402, Validation_mae: 1.15099, Validation_rmsd: 2.92801, res_acc: 0.93, kl_x: 0.00, kl_h: 0.00, elapse: 105.52086\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 2.8226031508757528, epoch: 3\n",
            "Best validation rec acc so far: 0.9347569346427917, epoch: 26\n",
            "=====Epoch 27\n",
            "Training...\n",
            "loss_dist 1.587, loss_coords 1.148, loss_res 0.146, : 100% 32/32 [01:35<00:00,  2.98s/it]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:10<00:00,  1.44s/it]\n",
            "Epoch 27, valid_edge_mae: 1.62347, Train_mae: 1.13217, Validation_mae: 1.17754, Validation_rmsd: 2.97396, res_acc: 0.94, kl_x: 0.00, kl_h: 0.00, elapse: 105.35403\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 2.8226031508757528, epoch: 3\n",
            "Best validation rec acc so far: 0.9364583492279053, epoch: 27\n",
            "=====Epoch 28\n",
            "Training...\n",
            "loss_dist 1.629, loss_coords 1.181, loss_res 0.136, : 100% 32/32 [01:35<00:00,  2.99s/it]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:10<00:00,  1.50s/it]\n",
            "Epoch 28, valid_edge_mae: 1.60655, Train_mae: 1.15658, Validation_mae: 1.14998, Validation_rmsd: 2.92780, res_acc: 0.94, kl_x: 0.00, kl_h: 0.00, elapse: 106.25740\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 2.8226031508757528, epoch: 3\n",
            "Best validation rec acc so far: 0.9369444251060486, epoch: 28\n",
            "=====Epoch 29\n",
            "Training...\n",
            "loss_dist 1.575, loss_coords 1.121, loss_res 0.099, : 100% 32/32 [01:34<00:00,  2.96s/it]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:09<00:00,  1.35s/it]\n",
            "Epoch 29, valid_edge_mae: 1.57638, Train_mae: 1.14004, Validation_mae: 1.12216, Validation_rmsd: 2.87479, res_acc: 0.95, kl_x: 0.00, kl_h: 0.00, elapse: 104.38203\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 2.8226031508757528, epoch: 3\n",
            "Best validation rec acc so far: 0.9478124976158142, epoch: 29\n",
            "=====Epoch 30\n",
            "Training...\n",
            "loss_dist 1.619, loss_coords 1.148, loss_res 0.129, : 100% 32/32 [01:40<00:00,  3.14s/it]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:09<00:00,  1.37s/it]\n",
            "Epoch 30, valid_edge_mae: 1.60660, Train_mae: 1.11913, Validation_mae: 1.12494, Validation_rmsd: 2.88774, res_acc: 0.95, kl_x: 0.00, kl_h: 0.00, elapse: 110.02837\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 2.8226031508757528, epoch: 3\n",
            "Best validation rec acc so far: 0.949548602104187, epoch: 30\n",
            "=====Epoch 31\n",
            "Training...\n",
            "loss_dist 1.617, loss_coords 1.104, loss_res 0.087, : 100% 32/32 [01:35<00:00,  2.99s/it]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:10<00:00,  1.45s/it]\n",
            "Epoch 31, valid_edge_mae: 1.60303, Train_mae: 1.11533, Validation_mae: 1.11643, Validation_rmsd: 2.87389, res_acc: 0.95, kl_x: 0.00, kl_h: 0.00, elapse: 105.86048\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 2.8226031508757528, epoch: 3\n",
            "Best validation rec acc so far: 0.9537152647972107, epoch: 31\n",
            "=====Epoch 32\n",
            "Training...\n",
            "loss_dist 1.587, loss_coords 1.100, loss_res 0.081, : 100% 32/32 [01:35<00:00,  3.00s/it]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:10<00:00,  1.46s/it]\n",
            "Epoch 32, valid_edge_mae: 1.57711, Train_mae: 1.10838, Validation_mae: 1.08261, Validation_rmsd: 2.79381, res_acc: 0.95, kl_x: 0.00, kl_h: 0.00, elapse: 106.11774\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 2.7938109793731485, epoch: 32\n",
            "Best validation rec acc so far: 0.9537152647972107, epoch: 31\n",
            "=====Epoch 33\n",
            "Training...\n",
            "loss_dist 1.547, loss_coords 1.070, loss_res 0.077, : 100% 32/32 [01:35<00:00,  2.97s/it]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:09<00:00,  1.39s/it]\n",
            "Epoch 33, valid_edge_mae: 1.54925, Train_mae: 1.10669, Validation_mae: 1.10344, Validation_rmsd: 2.83364, res_acc: 0.96, kl_x: 0.00, kl_h: 0.00, elapse: 104.92912\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 2.7938109793731485, epoch: 32\n",
            "Best validation rec acc so far: 0.9587846994400024, epoch: 33\n",
            "=====Epoch 34\n",
            "Training...\n",
            "loss_dist 1.542, loss_coords 1.064, loss_res 0.098, : 100% 32/32 [01:35<00:00,  3.00s/it]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:10<00:00,  1.46s/it]\n",
            "Epoch 34, valid_edge_mae: 1.57841, Train_mae: 1.09407, Validation_mae: 1.09055, Validation_rmsd: 2.82299, res_acc: 0.96, kl_x: 0.00, kl_h: 0.00, elapse: 106.20511\n",
            "Best validation RMSD so far: 2.7938109793731485, epoch: 32\n",
            "Best validation rec acc so far: 0.9587846994400024, epoch: 33\n",
            "=====Epoch 35\n",
            "Training...\n",
            "loss_dist 1.567, loss_coords 1.108, loss_res 0.095, : 100% 32/32 [01:35<00:00,  2.97s/it]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:10<00:00,  1.50s/it]\n",
            "Epoch 35, valid_edge_mae: 1.50211, Train_mae: 1.08224, Validation_mae: 1.05656, Validation_rmsd: 2.77485, res_acc: 0.96, kl_x: 0.00, kl_h: 0.00, elapse: 105.59547\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 2.7748490095714, epoch: 35\n",
            "Best validation rec acc so far: 0.9634374976158142, epoch: 35\n",
            "=====Epoch 36\n",
            "Training...\n",
            "loss_dist 1.535, loss_coords 1.051, loss_res 0.078, : 100% 32/32 [01:35<00:00,  2.99s/it]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:10<00:00,  1.45s/it]\n",
            "Epoch 36, valid_edge_mae: 1.52340, Train_mae: 1.07408, Validation_mae: 1.04149, Validation_rmsd: 2.73862, res_acc: 0.96, kl_x: 0.00, kl_h: 0.00, elapse: 105.75889\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 2.7386158609350413, epoch: 36\n",
            "Best validation rec acc so far: 0.9634374976158142, epoch: 35\n",
            "=====Epoch 37\n",
            "Training...\n",
            "loss_dist 1.522, loss_coords 1.048, loss_res 0.101, : 100% 32/32 [01:35<00:00,  2.99s/it]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:09<00:00,  1.35s/it]\n",
            "Epoch 37, valid_edge_mae: 1.52679, Train_mae: 1.06807, Validation_mae: 1.08996, Validation_rmsd: 2.84515, res_acc: 0.95, kl_x: 0.00, kl_h: 0.00, elapse: 105.09609\n",
            "Best validation RMSD so far: 2.7386158609350413, epoch: 36\n",
            "Best validation rec acc so far: 0.9634374976158142, epoch: 35\n",
            "=====Epoch 38\n",
            "Training...\n",
            "loss_dist 1.542, loss_coords 1.091, loss_res 0.059, : 100% 32/32 [01:35<00:00,  2.98s/it]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:10<00:00,  1.46s/it]\n",
            "Epoch 38, valid_edge_mae: 1.53162, Train_mae: 1.07312, Validation_mae: 1.06492, Validation_rmsd: 2.77534, res_acc: 0.97, kl_x: 0.00, kl_h: 0.00, elapse: 105.49531\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 2.7386158609350413, epoch: 36\n",
            "Best validation rec acc so far: 0.9655902981758118, epoch: 38\n",
            "=====Epoch 39\n",
            "Training...\n",
            "loss_dist 1.531, loss_coords 1.099, loss_res 0.063, : 100% 32/32 [01:35<00:00,  2.98s/it]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:10<00:00,  1.45s/it]\n",
            "Epoch 39, valid_edge_mae: 1.51055, Train_mae: 1.04936, Validation_mae: 1.04662, Validation_rmsd: 2.76965, res_acc: 0.97, kl_x: 0.00, kl_h: 0.00, elapse: 105.45925\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 2.7386158609350413, epoch: 36\n",
            "Best validation rec acc so far: 0.9731597304344177, epoch: 39\n",
            "=====Epoch 40\n",
            "Training...\n",
            "loss_dist 1.536, loss_coords 1.055, loss_res 0.067, : 100% 32/32 [01:35<00:00,  2.98s/it]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:10<00:00,  1.45s/it]\n",
            "Epoch 40, valid_edge_mae: 1.52307, Train_mae: 1.05052, Validation_mae: 1.04315, Validation_rmsd: 2.74246, res_acc: 0.97, kl_x: 0.00, kl_h: 0.00, elapse: 105.38712\n",
            "Best validation RMSD so far: 2.7386158609350413, epoch: 36\n",
            "Best validation rec acc so far: 0.9731597304344177, epoch: 39\n"
          ]
        }
      ],
      "source": [
        "! python LatentLattice/train.py --mp_steps 3 --batch_size 32 --debug --layers 2 --edgeloss_weight 0.0"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "mn6dagiz0-ti",
        "outputId": "bf4f200a-4f0d-4687-cef8-3918188731cf"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Namespace(debug=True, mp_steps=3, emb_dim=32, layers=2, pooling=True, up_mlp=False, residual=True, noise=False, transpose=False, attn=False, loss='all', mode='train', lr_init=0.001, epochs=50, batch_size=32, edgeloss_weight=0.0, kl_weight=0, dataname='2d_square_lattice', num_workers=0, data_path='data/', working_dir='', suffix='', log_dir='', checkpoint_dir='trained_models', saved_model_dir=None)\n",
            "Training with 1 GPUs!\n",
            "\n",
            "# Params: 205090\n",
            "=====Epoch 1\n",
            "Training...\n",
            "Iteration:   0% 0/32 [00:00<?, ?it/s]/usr/local/lib/python3.10/dist-packages/torch_geometric/data/storage.py:450: UserWarning: Unable to accurately infer 'num_nodes' from the attribute set '{'edge_index'}'. Please explicitly set 'num_nodes' as an attribute of 'data' to suppress this warning\n",
            "  warnings.warn(\n",
            "loss_dist 1.281, loss_coords 0.863, loss_res 0.580, : 100% 32/32 [01:32<00:00,  2.89s/it]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:09<00:00,  1.40s/it]\n",
            "Epoch 1, valid_edge_mae: 1.27398, Train_mae: 1.10613, Validation_mae: 0.84545, Validation_rmsd: 2.52852, res_acc: 0.72, kl_x: 0.00, kl_h: 0.00, elapse: 102.42512\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 2.5285206587020137, epoch: 1\n",
            "Best validation rec acc so far: 0.7176735997200012, epoch: 1\n",
            "=====Epoch 2\n",
            "Training...\n",
            "loss_dist 1.009, loss_coords 0.638, loss_res 0.603, : 100% 32/32 [01:31<00:00,  2.85s/it]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:10<00:00,  1.45s/it]\n",
            "Epoch 2, valid_edge_mae: 1.22698, Train_mae: 0.71811, Validation_mae: 0.64936, Validation_rmsd: 1.86304, res_acc: 0.67, kl_x: 0.00, kl_h: 0.00, elapse: 101.62071\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 1.863044473015507, epoch: 2\n",
            "Best validation rec acc so far: 0.7176735997200012, epoch: 1\n",
            "=====Epoch 3\n",
            "Training...\n",
            "loss_dist 0.319, loss_coords 0.209, loss_res 0.562, : 100% 32/32 [01:33<00:00,  2.93s/it]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:10<00:00,  1.55s/it]\n",
            "Epoch 3, valid_edge_mae: 0.36572, Train_mae: 0.40202, Validation_mae: 0.22753, Validation_rmsd: 0.53316, res_acc: 0.71, kl_x: 0.00, kl_h: 0.00, elapse: 104.66811\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.5331557063493334, epoch: 3\n",
            "Best validation rec acc so far: 0.7176735997200012, epoch: 1\n",
            "=====Epoch 4\n",
            "Training...\n",
            "loss_dist 0.212, loss_coords 0.145, loss_res 0.576, : 100% 32/32 [01:33<00:00,  2.92s/it]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:09<00:00,  1.33s/it]\n",
            "Epoch 4, valid_edge_mae: 0.19099, Train_mae: 0.15558, Validation_mae: 0.12928, Validation_rmsd: 0.31696, res_acc: 0.70, kl_x: 0.00, kl_h: 0.00, elapse: 102.81647\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.3169647273792016, epoch: 4\n",
            "Best validation rec acc so far: 0.7176735997200012, epoch: 1\n",
            "=====Epoch 5\n",
            "Training...\n",
            "loss_dist 0.144, loss_coords 0.107, loss_res 0.554, : 100% 32/32 [01:34<00:00,  2.96s/it]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:09<00:00,  1.42s/it]\n",
            "Epoch 5, valid_edge_mae: 0.13616, Train_mae: 0.12334, Validation_mae: 0.09417, Validation_rmsd: 0.26188, res_acc: 0.71, kl_x: 0.00, kl_h: 0.00, elapse: 104.66852\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.26188320432051454, epoch: 5\n",
            "Best validation rec acc so far: 0.7176735997200012, epoch: 1\n",
            "=====Epoch 6\n",
            "Training...\n",
            "loss_dist 0.106, loss_coords 0.069, loss_res 0.556, : 100% 32/32 [01:34<00:00,  2.94s/it]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:10<00:00,  1.45s/it]\n",
            "Epoch 6, valid_edge_mae: 0.13298, Train_mae: 0.08916, Validation_mae: 0.08292, Validation_rmsd: 0.23016, res_acc: 0.71, kl_x: 0.00, kl_h: 0.00, elapse: 104.30531\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.23016019294535678, epoch: 6\n",
            "Best validation rec acc so far: 0.7176735997200012, epoch: 1\n",
            "=====Epoch 7\n",
            "Training...\n",
            "loss_dist 0.160, loss_coords 0.092, loss_res 0.572, : 100% 32/32 [01:34<00:00,  2.95s/it]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:09<00:00,  1.39s/it]\n",
            "Epoch 7, valid_edge_mae: 0.12186, Train_mae: 0.08180, Validation_mae: 0.07397, Validation_rmsd: 0.21168, res_acc: 0.71, kl_x: 0.00, kl_h: 0.00, elapse: 104.12063\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.21167770247741266, epoch: 7\n",
            "Best validation rec acc so far: 0.7176735997200012, epoch: 1\n",
            "=====Epoch 8\n",
            "Training...\n",
            "loss_dist 0.087, loss_coords 0.057, loss_res 0.561, : 100% 32/32 [01:34<00:00,  2.95s/it]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:10<00:00,  1.47s/it]\n",
            "Epoch 8, valid_edge_mae: 0.10065, Train_mae: 0.06721, Validation_mae: 0.07053, Validation_rmsd: 0.18877, res_acc: 0.71, kl_x: 0.00, kl_h: 0.00, elapse: 104.58952\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.18877009693071078, epoch: 8\n",
            "Best validation rec acc so far: 0.7176735997200012, epoch: 1\n",
            "=====Epoch 9\n",
            "Training...\n",
            "loss_dist 0.106, loss_coords 0.088, loss_res 0.558, : 100% 32/32 [01:34<00:00,  2.95s/it]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:09<00:00,  1.38s/it]\n",
            "Epoch 9, valid_edge_mae: 0.10401, Train_mae: 0.06845, Validation_mae: 0.06767, Validation_rmsd: 0.17767, res_acc: 0.71, kl_x: 0.00, kl_h: 0.00, elapse: 104.07789\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.1776656402219464, epoch: 9\n",
            "Best validation rec acc so far: 0.7176735997200012, epoch: 1\n",
            "=====Epoch 10\n",
            "Training...\n",
            "loss_dist 0.077, loss_coords 0.062, loss_res 0.542, : 100% 32/32 [01:34<00:00,  2.96s/it]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:10<00:00,  1.44s/it]\n",
            "Epoch 10, valid_edge_mae: 0.07444, Train_mae: 0.06153, Validation_mae: 0.04800, Validation_rmsd: 0.15094, res_acc: 0.72, kl_x: 0.00, kl_h: 0.00, elapse: 104.89507\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.1509355760856085, epoch: 10\n",
            "Best validation rec acc so far: 0.7176735997200012, epoch: 1\n",
            "=====Epoch 11\n",
            "Training...\n",
            "loss_dist 0.089, loss_coords 0.058, loss_res 0.584, : 100% 32/32 [01:34<00:00,  2.96s/it]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:10<00:00,  1.43s/it]\n",
            "Epoch 11, valid_edge_mae: 0.09666, Train_mae: 0.05429, Validation_mae: 0.05750, Validation_rmsd: 0.15140, res_acc: 0.73, kl_x: 0.00, kl_h: 0.00, elapse: 104.75040\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.1509355760856085, epoch: 10\n",
            "Best validation rec acc so far: 0.7273263931274414, epoch: 11\n",
            "=====Epoch 12\n",
            "Training...\n",
            "loss_dist 0.075, loss_coords 0.048, loss_res 0.534, : 100% 32/32 [01:34<00:00,  2.97s/it]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:09<00:00,  1.39s/it]\n",
            "Epoch 12, valid_edge_mae: 0.07615, Train_mae: 0.05982, Validation_mae: 0.04837, Validation_rmsd: 0.15137, res_acc: 0.72, kl_x: 0.00, kl_h: 0.00, elapse: 104.73082\n",
            "Best validation RMSD so far: 0.1509355760856085, epoch: 10\n",
            "Best validation rec acc so far: 0.7273263931274414, epoch: 11\n",
            "=====Epoch 13\n",
            "Training...\n",
            "loss_dist 0.108, loss_coords 0.072, loss_res 0.559, : 100% 32/32 [01:34<00:00,  2.96s/it]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:10<00:00,  1.43s/it]\n",
            "Epoch 13, valid_edge_mae: 0.09875, Train_mae: 0.06997, Validation_mae: 0.07442, Validation_rmsd: 0.17952, res_acc: 0.71, kl_x: 0.00, kl_h: 0.00, elapse: 104.72860\n",
            "Best validation RMSD so far: 0.1509355760856085, epoch: 10\n",
            "Best validation rec acc so far: 0.7273263931274414, epoch: 11\n",
            "=====Epoch 14\n",
            "Training...\n",
            "loss_dist 0.094, loss_coords 0.056, loss_res 0.566, : 100% 32/32 [01:34<00:00,  2.96s/it]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:09<00:00,  1.37s/it]\n",
            "Epoch 14, valid_edge_mae: 0.07987, Train_mae: 0.06029, Validation_mae: 0.05144, Validation_rmsd: 0.14988, res_acc: 0.72, kl_x: 0.00, kl_h: 0.00, elapse: 104.33725\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.14987665697371752, epoch: 14\n",
            "Best validation rec acc so far: 0.7273263931274414, epoch: 11\n",
            "=====Epoch 15\n",
            "Training...\n",
            "loss_dist 0.125, loss_coords 0.077, loss_res 0.534, : 100% 32/32 [01:34<00:00,  2.96s/it]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:10<00:00,  1.43s/it]\n",
            "Epoch 15, valid_edge_mae: 0.11585, Train_mae: 0.05801, Validation_mae: 0.07333, Validation_rmsd: 0.18742, res_acc: 0.73, kl_x: 0.00, kl_h: 0.00, elapse: 104.90278\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.14987665697371752, epoch: 14\n",
            "Best validation rec acc so far: 0.7324305772781372, epoch: 15\n",
            "=====Epoch 16\n",
            "Training...\n",
            "Iteration:   0% 0/32 [00:00<?, ?it/s]"
          ]
        }
      ],
      "source": [
        "! python LatentLattice/train.py --mp_steps 3 --batch_size 32 --debug --layers 2 --edgeloss_weight 0.0 --epochs 50"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9nLMAeUuT4FU",
        "outputId": "dc173b65-18aa-4fc3-b35d-201293179a93"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Namespace(debug=True, mp_steps=3, emb_dim=32, layers=2, pooling=True, up_mlp=False, residual=True, noise=False, transpose=False, attn=False, loss='all', mode='train', lr_init=0.001, epochs=50, batch_size=32, edgeloss_weight=0.0, kl_weight=0, dataname='2d_square_lattice', num_workers=0, data_path='data/', working_dir='', suffix='', log_dir='', checkpoint_dir='trained_models', saved_model_dir=None)\n",
            "Training with 1 GPUs!\n",
            "\n",
            "# Params: 205090\n",
            "=====Epoch 1\n",
            "Training...\n",
            "Iteration:   0% 0/32 [00:00<?, ?it/s]/usr/local/lib/python3.10/dist-packages/torch_geometric/data/storage.py:450: UserWarning: Unable to accurately infer 'num_nodes' from the attribute set '{'edge_index'}'. Please explicitly set 'num_nodes' as an attribute of 'data' to suppress this warning\n",
            "  warnings.warn(\n",
            "loss_dist 1.281, loss_coords 0.863, loss_res 0.580, : 100% 32/32 [00:27<00:00,  1.17it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.47it/s]\n",
            "Epoch 1, valid_edge_mae: 1.27398, Train_mae: 1.10613, Validation_mae: 0.84545, Validation_rmsd: 2.52852, res_acc: 0.72, kl_x: 0.00, kl_h: 0.00, elapse: 32.28552\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 2.528520658702029, epoch: 1\n",
            "Best validation rec acc so far: 0.7176735997200012, epoch: 1\n",
            "=====Epoch 2\n",
            "Training...\n",
            "loss_dist 1.009, loss_coords 0.638, loss_res 0.603, : 100% 32/32 [00:24<00:00,  1.29it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.47it/s]\n",
            "Epoch 2, valid_edge_mae: 1.22698, Train_mae: 0.71811, Validation_mae: 0.64936, Validation_rmsd: 1.86304, res_acc: 0.67, kl_x: 0.00, kl_h: 0.00, elapse: 29.71375\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 1.8630440515197486, epoch: 2\n",
            "Best validation rec acc so far: 0.7176735997200012, epoch: 1\n",
            "=====Epoch 3\n",
            "Training...\n",
            "loss_dist 0.355, loss_coords 0.217, loss_res 0.574, : 100% 32/32 [00:25<00:00,  1.26it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.49it/s]\n",
            "Epoch 3, valid_edge_mae: 0.36911, Train_mae: 0.42102, Validation_mae: 0.22189, Validation_rmsd: 0.56836, res_acc: 0.69, kl_x: 0.00, kl_h: 0.00, elapse: 30.05539\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.5683610898870257, epoch: 3\n",
            "Best validation rec acc so far: 0.7176735997200012, epoch: 1\n",
            "=====Epoch 4\n",
            "Training...\n",
            "loss_dist 0.182, loss_coords 0.122, loss_res 0.567, : 100% 32/32 [00:25<00:00,  1.28it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.48it/s]\n",
            "Epoch 4, valid_edge_mae: 0.17236, Train_mae: 0.15674, Validation_mae: 0.11100, Validation_rmsd: 0.31772, res_acc: 0.71, kl_x: 0.00, kl_h: 0.00, elapse: 29.80957\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.3177172519932483, epoch: 4\n",
            "Best validation rec acc so far: 0.7176735997200012, epoch: 1\n",
            "=====Epoch 5\n",
            "Training...\n",
            "loss_dist 0.166, loss_coords 0.109, loss_res 0.554, : 100% 32/32 [00:25<00:00,  1.27it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.49it/s]\n",
            "Epoch 5, valid_edge_mae: 0.14516, Train_mae: 0.11955, Validation_mae: 0.10557, Validation_rmsd: 0.28660, res_acc: 0.71, kl_x: 0.00, kl_h: 0.00, elapse: 29.85064\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.2866022368777516, epoch: 5\n",
            "Best validation rec acc so far: 0.7176735997200012, epoch: 1\n",
            "=====Epoch 6\n",
            "Training...\n",
            "loss_dist 0.143, loss_coords 0.108, loss_res 0.571, : 100% 32/32 [00:25<00:00,  1.27it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.49it/s]\n",
            "Epoch 6, valid_edge_mae: 0.18042, Train_mae: 0.10063, Validation_mae: 0.10301, Validation_rmsd: 0.28271, res_acc: 0.71, kl_x: 0.00, kl_h: 0.00, elapse: 29.93918\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.28271338062622897, epoch: 6\n",
            "Best validation rec acc so far: 0.7176735997200012, epoch: 1\n",
            "=====Epoch 7\n",
            "Training...\n",
            "loss_dist 0.098, loss_coords 0.063, loss_res 0.571, : 100% 32/32 [00:24<00:00,  1.29it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.47it/s]\n",
            "Epoch 7, valid_edge_mae: 0.13388, Train_mae: 0.07979, Validation_mae: 0.08601, Validation_rmsd: 0.23894, res_acc: 0.71, kl_x: 0.00, kl_h: 0.00, elapse: 29.58291\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.23894274595816256, epoch: 7\n",
            "Best validation rec acc so far: 0.7176735997200012, epoch: 1\n",
            "=====Epoch 8\n",
            "Training...\n",
            "loss_dist 0.185, loss_coords 0.107, loss_res 0.561, : 100% 32/32 [00:25<00:00,  1.26it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.49it/s]\n",
            "Epoch 8, valid_edge_mae: 0.15769, Train_mae: 0.07320, Validation_mae: 0.09746, Validation_rmsd: 0.21984, res_acc: 0.71, kl_x: 0.00, kl_h: 0.00, elapse: 30.10441\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.2198368405832438, epoch: 8\n",
            "Best validation rec acc so far: 0.7176735997200012, epoch: 1\n",
            "=====Epoch 9\n",
            "Training...\n",
            "loss_dist 0.087, loss_coords 0.057, loss_res 0.553, : 100% 32/32 [00:24<00:00,  1.29it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.48it/s]\n",
            "Epoch 9, valid_edge_mae: 0.10315, Train_mae: 0.08368, Validation_mae: 0.06406, Validation_rmsd: 0.19226, res_acc: 0.71, kl_x: 0.00, kl_h: 0.00, elapse: 29.62188\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.19225971267114667, epoch: 9\n",
            "Best validation rec acc so far: 0.7176735997200012, epoch: 1\n",
            "=====Epoch 10\n",
            "Training...\n",
            "loss_dist 0.107, loss_coords 0.064, loss_res 0.550, : 100% 32/32 [00:25<00:00,  1.27it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.49it/s]\n",
            "Epoch 10, valid_edge_mae: 0.10260, Train_mae: 0.06498, Validation_mae: 0.06119, Validation_rmsd: 0.18968, res_acc: 0.71, kl_x: 0.00, kl_h: 0.00, elapse: 29.99817\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.18968426198368252, epoch: 10\n",
            "Best validation rec acc so far: 0.7176735997200012, epoch: 1\n",
            "=====Epoch 11\n",
            "Training...\n",
            "loss_dist 0.071, loss_coords 0.047, loss_res 0.564, : 100% 32/32 [00:25<00:00,  1.26it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.49it/s]\n",
            "Epoch 11, valid_edge_mae: 0.08403, Train_mae: 0.05856, Validation_mae: 0.07806, Validation_rmsd: 0.18098, res_acc: 0.72, kl_x: 0.00, kl_h: 0.00, elapse: 30.10040\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.18097825586118105, epoch: 11\n",
            "Best validation rec acc so far: 0.7226041555404663, epoch: 11\n",
            "=====Epoch 12\n",
            "Training...\n",
            "loss_dist 0.096, loss_coords 0.059, loss_res 0.533, : 100% 32/32 [00:25<00:00,  1.28it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.46it/s]\n",
            "Epoch 12, valid_edge_mae: 0.07211, Train_mae: 0.05792, Validation_mae: 0.05794, Validation_rmsd: 0.16041, res_acc: 0.73, kl_x: 0.00, kl_h: 0.00, elapse: 29.83638\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.1604106686848164, epoch: 12\n",
            "Best validation rec acc so far: 0.7253124713897705, epoch: 12\n",
            "=====Epoch 13\n",
            "Training...\n",
            "loss_dist 0.073, loss_coords 0.054, loss_res 0.532, : 100% 32/32 [00:25<00:00,  1.26it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.48it/s]\n",
            "Epoch 13, valid_edge_mae: 0.08843, Train_mae: 0.05973, Validation_mae: 0.06156, Validation_rmsd: 0.16713, res_acc: 0.73, kl_x: 0.00, kl_h: 0.00, elapse: 30.09100\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.1604106686848164, epoch: 12\n",
            "Best validation rec acc so far: 0.7277777791023254, epoch: 13\n",
            "=====Epoch 14\n",
            "Training...\n",
            "loss_dist 0.072, loss_coords 0.046, loss_res 0.521, : 100% 32/32 [00:24<00:00,  1.29it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.49it/s]\n",
            "Epoch 14, valid_edge_mae: 0.07628, Train_mae: 0.04978, Validation_mae: 0.05068, Validation_rmsd: 0.15009, res_acc: 0.72, kl_x: 0.00, kl_h: 0.00, elapse: 29.57628\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.15008811749415688, epoch: 14\n",
            "Best validation rec acc so far: 0.7277777791023254, epoch: 13\n",
            "=====Epoch 15\n",
            "Training...\n",
            "loss_dist 0.078, loss_coords 0.059, loss_res 0.482, : 100% 32/32 [00:25<00:00,  1.27it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.48it/s]\n",
            "Epoch 15, valid_edge_mae: 0.07318, Train_mae: 0.05643, Validation_mae: 0.04918, Validation_rmsd: 0.14512, res_acc: 0.75, kl_x: 0.00, kl_h: 0.00, elapse: 29.94396\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.14511551857199464, epoch: 15\n",
            "Best validation rec acc so far: 0.7528125047683716, epoch: 15\n",
            "=====Epoch 16\n",
            "Training...\n",
            "loss_dist 0.154, loss_coords 0.100, loss_res 0.550, : 100% 32/32 [00:25<00:00,  1.26it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.49it/s]\n",
            "Epoch 16, valid_edge_mae: 0.13692, Train_mae: 0.08294, Validation_mae: 0.09117, Validation_rmsd: 0.22688, res_acc: 0.71, kl_x: 0.00, kl_h: 0.00, elapse: 30.05488\n",
            "Best validation RMSD so far: 0.14511551857199464, epoch: 15\n",
            "Best validation rec acc so far: 0.7528125047683716, epoch: 15\n",
            "=====Epoch 17\n",
            "Training...\n",
            "loss_dist 0.073, loss_coords 0.045, loss_res 0.534, : 100% 32/32 [00:24<00:00,  1.28it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.49it/s]\n",
            "Epoch 17, valid_edge_mae: 0.06519, Train_mae: 0.05762, Validation_mae: 0.04181, Validation_rmsd: 0.13410, res_acc: 0.74, kl_x: 0.00, kl_h: 0.00, elapse: 29.66004\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.13410144568340038, epoch: 17\n",
            "Best validation rec acc so far: 0.7528125047683716, epoch: 15\n",
            "=====Epoch 18\n",
            "Training...\n",
            "loss_dist 0.097, loss_coords 0.065, loss_res 0.495, : 100% 32/32 [00:25<00:00,  1.27it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.48it/s]\n",
            "Epoch 18, valid_edge_mae: 0.08921, Train_mae: 0.05444, Validation_mae: 0.05552, Validation_rmsd: 0.14465, res_acc: 0.76, kl_x: 0.00, kl_h: 0.00, elapse: 30.04070\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.13410144568340038, epoch: 17\n",
            "Best validation rec acc so far: 0.7591666579246521, epoch: 18\n",
            "=====Epoch 19\n",
            "Training...\n",
            "loss_dist 0.091, loss_coords 0.058, loss_res 0.464, : 100% 32/32 [00:24<00:00,  1.29it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.48it/s]\n",
            "Epoch 19, valid_edge_mae: 0.08628, Train_mae: 0.05760, Validation_mae: 0.05551, Validation_rmsd: 0.14587, res_acc: 0.78, kl_x: 0.00, kl_h: 0.00, elapse: 29.53447\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.13410144568340038, epoch: 17\n",
            "Best validation rec acc so far: 0.7752430438995361, epoch: 19\n",
            "=====Epoch 20\n",
            "Training...\n",
            "loss_dist 0.058, loss_coords 0.040, loss_res 0.432, : 100% 32/32 [00:25<00:00,  1.27it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.48it/s]\n",
            "Epoch 20, valid_edge_mae: 0.06380, Train_mae: 0.04707, Validation_mae: 0.04212, Validation_rmsd: 0.11710, res_acc: 0.78, kl_x: 0.00, kl_h: 0.00, elapse: 29.96680\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.11709634151996216, epoch: 20\n",
            "Best validation rec acc so far: 0.7836458086967468, epoch: 20\n",
            "=====Epoch 21\n",
            "Training...\n",
            "Iteration:   0% 0/32 [00:00<?, ?it/s]/content/drive/.shortcut-targets-by-id/1cPQ2fA-SRAPng-aTI1P8QDLacE-wxHcy/lattices/LatentLattice/train.py:135: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`). Consider using `matplotlib.pyplot.close()`.\n",
            "  fig = plt.figure()\n",
            "loss_dist 0.060, loss_coords 0.050, loss_res 0.417, : 100% 32/32 [00:25<00:00,  1.27it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.49it/s]\n",
            "Epoch 21, valid_edge_mae: 0.07967, Train_mae: 0.04419, Validation_mae: 0.05099, Validation_rmsd: 0.12223, res_acc: 0.80, kl_x: 0.00, kl_h: 0.00, elapse: 29.97927\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.11709634151996216, epoch: 20\n",
            "Best validation rec acc so far: 0.7952777743339539, epoch: 21\n",
            "=====Epoch 22\n",
            "Training...\n",
            "loss_dist 0.059, loss_coords 0.040, loss_res 0.407, : 100% 32/32 [00:24<00:00,  1.28it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.48it/s]\n",
            "Epoch 22, valid_edge_mae: 0.06350, Train_mae: 0.04244, Validation_mae: 0.04117, Validation_rmsd: 0.10841, res_acc: 0.79, kl_x: 0.00, kl_h: 0.00, elapse: 29.71814\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.10840928864952085, epoch: 22\n",
            "Best validation rec acc so far: 0.7952777743339539, epoch: 21\n",
            "=====Epoch 23\n",
            "Training...\n",
            "loss_dist 0.069, loss_coords 0.049, loss_res 0.385, : 100% 32/32 [00:25<00:00,  1.27it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.49it/s]\n",
            "Epoch 23, valid_edge_mae: 0.05826, Train_mae: 0.04657, Validation_mae: 0.03880, Validation_rmsd: 0.10318, res_acc: 0.79, kl_x: 0.00, kl_h: 0.00, elapse: 29.93409\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.10318010118014831, epoch: 23\n",
            "Best validation rec acc so far: 0.7952777743339539, epoch: 21\n",
            "=====Epoch 24\n",
            "Training...\n",
            "loss_dist 0.064, loss_coords 0.043, loss_res 0.407, : 100% 32/32 [00:24<00:00,  1.28it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.48it/s]\n",
            "Epoch 24, valid_edge_mae: 0.05506, Train_mae: 0.04277, Validation_mae: 0.04238, Validation_rmsd: 0.10979, res_acc: 0.79, kl_x: 0.00, kl_h: 0.00, elapse: 29.70402\n",
            "Best validation RMSD so far: 0.10318010118014831, epoch: 23\n",
            "Best validation rec acc so far: 0.7952777743339539, epoch: 21\n",
            "=====Epoch 25\n",
            "Training...\n",
            "loss_dist 0.082, loss_coords 0.050, loss_res 0.440, : 100% 32/32 [00:25<00:00,  1.27it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.48it/s]\n",
            "Epoch 25, valid_edge_mae: 0.08622, Train_mae: 0.04230, Validation_mae: 0.05603, Validation_rmsd: 0.14138, res_acc: 0.80, kl_x: 0.00, kl_h: 0.00, elapse: 29.98506\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.10318010118014831, epoch: 23\n",
            "Best validation rec acc so far: 0.8029513955116272, epoch: 25\n",
            "=====Epoch 26\n",
            "Training...\n",
            "loss_dist 0.061, loss_coords 0.047, loss_res 0.366, : 100% 32/32 [00:24<00:00,  1.28it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.47it/s]\n",
            "Epoch 26, valid_edge_mae: 0.05909, Train_mae: 0.04491, Validation_mae: 0.04099, Validation_rmsd: 0.10428, res_acc: 0.83, kl_x: 0.00, kl_h: 0.00, elapse: 29.74016\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.10318010118014831, epoch: 23\n",
            "Best validation rec acc so far: 0.8263888955116272, epoch: 26\n",
            "=====Epoch 27\n",
            "Training...\n",
            "loss_dist 0.055, loss_coords 0.037, loss_res 0.337, : 100% 32/32 [00:25<00:00,  1.27it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.47it/s]\n",
            "Epoch 27, valid_edge_mae: 0.05150, Train_mae: 0.04475, Validation_mae: 0.03549, Validation_rmsd: 0.09955, res_acc: 0.83, kl_x: 0.00, kl_h: 0.00, elapse: 30.07175\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.09954957230639856, epoch: 27\n",
            "Best validation rec acc so far: 0.8347569704055786, epoch: 27\n",
            "=====Epoch 28\n",
            "Training...\n",
            "loss_dist 0.061, loss_coords 0.044, loss_res 0.335, : 100% 32/32 [00:25<00:00,  1.26it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.50it/s]\n",
            "Epoch 28, valid_edge_mae: 0.05546, Train_mae: 0.04251, Validation_mae: 0.03811, Validation_rmsd: 0.10082, res_acc: 0.85, kl_x: 0.00, kl_h: 0.00, elapse: 30.07478\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.09954957230639856, epoch: 27\n",
            "Best validation rec acc so far: 0.8470486402511597, epoch: 28\n",
            "=====Epoch 29\n",
            "Training...\n",
            "loss_dist 0.079, loss_coords 0.051, loss_res 0.403, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.51it/s]\n",
            "Epoch 29, valid_edge_mae: 0.07272, Train_mae: 0.06699, Validation_mae: 0.04769, Validation_rmsd: 0.13851, res_acc: 0.80, kl_x: 0.00, kl_h: 0.00, elapse: 29.26330\n",
            "Best validation RMSD so far: 0.09954957230639856, epoch: 27\n",
            "Best validation rec acc so far: 0.8470486402511597, epoch: 28\n",
            "=====Epoch 30\n",
            "Training...\n",
            "loss_dist 0.055, loss_coords 0.036, loss_res 0.386, : 100% 32/32 [00:24<00:00,  1.29it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.50it/s]\n",
            "Epoch 30, valid_edge_mae: 0.05665, Train_mae: 0.03942, Validation_mae: 0.03584, Validation_rmsd: 0.10171, res_acc: 0.84, kl_x: 0.00, kl_h: 0.00, elapse: 29.57111\n",
            "Best validation RMSD so far: 0.09954957230639856, epoch: 27\n",
            "Best validation rec acc so far: 0.8470486402511597, epoch: 28\n",
            "=====Epoch 31\n",
            "Training...\n",
            "loss_dist 0.050, loss_coords 0.035, loss_res 0.305, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.49it/s]\n",
            "Epoch 31, valid_edge_mae: 0.04689, Train_mae: 0.03766, Validation_mae: 0.03138, Validation_rmsd: 0.09594, res_acc: 0.85, kl_x: 0.00, kl_h: 0.00, elapse: 29.32622\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.09593657156979214, epoch: 31\n",
            "Best validation rec acc so far: 0.8514236211776733, epoch: 31\n",
            "=====Epoch 32\n",
            "Training...\n",
            "loss_dist 0.063, loss_coords 0.043, loss_res 0.314, : 100% 32/32 [00:24<00:00,  1.28it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.51it/s]\n",
            "Epoch 32, valid_edge_mae: 0.06501, Train_mae: 0.04181, Validation_mae: 0.04388, Validation_rmsd: 0.11393, res_acc: 0.85, kl_x: 0.00, kl_h: 0.00, elapse: 29.62093\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.09593657156979214, epoch: 31\n",
            "Best validation rec acc so far: 0.851597249507904, epoch: 32\n",
            "=====Epoch 33\n",
            "Training...\n",
            "loss_dist 0.066, loss_coords 0.041, loss_res 0.294, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.41it/s]\n",
            "Epoch 33, valid_edge_mae: 0.08815, Train_mae: 0.03594, Validation_mae: 0.04923, Validation_rmsd: 0.11833, res_acc: 0.86, kl_x: 0.00, kl_h: 0.00, elapse: 29.54995\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.09593657156979214, epoch: 31\n",
            "Best validation rec acc so far: 0.8550000190734863, epoch: 33\n",
            "=====Epoch 34\n",
            "Training...\n",
            "loss_dist 0.067, loss_coords 0.041, loss_res 0.316, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.50it/s]\n",
            "Epoch 34, valid_edge_mae: 0.06416, Train_mae: 0.03990, Validation_mae: 0.04217, Validation_rmsd: 0.10555, res_acc: 0.86, kl_x: 0.00, kl_h: 0.00, elapse: 29.29801\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.09593657156979214, epoch: 31\n",
            "Best validation rec acc so far: 0.8627777695655823, epoch: 34\n",
            "=====Epoch 35\n",
            "Training...\n",
            "loss_dist 0.045, loss_coords 0.028, loss_res 0.295, : 100% 32/32 [00:24<00:00,  1.29it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.50it/s]\n",
            "Epoch 35, valid_edge_mae: 0.04293, Train_mae: 0.03550, Validation_mae: 0.02855, Validation_rmsd: 0.08717, res_acc: 0.87, kl_x: 0.00, kl_h: 0.00, elapse: 29.59373\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.08717220874836354, epoch: 35\n",
            "Best validation rec acc so far: 0.8737152814865112, epoch: 35\n",
            "=====Epoch 36\n",
            "Training...\n",
            "loss_dist 0.046, loss_coords 0.035, loss_res 0.240, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.49it/s]\n",
            "Epoch 36, valid_edge_mae: 0.04412, Train_mae: 0.03071, Validation_mae: 0.02971, Validation_rmsd: 0.08579, res_acc: 0.87, kl_x: 0.00, kl_h: 0.00, elapse: 29.41051\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.0857894793268255, epoch: 36\n",
            "Best validation rec acc so far: 0.8748958110809326, epoch: 36\n",
            "=====Epoch 37\n",
            "Training...\n",
            "loss_dist 0.042, loss_coords 0.029, loss_res 0.263, : 100% 32/32 [00:24<00:00,  1.29it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.50it/s]\n",
            "Epoch 37, valid_edge_mae: 0.04430, Train_mae: 0.03012, Validation_mae: 0.03009, Validation_rmsd: 0.08251, res_acc: 0.87, kl_x: 0.00, kl_h: 0.00, elapse: 29.57323\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.08250771552199344, epoch: 37\n",
            "Best validation rec acc so far: 0.8748958110809326, epoch: 36\n",
            "=====Epoch 38\n",
            "Training...\n",
            "loss_dist 0.072, loss_coords 0.050, loss_res 0.311, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.49it/s]\n",
            "Epoch 38, valid_edge_mae: 0.06682, Train_mae: 0.03340, Validation_mae: 0.04402, Validation_rmsd: 0.10390, res_acc: 0.86, kl_x: 0.00, kl_h: 0.00, elapse: 29.33010\n",
            "Best validation RMSD so far: 0.08250771552199344, epoch: 37\n",
            "Best validation rec acc so far: 0.8748958110809326, epoch: 36\n",
            "=====Epoch 39\n",
            "Training...\n",
            "loss_dist 0.051, loss_coords 0.034, loss_res 0.264, : 100% 32/32 [00:24<00:00,  1.29it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.50it/s]\n",
            "Epoch 39, valid_edge_mae: 0.05545, Train_mae: 0.03637, Validation_mae: 0.03363, Validation_rmsd: 0.08926, res_acc: 0.89, kl_x: 0.00, kl_h: 0.00, elapse: 29.54665\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.08250771552199344, epoch: 37\n",
            "Best validation rec acc so far: 0.8854861259460449, epoch: 39\n",
            "=====Epoch 40\n",
            "Training...\n",
            "loss_dist 0.055, loss_coords 0.038, loss_res 0.246, : 100% 32/32 [00:24<00:00,  1.28it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.50it/s]\n",
            "Epoch 40, valid_edge_mae: 0.04964, Train_mae: 0.03290, Validation_mae: 0.03219, Validation_rmsd: 0.09209, res_acc: 0.88, kl_x: 0.00, kl_h: 0.00, elapse: 29.68644\n",
            "Best validation RMSD so far: 0.08250771552199344, epoch: 37\n",
            "Best validation rec acc so far: 0.8854861259460449, epoch: 39\n",
            "=====Epoch 41\n",
            "Training...\n",
            "loss_dist 0.052, loss_coords 0.035, loss_res 0.232, : 100% 32/32 [00:24<00:00,  1.31it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.50it/s]\n",
            "Epoch 41, valid_edge_mae: 0.05956, Train_mae: 0.04929, Validation_mae: 0.03705, Validation_rmsd: 0.10017, res_acc: 0.89, kl_x: 0.00, kl_h: 0.00, elapse: 29.21817\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.08250771552199344, epoch: 37\n",
            "Best validation rec acc so far: 0.8880555629730225, epoch: 41\n",
            "=====Epoch 42\n",
            "Training...\n",
            "loss_dist 0.046, loss_coords 0.030, loss_res 0.203, : 100% 32/32 [00:24<00:00,  1.29it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.51it/s]\n",
            "Epoch 42, valid_edge_mae: 0.04248, Train_mae: 0.03186, Validation_mae: 0.02817, Validation_rmsd: 0.08114, res_acc: 0.91, kl_x: 0.00, kl_h: 0.00, elapse: 29.55243\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.08113714117237233, epoch: 42\n",
            "Best validation rec acc so far: 0.9070485830307007, epoch: 42\n",
            "=====Epoch 43\n",
            "Training...\n",
            "loss_dist 0.053, loss_coords 0.034, loss_res 0.186, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.50it/s]\n",
            "Epoch 43, valid_edge_mae: 0.05039, Train_mae: 0.03284, Validation_mae: 0.03137, Validation_rmsd: 0.08439, res_acc: 0.91, kl_x: 0.00, kl_h: 0.00, elapse: 29.28610\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.08113714117237233, epoch: 42\n",
            "Best validation rec acc so far: 0.9082638621330261, epoch: 43\n",
            "=====Epoch 44\n",
            "Training...\n",
            "loss_dist 0.047, loss_coords 0.034, loss_res 0.195, : 100% 32/32 [00:24<00:00,  1.28it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.51it/s]\n",
            "Epoch 44, valid_edge_mae: 0.03848, Train_mae: 0.02996, Validation_mae: 0.02691, Validation_rmsd: 0.07657, res_acc: 0.91, kl_x: 0.00, kl_h: 0.00, elapse: 29.59828\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.07657201989155289, epoch: 44\n",
            "Best validation rec acc so far: 0.9113194346427917, epoch: 44\n",
            "=====Epoch 45\n",
            "Training...\n",
            "loss_dist 0.043, loss_coords 0.031, loss_res 0.185, : 100% 32/32 [00:24<00:00,  1.28it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.49it/s]\n",
            "Epoch 45, valid_edge_mae: 0.04640, Train_mae: 0.03417, Validation_mae: 0.02931, Validation_rmsd: 0.07931, res_acc: 0.91, kl_x: 0.00, kl_h: 0.00, elapse: 29.67874\n",
            "Best validation RMSD so far: 0.07657201989155289, epoch: 44\n",
            "Best validation rec acc so far: 0.9113194346427917, epoch: 44\n",
            "=====Epoch 46\n",
            "Training...\n",
            "loss_dist 0.040, loss_coords 0.027, loss_res 0.167, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.49it/s]\n",
            "Epoch 46, valid_edge_mae: 0.04184, Train_mae: 0.02763, Validation_mae: 0.02704, Validation_rmsd: 0.07804, res_acc: 0.90, kl_x: 0.00, kl_h: 0.00, elapse: 29.29251\n",
            "Best validation RMSD so far: 0.07657201989155289, epoch: 44\n",
            "Best validation rec acc so far: 0.9113194346427917, epoch: 44\n",
            "=====Epoch 47\n",
            "Training...\n",
            "loss_dist 0.066, loss_coords 0.044, loss_res 0.248, : 100% 32/32 [00:24<00:00,  1.29it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.49it/s]\n",
            "Epoch 47, valid_edge_mae: 0.07281, Train_mae: 0.06357, Validation_mae: 0.04480, Validation_rmsd: 0.11836, res_acc: 0.88, kl_x: 0.00, kl_h: 0.00, elapse: 29.51860\n",
            "Best validation RMSD so far: 0.07657201989155289, epoch: 44\n",
            "Best validation rec acc so far: 0.9113194346427917, epoch: 44\n",
            "=====Epoch 48\n",
            "Training...\n",
            "loss_dist 0.048, loss_coords 0.030, loss_res 0.189, : 100% 32/32 [00:24<00:00,  1.29it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.49it/s]\n",
            "Epoch 48, valid_edge_mae: 0.04682, Train_mae: 0.03318, Validation_mae: 0.02898, Validation_rmsd: 0.08310, res_acc: 0.91, kl_x: 0.00, kl_h: 0.00, elapse: 29.45137\n",
            "Best validation RMSD so far: 0.07657201989155289, epoch: 44\n",
            "Best validation rec acc so far: 0.9113194346427917, epoch: 44\n",
            "=====Epoch 49\n",
            "Training...\n",
            "loss_dist 0.038, loss_coords 0.025, loss_res 0.154, : 100% 32/32 [00:25<00:00,  1.28it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.49it/s]\n",
            "Epoch 49, valid_edge_mae: 0.04474, Train_mae: 0.02777, Validation_mae: 0.02710, Validation_rmsd: 0.07657, res_acc: 0.91, kl_x: 0.00, kl_h: 0.00, elapse: 29.83768\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.07656857209860185, epoch: 49\n",
            "Best validation rec acc so far: 0.9129166603088379, epoch: 49\n",
            "=====Epoch 50\n",
            "Training...\n",
            "loss_dist 0.097, loss_coords 0.053, loss_res 0.236, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.50it/s]\n",
            "Epoch 50, valid_edge_mae: 0.05980, Train_mae: 0.03656, Validation_mae: 0.04662, Validation_rmsd: 0.11555, res_acc: 0.89, kl_x: 0.00, kl_h: 0.00, elapse: 29.38912\n",
            "Best validation RMSD so far: 0.07656857209860185, epoch: 49\n",
            "Best validation rec acc so far: 0.9129166603088379, epoch: 49\n"
          ]
        }
      ],
      "source": [
        "! python LatentLattice/train.py --mp_steps 3 --batch_size 32 --debug --layers 2 --edgeloss_weight 0.0 --epochs 50"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ENsHFotFT5eU",
        "outputId": "11b17bf0-37dc-4009-811a-13b9ad305324"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Namespace(debug=False, mp_steps=3, emb_dim=32, layers=2, pooling=True, up_mlp=False, residual=True, noise=False, transpose=False, attn=False, loss='all', mode='train', lr_init=0.001, epochs=100, batch_size=32, edgeloss_weight=0.0, kl_weight=0, dataname='2d_square_lattice', num_workers=0, data_path='data/', working_dir='', suffix='', log_dir='', checkpoint_dir='trained_models', saved_model_dir=None)\n",
            "Training with 1 GPUs!\n",
            "\n",
            "# Params: 205090\n",
            "=====Epoch 1\n",
            "Training...\n",
            "Iteration:   0% 0/32 [00:00<?, ?it/s]/usr/local/lib/python3.10/dist-packages/torch_geometric/data/storage.py:450: UserWarning: Unable to accurately infer 'num_nodes' from the attribute set '{'edge_index'}'. Please explicitly set 'num_nodes' as an attribute of 'data' to suppress this warning\n",
            "  warnings.warn(\n",
            "loss_dist 1.281, loss_coords 0.863, loss_res 0.580, : 100% 32/32 [00:25<00:00,  1.26it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 1, valid_edge_mae: 1.27398, Train_mae: 1.10613, Validation_mae: 0.84545, Validation_rmsd: 2.52852, res_acc: 0.72, kl_x: 0.00, kl_h: 0.00, elapse: 29.97950\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 2.5285206587020075, epoch: 1\n",
            "Best validation rec acc so far: 0.7176735997200012, epoch: 1\n",
            "=====Epoch 2\n",
            "Training...\n",
            "loss_dist 1.009, loss_coords 0.638, loss_res 0.603, : 100% 32/32 [00:24<00:00,  1.33it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.51it/s]\n",
            "Epoch 2, valid_edge_mae: 1.22698, Train_mae: 0.71811, Validation_mae: 0.64936, Validation_rmsd: 1.86304, res_acc: 0.67, kl_x: 0.00, kl_h: 0.00, elapse: 28.69955\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 1.86304483801597, epoch: 2\n",
            "Best validation rec acc so far: 0.7176735997200012, epoch: 1\n",
            "=====Epoch 3\n",
            "Training...\n",
            "loss_dist 0.308, loss_coords 0.194, loss_res 0.566, : 100% 32/32 [00:24<00:00,  1.31it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 3, valid_edge_mae: 0.30912, Train_mae: 0.40117, Validation_mae: 0.19716, Validation_rmsd: 0.45697, res_acc: 0.70, kl_x: 0.00, kl_h: 0.00, elapse: 28.95456\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.45696896589011493, epoch: 3\n",
            "Best validation rec acc so far: 0.7176735997200012, epoch: 1\n",
            "=====Epoch 4\n",
            "Training...\n",
            "loss_dist 0.189, loss_coords 0.130, loss_res 0.566, : 100% 32/32 [00:24<00:00,  1.32it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.54it/s]\n",
            "Epoch 4, valid_edge_mae: 0.24052, Train_mae: 0.15277, Validation_mae: 0.15257, Validation_rmsd: 0.35924, res_acc: 0.71, kl_x: 0.00, kl_h: 0.00, elapse: 28.86505\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.359243179457122, epoch: 4\n",
            "Best validation rec acc so far: 0.7176735997200012, epoch: 1\n",
            "=====Epoch 5\n",
            "Training...\n",
            "loss_dist 0.188, loss_coords 0.130, loss_res 0.548, : 100% 32/32 [00:24<00:00,  1.31it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.55it/s]\n",
            "Epoch 5, valid_edge_mae: 0.15379, Train_mae: 0.12022, Validation_mae: 0.10258, Validation_rmsd: 0.27405, res_acc: 0.71, kl_x: 0.00, kl_h: 0.00, elapse: 28.90253\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.2740549256713086, epoch: 5\n",
            "Best validation rec acc so far: 0.7176735997200012, epoch: 1\n",
            "=====Epoch 6\n",
            "Training...\n",
            "loss_dist 0.130, loss_coords 0.083, loss_res 0.556, : 100% 32/32 [00:24<00:00,  1.31it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 6, valid_edge_mae: 0.11518, Train_mae: 0.09633, Validation_mae: 0.08222, Validation_rmsd: 0.23977, res_acc: 0.71, kl_x: 0.00, kl_h: 0.00, elapse: 28.97683\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.2397738275816587, epoch: 6\n",
            "Best validation rec acc so far: 0.7176735997200012, epoch: 1\n",
            "=====Epoch 7\n",
            "Training...\n",
            "loss_dist 0.118, loss_coords 0.074, loss_res 0.573, : 100% 32/32 [00:24<00:00,  1.32it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 7, valid_edge_mae: 0.15184, Train_mae: 0.07628, Validation_mae: 0.08624, Validation_rmsd: 0.24358, res_acc: 0.71, kl_x: 0.00, kl_h: 0.00, elapse: 28.78665\n",
            "Best validation RMSD so far: 0.2397738275816587, epoch: 6\n",
            "Best validation rec acc so far: 0.7176735997200012, epoch: 1\n",
            "=====Epoch 8\n",
            "Training...\n",
            "loss_dist 0.104, loss_coords 0.079, loss_res 0.563, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 8, valid_edge_mae: 0.11972, Train_mae: 0.08437, Validation_mae: 0.07321, Validation_rmsd: 0.21020, res_acc: 0.71, kl_x: 0.00, kl_h: 0.00, elapse: 29.13005\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.21020498358872608, epoch: 8\n",
            "Best validation rec acc so far: 0.7176735997200012, epoch: 1\n",
            "=====Epoch 9\n",
            "Training...\n",
            "loss_dist 0.082, loss_coords 0.066, loss_res 0.558, : 100% 32/32 [00:23<00:00,  1.33it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.52it/s]\n",
            "Epoch 9, valid_edge_mae: 0.08332, Train_mae: 0.07401, Validation_mae: 0.05232, Validation_rmsd: 0.18518, res_acc: 0.71, kl_x: 0.00, kl_h: 0.00, elapse: 28.62347\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.18517982005567582, epoch: 9\n",
            "Best validation rec acc so far: 0.7176735997200012, epoch: 1\n",
            "=====Epoch 10\n",
            "Training...\n",
            "loss_dist 0.091, loss_coords 0.062, loss_res 0.540, : 100% 32/32 [00:24<00:00,  1.31it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.54it/s]\n",
            "Epoch 10, valid_edge_mae: 0.09153, Train_mae: 0.07692, Validation_mae: 0.05711, Validation_rmsd: 0.18775, res_acc: 0.71, kl_x: 0.00, kl_h: 0.00, elapse: 28.90926\n",
            "Best validation RMSD so far: 0.18517982005567582, epoch: 9\n",
            "Best validation rec acc so far: 0.7176735997200012, epoch: 1\n",
            "=====Epoch 11\n",
            "Training...\n",
            "loss_dist 0.066, loss_coords 0.043, loss_res 0.569, : 100% 32/32 [00:24<00:00,  1.32it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.41it/s]\n",
            "Epoch 11, valid_edge_mae: 0.07742, Train_mae: 0.05344, Validation_mae: 0.05077, Validation_rmsd: 0.15695, res_acc: 0.72, kl_x: 0.00, kl_h: 0.00, elapse: 29.26428\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.15694621625711655, epoch: 11\n",
            "Best validation rec acc so far: 0.7213541865348816, epoch: 11\n",
            "=====Epoch 12\n",
            "Training...\n",
            "loss_dist 0.072, loss_coords 0.053, loss_res 0.545, : 100% 32/32 [00:24<00:00,  1.31it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.55it/s]\n",
            "Epoch 12, valid_edge_mae: 0.07498, Train_mae: 0.06031, Validation_mae: 0.04770, Validation_rmsd: 0.14879, res_acc: 0.72, kl_x: 0.00, kl_h: 0.00, elapse: 28.91486\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.14879251162653703, epoch: 12\n",
            "Best validation rec acc so far: 0.7213541865348816, epoch: 11\n",
            "=====Epoch 13\n",
            "Training...\n",
            "loss_dist 0.119, loss_coords 0.074, loss_res 0.563, : 100% 32/32 [00:24<00:00,  1.32it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.54it/s]\n",
            "Epoch 13, valid_edge_mae: 0.10786, Train_mae: 0.06407, Validation_mae: 0.07029, Validation_rmsd: 0.18458, res_acc: 0.72, kl_x: 0.00, kl_h: 0.00, elapse: 28.88429\n",
            "Best validation RMSD so far: 0.14879251162653703, epoch: 12\n",
            "Best validation rec acc so far: 0.7213541865348816, epoch: 11\n",
            "=====Epoch 14\n",
            "Training...\n",
            "loss_dist 0.088, loss_coords 0.055, loss_res 0.541, : 100% 32/32 [00:24<00:00,  1.32it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.51it/s]\n",
            "Epoch 14, valid_edge_mae: 0.06367, Train_mae: 0.05257, Validation_mae: 0.04305, Validation_rmsd: 0.13680, res_acc: 0.73, kl_x: 0.00, kl_h: 0.00, elapse: 28.92936\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.13679602901186202, epoch: 14\n",
            "Best validation rec acc so far: 0.7270486354827881, epoch: 14\n",
            "=====Epoch 15\n",
            "Training...\n",
            "loss_dist 0.148, loss_coords 0.079, loss_res 0.533, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.54it/s]\n",
            "Epoch 15, valid_edge_mae: 0.08678, Train_mae: 0.04827, Validation_mae: 0.06001, Validation_rmsd: 0.15713, res_acc: 0.74, kl_x: 0.00, kl_h: 0.00, elapse: 29.25100\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.13679602901186202, epoch: 14\n",
            "Best validation rec acc so far: 0.739270806312561, epoch: 15\n",
            "=====Epoch 16\n",
            "Training...\n",
            "loss_dist 0.139, loss_coords 0.088, loss_res 0.635, : 100% 32/32 [00:24<00:00,  1.33it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.44it/s]\n",
            "Epoch 16, valid_edge_mae: 0.15936, Train_mae: 0.05721, Validation_mae: 0.11296, Validation_rmsd: 0.26339, res_acc: 0.65, kl_x: 0.00, kl_h: 0.00, elapse: 28.95030\n",
            "Best validation RMSD so far: 0.13679602901186202, epoch: 14\n",
            "Best validation rec acc so far: 0.739270806312561, epoch: 15\n",
            "=====Epoch 17\n",
            "Training...\n",
            "loss_dist 0.077, loss_coords 0.056, loss_res 0.496, : 100% 32/32 [00:24<00:00,  1.33it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.55it/s]\n",
            "Epoch 17, valid_edge_mae: 0.08261, Train_mae: 0.07518, Validation_mae: 0.05231, Validation_rmsd: 0.15537, res_acc: 0.77, kl_x: 0.00, kl_h: 0.00, elapse: 28.59285\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.13679602901186202, epoch: 14\n",
            "Best validation rec acc so far: 0.7708680629730225, epoch: 17\n",
            "=====Epoch 18\n",
            "Training...\n",
            "loss_dist 0.089, loss_coords 0.054, loss_res 0.433, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 18, valid_edge_mae: 0.07890, Train_mae: 0.05228, Validation_mae: 0.04929, Validation_rmsd: 0.13359, res_acc: 0.77, kl_x: 0.00, kl_h: 0.00, elapse: 29.23473\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.1335883545364354, epoch: 18\n",
            "Best validation rec acc so far: 0.77322918176651, epoch: 18\n",
            "=====Epoch 19\n",
            "Training...\n",
            "loss_dist 0.093, loss_coords 0.060, loss_res 0.449, : 100% 32/32 [00:24<00:00,  1.32it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.54it/s]\n",
            "Epoch 19, valid_edge_mae: 0.08507, Train_mae: 0.05563, Validation_mae: 0.05835, Validation_rmsd: 0.15420, res_acc: 0.80, kl_x: 0.00, kl_h: 0.00, elapse: 28.77689\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.1335883545364354, epoch: 18\n",
            "Best validation rec acc so far: 0.7950000166893005, epoch: 19\n",
            "=====Epoch 20\n",
            "Training...\n",
            "loss_dist 0.066, loss_coords 0.048, loss_res 0.449, : 100% 32/32 [00:24<00:00,  1.32it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 20, valid_edge_mae: 0.06670, Train_mae: 0.05271, Validation_mae: 0.04256, Validation_rmsd: 0.13047, res_acc: 0.79, kl_x: 0.00, kl_h: 0.00, elapse: 28.93629\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.13047413728766952, epoch: 20\n",
            "Best validation rec acc so far: 0.7950000166893005, epoch: 19\n",
            "=====Epoch 21\n",
            "Training...\n",
            "Iteration:   0% 0/32 [00:00<?, ?it/s]/content/drive/.shortcut-targets-by-id/1cPQ2fA-SRAPng-aTI1P8QDLacE-wxHcy/lattices/LatentLattice/train.py:135: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`). Consider using `matplotlib.pyplot.close()`.\n",
            "  fig = plt.figure()\n",
            "loss_dist 0.076, loss_coords 0.047, loss_res 0.426, : 100% 32/32 [00:24<00:00,  1.33it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 21, valid_edge_mae: 0.07533, Train_mae: 0.04777, Validation_mae: 0.04766, Validation_rmsd: 0.14037, res_acc: 0.79, kl_x: 0.00, kl_h: 0.00, elapse: 28.65492\n",
            "Best validation RMSD so far: 0.13047413728766952, epoch: 20\n",
            "Best validation rec acc so far: 0.7950000166893005, epoch: 19\n",
            "=====Epoch 22\n",
            "Training...\n",
            "loss_dist 0.064, loss_coords 0.056, loss_res 0.412, : 100% 32/32 [00:24<00:00,  1.31it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 22, valid_edge_mae: 0.05750, Train_mae: 0.04779, Validation_mae: 0.04467, Validation_rmsd: 0.12635, res_acc: 0.80, kl_x: 0.00, kl_h: 0.00, elapse: 29.01322\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.1263533978653287, epoch: 22\n",
            "Best validation rec acc so far: 0.8014236092567444, epoch: 22\n",
            "=====Epoch 23\n",
            "Training...\n",
            "loss_dist 0.074, loss_coords 0.043, loss_res 0.376, : 100% 32/32 [00:24<00:00,  1.31it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.55it/s]\n",
            "Epoch 23, valid_edge_mae: 0.07485, Train_mae: 0.04623, Validation_mae: 0.04905, Validation_rmsd: 0.11766, res_acc: 0.81, kl_x: 0.00, kl_h: 0.00, elapse: 29.08511\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.117661090665603, epoch: 23\n",
            "Best validation rec acc so far: 0.8073611259460449, epoch: 23\n",
            "=====Epoch 24\n",
            "Training...\n",
            "loss_dist 0.057, loss_coords 0.037, loss_res 0.383, : 100% 32/32 [00:24<00:00,  1.32it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 24, valid_edge_mae: 0.05284, Train_mae: 0.04615, Validation_mae: 0.03520, Validation_rmsd: 0.10799, res_acc: 0.81, kl_x: 0.00, kl_h: 0.00, elapse: 28.80663\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.10799194485837708, epoch: 24\n",
            "Best validation rec acc so far: 0.8111110925674438, epoch: 24\n",
            "=====Epoch 25\n",
            "Training...\n",
            "loss_dist 0.061, loss_coords 0.036, loss_res 0.392, : 100% 32/32 [00:24<00:00,  1.31it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.54it/s]\n",
            "Epoch 25, valid_edge_mae: 0.04992, Train_mae: 0.03571, Validation_mae: 0.03222, Validation_rmsd: 0.10386, res_acc: 0.80, kl_x: 0.00, kl_h: 0.00, elapse: 28.94780\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.10386147682931403, epoch: 25\n",
            "Best validation rec acc so far: 0.8111110925674438, epoch: 24\n",
            "=====Epoch 26\n",
            "Training...\n",
            "loss_dist 0.050, loss_coords 0.033, loss_res 0.359, : 100% 32/32 [00:24<00:00,  1.33it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 26, valid_edge_mae: 0.05042, Train_mae: 0.04465, Validation_mae: 0.03211, Validation_rmsd: 0.10630, res_acc: 0.81, kl_x: 0.00, kl_h: 0.00, elapse: 28.74948\n",
            "Best validation RMSD so far: 0.10386147682931403, epoch: 25\n",
            "Best validation rec acc so far: 0.8111110925674438, epoch: 24\n",
            "=====Epoch 27\n",
            "Training...\n",
            "loss_dist 0.046, loss_coords 0.032, loss_res 0.356, : 100% 32/32 [00:24<00:00,  1.31it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.54it/s]\n",
            "Epoch 27, valid_edge_mae: 0.04714, Train_mae: 0.03558, Validation_mae: 0.03110, Validation_rmsd: 0.09900, res_acc: 0.82, kl_x: 0.00, kl_h: 0.00, elapse: 28.92899\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.0990008660315414, epoch: 27\n",
            "Best validation rec acc so far: 0.8216319680213928, epoch: 27\n",
            "=====Epoch 28\n",
            "Training...\n",
            "loss_dist 0.042, loss_coords 0.028, loss_res 0.373, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.52it/s]\n",
            "Epoch 28, valid_edge_mae: 0.04236, Train_mae: 0.03303, Validation_mae: 0.02852, Validation_rmsd: 0.08915, res_acc: 0.83, kl_x: 0.00, kl_h: 0.00, elapse: 29.33793\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.08914798287799197, epoch: 28\n",
            "Best validation rec acc so far: 0.8271874785423279, epoch: 28\n",
            "=====Epoch 29\n",
            "Training...\n",
            "loss_dist 0.056, loss_coords 0.038, loss_res 0.363, : 100% 32/32 [00:24<00:00,  1.33it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 29, valid_edge_mae: 0.05199, Train_mae: 0.04394, Validation_mae: 0.03456, Validation_rmsd: 0.09639, res_acc: 0.82, kl_x: 0.00, kl_h: 0.00, elapse: 28.68745\n",
            "Best validation RMSD so far: 0.08914798287799197, epoch: 28\n",
            "Best validation rec acc so far: 0.8271874785423279, epoch: 28\n",
            "=====Epoch 30\n",
            "Training...\n",
            "loss_dist 0.053, loss_coords 0.035, loss_res 0.375, : 100% 32/32 [00:24<00:00,  1.32it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.51it/s]\n",
            "Epoch 30, valid_edge_mae: 0.05235, Train_mae: 0.03536, Validation_mae: 0.03409, Validation_rmsd: 0.09547, res_acc: 0.81, kl_x: 0.00, kl_h: 0.00, elapse: 28.98633\n",
            "Best validation RMSD so far: 0.08914798287799197, epoch: 28\n",
            "Best validation rec acc so far: 0.8271874785423279, epoch: 28\n",
            "=====Epoch 31\n",
            "Training...\n",
            "loss_dist 0.047, loss_coords 0.035, loss_res 0.309, : 100% 32/32 [00:24<00:00,  1.31it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.52it/s]\n",
            "Epoch 31, valid_edge_mae: 0.04502, Train_mae: 0.03553, Validation_mae: 0.03064, Validation_rmsd: 0.08727, res_acc: 0.83, kl_x: 0.00, kl_h: 0.00, elapse: 29.11576\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.08727166619367782, epoch: 31\n",
            "Best validation rec acc so far: 0.8271874785423279, epoch: 28\n",
            "=====Epoch 32\n",
            "Training...\n",
            "loss_dist 0.064, loss_coords 0.040, loss_res 0.323, : 100% 32/32 [00:24<00:00,  1.31it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.54it/s]\n",
            "Epoch 32, valid_edge_mae: 0.06573, Train_mae: 0.03469, Validation_mae: 0.03978, Validation_rmsd: 0.11043, res_acc: 0.83, kl_x: 0.00, kl_h: 0.00, elapse: 28.94344\n",
            "Best validation RMSD so far: 0.08727166619367782, epoch: 31\n",
            "Best validation rec acc so far: 0.8271874785423279, epoch: 28\n",
            "=====Epoch 33\n",
            "Training...\n",
            "loss_dist 0.154, loss_coords 0.096, loss_res 0.400, : 100% 32/32 [00:24<00:00,  1.33it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.43it/s]\n",
            "Epoch 33, valid_edge_mae: 0.11182, Train_mae: 0.05601, Validation_mae: 0.07587, Validation_rmsd: 0.18696, res_acc: 0.81, kl_x: 0.00, kl_h: 0.00, elapse: 29.06420\n",
            "Best validation RMSD so far: 0.08727166619367782, epoch: 31\n",
            "Best validation rec acc so far: 0.8271874785423279, epoch: 28\n",
            "=====Epoch 34\n",
            "Training...\n",
            "loss_dist 0.070, loss_coords 0.047, loss_res 0.346, : 100% 32/32 [00:24<00:00,  1.33it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 34, valid_edge_mae: 0.06478, Train_mae: 0.05346, Validation_mae: 0.04351, Validation_rmsd: 0.11346, res_acc: 0.84, kl_x: 0.00, kl_h: 0.00, elapse: 28.73080\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.08727166619367782, epoch: 31\n",
            "Best validation rec acc so far: 0.8394097089767456, epoch: 34\n",
            "=====Epoch 35\n",
            "Training...\n",
            "loss_dist 0.047, loss_coords 0.031, loss_res 0.288, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.52it/s]\n",
            "Epoch 35, valid_edge_mae: 0.04959, Train_mae: 0.04002, Validation_mae: 0.03224, Validation_rmsd: 0.09441, res_acc: 0.86, kl_x: 0.00, kl_h: 0.00, elapse: 29.32756\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.08727166619367782, epoch: 31\n",
            "Best validation rec acc so far: 0.8631250262260437, epoch: 35\n",
            "=====Epoch 36\n",
            "Training...\n",
            "loss_dist 0.103, loss_coords 0.057, loss_res 0.295, : 100% 32/32 [00:24<00:00,  1.32it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 36, valid_edge_mae: 0.09560, Train_mae: 0.03456, Validation_mae: 0.07203, Validation_rmsd: 0.15925, res_acc: 0.82, kl_x: 0.00, kl_h: 0.00, elapse: 28.82560\n",
            "Best validation RMSD so far: 0.08727166619367782, epoch: 31\n",
            "Best validation rec acc so far: 0.8631250262260437, epoch: 35\n",
            "=====Epoch 37\n",
            "Training...\n",
            "loss_dist 0.046, loss_coords 0.031, loss_res 0.273, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 37, valid_edge_mae: 0.05073, Train_mae: 0.04328, Validation_mae: 0.03400, Validation_rmsd: 0.09360, res_acc: 0.87, kl_x: 0.00, kl_h: 0.00, elapse: 29.14637\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.08727166619367782, epoch: 31\n",
            "Best validation rec acc so far: 0.8687499761581421, epoch: 37\n",
            "=====Epoch 38\n",
            "Training...\n",
            "loss_dist 0.047, loss_coords 0.033, loss_res 0.242, : 100% 32/32 [00:24<00:00,  1.33it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.54it/s]\n",
            "Epoch 38, valid_edge_mae: 0.05130, Train_mae: 0.03197, Validation_mae: 0.04140, Validation_rmsd: 0.09639, res_acc: 0.88, kl_x: 0.00, kl_h: 0.00, elapse: 28.63884\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.08727166619367782, epoch: 31\n",
            "Best validation rec acc so far: 0.8786805272102356, epoch: 38\n",
            "=====Epoch 39\n",
            "Training...\n",
            "loss_dist 0.050, loss_coords 0.033, loss_res 0.242, : 100% 32/32 [00:24<00:00,  1.31it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.54it/s]\n",
            "Epoch 39, valid_edge_mae: 0.05171, Train_mae: 0.02976, Validation_mae: 0.03198, Validation_rmsd: 0.08612, res_acc: 0.87, kl_x: 0.00, kl_h: 0.00, elapse: 28.95132\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.08612121156101324, epoch: 39\n",
            "Best validation rec acc so far: 0.8786805272102356, epoch: 38\n",
            "=====Epoch 40\n",
            "Training...\n",
            "loss_dist 0.114, loss_coords 0.063, loss_res 0.348, : 100% 32/32 [00:24<00:00,  1.33it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.42it/s]\n",
            "Epoch 40, valid_edge_mae: 0.10732, Train_mae: 0.03437, Validation_mae: 0.06614, Validation_rmsd: 0.16382, res_acc: 0.83, kl_x: 0.00, kl_h: 0.00, elapse: 29.03717\n",
            "Best validation RMSD so far: 0.08612121156101324, epoch: 39\n",
            "Best validation rec acc so far: 0.8786805272102356, epoch: 38\n",
            "=====Epoch 41\n",
            "Training...\n",
            "loss_dist 0.046, loss_coords 0.030, loss_res 0.219, : 100% 32/32 [00:24<00:00,  1.31it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.52it/s]\n",
            "Epoch 41, valid_edge_mae: 0.04380, Train_mae: 0.04592, Validation_mae: 0.03170, Validation_rmsd: 0.08994, res_acc: 0.88, kl_x: 0.00, kl_h: 0.00, elapse: 29.04915\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.08612121156101324, epoch: 39\n",
            "Best validation rec acc so far: 0.8843055367469788, epoch: 41\n",
            "=====Epoch 42\n",
            "Training...\n",
            "loss_dist 0.045, loss_coords 0.031, loss_res 0.199, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.52it/s]\n",
            "Epoch 42, valid_edge_mae: 0.04632, Train_mae: 0.02834, Validation_mae: 0.03061, Validation_rmsd: 0.08859, res_acc: 0.90, kl_x: 0.00, kl_h: 0.00, elapse: 29.16237\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.08612121156101324, epoch: 39\n",
            "Best validation rec acc so far: 0.9033680558204651, epoch: 42\n",
            "=====Epoch 43\n",
            "Training...\n",
            "loss_dist 0.054, loss_coords 0.036, loss_res 0.174, : 100% 32/32 [00:24<00:00,  1.33it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 43, valid_edge_mae: 0.05984, Train_mae: 0.03642, Validation_mae: 0.03825, Validation_rmsd: 0.11114, res_acc: 0.91, kl_x: 0.00, kl_h: 0.00, elapse: 28.75472\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.08612121156101324, epoch: 39\n",
            "Best validation rec acc so far: 0.9063541889190674, epoch: 43\n",
            "=====Epoch 44\n",
            "Training...\n",
            "loss_dist 0.085, loss_coords 0.052, loss_res 0.284, : 100% 32/32 [00:24<00:00,  1.32it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.55it/s]\n",
            "Epoch 44, valid_edge_mae: 0.08284, Train_mae: 0.03554, Validation_mae: 0.04758, Validation_rmsd: 0.14826, res_acc: 0.88, kl_x: 0.00, kl_h: 0.00, elapse: 28.87405\n",
            "Best validation RMSD so far: 0.08612121156101324, epoch: 39\n",
            "Best validation rec acc so far: 0.9063541889190674, epoch: 43\n",
            "=====Epoch 45\n",
            "Training...\n",
            "loss_dist 0.046, loss_coords 0.031, loss_res 0.189, : 100% 32/32 [00:24<00:00,  1.32it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 45, valid_edge_mae: 0.04639, Train_mae: 0.03450, Validation_mae: 0.02978, Validation_rmsd: 0.08671, res_acc: 0.91, kl_x: 0.00, kl_h: 0.00, elapse: 28.76680\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.08612121156101324, epoch: 39\n",
            "Best validation rec acc so far: 0.9092708230018616, epoch: 45\n",
            "=====Epoch 46\n",
            "Training...\n",
            "loss_dist 0.038, loss_coords 0.025, loss_res 0.134, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 46, valid_edge_mae: 0.03821, Train_mae: 0.02817, Validation_mae: 0.02580, Validation_rmsd: 0.07772, res_acc: 0.93, kl_x: 0.00, kl_h: 0.00, elapse: 29.19006\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.07772404335213402, epoch: 46\n",
            "Best validation rec acc so far: 0.9253125190734863, epoch: 46\n",
            "=====Epoch 47\n",
            "Training...\n",
            "loss_dist 0.045, loss_coords 0.029, loss_res 0.104, : 100% 32/32 [00:24<00:00,  1.31it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.55it/s]\n",
            "Epoch 47, valid_edge_mae: 0.05021, Train_mae: 0.03477, Validation_mae: 0.03228, Validation_rmsd: 0.08274, res_acc: 0.94, kl_x: 0.00, kl_h: 0.00, elapse: 28.95027\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.07772404335213402, epoch: 46\n",
            "Best validation rec acc so far: 0.9374305605888367, epoch: 47\n",
            "=====Epoch 48\n",
            "Training...\n",
            "loss_dist 0.051, loss_coords 0.030, loss_res 0.096, : 100% 32/32 [00:24<00:00,  1.32it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.52it/s]\n",
            "Epoch 48, valid_edge_mae: 0.05639, Train_mae: 0.03387, Validation_mae: 0.04215, Validation_rmsd: 0.10696, res_acc: 0.94, kl_x: 0.00, kl_h: 0.00, elapse: 28.81398\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.07772404335213402, epoch: 46\n",
            "Best validation rec acc so far: 0.9434027671813965, epoch: 48\n",
            "=====Epoch 49\n",
            "Training...\n",
            "loss_dist 0.045, loss_coords 0.029, loss_res 0.077, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 49, valid_edge_mae: 0.04331, Train_mae: 0.03129, Validation_mae: 0.02823, Validation_rmsd: 0.07778, res_acc: 0.97, kl_x: 0.00, kl_h: 0.00, elapse: 29.16592\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.07772404335213402, epoch: 46\n",
            "Best validation rec acc so far: 0.9669444561004639, epoch: 49\n",
            "=====Epoch 50\n",
            "Training...\n",
            "loss_dist 0.198, loss_coords 0.130, loss_res 0.615, : 100% 32/32 [00:24<00:00,  1.32it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.52it/s]\n",
            "Epoch 50, valid_edge_mae: 0.21061, Train_mae: 0.12596, Validation_mae: 0.13488, Validation_rmsd: 0.30688, res_acc: 0.67, kl_x: 0.00, kl_h: 0.00, elapse: 28.87764\n",
            "Best validation RMSD so far: 0.07772404335213402, epoch: 46\n",
            "Best validation rec acc so far: 0.9669444561004639, epoch: 49\n",
            "=====Epoch 51\n",
            "Training...\n",
            "loss_dist 0.083, loss_coords 0.055, loss_res 0.478, : 100% 32/32 [00:24<00:00,  1.31it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.54it/s]\n",
            "Epoch 51, valid_edge_mae: 0.07879, Train_mae: 0.08469, Validation_mae: 0.05119, Validation_rmsd: 0.13804, res_acc: 0.78, kl_x: 0.00, kl_h: 0.00, elapse: 29.04309\n",
            "Best validation RMSD so far: 0.07772404335213402, epoch: 46\n",
            "Best validation rec acc so far: 0.9669444561004639, epoch: 49\n",
            "=====Epoch 52\n",
            "Training...\n",
            "loss_dist 0.059, loss_coords 0.038, loss_res 0.457, : 100% 32/32 [00:23<00:00,  1.33it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.51it/s]\n",
            "Epoch 52, valid_edge_mae: 0.05986, Train_mae: 0.04279, Validation_mae: 0.03860, Validation_rmsd: 0.10238, res_acc: 0.80, kl_x: 0.00, kl_h: 0.00, elapse: 28.65838\n",
            "Best validation RMSD so far: 0.07772404335213402, epoch: 46\n",
            "Best validation rec acc so far: 0.9669444561004639, epoch: 49\n",
            "=====Epoch 53\n",
            "Training...\n",
            "loss_dist 0.059, loss_coords 0.037, loss_res 0.352, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.52it/s]\n",
            "Epoch 53, valid_edge_mae: 0.05056, Train_mae: 0.03566, Validation_mae: 0.03197, Validation_rmsd: 0.09599, res_acc: 0.86, kl_x: 0.00, kl_h: 0.00, elapse: 29.32363\n",
            "Best validation RMSD so far: 0.07772404335213402, epoch: 46\n",
            "Best validation rec acc so far: 0.9669444561004639, epoch: 49\n",
            "=====Epoch 54\n",
            "Training...\n",
            "loss_dist 0.042, loss_coords 0.028, loss_res 0.324, : 100% 32/32 [00:24<00:00,  1.32it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.44it/s]\n",
            "Epoch 54, valid_edge_mae: 0.04377, Train_mae: 0.03587, Validation_mae: 0.03124, Validation_rmsd: 0.09431, res_acc: 0.86, kl_x: 0.00, kl_h: 0.00, elapse: 29.12263\n",
            "Best validation RMSD so far: 0.07772404335213402, epoch: 46\n",
            "Best validation rec acc so far: 0.9669444561004639, epoch: 49\n",
            "=====Epoch 55\n",
            "Training...\n",
            "loss_dist 0.042, loss_coords 0.026, loss_res 0.240, : 100% 32/32 [00:24<00:00,  1.33it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.52it/s]\n",
            "Epoch 55, valid_edge_mae: 0.03954, Train_mae: 0.02895, Validation_mae: 0.02660, Validation_rmsd: 0.08630, res_acc: 0.87, kl_x: 0.00, kl_h: 0.00, elapse: 28.75091\n",
            "Best validation RMSD so far: 0.07772404335213402, epoch: 46\n",
            "Best validation rec acc so far: 0.9669444561004639, epoch: 49\n",
            "=====Epoch 56\n",
            "Training...\n",
            "loss_dist 0.055, loss_coords 0.035, loss_res 0.270, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.55it/s]\n",
            "Epoch 56, valid_edge_mae: 0.05757, Train_mae: 0.03098, Validation_mae: 0.03447, Validation_rmsd: 0.09539, res_acc: 0.86, kl_x: 0.00, kl_h: 0.00, elapse: 29.08770\n",
            "Best validation RMSD so far: 0.07772404335213402, epoch: 46\n",
            "Best validation rec acc so far: 0.9669444561004639, epoch: 49\n",
            "=====Epoch 57\n",
            "Training...\n",
            "loss_dist 0.036, loss_coords 0.023, loss_res 0.211, : 100% 32/32 [00:23<00:00,  1.33it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 57, valid_edge_mae: 0.04144, Train_mae: 0.02928, Validation_mae: 0.02518, Validation_rmsd: 0.08198, res_acc: 0.89, kl_x: 0.00, kl_h: 0.00, elapse: 28.60364\n",
            "Best validation RMSD so far: 0.07772404335213402, epoch: 46\n",
            "Best validation rec acc so far: 0.9669444561004639, epoch: 49\n",
            "=====Epoch 58\n",
            "Training...\n",
            "loss_dist 0.056, loss_coords 0.036, loss_res 0.258, : 100% 32/32 [00:24<00:00,  1.31it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.54it/s]\n",
            "Epoch 58, valid_edge_mae: 0.05280, Train_mae: 0.03855, Validation_mae: 0.03372, Validation_rmsd: 0.09601, res_acc: 0.88, kl_x: 0.00, kl_h: 0.00, elapse: 29.01907\n",
            "Best validation RMSD so far: 0.07772404335213402, epoch: 46\n",
            "Best validation rec acc so far: 0.9669444561004639, epoch: 49\n",
            "=====Epoch 59\n",
            "Training...\n",
            "loss_dist 0.038, loss_coords 0.024, loss_res 0.195, : 100% 32/32 [00:24<00:00,  1.33it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.55it/s]\n",
            "Epoch 59, valid_edge_mae: 0.03908, Train_mae: 0.02830, Validation_mae: 0.02502, Validation_rmsd: 0.07885, res_acc: 0.89, kl_x: 0.00, kl_h: 0.00, elapse: 28.61748\n",
            "Best validation RMSD so far: 0.07772404335213402, epoch: 46\n",
            "Best validation rec acc so far: 0.9669444561004639, epoch: 49\n",
            "=====Epoch 60\n",
            "Training...\n",
            "loss_dist 0.048, loss_coords 0.036, loss_res 0.212, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.52it/s]\n",
            "Epoch 60, valid_edge_mae: 0.05850, Train_mae: 0.03001, Validation_mae: 0.03327, Validation_rmsd: 0.08979, res_acc: 0.91, kl_x: 0.00, kl_h: 0.00, elapse: 29.17375\n",
            "Best validation RMSD so far: 0.07772404335213402, epoch: 46\n",
            "Best validation rec acc so far: 0.9669444561004639, epoch: 49\n",
            "=====Epoch 61\n",
            "Training...\n",
            "loss_dist 0.043, loss_coords 0.026, loss_res 0.170, : 100% 32/32 [00:24<00:00,  1.33it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.54it/s]\n",
            "Epoch 61, valid_edge_mae: 0.04319, Train_mae: 0.02965, Validation_mae: 0.02692, Validation_rmsd: 0.08071, res_acc: 0.83, kl_x: 0.00, kl_h: 0.00, elapse: 28.62627\n",
            "Best validation RMSD so far: 0.07772404335213402, epoch: 46\n",
            "Best validation rec acc so far: 0.9669444561004639, epoch: 49\n",
            "=====Epoch 62\n",
            "Training...\n",
            "loss_dist 0.052, loss_coords 0.033, loss_res 0.183, : 100% 32/32 [00:24<00:00,  1.31it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 62, valid_edge_mae: 0.05192, Train_mae: 0.04268, Validation_mae: 0.03349, Validation_rmsd: 0.09366, res_acc: 0.91, kl_x: 0.00, kl_h: 0.00, elapse: 29.00337\n",
            "Best validation RMSD so far: 0.07772404335213402, epoch: 46\n",
            "Best validation rec acc so far: 0.9669444561004639, epoch: 49\n",
            "=====Epoch 63\n",
            "Training...\n",
            "loss_dist 0.047, loss_coords 0.029, loss_res 0.121, : 100% 32/32 [00:24<00:00,  1.33it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:05<00:00,  1.39it/s]\n",
            "Epoch 63, valid_edge_mae: 0.04444, Train_mae: 0.03050, Validation_mae: 0.03341, Validation_rmsd: 0.08505, res_acc: 0.92, kl_x: 0.00, kl_h: 0.00, elapse: 29.18436\n",
            "Best validation RMSD so far: 0.07772404335213402, epoch: 46\n",
            "Best validation rec acc so far: 0.9669444561004639, epoch: 49\n",
            "=====Epoch 64\n",
            "Training...\n",
            "loss_dist 0.066, loss_coords 0.042, loss_res 0.122, : 100% 32/32 [00:24<00:00,  1.32it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.52it/s]\n",
            "Epoch 64, valid_edge_mae: 0.06845, Train_mae: 0.03686, Validation_mae: 0.04497, Validation_rmsd: 0.10376, res_acc: 0.95, kl_x: 0.00, kl_h: 0.00, elapse: 28.86769\n",
            "Best validation RMSD so far: 0.07772404335213402, epoch: 46\n",
            "Best validation rec acc so far: 0.9669444561004639, epoch: 49\n",
            "=====Epoch 65\n",
            "Training...\n",
            "loss_dist 0.039, loss_coords 0.025, loss_res 0.112, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 65, valid_edge_mae: 0.04088, Train_mae: 0.03056, Validation_mae: 0.02881, Validation_rmsd: 0.07789, res_acc: 0.94, kl_x: 0.00, kl_h: 0.00, elapse: 29.32086\n",
            "Best validation RMSD so far: 0.07772404335213402, epoch: 46\n",
            "Best validation rec acc so far: 0.9669444561004639, epoch: 49\n",
            "=====Epoch 66\n",
            "Training...\n",
            "loss_dist 0.045, loss_coords 0.029, loss_res 0.110, : 100% 32/32 [00:24<00:00,  1.32it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.52it/s]\n",
            "Epoch 66, valid_edge_mae: 0.04479, Train_mae: 0.02883, Validation_mae: 0.03234, Validation_rmsd: 0.07826, res_acc: 0.95, kl_x: 0.00, kl_h: 0.00, elapse: 28.88326\n",
            "Best validation RMSD so far: 0.07772404335213402, epoch: 46\n",
            "Best validation rec acc so far: 0.9669444561004639, epoch: 49\n",
            "=====Epoch 67\n",
            "Training...\n",
            "loss_dist 0.036, loss_coords 0.023, loss_res 0.059, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.54it/s]\n",
            "Epoch 67, valid_edge_mae: 0.04411, Train_mae: 0.02696, Validation_mae: 0.02734, Validation_rmsd: 0.07831, res_acc: 0.97, kl_x: 0.00, kl_h: 0.00, elapse: 29.11507\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.07772404335213402, epoch: 46\n",
            "Best validation rec acc so far: 0.96875, epoch: 67\n",
            "=====Epoch 68\n",
            "Training...\n",
            "loss_dist 0.078, loss_coords 0.051, loss_res 0.441, : 100% 32/32 [00:24<00:00,  1.32it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 68, valid_edge_mae: 0.05081, Train_mae: 0.02553, Validation_mae: 0.03341, Validation_rmsd: 0.08517, res_acc: 0.83, kl_x: 0.00, kl_h: 0.00, elapse: 28.79103\n",
            "Best validation RMSD so far: 0.07772404335213402, epoch: 46\n",
            "Best validation rec acc so far: 0.96875, epoch: 67\n",
            "=====Epoch 69\n",
            "Training...\n",
            "loss_dist 0.056, loss_coords 0.036, loss_res 0.135, : 100% 32/32 [00:24<00:00,  1.31it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.52it/s]\n",
            "Epoch 69, valid_edge_mae: 0.04984, Train_mae: 0.04635, Validation_mae: 0.03369, Validation_rmsd: 0.08806, res_acc: 0.95, kl_x: 0.00, kl_h: 0.00, elapse: 29.07288\n",
            "Best validation RMSD so far: 0.07772404335213402, epoch: 46\n",
            "Best validation rec acc so far: 0.96875, epoch: 67\n",
            "=====Epoch 70\n",
            "Training...\n",
            "loss_dist 0.035, loss_coords 0.023, loss_res 0.040, : 100% 32/32 [00:24<00:00,  1.33it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 70, valid_edge_mae: 0.03567, Train_mae: 0.02766, Validation_mae: 0.02339, Validation_rmsd: 0.07094, res_acc: 0.98, kl_x: 0.00, kl_h: 0.00, elapse: 28.73173\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.07094202664616377, epoch: 70\n",
            "Best validation rec acc so far: 0.97635418176651, epoch: 70\n",
            "=====Epoch 71\n",
            "Training...\n",
            "loss_dist 0.034, loss_coords 0.025, loss_res 0.051, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 71, valid_edge_mae: 0.03990, Train_mae: 0.02303, Validation_mae: 0.02537, Validation_rmsd: 0.06854, res_acc: 0.98, kl_x: 0.00, kl_h: 0.00, elapse: 29.18616\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.06853780909603385, epoch: 71\n",
            "Best validation rec acc so far: 0.980347216129303, epoch: 71\n",
            "=====Epoch 72\n",
            "Training...\n",
            "loss_dist 0.034, loss_coords 0.022, loss_res 0.030, : 100% 32/32 [00:24<00:00,  1.33it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.44it/s]\n",
            "Epoch 72, valid_edge_mae: 0.03171, Train_mae: 0.02329, Validation_mae: 0.02461, Validation_rmsd: 0.06420, res_acc: 0.98, kl_x: 0.00, kl_h: 0.00, elapse: 29.03713\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.06419962113325604, epoch: 72\n",
            "Best validation rec acc so far: 0.980347216129303, epoch: 71\n",
            "=====Epoch 73\n",
            "Training...\n",
            "loss_dist 0.058, loss_coords 0.032, loss_res 0.027, : 100% 32/32 [00:24<00:00,  1.33it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 73, valid_edge_mae: 0.04048, Train_mae: 0.02640, Validation_mae: 0.03237, Validation_rmsd: 0.07725, res_acc: 0.99, kl_x: 0.00, kl_h: 0.00, elapse: 28.64036\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.06419962113325604, epoch: 72\n",
            "Best validation rec acc so far: 0.9886805415153503, epoch: 73\n",
            "=====Epoch 74\n",
            "Training...\n",
            "loss_dist 0.072, loss_coords 0.045, loss_res 0.230, : 100% 32/32 [00:24<00:00,  1.31it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 74, valid_edge_mae: 0.05233, Train_mae: 0.03398, Validation_mae: 0.04124, Validation_rmsd: 0.09360, res_acc: 0.94, kl_x: 0.00, kl_h: 0.00, elapse: 29.04324\n",
            "Best validation RMSD so far: 0.06419962113325604, epoch: 72\n",
            "Best validation rec acc so far: 0.9886805415153503, epoch: 73\n",
            "=====Epoch 75\n",
            "Training...\n",
            "loss_dist 0.039, loss_coords 0.026, loss_res 0.038, : 100% 32/32 [00:24<00:00,  1.33it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.54it/s]\n",
            "Epoch 75, valid_edge_mae: 0.03918, Train_mae: 0.03479, Validation_mae: 0.02579, Validation_rmsd: 0.07089, res_acc: 0.98, kl_x: 0.00, kl_h: 0.00, elapse: 28.72955\n",
            "Best validation RMSD so far: 0.06419962113325604, epoch: 72\n",
            "Best validation rec acc so far: 0.9886805415153503, epoch: 73\n",
            "=====Epoch 76\n",
            "Training...\n",
            "loss_dist 0.030, loss_coords 0.020, loss_res 0.029, : 100% 32/32 [00:24<00:00,  1.31it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.54it/s]\n",
            "Epoch 76, valid_edge_mae: 0.02985, Train_mae: 0.02273, Validation_mae: 0.01973, Validation_rmsd: 0.06073, res_acc: 0.99, kl_x: 0.00, kl_h: 0.00, elapse: 29.03976\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.06072650103883431, epoch: 76\n",
            "Best validation rec acc so far: 0.9886805415153503, epoch: 73\n",
            "=====Epoch 77\n",
            "Training...\n",
            "loss_dist 0.044, loss_coords 0.027, loss_res 0.014, : 100% 32/32 [00:24<00:00,  1.33it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.54it/s]\n",
            "Epoch 77, valid_edge_mae: 0.03014, Train_mae: 0.02057, Validation_mae: 0.02002, Validation_rmsd: 0.05956, res_acc: 0.99, kl_x: 0.00, kl_h: 0.00, elapse: 28.67250\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.059555894574959876, epoch: 77\n",
            "Best validation rec acc so far: 0.9896180629730225, epoch: 77\n",
            "=====Epoch 78\n",
            "Training...\n",
            "loss_dist 0.034, loss_coords 0.021, loss_res 0.021, : 100% 32/32 [00:24<00:00,  1.31it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.54it/s]\n",
            "Epoch 78, valid_edge_mae: 0.03610, Train_mae: 0.01987, Validation_mae: 0.02115, Validation_rmsd: 0.06110, res_acc: 0.99, kl_x: 0.00, kl_h: 0.00, elapse: 29.07944\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.059555894574959876, epoch: 77\n",
            "Best validation rec acc so far: 0.9907639026641846, epoch: 78\n",
            "=====Epoch 79\n",
            "Training...\n",
            "loss_dist 0.072, loss_coords 0.070, loss_res 0.364, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.54it/s]\n",
            "Epoch 79, valid_edge_mae: 0.23348, Train_mae: 0.02865, Validation_mae: 0.15280, Validation_rmsd: 0.39168, res_acc: 0.88, kl_x: 0.00, kl_h: 0.00, elapse: 29.15818\n",
            "Best validation RMSD so far: 0.059555894574959876, epoch: 77\n",
            "Best validation rec acc so far: 0.9907639026641846, epoch: 78\n",
            "=====Epoch 80\n",
            "Training...\n",
            "loss_dist 0.047, loss_coords 0.030, loss_res 0.093, : 100% 32/32 [00:24<00:00,  1.33it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 80, valid_edge_mae: 0.04832, Train_mae: 0.05732, Validation_mae: 0.03192, Validation_rmsd: 0.08150, res_acc: 0.96, kl_x: 0.00, kl_h: 0.00, elapse: 28.64601\n",
            "Best validation RMSD so far: 0.059555894574959876, epoch: 77\n",
            "Best validation rec acc so far: 0.9907639026641846, epoch: 78\n",
            "=====Epoch 81\n",
            "Training...\n",
            "loss_dist 0.031, loss_coords 0.021, loss_res 0.039, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.52it/s]\n",
            "Epoch 81, valid_edge_mae: 0.03193, Train_mae: 0.02472, Validation_mae: 0.02218, Validation_rmsd: 0.06394, res_acc: 0.98, kl_x: 0.00, kl_h: 0.00, elapse: 29.20351\n",
            "Best validation RMSD so far: 0.059555894574959876, epoch: 77\n",
            "Best validation rec acc so far: 0.9907639026641846, epoch: 78\n",
            "=====Epoch 82\n",
            "Training...\n",
            "loss_dist 0.033, loss_coords 0.021, loss_res 0.024, : 100% 32/32 [00:24<00:00,  1.33it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 82, valid_edge_mae: 0.03213, Train_mae: 0.02017, Validation_mae: 0.02106, Validation_rmsd: 0.05810, res_acc: 0.98, kl_x: 0.00, kl_h: 0.00, elapse: 28.70336\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.05810262247129911, epoch: 82\n",
            "Best validation rec acc so far: 0.9907639026641846, epoch: 78\n",
            "=====Epoch 83\n",
            "Training...\n",
            "loss_dist 0.033, loss_coords 0.022, loss_res 0.029, : 100% 32/32 [00:24<00:00,  1.31it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.52it/s]\n",
            "Epoch 83, valid_edge_mae: 0.03445, Train_mae: 0.02298, Validation_mae: 0.02219, Validation_rmsd: 0.06140, res_acc: 0.99, kl_x: 0.00, kl_h: 0.00, elapse: 29.10230\n",
            "Best validation RMSD so far: 0.05810262247129911, epoch: 82\n",
            "Best validation rec acc so far: 0.9907639026641846, epoch: 78\n",
            "=====Epoch 84\n",
            "Training...\n",
            "loss_dist 0.029, loss_coords 0.019, loss_res 0.012, : 100% 32/32 [00:24<00:00,  1.32it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.51it/s]\n",
            "Epoch 84, valid_edge_mae: 0.03242, Train_mae: 0.02242, Validation_mae: 0.02212, Validation_rmsd: 0.06041, res_acc: 0.99, kl_x: 0.00, kl_h: 0.00, elapse: 28.90828\n",
            "Best validation RMSD so far: 0.05810262247129911, epoch: 82\n",
            "Best validation rec acc so far: 0.9907639026641846, epoch: 78\n",
            "=====Epoch 85\n",
            "Training...\n",
            "loss_dist 0.023, loss_coords 0.016, loss_res 0.015, : 100% 32/32 [00:24<00:00,  1.31it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 85, valid_edge_mae: 0.02501, Train_mae: 0.01854, Validation_mae: 0.01680, Validation_rmsd: 0.05485, res_acc: 0.99, kl_x: 0.00, kl_h: 0.00, elapse: 29.02534\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.05485267067212325, epoch: 85\n",
            "Best validation rec acc so far: 0.9926736354827881, epoch: 85\n",
            "=====Epoch 86\n",
            "Training...\n",
            "loss_dist 0.027, loss_coords 0.019, loss_res 0.012, : 100% 32/32 [00:24<00:00,  1.33it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.42it/s]\n",
            "Epoch 86, valid_edge_mae: 0.02781, Train_mae: 0.01915, Validation_mae: 0.01810, Validation_rmsd: 0.05084, res_acc: 0.96, kl_x: 0.00, kl_h: 0.00, elapse: 29.10385\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.05083885116499729, epoch: 86\n",
            "Best validation rec acc so far: 0.9926736354827881, epoch: 85\n",
            "=====Epoch 87\n",
            "Training...\n",
            "loss_dist 0.042, loss_coords 0.030, loss_res 0.039, : 100% 32/32 [00:24<00:00,  1.33it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.52it/s]\n",
            "Epoch 87, valid_edge_mae: 0.04038, Train_mae: 0.03330, Validation_mae: 0.02745, Validation_rmsd: 0.07218, res_acc: 0.98, kl_x: 0.00, kl_h: 0.00, elapse: 28.74510\n",
            "Best validation RMSD so far: 0.05083885116499729, epoch: 86\n",
            "Best validation rec acc so far: 0.9926736354827881, epoch: 85\n",
            "=====Epoch 88\n",
            "Training...\n",
            "loss_dist 0.024, loss_coords 0.016, loss_res 0.018, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 88, valid_edge_mae: 0.02627, Train_mae: 0.02175, Validation_mae: 0.01800, Validation_rmsd: 0.05360, res_acc: 0.99, kl_x: 0.00, kl_h: 0.00, elapse: 29.24394\n",
            "Best validation RMSD so far: 0.05083885116499729, epoch: 86\n",
            "Best validation rec acc so far: 0.9926736354827881, epoch: 85\n",
            "=====Epoch 89\n",
            "Training...\n",
            "loss_dist 0.043, loss_coords 0.028, loss_res 0.081, : 100% 32/32 [00:24<00:00,  1.32it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 89, valid_edge_mae: 0.07243, Train_mae: 0.02089, Validation_mae: 0.04725, Validation_rmsd: 0.10317, res_acc: 0.93, kl_x: 0.00, kl_h: 0.00, elapse: 28.86712\n",
            "Best validation RMSD so far: 0.05083885116499729, epoch: 86\n",
            "Best validation rec acc so far: 0.9926736354827881, epoch: 85\n",
            "=====Epoch 90\n",
            "Training...\n",
            "loss_dist 0.041, loss_coords 0.027, loss_res 0.028, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.52it/s]\n",
            "Epoch 90, valid_edge_mae: 0.03954, Train_mae: 0.04272, Validation_mae: 0.02590, Validation_rmsd: 0.06780, res_acc: 0.99, kl_x: 0.00, kl_h: 0.00, elapse: 29.31228\n",
            "Best validation RMSD so far: 0.05083885116499729, epoch: 86\n",
            "Best validation rec acc so far: 0.9926736354827881, epoch: 85\n",
            "=====Epoch 91\n",
            "Training...\n",
            "loss_dist 0.028, loss_coords 0.018, loss_res 0.020, : 100% 32/32 [00:24<00:00,  1.32it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 91, valid_edge_mae: 0.02532, Train_mae: 0.02116, Validation_mae: 0.01741, Validation_rmsd: 0.05251, res_acc: 0.99, kl_x: 0.00, kl_h: 0.00, elapse: 28.77931\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.05083885116499729, epoch: 86\n",
            "Best validation rec acc so far: 0.9928125143051147, epoch: 91\n",
            "=====Epoch 92\n",
            "Training...\n",
            "loss_dist 0.023, loss_coords 0.015, loss_res 0.014, : 100% 32/32 [00:24<00:00,  1.31it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 92, valid_edge_mae: 0.02285, Train_mae: 0.01624, Validation_mae: 0.01596, Validation_rmsd: 0.04836, res_acc: 0.99, kl_x: 0.00, kl_h: 0.00, elapse: 29.13963\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.04836417801761748, epoch: 92\n",
            "Best validation rec acc so far: 0.9935416579246521, epoch: 92\n",
            "=====Epoch 93\n",
            "Training...\n",
            "loss_dist 0.024, loss_coords 0.016, loss_res 0.013, : 100% 32/32 [00:24<00:00,  1.33it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 93, valid_edge_mae: 0.02321, Train_mae: 0.01579, Validation_mae: 0.01641, Validation_rmsd: 0.04496, res_acc: 0.99, kl_x: 0.00, kl_h: 0.00, elapse: 28.64078\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.04495611031386531, epoch: 93\n",
            "Best validation rec acc so far: 0.9937152862548828, epoch: 93\n",
            "=====Epoch 94\n",
            "Training...\n",
            "loss_dist 0.024, loss_coords 0.016, loss_res 0.012, : 100% 32/32 [00:24<00:00,  1.33it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 94, valid_edge_mae: 0.02490, Train_mae: 0.01546, Validation_mae: 0.01551, Validation_rmsd: 0.04354, res_acc: 0.99, kl_x: 0.00, kl_h: 0.00, elapse: 28.74946\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.04354320498125427, epoch: 94\n",
            "Best validation rec acc so far: 0.9940624833106995, epoch: 94\n",
            "=====Epoch 95\n",
            "Training...\n",
            "loss_dist 0.026, loss_coords 0.016, loss_res 0.013, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.51it/s]\n",
            "Epoch 95, valid_edge_mae: 0.02237, Train_mae: 0.01538, Validation_mae: 0.01441, Validation_rmsd: 0.04257, res_acc: 0.99, kl_x: 0.00, kl_h: 0.00, elapse: 29.23906\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.042574662871610706, epoch: 95\n",
            "Best validation rec acc so far: 0.9940624833106995, epoch: 94\n",
            "=====Epoch 96\n",
            "Training...\n",
            "loss_dist 0.020, loss_coords 0.013, loss_res 0.014, : 100% 32/32 [00:24<00:00,  1.31it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.52it/s]\n",
            "Epoch 96, valid_edge_mae: 0.02011, Train_mae: 0.01406, Validation_mae: 0.01270, Validation_rmsd: 0.03644, res_acc: 0.99, kl_x: 0.00, kl_h: 0.00, elapse: 28.99834\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.03644098845721869, epoch: 96\n",
            "Best validation rec acc so far: 0.9940624833106995, epoch: 94\n",
            "=====Epoch 97\n",
            "Training...\n",
            "loss_dist 0.017, loss_coords 0.012, loss_res 0.009, : 100% 32/32 [00:24<00:00,  1.29it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.51it/s]\n",
            "Epoch 97, valid_edge_mae: 0.01749, Train_mae: 0.01380, Validation_mae: 0.01160, Validation_rmsd: 0.03315, res_acc: 0.99, kl_x: 0.00, kl_h: 0.00, elapse: 29.50320\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.03314529147557937, epoch: 97\n",
            "Best validation rec acc so far: 0.9940624833106995, epoch: 94\n",
            "=====Epoch 98\n",
            "Training...\n",
            "loss_dist 0.017, loss_coords 0.011, loss_res 0.013, : 100% 32/32 [00:24<00:00,  1.31it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.51it/s]\n",
            "Epoch 98, valid_edge_mae: 0.01725, Train_mae: 0.01345, Validation_mae: 0.01417, Validation_rmsd: 0.03374, res_acc: 0.99, kl_x: 0.00, kl_h: 0.00, elapse: 29.17881\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.03314529147557937, epoch: 97\n",
            "Best validation rec acc so far: 0.9943403005599976, epoch: 98\n",
            "=====Epoch 99\n",
            "Training...\n",
            "loss_dist 0.022, loss_coords 0.018, loss_res 0.011, : 100% 32/32 [00:24<00:00,  1.29it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.51it/s]\n",
            "Epoch 99, valid_edge_mae: 0.03018, Train_mae: 0.01934, Validation_mae: 0.01892, Validation_rmsd: 0.04164, res_acc: 0.99, kl_x: 0.00, kl_h: 0.00, elapse: 29.47983\n",
            "Best validation RMSD so far: 0.03314529147557937, epoch: 97\n",
            "Best validation rec acc so far: 0.9943403005599976, epoch: 98\n",
            "=====Epoch 100\n",
            "Training...\n",
            "loss_dist 0.018, loss_coords 0.014, loss_res 0.005, : 100% 32/32 [00:24<00:00,  1.31it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.51it/s]\n",
            "Epoch 100, valid_edge_mae: 0.01709, Train_mae: 0.01511, Validation_mae: 0.01634, Validation_rmsd: 0.03471, res_acc: 0.99, kl_x: 0.00, kl_h: 0.00, elapse: 29.09326\n",
            "Best validation RMSD so far: 0.03314529147557937, epoch: 97\n",
            "Best validation rec acc so far: 0.9943403005599976, epoch: 98\n"
          ]
        }
      ],
      "source": [
        "! python LatentLattice/train.py --mp_steps 3 --batch_size 32 --layers 2 --edgeloss_weight 0.0 --epochs 100"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "kL6MhijCsEwW"
      },
      "source": [
        "Rectangle:"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "fhOqOpu3sEYp",
        "outputId": "697aa3b3-e00d-41ae-fe46-6b36b9474007"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Namespace(debug=True, mp_steps=3, emb_dim=32, layers=2, pooling=True, up_mlp=False, residual=True, noise=False, transpose=False, attn=False, loss='all', mode='train', lr_init=0.001, epochs=100, batch_size=32, edgeloss_weight=0.0, kl_weight=0, dataname='2d_square_lattice', num_workers=0, data_path='data/', working_dir='', suffix='', log_dir='', checkpoint_dir='trained_models', saved_model_dir=None)\n",
            "Training with 1 GPUs!\n",
            "\n",
            "# Params: 205090\n",
            "=====Epoch 1\n",
            "Training...\n",
            "Iteration:   0% 0/32 [00:00<?, ?it/s]/usr/local/lib/python3.10/dist-packages/torch_geometric/data/storage.py:450: UserWarning: Unable to accurately infer 'num_nodes' from the attribute set '{'edge_index'}'. Please explicitly set 'num_nodes' as an attribute of 'data' to suppress this warning\n",
            "  warnings.warn(\n",
            "loss_dist 1.105, loss_coords 0.937, loss_res 0.696, : 100% 32/32 [00:25<00:00,  1.24it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.52it/s]\n",
            "Epoch 1, valid_edge_mae: 1.08917, Train_mae: 1.13869, Validation_mae: 0.90132, Validation_rmsd: 2.52450, res_acc: 0.50, kl_x: 0.00, kl_h: 0.00, elapse: 30.46321\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 2.5245023402593603, epoch: 1\n",
            "Best validation rec acc so far: 0.49677082896232605, epoch: 1\n",
            "=====Epoch 2\n",
            "Training...\n",
            "loss_dist 0.901, loss_coords 0.575, loss_res 0.693, : 100% 32/32 [00:24<00:00,  1.33it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.52it/s]\n",
            "Epoch 2, valid_edge_mae: 0.90258, Train_mae: 0.74074, Validation_mae: 0.55603, Validation_rmsd: 1.74483, res_acc: 0.50, kl_x: 0.00, kl_h: 0.00, elapse: 28.79124\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 1.7448349424455156, epoch: 2\n",
            "Best validation rec acc so far: 0.49677082896232605, epoch: 1\n",
            "=====Epoch 3\n",
            "Training...\n",
            "loss_dist 0.523, loss_coords 0.341, loss_res 0.693, : 100% 32/32 [00:24<00:00,  1.29it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 3, valid_edge_mae: 0.42788, Train_mae: 0.45649, Validation_mae: 0.29247, Validation_rmsd: 0.64500, res_acc: 0.50, kl_x: 0.00, kl_h: 0.00, elapse: 29.51359\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.6449973659161112, epoch: 3\n",
            "Best validation rec acc so far: 0.5032291412353516, epoch: 3\n",
            "=====Epoch 4\n",
            "Training...\n",
            "loss_dist 0.218, loss_coords 0.166, loss_res 0.694, : 100% 32/32 [00:24<00:00,  1.32it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.52it/s]\n",
            "Epoch 4, valid_edge_mae: 0.22193, Train_mae: 0.21278, Validation_mae: 0.17907, Validation_rmsd: 0.39923, res_acc: 0.50, kl_x: 0.00, kl_h: 0.00, elapse: 28.88660\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.3992281341178669, epoch: 4\n",
            "Best validation rec acc so far: 0.5032291412353516, epoch: 3\n",
            "=====Epoch 5\n",
            "Training...\n",
            "loss_dist 0.197, loss_coords 0.163, loss_res 0.695, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.51it/s]\n",
            "Epoch 5, valid_edge_mae: 0.21882, Train_mae: 0.16917, Validation_mae: 0.18279, Validation_rmsd: 0.36202, res_acc: 0.50, kl_x: 0.00, kl_h: 0.00, elapse: 29.25963\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.36202196004562454, epoch: 5\n",
            "Best validation rec acc so far: 0.5032291412353516, epoch: 3\n",
            "=====Epoch 6\n",
            "Training...\n",
            "loss_dist 0.254, loss_coords 0.195, loss_res 0.693, : 100% 32/32 [00:24<00:00,  1.28it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.54it/s]\n",
            "Epoch 6, valid_edge_mae: 0.22192, Train_mae: 0.14016, Validation_mae: 0.14460, Validation_rmsd: 0.32023, res_acc: 0.50, kl_x: 0.00, kl_h: 0.00, elapse: 29.57484\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.32023413895954, epoch: 6\n",
            "Best validation rec acc so far: 0.5032291412353516, epoch: 3\n",
            "=====Epoch 7\n",
            "Training...\n",
            "loss_dist 0.175, loss_coords 0.123, loss_res 0.693, : 100% 32/32 [00:24<00:00,  1.31it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.51it/s]\n",
            "Epoch 7, valid_edge_mae: 0.15411, Train_mae: 0.14479, Validation_mae: 0.12396, Validation_rmsd: 0.27722, res_acc: 0.51, kl_x: 0.00, kl_h: 0.00, elapse: 29.00931\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.2772234959542225, epoch: 7\n",
            "Best validation rec acc so far: 0.5080902576446533, epoch: 7\n",
            "=====Epoch 8\n",
            "Training...\n",
            "loss_dist 0.130, loss_coords 0.091, loss_res 0.693, : 100% 32/32 [00:24<00:00,  1.29it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 8, valid_edge_mae: 0.12607, Train_mae: 0.10233, Validation_mae: 0.08072, Validation_rmsd: 0.22769, res_acc: 0.50, kl_x: 0.00, kl_h: 0.00, elapse: 29.41046\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.2276934825030782, epoch: 8\n",
            "Best validation rec acc so far: 0.5080902576446533, epoch: 7\n",
            "=====Epoch 9\n",
            "Training...\n",
            "loss_dist 0.181, loss_coords 0.122, loss_res 0.693, : 100% 32/32 [00:24<00:00,  1.32it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.50it/s]\n",
            "Epoch 9, valid_edge_mae: 0.25238, Train_mae: 0.10025, Validation_mae: 0.13626, Validation_rmsd: 0.33274, res_acc: 0.50, kl_x: 0.00, kl_h: 0.00, elapse: 28.95191\n",
            "Best validation RMSD so far: 0.2276934825030782, epoch: 8\n",
            "Best validation rec acc so far: 0.5080902576446533, epoch: 7\n",
            "=====Epoch 10\n",
            "Training...\n",
            "loss_dist 0.119, loss_coords 0.075, loss_res 0.693, : 100% 32/32 [00:24<00:00,  1.28it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 10, valid_edge_mae: 0.14213, Train_mae: 0.10476, Validation_mae: 0.10889, Validation_rmsd: 0.25434, res_acc: 0.50, kl_x: 0.00, kl_h: 0.00, elapse: 29.50865\n",
            "Best validation RMSD so far: 0.2276934825030782, epoch: 8\n",
            "Best validation rec acc so far: 0.5080902576446533, epoch: 7\n",
            "=====Epoch 11\n",
            "Training...\n",
            "loss_dist 0.120, loss_coords 0.075, loss_res 0.693, : 100% 32/32 [00:24<00:00,  1.32it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.42it/s]\n",
            "Epoch 11, valid_edge_mae: 0.12238, Train_mae: 0.09414, Validation_mae: 0.09760, Validation_rmsd: 0.23066, res_acc: 0.51, kl_x: 0.00, kl_h: 0.00, elapse: 29.10816\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.2276934825030782, epoch: 8\n",
            "Best validation rec acc so far: 0.5085069537162781, epoch: 11\n",
            "=====Epoch 12\n",
            "Training...\n",
            "loss_dist 0.091, loss_coords 0.062, loss_res 0.693, : 100% 32/32 [00:24<00:00,  1.31it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.49it/s]\n",
            "Epoch 12, valid_edge_mae: 0.10692, Train_mae: 0.07613, Validation_mae: 0.07492, Validation_rmsd: 0.20430, res_acc: 0.50, kl_x: 0.00, kl_h: 0.00, elapse: 29.12437\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.2043002783782869, epoch: 12\n",
            "Best validation rec acc so far: 0.5085069537162781, epoch: 11\n",
            "=====Epoch 13\n",
            "Training...\n",
            "loss_dist 0.173, loss_coords 0.125, loss_res 0.693, : 100% 32/32 [00:24<00:00,  1.29it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 13, valid_edge_mae: 0.20305, Train_mae: 0.07706, Validation_mae: 0.14053, Validation_rmsd: 0.33823, res_acc: 0.50, kl_x: 0.00, kl_h: 0.00, elapse: 29.39299\n",
            "Best validation RMSD so far: 0.2043002783782869, epoch: 12\n",
            "Best validation rec acc so far: 0.5085069537162781, epoch: 11\n",
            "=====Epoch 14\n",
            "Training...\n",
            "loss_dist 0.111, loss_coords 0.090, loss_res 0.693, : 100% 32/32 [00:24<00:00,  1.32it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.52it/s]\n",
            "Epoch 14, valid_edge_mae: 0.13651, Train_mae: 0.09730, Validation_mae: 0.09710, Validation_rmsd: 0.21310, res_acc: 0.51, kl_x: 0.00, kl_h: 0.00, elapse: 28.87146\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.2043002783782869, epoch: 12\n",
            "Best validation rec acc so far: 0.5089930295944214, epoch: 14\n",
            "=====Epoch 15\n",
            "Training...\n",
            "loss_dist 0.157, loss_coords 0.131, loss_res 0.693, : 100% 32/32 [00:24<00:00,  1.29it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.54it/s]\n",
            "Epoch 15, valid_edge_mae: 0.16349, Train_mae: 0.13450, Validation_mae: 0.15756, Validation_rmsd: 0.30122, res_acc: 0.51, kl_x: 0.00, kl_h: 0.00, elapse: 29.32529\n",
            "Best validation RMSD so far: 0.2043002783782869, epoch: 12\n",
            "Best validation rec acc so far: 0.5089930295944214, epoch: 14\n",
            "=====Epoch 16\n",
            "Training...\n",
            "loss_dist 0.130, loss_coords 0.082, loss_res 0.693, : 100% 32/32 [00:24<00:00,  1.32it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.51it/s]\n",
            "Epoch 16, valid_edge_mae: 0.14984, Train_mae: 0.08833, Validation_mae: 0.09272, Validation_rmsd: 0.21037, res_acc: 0.50, kl_x: 0.00, kl_h: 0.00, elapse: 28.94642\n",
            "Best validation RMSD so far: 0.2043002783782869, epoch: 12\n",
            "Best validation rec acc so far: 0.5089930295944214, epoch: 14\n",
            "=====Epoch 17\n",
            "Training...\n",
            "loss_dist 0.091, loss_coords 0.065, loss_res 0.693, : 100% 32/32 [00:24<00:00,  1.29it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.50it/s]\n",
            "Epoch 17, valid_edge_mae: 0.13522, Train_mae: 0.09435, Validation_mae: 0.08839, Validation_rmsd: 0.19488, res_acc: 0.50, kl_x: 0.00, kl_h: 0.00, elapse: 29.47250\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.1948816867001993, epoch: 17\n",
            "Best validation rec acc so far: 0.5089930295944214, epoch: 14\n",
            "=====Epoch 18\n",
            "Training...\n",
            "loss_dist 0.085, loss_coords 0.073, loss_res 0.693, : 100% 32/32 [00:24<00:00,  1.31it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.44it/s]\n",
            "Epoch 18, valid_edge_mae: 0.08364, Train_mae: 0.07949, Validation_mae: 0.05998, Validation_rmsd: 0.16177, res_acc: 0.51, kl_x: 0.00, kl_h: 0.00, elapse: 29.29594\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.16176972816806198, epoch: 18\n",
            "Best validation rec acc so far: 0.5089930295944214, epoch: 14\n",
            "=====Epoch 19\n",
            "Training...\n",
            "loss_dist 0.071, loss_coords 0.053, loss_res 0.693, : 100% 32/32 [00:24<00:00,  1.33it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.52it/s]\n",
            "Epoch 19, valid_edge_mae: 0.07249, Train_mae: 0.06669, Validation_mae: 0.04951, Validation_rmsd: 0.14265, res_acc: 0.50, kl_x: 0.00, kl_h: 0.00, elapse: 28.79001\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.14264996009807035, epoch: 19\n",
            "Best validation rec acc so far: 0.5089930295944214, epoch: 14\n",
            "=====Epoch 20\n",
            "Training...\n",
            "loss_dist 0.115, loss_coords 0.070, loss_res 0.693, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 20, valid_edge_mae: 0.07456, Train_mae: 0.05398, Validation_mae: 0.05978, Validation_rmsd: 0.14906, res_acc: 0.50, kl_x: 0.00, kl_h: 0.00, elapse: 29.22557\n",
            "Best validation RMSD so far: 0.14264996009807035, epoch: 19\n",
            "Best validation rec acc so far: 0.5089930295944214, epoch: 14\n",
            "=====Epoch 21\n",
            "Training...\n",
            "Iteration:   0% 0/32 [00:00<?, ?it/s]/content/drive/.shortcut-targets-by-id/1cPQ2fA-SRAPng-aTI1P8QDLacE-wxHcy/lattices/LatentLattice/train.py:135: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`). Consider using `matplotlib.pyplot.close()`.\n",
            "  fig = plt.figure()\n",
            "loss_dist 0.101, loss_coords 0.060, loss_res 0.693, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.50it/s]\n",
            "Epoch 21, valid_edge_mae: 0.07065, Train_mae: 0.05596, Validation_mae: 0.05383, Validation_rmsd: 0.14341, res_acc: 0.51, kl_x: 0.00, kl_h: 0.00, elapse: 29.30570\n",
            "Best validation RMSD so far: 0.14264996009807035, epoch: 19\n",
            "Best validation rec acc so far: 0.5089930295944214, epoch: 14\n",
            "=====Epoch 22\n",
            "Training...\n",
            "loss_dist 0.079, loss_coords 0.057, loss_res 0.693, : 100% 32/32 [00:24<00:00,  1.29it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 22, valid_edge_mae: 0.05904, Train_mae: 0.06095, Validation_mae: 0.04403, Validation_rmsd: 0.13000, res_acc: 0.50, kl_x: 0.00, kl_h: 0.00, elapse: 29.41567\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.13000029871132057, epoch: 22\n",
            "Best validation rec acc so far: 0.5089930295944214, epoch: 14\n",
            "=====Epoch 23\n",
            "Training...\n",
            "loss_dist 0.085, loss_coords 0.053, loss_res 0.694, : 100% 32/32 [00:24<00:00,  1.32it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.51it/s]\n",
            "Epoch 23, valid_edge_mae: 0.06325, Train_mae: 0.05648, Validation_mae: 0.04854, Validation_rmsd: 0.13401, res_acc: 0.50, kl_x: 0.00, kl_h: 0.00, elapse: 28.88988\n",
            "Best validation RMSD so far: 0.13000029871132057, epoch: 22\n",
            "Best validation rec acc so far: 0.5089930295944214, epoch: 14\n",
            "=====Epoch 24\n",
            "Training...\n",
            "loss_dist 0.072, loss_coords 0.047, loss_res 0.693, : 100% 32/32 [00:24<00:00,  1.28it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.50it/s]\n",
            "Epoch 24, valid_edge_mae: 0.07773, Train_mae: 0.04881, Validation_mae: 0.05188, Validation_rmsd: 0.13717, res_acc: 0.50, kl_x: 0.00, kl_h: 0.00, elapse: 29.64963\n",
            "Best validation RMSD so far: 0.13000029871132057, epoch: 22\n",
            "Best validation rec acc so far: 0.5089930295944214, epoch: 14\n",
            "=====Epoch 25\n",
            "Training...\n",
            "loss_dist 0.056, loss_coords 0.045, loss_res 0.693, : 100% 32/32 [00:24<00:00,  1.31it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.42it/s]\n",
            "Epoch 25, valid_edge_mae: 0.06601, Train_mae: 0.04741, Validation_mae: 0.04417, Validation_rmsd: 0.12915, res_acc: 0.50, kl_x: 0.00, kl_h: 0.00, elapse: 29.31842\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.12915042319686504, epoch: 25\n",
            "Best validation rec acc so far: 0.5089930295944214, epoch: 14\n",
            "=====Epoch 26\n",
            "Training...\n",
            "loss_dist 0.099, loss_coords 0.055, loss_res 0.693, : 100% 32/32 [00:24<00:00,  1.32it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 26, valid_edge_mae: 0.07583, Train_mae: 0.04419, Validation_mae: 0.05081, Validation_rmsd: 0.14514, res_acc: 0.51, kl_x: 0.00, kl_h: 0.00, elapse: 28.94023\n",
            "Best validation RMSD so far: 0.12915042319686504, epoch: 25\n",
            "Best validation rec acc so far: 0.5089930295944214, epoch: 14\n",
            "=====Epoch 27\n",
            "Training...\n",
            "loss_dist 0.056, loss_coords 0.037, loss_res 0.693, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.52it/s]\n",
            "Epoch 27, valid_edge_mae: 0.06054, Train_mae: 0.04247, Validation_mae: 0.04033, Validation_rmsd: 0.12599, res_acc: 0.50, kl_x: 0.00, kl_h: 0.00, elapse: 29.24957\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.12599002197814765, epoch: 27\n",
            "Best validation rec acc so far: 0.5089930295944214, epoch: 14\n",
            "=====Epoch 28\n",
            "Training...\n",
            "loss_dist 0.060, loss_coords 0.042, loss_res 0.693, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.50it/s]\n",
            "Epoch 28, valid_edge_mae: 0.05907, Train_mae: 0.04328, Validation_mae: 0.03671, Validation_rmsd: 0.11297, res_acc: 0.51, kl_x: 0.00, kl_h: 0.00, elapse: 29.27191\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.11296633324122707, epoch: 28\n",
            "Best validation rec acc so far: 0.5092708468437195, epoch: 28\n",
            "=====Epoch 29\n",
            "Training...\n",
            "loss_dist 0.043, loss_coords 0.034, loss_res 0.693, : 100% 32/32 [00:25<00:00,  1.28it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.50it/s]\n",
            "Epoch 29, valid_edge_mae: 0.06389, Train_mae: 0.04241, Validation_mae: 0.04599, Validation_rmsd: 0.12934, res_acc: 0.51, kl_x: 0.00, kl_h: 0.00, elapse: 29.72195\n",
            "Best validation RMSD so far: 0.11296633324122707, epoch: 28\n",
            "Best validation rec acc so far: 0.5092708468437195, epoch: 28\n",
            "=====Epoch 30\n",
            "Training...\n",
            "loss_dist 0.045, loss_coords 0.044, loss_res 0.693, : 100% 32/32 [00:24<00:00,  1.32it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 30, valid_edge_mae: 0.04902, Train_mae: 0.04058, Validation_mae: 0.04431, Validation_rmsd: 0.11614, res_acc: 0.50, kl_x: 0.00, kl_h: 0.00, elapse: 28.90777\n",
            "Best validation RMSD so far: 0.11296633324122707, epoch: 28\n",
            "Best validation rec acc so far: 0.5092708468437195, epoch: 28\n",
            "=====Epoch 31\n",
            "Training...\n",
            "loss_dist 0.053, loss_coords 0.038, loss_res 0.693, : 100% 32/32 [00:24<00:00,  1.28it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 31, valid_edge_mae: 0.08228, Train_mae: 0.04422, Validation_mae: 0.05284, Validation_rmsd: 0.15312, res_acc: 0.50, kl_x: 0.00, kl_h: 0.00, elapse: 29.54855\n",
            "Best validation RMSD so far: 0.11296633324122707, epoch: 28\n",
            "Best validation rec acc so far: 0.5092708468437195, epoch: 28\n",
            "=====Epoch 32\n",
            "Training...\n",
            "loss_dist 0.056, loss_coords 0.036, loss_res 0.693, : 100% 32/32 [00:24<00:00,  1.32it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.51it/s]\n",
            "Epoch 32, valid_edge_mae: 0.05164, Train_mae: 0.04282, Validation_mae: 0.03383, Validation_rmsd: 0.11029, res_acc: 0.50, kl_x: 0.00, kl_h: 0.00, elapse: 28.91029\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.11029048796229633, epoch: 32\n",
            "Best validation rec acc so far: 0.5092708468437195, epoch: 28\n",
            "=====Epoch 33\n",
            "Training...\n",
            "loss_dist 0.041, loss_coords 0.028, loss_res 0.693, : 100% 32/32 [00:24<00:00,  1.32it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 33, valid_edge_mae: 0.04433, Train_mae: 0.03348, Validation_mae: 0.03623, Validation_rmsd: 0.10664, res_acc: 0.51, kl_x: 0.00, kl_h: 0.00, elapse: 28.86466\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.1066442529477994, epoch: 33\n",
            "Best validation rec acc so far: 0.5092708468437195, epoch: 28\n",
            "=====Epoch 34\n",
            "Training...\n",
            "loss_dist 0.050, loss_coords 0.034, loss_res 0.694, : 100% 32/32 [00:24<00:00,  1.29it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.52it/s]\n",
            "Epoch 34, valid_edge_mae: 0.05369, Train_mae: 0.03587, Validation_mae: 0.03699, Validation_rmsd: 0.10906, res_acc: 0.50, kl_x: 0.00, kl_h: 0.00, elapse: 29.37365\n",
            "Best validation RMSD so far: 0.1066442529477994, epoch: 33\n",
            "Best validation rec acc so far: 0.5092708468437195, epoch: 28\n",
            "=====Epoch 35\n",
            "Training...\n",
            "loss_dist 0.049, loss_coords 0.032, loss_res 0.693, : 100% 32/32 [00:24<00:00,  1.32it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.52it/s]\n",
            "Epoch 35, valid_edge_mae: 0.04530, Train_mae: 0.03698, Validation_mae: 0.03106, Validation_rmsd: 0.10120, res_acc: 0.49, kl_x: 0.00, kl_h: 0.00, elapse: 28.80707\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.10120183981799993, epoch: 35\n",
            "Best validation rec acc so far: 0.5092708468437195, epoch: 28\n",
            "=====Epoch 36\n",
            "Training...\n",
            "loss_dist 0.067, loss_coords 0.036, loss_res 0.693, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 36, valid_edge_mae: 0.04453, Train_mae: 0.03170, Validation_mae: 0.03429, Validation_rmsd: 0.10552, res_acc: 0.50, kl_x: 0.00, kl_h: 0.00, elapse: 29.15134\n",
            "Best validation RMSD so far: 0.10120183981799993, epoch: 35\n",
            "Best validation rec acc so far: 0.5092708468437195, epoch: 28\n",
            "=====Epoch 37\n",
            "Training...\n",
            "loss_dist 0.059, loss_coords 0.033, loss_res 0.693, : 100% 32/32 [00:24<00:00,  1.31it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.52it/s]\n",
            "Epoch 37, valid_edge_mae: 0.05697, Train_mae: 0.02998, Validation_mae: 0.03572, Validation_rmsd: 0.10503, res_acc: 0.50, kl_x: 0.00, kl_h: 0.00, elapse: 29.06545\n",
            "Best validation RMSD so far: 0.10120183981799993, epoch: 35\n",
            "Best validation rec acc so far: 0.5092708468437195, epoch: 28\n",
            "=====Epoch 38\n",
            "Training...\n",
            "loss_dist 0.067, loss_coords 0.041, loss_res 0.693, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.51it/s]\n",
            "Epoch 38, valid_edge_mae: 0.07700, Train_mae: 0.03117, Validation_mae: 0.04355, Validation_rmsd: 0.12912, res_acc: 0.50, kl_x: 0.00, kl_h: 0.00, elapse: 29.37156\n",
            "Best validation RMSD so far: 0.10120183981799993, epoch: 35\n",
            "Best validation rec acc so far: 0.5092708468437195, epoch: 28\n",
            "=====Epoch 39\n",
            "Training...\n",
            "loss_dist 0.039, loss_coords 0.024, loss_res 0.693, : 100% 32/32 [00:24<00:00,  1.31it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 39, valid_edge_mae: 0.04120, Train_mae: 0.03516, Validation_mae: 0.02521, Validation_rmsd: 0.09297, res_acc: 0.50, kl_x: 0.00, kl_h: 0.00, elapse: 29.00410\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.09297209542748053, epoch: 39\n",
            "Best validation rec acc so far: 0.5092708468437195, epoch: 28\n",
            "=====Epoch 40\n",
            "Training...\n",
            "loss_dist 0.037, loss_coords 0.025, loss_res 0.693, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.52it/s]\n",
            "Epoch 40, valid_edge_mae: 0.05254, Train_mae: 0.02914, Validation_mae: 0.03479, Validation_rmsd: 0.10235, res_acc: 0.50, kl_x: 0.00, kl_h: 0.00, elapse: 29.28734\n",
            "Best validation RMSD so far: 0.09297209542748053, epoch: 39\n",
            "Best validation rec acc so far: 0.5092708468437195, epoch: 28\n",
            "=====Epoch 41\n",
            "Training...\n",
            "loss_dist 0.046, loss_coords 0.027, loss_res 0.693, : 100% 32/32 [00:24<00:00,  1.31it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.40it/s]\n",
            "Epoch 41, valid_edge_mae: 0.03948, Train_mae: 0.02691, Validation_mae: 0.02884, Validation_rmsd: 0.09514, res_acc: 0.50, kl_x: 0.00, kl_h: 0.00, elapse: 29.53793\n",
            "Best validation RMSD so far: 0.09297209542748053, epoch: 39\n",
            "Best validation rec acc so far: 0.5092708468437195, epoch: 28\n",
            "=====Epoch 42\n",
            "Training...\n",
            "loss_dist 0.071, loss_coords 0.041, loss_res 0.693, : 100% 32/32 [00:24<00:00,  1.31it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 42, valid_edge_mae: 0.05531, Train_mae: 0.03207, Validation_mae: 0.03495, Validation_rmsd: 0.10570, res_acc: 0.50, kl_x: 0.00, kl_h: 0.00, elapse: 28.96630\n",
            "Best validation RMSD so far: 0.09297209542748053, epoch: 39\n",
            "Best validation rec acc so far: 0.5092708468437195, epoch: 28\n",
            "=====Epoch 43\n",
            "Training...\n",
            "loss_dist 0.029, loss_coords 0.019, loss_res 0.693, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.51it/s]\n",
            "Epoch 43, valid_edge_mae: 0.03953, Train_mae: 0.02390, Validation_mae: 0.02203, Validation_rmsd: 0.08740, res_acc: 0.50, kl_x: 0.00, kl_h: 0.00, elapse: 29.23913\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.08739969332826261, epoch: 43\n",
            "Best validation rec acc so far: 0.5092708468437195, epoch: 28\n",
            "=====Epoch 44\n",
            "Training...\n",
            "loss_dist 0.047, loss_coords 0.027, loss_res 0.693, : 100% 32/32 [00:24<00:00,  1.32it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.52it/s]\n",
            "Epoch 44, valid_edge_mae: 0.03137, Train_mae: 0.02425, Validation_mae: 0.02176, Validation_rmsd: 0.08258, res_acc: 0.50, kl_x: 0.00, kl_h: 0.00, elapse: 28.92889\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.08257923991411324, epoch: 44\n",
            "Best validation rec acc so far: 0.5092708468437195, epoch: 28\n",
            "=====Epoch 45\n",
            "Training...\n",
            "loss_dist 0.028, loss_coords 0.018, loss_res 0.693, : 100% 32/32 [00:24<00:00,  1.29it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.49it/s]\n",
            "Epoch 45, valid_edge_mae: 0.03021, Train_mae: 0.02299, Validation_mae: 0.02474, Validation_rmsd: 0.08489, res_acc: 0.50, kl_x: 0.00, kl_h: 0.00, elapse: 29.61012\n",
            "Best validation RMSD so far: 0.08257923991411324, epoch: 44\n",
            "Best validation rec acc so far: 0.5092708468437195, epoch: 28\n",
            "=====Epoch 46\n",
            "Training...\n",
            "loss_dist 0.042, loss_coords 0.024, loss_res 0.693, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.52it/s]\n",
            "Epoch 46, valid_edge_mae: 0.03638, Train_mae: 0.02450, Validation_mae: 0.03213, Validation_rmsd: 0.09264, res_acc: 0.50, kl_x: 0.00, kl_h: 0.00, elapse: 29.26696\n",
            "Best validation RMSD so far: 0.08257923991411324, epoch: 44\n",
            "Best validation rec acc so far: 0.5092708468437195, epoch: 28\n",
            "=====Epoch 47\n",
            "Training...\n",
            "loss_dist 0.034, loss_coords 0.021, loss_res 0.693, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 47, valid_edge_mae: 0.02662, Train_mae: 0.02887, Validation_mae: 0.01896, Validation_rmsd: 0.08205, res_acc: 0.50, kl_x: 0.00, kl_h: 0.00, elapse: 29.25213\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.08205083315003384, epoch: 47\n",
            "Best validation rec acc so far: 0.5092708468437195, epoch: 28\n",
            "=====Epoch 48\n",
            "Training...\n",
            "loss_dist 0.052, loss_coords 0.034, loss_res 0.693, : 100% 32/32 [00:24<00:00,  1.32it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.42it/s]\n",
            "Epoch 48, valid_edge_mae: 0.04409, Train_mae: 0.02216, Validation_mae: 0.02987, Validation_rmsd: 0.09400, res_acc: 0.50, kl_x: 0.00, kl_h: 0.00, elapse: 29.17762\n",
            "Best validation RMSD so far: 0.08205083315003384, epoch: 47\n",
            "Best validation rec acc so far: 0.5092708468437195, epoch: 28\n",
            "=====Epoch 49\n",
            "Training...\n",
            "loss_dist 0.038, loss_coords 0.025, loss_res 0.693, : 100% 32/32 [00:24<00:00,  1.32it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.52it/s]\n",
            "Epoch 49, valid_edge_mae: 0.03342, Train_mae: 0.02564, Validation_mae: 0.02871, Validation_rmsd: 0.08543, res_acc: 0.50, kl_x: 0.00, kl_h: 0.00, elapse: 28.91150\n",
            "Best validation RMSD so far: 0.08205083315003384, epoch: 47\n",
            "Best validation rec acc so far: 0.5092708468437195, epoch: 28\n",
            "=====Epoch 50\n",
            "Training...\n",
            "loss_dist 0.031, loss_coords 0.018, loss_res 0.693, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 50, valid_edge_mae: 0.02774, Train_mae: 0.02343, Validation_mae: 0.01763, Validation_rmsd: 0.07718, res_acc: 0.50, kl_x: 0.00, kl_h: 0.00, elapse: 29.26537\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.07718468370119064, epoch: 50\n",
            "Best validation rec acc so far: 0.5092708468437195, epoch: 28\n",
            "=====Epoch 51\n",
            "Training...\n",
            "loss_dist 0.049, loss_coords 0.027, loss_res 0.693, :  16% 5/32 [00:03<00:20,  1.32it/s]Exception ignored in: <generator object tqdm.__iter__ at 0x7b693013cd60>\n",
            "Traceback (most recent call last):\n",
            "  File \"/usr/local/lib/python3.10/dist-packages/tqdm/std.py\", line 1182, in __iter__\n",
            "    yield obj\n",
            "KeyboardInterrupt: \n",
            "Traceback (most recent call last):\n",
            "  File \"/content/drive/.shortcut-targets-by-id/1cPQ2fA-SRAPng-aTI1P8QDLacE-wxHcy/lattices/LatentLattice/train.py\", line 432, in <module>\n",
            "    main()\n",
            "  File \"/content/drive/.shortcut-targets-by-id/1cPQ2fA-SRAPng-aTI1P8QDLacE-wxHcy/lattices/LatentLattice/train.py\", line 343, in main\n",
            "    total_loss, train_mae, res_loss, train_edge_mae, train_kl_x, train_kl_h = train(args, \n",
            "  File \"/content/drive/.shortcut-targets-by-id/1cPQ2fA-SRAPng-aTI1P8QDLacE-wxHcy/lattices/LatentLattice/train.py\", line 144, in train\n",
            "    pred_coords, pred_atom, kl_x, kl_h = model(batch)\n",
            "  File \"/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py\", line 1511, in _wrapped_call_impl\n",
            "    return self._call_impl(*args, **kwargs)\n",
            "  File \"/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py\", line 1520, in _call_impl\n",
            "    return forward_call(*args, **kwargs)\n",
            "  File \"/content/drive/.shortcut-targets-by-id/1cPQ2fA-SRAPng-aTI1P8QDLacE-wxHcy/lattices/LatentLattice/model.py\", line 415, in forward\n",
            "    coords_pred, h = self.decoder(emb_coords, emb_h, batched_data.batch, batched_data, edge_index=edge_index)\n",
            "  File \"/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py\", line 1511, in _wrapped_call_impl\n",
            "    return self._call_impl(*args, **kwargs)\n",
            "  File \"/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py\", line 1520, in _call_impl\n",
            "    return forward_call(*args, **kwargs)\n",
            "  File \"/content/drive/.shortcut-targets-by-id/1cPQ2fA-SRAPng-aTI1P8QDLacE-wxHcy/lattices/LatentLattice/model.py\", line 344, in forward\n",
            "    h, coords = self.unpooling[i](h, coords, batch, edge_index=edge_index)\n",
            "  File \"/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py\", line 1511, in _wrapped_call_impl\n",
            "    return self._call_impl(*args, **kwargs)\n",
            "  File \"/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py\", line 1520, in _call_impl\n",
            "    return forward_call(*args, **kwargs)\n",
            "  File \"/content/drive/.shortcut-targets-by-id/1cPQ2fA-SRAPng-aTI1P8QDLacE-wxHcy/lattices/LatentLattice/model.py\", line 241, in forward\n",
            "    edge_index = from_networkx(nx.complete_graph(coords.shape[1])).edge_index.to(device)\n",
            "  File \"/usr/local/lib/python3.10/dist-packages/torch_geometric/utils/convert.py\", line 235, in from_networkx\n",
            "    edge_index[1, i] = mapping[dst]\n",
            "KeyboardInterrupt\n",
            "loss_dist 0.049, loss_coords 0.027, loss_res 0.693, :  16% 5/32 [00:04<00:23,  1.14it/s]\n"
          ]
        }
      ],
      "source": [
        "! python LatentLattice/train.py --mp_steps 3 --batch_size 32 --debug --layers 2 --edgeloss_weight 0.0 --epochs 100"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "kgem72JTGl5E"
      },
      "source": [
        "Distortion"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "nkIR-TTo5_c-",
        "outputId": "739f5383-a156-4977-831c-16c37b286207"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Namespace(debug=True, mp_steps=3, emb_dim=32, layers=2, pooling=True, up_mlp=False, residual=True, noise=False, transpose=False, attn=False, loss='all', mode='train', lr_init=0.001, epochs=100, batch_size=32, edgeloss_weight=0.0, kl_weight=0, dataname='2d_square_lattice', num_workers=0, data_path='data/', working_dir='', suffix='', log_dir='', checkpoint_dir='trained_models', saved_model_dir=None)\n",
            "Training with 1 GPUs!\n",
            "\n",
            "# Params: 205090\n",
            "=====Epoch 1\n",
            "Training...\n",
            "Iteration:   0% 0/32 [00:00<?, ?it/s]/usr/local/lib/python3.10/dist-packages/torch_geometric/data/storage.py:450: UserWarning: Unable to accurately infer 'num_nodes' from the attribute set '{'edge_index'}'. Please explicitly set 'num_nodes' as an attribute of 'data' to suppress this warning\n",
            "  warnings.warn(\n",
            "loss_dist 1.665, loss_coords 1.151, loss_res 0.562, : 100% 32/32 [00:25<00:00,  1.25it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.50it/s]\n",
            "Epoch 1, valid_edge_mae: 1.54999, Train_mae: 1.35521, Validation_mae: 1.14432, Validation_rmsd: 2.49971, res_acc: 0.72, kl_x: 0.00, kl_h: 0.00, elapse: 30.34356\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 2.499714787162524, epoch: 1\n",
            "Best validation rec acc so far: 0.7216319441795349, epoch: 1\n",
            "=====Epoch 2\n",
            "Training...\n",
            "loss_dist 0.981, loss_coords 0.659, loss_res 0.584, : 100% 32/32 [00:24<00:00,  1.32it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.50it/s]\n",
            "Epoch 2, valid_edge_mae: 0.94096, Train_mae: 0.90411, Validation_mae: 0.65803, Validation_rmsd: 1.18499, res_acc: 0.71, kl_x: 0.00, kl_h: 0.00, elapse: 29.06350\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 1.1849861811427704, epoch: 2\n",
            "Best validation rec acc so far: 0.7216319441795349, epoch: 1\n",
            "=====Epoch 3\n",
            "Training...\n",
            "loss_dist 0.748, loss_coords 0.533, loss_res 0.558, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 3, valid_edge_mae: 0.75088, Train_mae: 0.58670, Validation_mae: 0.54003, Validation_rmsd: 0.96239, res_acc: 0.71, kl_x: 0.00, kl_h: 0.00, elapse: 29.26898\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.9623869823432952, epoch: 3\n",
            "Best validation rec acc so far: 0.7216319441795349, epoch: 1\n",
            "=====Epoch 4\n",
            "Training...\n",
            "loss_dist 0.723, loss_coords 0.522, loss_res 0.568, : 100% 32/32 [00:24<00:00,  1.32it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 4, valid_edge_mae: 0.73735, Train_mae: 0.52905, Validation_mae: 0.52414, Validation_rmsd: 0.94539, res_acc: 0.71, kl_x: 0.00, kl_h: 0.00, elapse: 28.78058\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.9453885927477285, epoch: 4\n",
            "Best validation rec acc so far: 0.7216319441795349, epoch: 1\n",
            "=====Epoch 5\n",
            "Training...\n",
            "loss_dist 0.712, loss_coords 0.497, loss_res 0.564, : 100% 32/32 [00:24<00:00,  1.31it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 5, valid_edge_mae: 0.72437, Train_mae: 0.51559, Validation_mae: 0.50887, Validation_rmsd: 0.92512, res_acc: 0.72, kl_x: 0.00, kl_h: 0.00, elapse: 29.07187\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.9251225996448287, epoch: 5\n",
            "Best validation rec acc so far: 0.7216319441795349, epoch: 1\n",
            "=====Epoch 6\n",
            "Training...\n",
            "loss_dist 0.716, loss_coords 0.503, loss_res 0.542, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.54it/s]\n",
            "Epoch 6, valid_edge_mae: 0.71955, Train_mae: 0.50970, Validation_mae: 0.50476, Validation_rmsd: 0.91622, res_acc: 0.72, kl_x: 0.00, kl_h: 0.00, elapse: 29.12727\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.9162226923817346, epoch: 6\n",
            "Best validation rec acc so far: 0.7216319441795349, epoch: 1\n",
            "=====Epoch 7\n",
            "Training...\n",
            "loss_dist 0.683, loss_coords 0.468, loss_res 0.528, : 100% 32/32 [00:24<00:00,  1.32it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 7, valid_edge_mae: 0.71774, Train_mae: 0.49596, Validation_mae: 0.49870, Validation_rmsd: 0.91839, res_acc: 0.71, kl_x: 0.00, kl_h: 0.00, elapse: 28.78698\n",
            "Best validation RMSD so far: 0.9162226923817346, epoch: 6\n",
            "Best validation rec acc so far: 0.7216319441795349, epoch: 1\n",
            "=====Epoch 8\n",
            "Training...\n",
            "loss_dist 0.726, loss_coords 0.509, loss_res 0.565, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.54it/s]\n",
            "Epoch 8, valid_edge_mae: 0.71551, Train_mae: 0.49782, Validation_mae: 0.49962, Validation_rmsd: 0.91578, res_acc: 0.72, kl_x: 0.00, kl_h: 0.00, elapse: 29.13824\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.9157767045162744, epoch: 8\n",
            "Best validation rec acc so far: 0.7216319441795349, epoch: 1\n",
            "=====Epoch 9\n",
            "Training...\n",
            "loss_dist 0.726, loss_coords 0.512, loss_res 0.546, : 100% 32/32 [00:24<00:00,  1.32it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.52it/s]\n",
            "Epoch 9, valid_edge_mae: 0.70810, Train_mae: 0.49237, Validation_mae: 0.48884, Validation_rmsd: 0.90451, res_acc: 0.72, kl_x: 0.00, kl_h: 0.00, elapse: 28.89656\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.904512934082392, epoch: 9\n",
            "Best validation rec acc so far: 0.7232986092567444, epoch: 9\n",
            "=====Epoch 10\n",
            "Training...\n",
            "loss_dist 0.720, loss_coords 0.485, loss_res 0.528, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.50it/s]\n",
            "Epoch 10, valid_edge_mae: 0.71053, Train_mae: 0.49162, Validation_mae: 0.49024, Validation_rmsd: 0.90513, res_acc: 0.73, kl_x: 0.00, kl_h: 0.00, elapse: 29.40140\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.904512934082392, epoch: 9\n",
            "Best validation rec acc so far: 0.7254514098167419, epoch: 10\n",
            "=====Epoch 11\n",
            "Training...\n",
            "loss_dist 0.689, loss_coords 0.471, loss_res 0.496, : 100% 32/32 [00:24<00:00,  1.29it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.54it/s]\n",
            "Epoch 11, valid_edge_mae: 0.70724, Train_mae: 0.48842, Validation_mae: 0.49150, Validation_rmsd: 0.90675, res_acc: 0.73, kl_x: 0.00, kl_h: 0.00, elapse: 29.45681\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.904512934082392, epoch: 9\n",
            "Best validation rec acc so far: 0.7288541793823242, epoch: 11\n",
            "=====Epoch 12\n",
            "Training...\n",
            "loss_dist 0.708, loss_coords 0.494, loss_res 0.534, : 100% 32/32 [00:24<00:00,  1.32it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.51it/s]\n",
            "Epoch 12, valid_edge_mae: 0.70411, Train_mae: 0.48915, Validation_mae: 0.48232, Validation_rmsd: 0.90144, res_acc: 0.73, kl_x: 0.00, kl_h: 0.00, elapse: 28.84409\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.9014386878935495, epoch: 12\n",
            "Best validation rec acc so far: 0.7311458587646484, epoch: 12\n",
            "=====Epoch 13\n",
            "Training...\n",
            "loss_dist 0.690, loss_coords 0.481, loss_res 0.495, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 13, valid_edge_mae: 0.70236, Train_mae: 0.48391, Validation_mae: 0.48325, Validation_rmsd: 0.90152, res_acc: 0.74, kl_x: 0.00, kl_h: 0.00, elapse: 29.31708\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.9014386878935495, epoch: 12\n",
            "Best validation rec acc so far: 0.7362152934074402, epoch: 13\n",
            "=====Epoch 14\n",
            "Training...\n",
            "loss_dist 0.684, loss_coords 0.463, loss_res 0.470, : 100% 32/32 [00:24<00:00,  1.32it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 14, valid_edge_mae: 0.70494, Train_mae: 0.48396, Validation_mae: 0.48653, Validation_rmsd: 0.90492, res_acc: 0.74, kl_x: 0.00, kl_h: 0.00, elapse: 28.82763\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.9014386878935495, epoch: 12\n",
            "Best validation rec acc so far: 0.7397916913032532, epoch: 14\n",
            "=====Epoch 15\n",
            "Training...\n",
            "loss_dist 0.730, loss_coords 0.494, loss_res 0.511, : 100% 32/32 [00:24<00:00,  1.31it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.52it/s]\n",
            "Epoch 15, valid_edge_mae: 0.73399, Train_mae: 0.48721, Validation_mae: 0.50227, Validation_rmsd: 0.92163, res_acc: 0.72, kl_x: 0.00, kl_h: 0.00, elapse: 29.10444\n",
            "Best validation RMSD so far: 0.9014386878935495, epoch: 12\n",
            "Best validation rec acc so far: 0.7397916913032532, epoch: 14\n",
            "=====Epoch 16\n",
            "Training...\n",
            "loss_dist 0.686, loss_coords 0.464, loss_res 0.460, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.51it/s]\n",
            "Epoch 16, valid_edge_mae: 0.70208, Train_mae: 0.48580, Validation_mae: 0.48103, Validation_rmsd: 0.89656, res_acc: 0.74, kl_x: 0.00, kl_h: 0.00, elapse: 29.23464\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.8965599259381344, epoch: 16\n",
            "Best validation rec acc so far: 0.7397916913032532, epoch: 14\n",
            "=====Epoch 17\n",
            "Training...\n",
            "loss_dist 0.689, loss_coords 0.471, loss_res 0.431, : 100% 32/32 [00:24<00:00,  1.31it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 17, valid_edge_mae: 0.69900, Train_mae: 0.48128, Validation_mae: 0.48567, Validation_rmsd: 0.89888, res_acc: 0.75, kl_x: 0.00, kl_h: 0.00, elapse: 29.12067\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.8965599259381344, epoch: 16\n",
            "Best validation rec acc so far: 0.745520830154419, epoch: 17\n",
            "=====Epoch 18\n",
            "Training...\n",
            "loss_dist 0.690, loss_coords 0.472, loss_res 0.434, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.54it/s]\n",
            "Epoch 18, valid_edge_mae: 0.70515, Train_mae: 0.48300, Validation_mae: 0.48591, Validation_rmsd: 0.89573, res_acc: 0.75, kl_x: 0.00, kl_h: 0.00, elapse: 29.22304\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.8957329189105002, epoch: 18\n",
            "Best validation rec acc so far: 0.7478471994400024, epoch: 18\n",
            "=====Epoch 19\n",
            "Training...\n",
            "loss_dist 0.689, loss_coords 0.473, loss_res 0.360, : 100% 32/32 [00:24<00:00,  1.32it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 19, valid_edge_mae: 0.69163, Train_mae: 0.47636, Validation_mae: 0.47560, Validation_rmsd: 0.88829, res_acc: 0.77, kl_x: 0.00, kl_h: 0.00, elapse: 28.82950\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.8882858207617568, epoch: 19\n",
            "Best validation rec acc so far: 0.7716319561004639, epoch: 19\n",
            "=====Epoch 20\n",
            "Training...\n",
            "loss_dist 0.678, loss_coords 0.465, loss_res 0.339, : 100% 32/32 [00:24<00:00,  1.31it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 20, valid_edge_mae: 0.70354, Train_mae: 0.47236, Validation_mae: 0.47880, Validation_rmsd: 0.88859, res_acc: 0.79, kl_x: 0.00, kl_h: 0.00, elapse: 29.03067\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.8882858207617568, epoch: 19\n",
            "Best validation rec acc so far: 0.7879166603088379, epoch: 20\n",
            "=====Epoch 21\n",
            "Training...\n",
            "Iteration:   0% 0/32 [00:00<?, ?it/s]/content/drive/.shortcut-targets-by-id/1cPQ2fA-SRAPng-aTI1P8QDLacE-wxHcy/lattices/LatentLattice/train.py:135: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`). Consider using `matplotlib.pyplot.close()`.\n",
            "  fig = plt.figure()\n",
            "loss_dist 0.700, loss_coords 0.486, loss_res 0.333, : 100% 32/32 [00:24<00:00,  1.33it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.43it/s]\n",
            "Epoch 21, valid_edge_mae: 0.68668, Train_mae: 0.47253, Validation_mae: 0.47054, Validation_rmsd: 0.87889, res_acc: 0.81, kl_x: 0.00, kl_h: 0.00, elapse: 29.06354\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.8788861957154225, epoch: 21\n",
            "Best validation rec acc so far: 0.8119444251060486, epoch: 21\n",
            "=====Epoch 22\n",
            "Training...\n",
            "loss_dist 0.692, loss_coords 0.479, loss_res 0.309, : 100% 32/32 [00:24<00:00,  1.32it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 22, valid_edge_mae: 0.70046, Train_mae: 0.47045, Validation_mae: 0.47615, Validation_rmsd: 0.88270, res_acc: 0.82, kl_x: 0.00, kl_h: 0.00, elapse: 28.82058\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.8788861957154225, epoch: 21\n",
            "Best validation rec acc so far: 0.8215625286102295, epoch: 22\n",
            "=====Epoch 23\n",
            "Training...\n",
            "loss_dist 0.661, loss_coords 0.441, loss_res 0.249, : 100% 32/32 [00:24<00:00,  1.31it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 23, valid_edge_mae: 0.68145, Train_mae: 0.46818, Validation_mae: 0.46906, Validation_rmsd: 0.87410, res_acc: 0.85, kl_x: 0.00, kl_h: 0.00, elapse: 29.09771\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.8740969848176463, epoch: 23\n",
            "Best validation rec acc so far: 0.8459722399711609, epoch: 23\n",
            "=====Epoch 24\n",
            "Training...\n",
            "loss_dist 0.680, loss_coords 0.463, loss_res 0.252, : 100% 32/32 [00:24<00:00,  1.32it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.52it/s]\n",
            "Epoch 24, valid_edge_mae: 0.68465, Train_mae: 0.46335, Validation_mae: 0.46674, Validation_rmsd: 0.86915, res_acc: 0.87, kl_x: 0.00, kl_h: 0.00, elapse: 28.83710\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.8691485659312264, epoch: 24\n",
            "Best validation rec acc so far: 0.8650346994400024, epoch: 24\n",
            "=====Epoch 25\n",
            "Training...\n",
            "loss_dist 0.686, loss_coords 0.472, loss_res 0.330, : 100% 32/32 [00:24<00:00,  1.31it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 25, valid_edge_mae: 0.68509, Train_mae: 0.46948, Validation_mae: 0.47088, Validation_rmsd: 0.87675, res_acc: 0.85, kl_x: 0.00, kl_h: 0.00, elapse: 29.11401\n",
            "Best validation RMSD so far: 0.8691485659312264, epoch: 24\n",
            "Best validation rec acc so far: 0.8650346994400024, epoch: 24\n",
            "=====Epoch 26\n",
            "Training...\n",
            "loss_dist 0.677, loss_coords 0.464, loss_res 0.236, : 100% 32/32 [00:24<00:00,  1.32it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 26, valid_edge_mae: 0.67539, Train_mae: 0.46281, Validation_mae: 0.46662, Validation_rmsd: 0.86574, res_acc: 0.87, kl_x: 0.00, kl_h: 0.00, elapse: 28.82165\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.8657382104041438, epoch: 26\n",
            "Best validation rec acc so far: 0.8658333420753479, epoch: 26\n",
            "=====Epoch 27\n",
            "Training...\n",
            "loss_dist 0.667, loss_coords 0.458, loss_res 0.229, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.50it/s]\n",
            "Epoch 27, valid_edge_mae: 0.68102, Train_mae: 0.46146, Validation_mae: 0.46207, Validation_rmsd: 0.86489, res_acc: 0.88, kl_x: 0.00, kl_h: 0.00, elapse: 29.35944\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.8648877043846255, epoch: 27\n",
            "Best validation rec acc so far: 0.8782291412353516, epoch: 27\n",
            "=====Epoch 28\n",
            "Training...\n",
            "loss_dist 0.692, loss_coords 0.474, loss_res 0.288, : 100% 32/32 [00:25<00:00,  1.28it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.50it/s]\n",
            "Epoch 28, valid_edge_mae: 0.68907, Train_mae: 0.46687, Validation_mae: 0.47590, Validation_rmsd: 0.87457, res_acc: 0.85, kl_x: 0.00, kl_h: 0.00, elapse: 29.71282\n",
            "Best validation RMSD so far: 0.8648877043846255, epoch: 27\n",
            "Best validation rec acc so far: 0.8782291412353516, epoch: 27\n",
            "=====Epoch 29\n",
            "Training...\n",
            "loss_dist 0.679, loss_coords 0.467, loss_res 0.223, : 100% 32/32 [00:24<00:00,  1.32it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.50it/s]\n",
            "Epoch 29, valid_edge_mae: 0.66980, Train_mae: 0.46175, Validation_mae: 0.45827, Validation_rmsd: 0.85870, res_acc: 0.88, kl_x: 0.00, kl_h: 0.00, elapse: 28.93065\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.8587009568294052, epoch: 29\n",
            "Best validation rec acc so far: 0.8805555701255798, epoch: 29\n",
            "=====Epoch 30\n",
            "Training...\n",
            "loss_dist 0.662, loss_coords 0.459, loss_res 0.204, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.52it/s]\n",
            "Epoch 30, valid_edge_mae: 0.67174, Train_mae: 0.45359, Validation_mae: 0.45784, Validation_rmsd: 0.85985, res_acc: 0.89, kl_x: 0.00, kl_h: 0.00, elapse: 29.33194\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.8587009568294052, epoch: 29\n",
            "Best validation rec acc so far: 0.8882291913032532, epoch: 30\n",
            "=====Epoch 31\n",
            "Training...\n",
            "loss_dist 0.659, loss_coords 0.449, loss_res 0.229, : 100% 32/32 [00:24<00:00,  1.32it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.51it/s]\n",
            "Epoch 31, valid_edge_mae: 0.66451, Train_mae: 0.45390, Validation_mae: 0.45465, Validation_rmsd: 0.85208, res_acc: 0.88, kl_x: 0.00, kl_h: 0.00, elapse: 28.81560\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.8520761279816395, epoch: 31\n",
            "Best validation rec acc so far: 0.8882291913032532, epoch: 30\n",
            "=====Epoch 32\n",
            "Training...\n",
            "loss_dist 0.691, loss_coords 0.490, loss_res 0.375, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.52it/s]\n",
            "Epoch 32, valid_edge_mae: 0.70524, Train_mae: 0.53191, Validation_mae: 0.49481, Validation_rmsd: 0.89799, res_acc: 0.79, kl_x: 0.00, kl_h: 0.00, elapse: 29.19468\n",
            "Best validation RMSD so far: 0.8520761279816395, epoch: 31\n",
            "Best validation rec acc so far: 0.8882291913032532, epoch: 30\n",
            "=====Epoch 33\n",
            "Training...\n",
            "loss_dist 0.685, loss_coords 0.464, loss_res 0.309, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:05<00:00,  1.39it/s]\n",
            "Epoch 33, valid_edge_mae: 0.69677, Train_mae: 0.48263, Validation_mae: 0.47856, Validation_rmsd: 0.88545, res_acc: 0.84, kl_x: 0.00, kl_h: 0.00, elapse: 29.71058\n",
            "Best validation RMSD so far: 0.8520761279816395, epoch: 31\n",
            "Best validation rec acc so far: 0.8882291913032532, epoch: 30\n",
            "=====Epoch 34\n",
            "Training...\n",
            "loss_dist 0.685, loss_coords 0.469, loss_res 0.263, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.50it/s]\n",
            "Epoch 34, valid_edge_mae: 0.68546, Train_mae: 0.47352, Validation_mae: 0.47184, Validation_rmsd: 0.87687, res_acc: 0.87, kl_x: 0.00, kl_h: 0.00, elapse: 29.31586\n",
            "Best validation RMSD so far: 0.8520761279816395, epoch: 31\n",
            "Best validation rec acc so far: 0.8882291913032532, epoch: 30\n",
            "=====Epoch 35\n",
            "Training...\n",
            "loss_dist 0.676, loss_coords 0.464, loss_res 0.256, : 100% 32/32 [00:25<00:00,  1.28it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.50it/s]\n",
            "Epoch 35, valid_edge_mae: 0.68244, Train_mae: 0.46826, Validation_mae: 0.46678, Validation_rmsd: 0.86988, res_acc: 0.89, kl_x: 0.00, kl_h: 0.00, elapse: 29.75007\n",
            "Best validation RMSD so far: 0.8520761279816395, epoch: 31\n",
            "Best validation rec acc so far: 0.8882291913032532, epoch: 30\n",
            "=====Epoch 36\n",
            "Training...\n",
            "loss_dist 0.657, loss_coords 0.450, loss_res 0.198, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.50it/s]\n",
            "Epoch 36, valid_edge_mae: 0.68026, Train_mae: 0.46624, Validation_mae: 0.46515, Validation_rmsd: 0.86745, res_acc: 0.89, kl_x: 0.00, kl_h: 0.00, elapse: 29.31810\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.8520761279816395, epoch: 31\n",
            "Best validation rec acc so far: 0.8910069465637207, epoch: 36\n",
            "=====Epoch 37\n",
            "Training...\n",
            "loss_dist 0.679, loss_coords 0.468, loss_res 0.199, : 100% 32/32 [00:24<00:00,  1.28it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.51it/s]\n",
            "Epoch 37, valid_edge_mae: 0.68247, Train_mae: 0.46203, Validation_mae: 0.46629, Validation_rmsd: 0.86537, res_acc: 0.89, kl_x: 0.00, kl_h: 0.00, elapse: 29.60689\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.8520761279816395, epoch: 31\n",
            "Best validation rec acc so far: 0.8934027552604675, epoch: 37\n",
            "=====Epoch 38\n",
            "Training...\n",
            "loss_dist 0.685, loss_coords 0.471, loss_res 0.347, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.50it/s]\n",
            "Epoch 38, valid_edge_mae: 0.68716, Train_mae: 0.45870, Validation_mae: 0.47970, Validation_rmsd: 0.87910, res_acc: 0.84, kl_x: 0.00, kl_h: 0.00, elapse: 29.31057\n",
            "Best validation RMSD so far: 0.8520761279816395, epoch: 31\n",
            "Best validation rec acc so far: 0.8934027552604675, epoch: 37\n",
            "=====Epoch 39\n",
            "Training...\n",
            "loss_dist 0.656, loss_coords 0.457, loss_res 0.143, : 100% 32/32 [00:24<00:00,  1.28it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.52it/s]\n",
            "Epoch 39, valid_edge_mae: 0.67310, Train_mae: 0.47226, Validation_mae: 0.46145, Validation_rmsd: 0.85892, res_acc: 0.92, kl_x: 0.00, kl_h: 0.00, elapse: 29.57665\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.8520761279816395, epoch: 31\n",
            "Best validation rec acc so far: 0.9181597232818604, epoch: 39\n",
            "=====Epoch 40\n",
            "Training...\n",
            "loss_dist 0.676, loss_coords 0.461, loss_res 0.115, : 100% 32/32 [00:24<00:00,  1.29it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.51it/s]\n",
            "Epoch 40, valid_edge_mae: 0.65982, Train_mae: 0.45138, Validation_mae: 0.45038, Validation_rmsd: 0.84786, res_acc: 0.94, kl_x: 0.00, kl_h: 0.00, elapse: 29.56962\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.8478584596591849, epoch: 40\n",
            "Best validation rec acc so far: 0.9429861307144165, epoch: 40\n",
            "=====Epoch 41\n",
            "Training...\n",
            "loss_dist 0.692, loss_coords 0.483, loss_res 0.233, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.49it/s]\n",
            "Epoch 41, valid_edge_mae: 0.67964, Train_mae: 0.47952, Validation_mae: 0.47261, Validation_rmsd: 0.86705, res_acc: 0.90, kl_x: 0.00, kl_h: 0.00, elapse: 29.28899\n",
            "Best validation RMSD so far: 0.8478584596591849, epoch: 40\n",
            "Best validation rec acc so far: 0.9429861307144165, epoch: 40\n",
            "=====Epoch 42\n",
            "Training...\n",
            "loss_dist 0.656, loss_coords 0.452, loss_res 0.130, : 100% 32/32 [00:24<00:00,  1.29it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.51it/s]\n",
            "Epoch 42, valid_edge_mae: 0.65610, Train_mae: 0.45647, Validation_mae: 0.44854, Validation_rmsd: 0.84358, res_acc: 0.95, kl_x: 0.00, kl_h: 0.00, elapse: 29.57367\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.8435770943874992, epoch: 42\n",
            "Best validation rec acc so far: 0.9467708468437195, epoch: 42\n",
            "=====Epoch 43\n",
            "Training...\n",
            "loss_dist 0.622, loss_coords 0.415, loss_res 0.061, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.50it/s]\n",
            "Epoch 43, valid_edge_mae: 0.64630, Train_mae: 0.44285, Validation_mae: 0.44073, Validation_rmsd: 0.83504, res_acc: 0.95, kl_x: 0.00, kl_h: 0.00, elapse: 29.32780\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.8350362970400407, epoch: 43\n",
            "Best validation rec acc so far: 0.9537500143051147, epoch: 43\n",
            "=====Epoch 44\n",
            "Training...\n",
            "loss_dist 0.666, loss_coords 0.467, loss_res 0.202, : 100% 32/32 [00:24<00:00,  1.29it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.50it/s]\n",
            "Epoch 44, valid_edge_mae: 0.66948, Train_mae: 0.45028, Validation_mae: 0.46189, Validation_rmsd: 0.85407, res_acc: 0.94, kl_x: 0.00, kl_h: 0.00, elapse: 29.51933\n",
            "Best validation RMSD so far: 0.8350362970400407, epoch: 43\n",
            "Best validation rec acc so far: 0.9537500143051147, epoch: 43\n",
            "=====Epoch 45\n",
            "Training...\n",
            "loss_dist 0.622, loss_coords 0.415, loss_res 0.073, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.40it/s]\n",
            "Epoch 45, valid_edge_mae: 0.63598, Train_mae: 0.43913, Validation_mae: 0.42782, Validation_rmsd: 0.82378, res_acc: 0.95, kl_x: 0.00, kl_h: 0.00, elapse: 29.64888\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.8237777949027404, epoch: 45\n",
            "Best validation rec acc so far: 0.9537500143051147, epoch: 43\n",
            "=====Epoch 46\n",
            "Training...\n",
            "loss_dist 0.630, loss_coords 0.420, loss_res 0.080, : 100% 32/32 [00:24<00:00,  1.31it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.50it/s]\n",
            "Epoch 46, valid_edge_mae: 0.62555, Train_mae: 0.42148, Validation_mae: 0.42115, Validation_rmsd: 0.81248, res_acc: 0.97, kl_x: 0.00, kl_h: 0.00, elapse: 29.21725\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.8124782217094448, epoch: 46\n",
            "Best validation rec acc so far: 0.9692361354827881, epoch: 46\n",
            "=====Epoch 47\n",
            "Training...\n",
            "loss_dist 0.662, loss_coords 0.455, loss_res 0.302, : 100% 32/32 [00:25<00:00,  1.28it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.50it/s]\n",
            "Epoch 47, valid_edge_mae: 0.65970, Train_mae: 0.42120, Validation_mae: 0.44926, Validation_rmsd: 0.84024, res_acc: 0.90, kl_x: 0.00, kl_h: 0.00, elapse: 29.73917\n",
            "Best validation RMSD so far: 0.8124782217094448, epoch: 46\n",
            "Best validation rec acc so far: 0.9692361354827881, epoch: 46\n",
            "=====Epoch 48\n",
            "Training...\n",
            "loss_dist 0.600, loss_coords 0.401, loss_res 0.057, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.50it/s]\n",
            "Epoch 48, valid_edge_mae: 0.61735, Train_mae: 0.42921, Validation_mae: 0.41419, Validation_rmsd: 0.80584, res_acc: 0.97, kl_x: 0.00, kl_h: 0.00, elapse: 29.28680\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.8058354128730456, epoch: 48\n",
            "Best validation rec acc so far: 0.9726389050483704, epoch: 48\n",
            "=====Epoch 49\n",
            "Training...\n",
            "loss_dist 0.594, loss_coords 0.390, loss_res 0.047, : 100% 32/32 [00:24<00:00,  1.29it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.51it/s]\n",
            "Epoch 49, valid_edge_mae: 0.59855, Train_mae: 0.40101, Validation_mae: 0.39575, Validation_rmsd: 0.78479, res_acc: 0.98, kl_x: 0.00, kl_h: 0.00, elapse: 29.57185\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.7847888877672504, epoch: 49\n",
            "Best validation rec acc so far: 0.979895830154419, epoch: 49\n",
            "=====Epoch 50\n",
            "Training...\n",
            "loss_dist 0.596, loss_coords 0.392, loss_res 0.038, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.51it/s]\n",
            "Epoch 50, valid_edge_mae: 0.59186, Train_mae: 0.38975, Validation_mae: 0.39084, Validation_rmsd: 0.77757, res_acc: 0.98, kl_x: 0.00, kl_h: 0.00, elapse: 29.35221\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.7775698446424494, epoch: 50\n",
            "Best validation rec acc so far: 0.979895830154419, epoch: 49\n",
            "=====Epoch 51\n",
            "Training...\n",
            "loss_dist 0.584, loss_coords 0.392, loss_res 0.047, : 100% 32/32 [00:24<00:00,  1.28it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.49it/s]\n",
            "Epoch 51, valid_edge_mae: 0.59378, Train_mae: 0.40085, Validation_mae: 0.39254, Validation_rmsd: 0.77868, res_acc: 0.98, kl_x: 0.00, kl_h: 0.00, elapse: 29.64940\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.7775698446424494, epoch: 50\n",
            "Best validation rec acc so far: 0.9817708134651184, epoch: 51\n",
            "=====Epoch 52\n",
            "Training...\n",
            "loss_dist 0.575, loss_coords 0.375, loss_res 0.024, : 100% 32/32 [00:25<00:00,  1.28it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.51it/s]\n",
            "Epoch 52, valid_edge_mae: 0.58219, Train_mae: 0.38497, Validation_mae: 0.38258, Validation_rmsd: 0.76904, res_acc: 0.99, kl_x: 0.00, kl_h: 0.00, elapse: 29.74095\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.769044084348647, epoch: 52\n",
            "Best validation rec acc so far: 0.9873611330986023, epoch: 52\n",
            "=====Epoch 53\n",
            "Training...\n",
            "loss_dist 0.575, loss_coords 0.379, loss_res 0.030, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.51it/s]\n",
            "Epoch 53, valid_edge_mae: 0.57519, Train_mae: 0.37697, Validation_mae: 0.37639, Validation_rmsd: 0.76075, res_acc: 0.99, kl_x: 0.00, kl_h: 0.00, elapse: 29.27130\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.7607534773421543, epoch: 53\n",
            "Best validation rec acc so far: 0.9880555272102356, epoch: 53\n",
            "=====Epoch 54\n",
            "Training...\n",
            "loss_dist 0.713, loss_coords 0.492, loss_res 0.621, : 100% 32/32 [00:24<00:00,  1.28it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.52it/s]\n",
            "Epoch 54, valid_edge_mae: 0.78746, Train_mae: 0.38350, Validation_mae: 0.54641, Validation_rmsd: 1.04940, res_acc: 0.84, kl_x: 0.00, kl_h: 0.00, elapse: 29.57187\n",
            "Best validation RMSD so far: 0.7607534773421543, epoch: 53\n",
            "Best validation rec acc so far: 0.9880555272102356, epoch: 53\n",
            "=====Epoch 55\n",
            "Training...\n",
            "loss_dist 0.673, loss_coords 0.464, loss_res 0.215, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.50it/s]\n",
            "Epoch 55, valid_edge_mae: 0.66365, Train_mae: 0.50360, Validation_mae: 0.45560, Validation_rmsd: 0.84915, res_acc: 0.91, kl_x: 0.00, kl_h: 0.00, elapse: 29.28876\n",
            "Best validation RMSD so far: 0.7607534773421543, epoch: 53\n",
            "Best validation rec acc so far: 0.9880555272102356, epoch: 53\n",
            "=====Epoch 56\n",
            "Training...\n",
            "loss_dist 0.603, loss_coords 0.406, loss_res 0.076, : 100% 32/32 [00:24<00:00,  1.28it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.50it/s]\n",
            "Epoch 56, valid_edge_mae: 0.60808, Train_mae: 0.42235, Validation_mae: 0.40422, Validation_rmsd: 0.79024, res_acc: 0.97, kl_x: 0.00, kl_h: 0.00, elapse: 29.69278\n",
            "Best validation RMSD so far: 0.7607534773421543, epoch: 53\n",
            "Best validation rec acc so far: 0.9880555272102356, epoch: 53\n",
            "=====Epoch 57\n",
            "Training...\n",
            "loss_dist 0.561, loss_coords 0.365, loss_res 0.033, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.50it/s]\n",
            "Epoch 57, valid_edge_mae: 0.58307, Train_mae: 0.39498, Validation_mae: 0.38535, Validation_rmsd: 0.76787, res_acc: 0.98, kl_x: 0.00, kl_h: 0.00, elapse: 29.34310\n",
            "Best validation RMSD so far: 0.7607534773421543, epoch: 53\n",
            "Best validation rec acc so far: 0.9880555272102356, epoch: 53\n",
            "=====Epoch 58\n",
            "Training...\n",
            "loss_dist 0.581, loss_coords 0.381, loss_res 0.030, : 100% 32/32 [00:24<00:00,  1.28it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.50it/s]\n",
            "Epoch 58, valid_edge_mae: 0.57600, Train_mae: 0.37683, Validation_mae: 0.37769, Validation_rmsd: 0.75748, res_acc: 0.99, kl_x: 0.00, kl_h: 0.00, elapse: 29.65941\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.7574792115596738, epoch: 58\n",
            "Best validation rec acc so far: 0.9880555272102356, epoch: 53\n",
            "=====Epoch 59\n",
            "Training...\n",
            "loss_dist 0.551, loss_coords 0.357, loss_res 0.026, : 100% 32/32 [00:24<00:00,  1.28it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.50it/s]\n",
            "Epoch 59, valid_edge_mae: 0.55899, Train_mae: 0.36867, Validation_mae: 0.36518, Validation_rmsd: 0.74197, res_acc: 0.99, kl_x: 0.00, kl_h: 0.00, elapse: 29.64781\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.741966494574647, epoch: 59\n",
            "Best validation rec acc so far: 0.9896875023841858, epoch: 59\n",
            "=====Epoch 60\n",
            "Training...\n",
            "loss_dist 0.554, loss_coords 0.358, loss_res 0.021, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.49it/s]\n",
            "Epoch 60, valid_edge_mae: 0.54856, Train_mae: 0.35782, Validation_mae: 0.35544, Validation_rmsd: 0.73129, res_acc: 0.99, kl_x: 0.00, kl_h: 0.00, elapse: 29.33504\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.7312859801449831, epoch: 60\n",
            "Best validation rec acc so far: 0.9896875023841858, epoch: 59\n",
            "=====Epoch 61\n",
            "Training...\n",
            "loss_dist 0.534, loss_coords 0.347, loss_res 0.023, : 100% 32/32 [00:24<00:00,  1.28it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.50it/s]\n",
            "Epoch 61, valid_edge_mae: 0.54440, Train_mae: 0.35006, Validation_mae: 0.35379, Validation_rmsd: 0.72473, res_acc: 0.99, kl_x: 0.00, kl_h: 0.00, elapse: 29.69704\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.72472792569426, epoch: 61\n",
            "Best validation rec acc so far: 0.9896875023841858, epoch: 59\n",
            "=====Epoch 62\n",
            "Training...\n",
            "loss_dist 0.532, loss_coords 0.345, loss_res 0.062, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.50it/s]\n",
            "Epoch 62, valid_edge_mae: 0.54181, Train_mae: 0.34870, Validation_mae: 0.36435, Validation_rmsd: 0.72800, res_acc: 0.98, kl_x: 0.00, kl_h: 0.00, elapse: 29.26484\n",
            "Best validation RMSD so far: 0.72472792569426, epoch: 61\n",
            "Best validation rec acc so far: 0.9896875023841858, epoch: 59\n",
            "=====Epoch 63\n",
            "Training...\n",
            "loss_dist 0.526, loss_coords 0.340, loss_res 0.023, : 100% 32/32 [00:25<00:00,  1.28it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.51it/s]\n",
            "Epoch 63, valid_edge_mae: 0.53160, Train_mae: 0.35448, Validation_mae: 0.34736, Validation_rmsd: 0.71026, res_acc: 0.99, kl_x: 0.00, kl_h: 0.00, elapse: 29.76861\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.7102618821200628, epoch: 63\n",
            "Best validation rec acc so far: 0.9896875023841858, epoch: 59\n",
            "=====Epoch 64\n",
            "Training...\n",
            "loss_dist 0.519, loss_coords 0.331, loss_res 0.023, : 100% 32/32 [00:24<00:00,  1.31it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:05<00:00,  1.40it/s]\n",
            "Epoch 64, valid_edge_mae: 0.51147, Train_mae: 0.33489, Validation_mae: 0.32996, Validation_rmsd: 0.69059, res_acc: 0.99, kl_x: 0.00, kl_h: 0.00, elapse: 29.45266\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.6905856577036085, epoch: 64\n",
            "Best validation rec acc so far: 0.9925000071525574, epoch: 64\n",
            "=====Epoch 65\n",
            "Training...\n",
            "loss_dist 0.494, loss_coords 0.316, loss_res 0.015, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.52it/s]\n",
            "Epoch 65, valid_edge_mae: 0.50584, Train_mae: 0.32328, Validation_mae: 0.32831, Validation_rmsd: 0.68683, res_acc: 0.99, kl_x: 0.00, kl_h: 0.00, elapse: 29.27331\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.686825544461839, epoch: 65\n",
            "Best validation rec acc so far: 0.9925000071525574, epoch: 64\n",
            "=====Epoch 66\n",
            "Training...\n",
            "loss_dist 0.489, loss_coords 0.307, loss_res 0.016, : 100% 32/32 [00:25<00:00,  1.28it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.51it/s]\n",
            "Epoch 66, valid_edge_mae: 0.50534, Train_mae: 0.32019, Validation_mae: 0.32163, Validation_rmsd: 0.68323, res_acc: 0.99, kl_x: 0.00, kl_h: 0.00, elapse: 29.67949\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.6832276110750573, epoch: 66\n",
            "Best validation rec acc so far: 0.9934375286102295, epoch: 66\n",
            "=====Epoch 67\n",
            "Training...\n",
            "loss_dist 0.501, loss_coords 0.321, loss_res 0.013, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.50it/s]\n",
            "Epoch 67, valid_edge_mae: 0.49654, Train_mae: 0.31532, Validation_mae: 0.31543, Validation_rmsd: 0.67572, res_acc: 0.99, kl_x: 0.00, kl_h: 0.00, elapse: 29.34286\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.6757193664811202, epoch: 67\n",
            "Best validation rec acc so far: 0.9935764074325562, epoch: 67\n",
            "=====Epoch 68\n",
            "Training...\n",
            "loss_dist 0.490, loss_coords 0.310, loss_res 0.011, : 100% 32/32 [00:24<00:00,  1.28it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.51it/s]\n",
            "Epoch 68, valid_edge_mae: 0.49174, Train_mae: 0.31256, Validation_mae: 0.30965, Validation_rmsd: 0.66969, res_acc: 0.99, kl_x: 0.00, kl_h: 0.00, elapse: 29.68019\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.6696907887492267, epoch: 68\n",
            "Best validation rec acc so far: 0.9938541650772095, epoch: 68\n",
            "=====Epoch 69\n",
            "Training...\n",
            "loss_dist 0.496, loss_coords 0.310, loss_res 0.022, : 100% 32/32 [00:24<00:00,  1.29it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.49it/s]\n",
            "Epoch 69, valid_edge_mae: 0.50203, Train_mae: 0.31268, Validation_mae: 0.32283, Validation_rmsd: 0.67453, res_acc: 0.99, kl_x: 0.00, kl_h: 0.00, elapse: 29.51225\n",
            "Best validation RMSD so far: 0.6696907887492267, epoch: 68\n",
            "Best validation rec acc so far: 0.9938541650772095, epoch: 68\n",
            "=====Epoch 70\n",
            "Training...\n",
            "loss_dist 0.749, loss_coords 0.528, loss_res 0.433, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.52it/s]\n",
            "Epoch 70, valid_edge_mae: 0.73959, Train_mae: 0.43957, Validation_mae: 0.51991, Validation_rmsd: 0.94817, res_acc: 0.78, kl_x: 0.00, kl_h: 0.00, elapse: 29.30243\n",
            "Best validation RMSD so far: 0.6696907887492267, epoch: 68\n",
            "Best validation rec acc so far: 0.9938541650772095, epoch: 68\n",
            "=====Epoch 71\n",
            "Training...\n",
            "loss_dist 0.659, loss_coords 0.448, loss_res 0.246, : 100% 32/32 [00:24<00:00,  1.32it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.52it/s]\n",
            "Epoch 71, valid_edge_mae: 0.65202, Train_mae: 0.47671, Validation_mae: 0.44419, Validation_rmsd: 0.84270, res_acc: 0.88, kl_x: 0.00, kl_h: 0.00, elapse: 28.95148\n",
            "Best validation RMSD so far: 0.6696907887492267, epoch: 68\n",
            "Best validation rec acc so far: 0.9938541650772095, epoch: 68\n",
            "=====Epoch 72\n",
            "Training...\n",
            "loss_dist 0.589, loss_coords 0.391, loss_res 0.144, : 100% 32/32 [00:24<00:00,  1.31it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 72, valid_edge_mae: 0.62129, Train_mae: 0.42877, Validation_mae: 0.41669, Validation_rmsd: 0.81055, res_acc: 0.93, kl_x: 0.00, kl_h: 0.00, elapse: 29.13844\n",
            "Best validation RMSD so far: 0.6696907887492267, epoch: 68\n",
            "Best validation rec acc so far: 0.9938541650772095, epoch: 68\n",
            "=====Epoch 73\n",
            "Training...\n",
            "loss_dist 0.599, loss_coords 0.400, loss_res 0.096, : 100% 32/32 [00:24<00:00,  1.32it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.41it/s]\n",
            "Epoch 73, valid_edge_mae: 0.59659, Train_mae: 0.40742, Validation_mae: 0.40310, Validation_rmsd: 0.78815, res_acc: 0.96, kl_x: 0.00, kl_h: 0.00, elapse: 29.25762\n",
            "Best validation RMSD so far: 0.6696907887492267, epoch: 68\n",
            "Best validation rec acc so far: 0.9938541650772095, epoch: 68\n",
            "=====Epoch 74\n",
            "Training...\n",
            "loss_dist 0.580, loss_coords 0.385, loss_res 0.062, : 100% 32/32 [00:24<00:00,  1.31it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.52it/s]\n",
            "Epoch 74, valid_edge_mae: 0.57872, Train_mae: 0.39311, Validation_mae: 0.38262, Validation_rmsd: 0.76819, res_acc: 0.96, kl_x: 0.00, kl_h: 0.00, elapse: 29.02041\n",
            "Best validation RMSD so far: 0.6696907887492267, epoch: 68\n",
            "Best validation rec acc so far: 0.9938541650772095, epoch: 68\n",
            "=====Epoch 75\n",
            "Training...\n",
            "loss_dist 0.558, loss_coords 0.366, loss_res 0.037, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 75, valid_edge_mae: 0.56596, Train_mae: 0.37485, Validation_mae: 0.36863, Validation_rmsd: 0.75246, res_acc: 0.98, kl_x: 0.00, kl_h: 0.00, elapse: 29.15822\n",
            "Best validation RMSD so far: 0.6696907887492267, epoch: 68\n",
            "Best validation rec acc so far: 0.9938541650772095, epoch: 68\n",
            "=====Epoch 76\n",
            "Training...\n",
            "loss_dist 0.567, loss_coords 0.369, loss_res 0.054, : 100% 32/32 [00:24<00:00,  1.32it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.52it/s]\n",
            "Epoch 76, valid_edge_mae: 0.56219, Train_mae: 0.36358, Validation_mae: 0.36826, Validation_rmsd: 0.75201, res_acc: 0.97, kl_x: 0.00, kl_h: 0.00, elapse: 28.85555\n",
            "Best validation RMSD so far: 0.6696907887492267, epoch: 68\n",
            "Best validation rec acc so far: 0.9938541650772095, epoch: 68\n",
            "=====Epoch 77\n",
            "Training...\n",
            "loss_dist 0.610, loss_coords 0.417, loss_res 0.189, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 77, valid_edge_mae: 0.61869, Train_mae: 0.40606, Validation_mae: 0.42070, Validation_rmsd: 0.80569, res_acc: 0.92, kl_x: 0.00, kl_h: 0.00, elapse: 29.25483\n",
            "Best validation RMSD so far: 0.6696907887492267, epoch: 68\n",
            "Best validation rec acc so far: 0.9938541650772095, epoch: 68\n",
            "=====Epoch 78\n",
            "Training...\n",
            "loss_dist 0.568, loss_coords 0.369, loss_res 0.065, : 100% 32/32 [00:24<00:00,  1.31it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.49it/s]\n",
            "Epoch 78, valid_edge_mae: 0.55583, Train_mae: 0.38464, Validation_mae: 0.36211, Validation_rmsd: 0.73814, res_acc: 0.97, kl_x: 0.00, kl_h: 0.00, elapse: 29.21109\n",
            "Best validation RMSD so far: 0.6696907887492267, epoch: 68\n",
            "Best validation rec acc so far: 0.9938541650772095, epoch: 68\n",
            "=====Epoch 79\n",
            "Training...\n",
            "loss_dist 0.536, loss_coords 0.346, loss_res 0.032, : 100% 32/32 [00:25<00:00,  1.28it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.51it/s]\n",
            "Epoch 79, valid_edge_mae: 0.53973, Train_mae: 0.35117, Validation_mae: 0.34695, Validation_rmsd: 0.72788, res_acc: 0.99, kl_x: 0.00, kl_h: 0.00, elapse: 29.71221\n",
            "Best validation RMSD so far: 0.6696907887492267, epoch: 68\n",
            "Best validation rec acc so far: 0.9938541650772095, epoch: 68\n",
            "=====Epoch 80\n",
            "Training...\n",
            "loss_dist 0.517, loss_coords 0.329, loss_res 0.027, : 100% 32/32 [00:24<00:00,  1.32it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 80, valid_edge_mae: 0.53255, Train_mae: 0.34135, Validation_mae: 0.33957, Validation_rmsd: 0.71987, res_acc: 0.99, kl_x: 0.00, kl_h: 0.00, elapse: 28.89311\n",
            "Best validation RMSD so far: 0.6696907887492267, epoch: 68\n",
            "Best validation rec acc so far: 0.9938541650772095, epoch: 68\n",
            "=====Epoch 81\n",
            "Training...\n",
            "loss_dist 0.530, loss_coords 0.337, loss_res 0.014, : 100% 32/32 [00:24<00:00,  1.28it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.52it/s]\n",
            "Epoch 81, valid_edge_mae: 0.53111, Train_mae: 0.33621, Validation_mae: 0.33662, Validation_rmsd: 0.71546, res_acc: 0.99, kl_x: 0.00, kl_h: 0.00, elapse: 29.65626\n",
            "Best validation RMSD so far: 0.6696907887492267, epoch: 68\n",
            "Best validation rec acc so far: 0.9938541650772095, epoch: 68\n",
            "=====Epoch 82\n",
            "Training...\n",
            "loss_dist 0.533, loss_coords 0.338, loss_res 0.014, : 100% 32/32 [00:24<00:00,  1.32it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.42it/s]\n",
            "Epoch 82, valid_edge_mae: 0.52860, Train_mae: 0.33434, Validation_mae: 0.33790, Validation_rmsd: 0.71341, res_acc: 0.99, kl_x: 0.00, kl_h: 0.00, elapse: 29.16993\n",
            "Best validation RMSD so far: 0.6696907887492267, epoch: 68\n",
            "Best validation rec acc so far: 0.9938541650772095, epoch: 68\n",
            "=====Epoch 83\n",
            "Training...\n",
            "loss_dist 0.493, loss_coords 0.308, loss_res 0.017, : 100% 32/32 [00:24<00:00,  1.32it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 83, valid_edge_mae: 0.52675, Train_mae: 0.33057, Validation_mae: 0.33299, Validation_rmsd: 0.70951, res_acc: 0.99, kl_x: 0.00, kl_h: 0.00, elapse: 28.77732\n",
            "Best validation RMSD so far: 0.6696907887492267, epoch: 68\n",
            "Best validation rec acc so far: 0.9938541650772095, epoch: 68\n",
            "=====Epoch 84\n",
            "Training...\n",
            "loss_dist 0.519, loss_coords 0.330, loss_res 0.016, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.52it/s]\n",
            "Epoch 84, valid_edge_mae: 0.51831, Train_mae: 0.33008, Validation_mae: 0.32619, Validation_rmsd: 0.70194, res_acc: 0.99, kl_x: 0.00, kl_h: 0.00, elapse: 29.25283\n",
            "Best validation RMSD so far: 0.6696907887492267, epoch: 68\n",
            "Best validation rec acc so far: 0.9938541650772095, epoch: 68\n",
            "=====Epoch 85\n",
            "Training...\n",
            "loss_dist 0.621, loss_coords 0.417, loss_res 0.130, : 100% 32/32 [00:24<00:00,  1.32it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 85, valid_edge_mae: 0.61660, Train_mae: 0.42302, Validation_mae: 0.41471, Validation_rmsd: 0.79575, res_acc: 0.95, kl_x: 0.00, kl_h: 0.00, elapse: 28.79837\n",
            "Best validation RMSD so far: 0.6696907887492267, epoch: 68\n",
            "Best validation rec acc so far: 0.9938541650772095, epoch: 68\n",
            "=====Epoch 86\n",
            "Training...\n",
            "loss_dist 0.562, loss_coords 0.360, loss_res 0.066, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.52it/s]\n",
            "Epoch 86, valid_edge_mae: 0.54126, Train_mae: 0.37047, Validation_mae: 0.34997, Validation_rmsd: 0.72680, res_acc: 0.97, kl_x: 0.00, kl_h: 0.00, elapse: 29.24387\n",
            "Best validation RMSD so far: 0.6696907887492267, epoch: 68\n",
            "Best validation rec acc so far: 0.9938541650772095, epoch: 68\n",
            "=====Epoch 87\n",
            "Training...\n",
            "loss_dist 0.536, loss_coords 0.342, loss_res 0.043, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.50it/s]\n",
            "Epoch 87, valid_edge_mae: 0.52962, Train_mae: 0.34187, Validation_mae: 0.33706, Validation_rmsd: 0.71559, res_acc: 0.99, kl_x: 0.00, kl_h: 0.00, elapse: 29.26410\n",
            "Best validation RMSD so far: 0.6696907887492267, epoch: 68\n",
            "Best validation rec acc so far: 0.9938541650772095, epoch: 68\n",
            "=====Epoch 88\n",
            "Training...\n",
            "loss_dist 0.525, loss_coords 0.331, loss_res 0.026, : 100% 32/32 [00:24<00:00,  1.29it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.52it/s]\n",
            "Epoch 88, valid_edge_mae: 0.52368, Train_mae: 0.33394, Validation_mae: 0.33173, Validation_rmsd: 0.70829, res_acc: 0.99, kl_x: 0.00, kl_h: 0.00, elapse: 29.45439\n",
            "Best validation RMSD so far: 0.6696907887492267, epoch: 68\n",
            "Best validation rec acc so far: 0.9938541650772095, epoch: 68\n",
            "=====Epoch 89\n",
            "Training...\n",
            "loss_dist 0.519, loss_coords 0.329, loss_res 0.021, : 100% 32/32 [00:24<00:00,  1.32it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 89, valid_edge_mae: 0.51720, Train_mae: 0.32859, Validation_mae: 0.32716, Validation_rmsd: 0.70174, res_acc: 0.99, kl_x: 0.00, kl_h: 0.00, elapse: 28.94106\n",
            "Best validation RMSD so far: 0.6696907887492267, epoch: 68\n",
            "Best validation rec acc so far: 0.9938541650772095, epoch: 68\n",
            "=====Epoch 90\n",
            "Training...\n",
            "loss_dist 0.494, loss_coords 0.309, loss_res 0.015, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.52it/s]\n",
            "Epoch 90, valid_edge_mae: 0.50876, Train_mae: 0.32346, Validation_mae: 0.32095, Validation_rmsd: 0.69063, res_acc: 0.99, kl_x: 0.00, kl_h: 0.00, elapse: 29.28692\n",
            "Best validation RMSD so far: 0.6696907887492267, epoch: 68\n",
            "Best validation rec acc so far: 0.9938541650772095, epoch: 68\n",
            "=====Epoch 91\n",
            "Training...\n",
            "loss_dist 0.500, loss_coords 0.316, loss_res 0.018, : 100% 32/32 [00:24<00:00,  1.31it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 91, valid_edge_mae: 0.50082, Train_mae: 0.31668, Validation_mae: 0.31712, Validation_rmsd: 0.68053, res_acc: 0.99, kl_x: 0.00, kl_h: 0.00, elapse: 29.08230\n",
            "Best validation RMSD so far: 0.6696907887492267, epoch: 68\n",
            "Best validation rec acc so far: 0.9938541650772095, epoch: 68\n",
            "=====Epoch 92\n",
            "Training...\n",
            "loss_dist 0.500, loss_coords 0.313, loss_res 0.018, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.52it/s]\n",
            "Epoch 92, valid_edge_mae: 0.49250, Train_mae: 0.31246, Validation_mae: 0.31037, Validation_rmsd: 0.67271, res_acc: 0.99, kl_x: 0.00, kl_h: 0.00, elapse: 29.35064\n",
            "Best validation RMSD so far: 0.6696907887492267, epoch: 68\n",
            "Best validation rec acc so far: 0.9938541650772095, epoch: 68\n",
            "=====Epoch 93\n",
            "Training...\n",
            "loss_dist 0.490, loss_coords 0.304, loss_res 0.008, : 100% 32/32 [00:24<00:00,  1.31it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 93, valid_edge_mae: 0.48825, Train_mae: 0.30722, Validation_mae: 0.30703, Validation_rmsd: 0.66896, res_acc: 0.99, kl_x: 0.00, kl_h: 0.00, elapse: 28.99885\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.6689628775061442, epoch: 93\n",
            "Best validation rec acc so far: 0.9945833086967468, epoch: 93\n",
            "=====Epoch 94\n",
            "Training...\n",
            "loss_dist 0.485, loss_coords 0.301, loss_res 0.016, : 100% 32/32 [00:24<00:00,  1.31it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.51it/s]\n",
            "Epoch 94, valid_edge_mae: 0.48374, Train_mae: 0.30150, Validation_mae: 0.30038, Validation_rmsd: 0.66380, res_acc: 1.00, kl_x: 0.00, kl_h: 0.00, elapse: 29.12204\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.6638044979017786, epoch: 94\n",
            "Best validation rec acc so far: 0.9950346946716309, epoch: 94\n",
            "=====Epoch 95\n",
            "Training...\n",
            "loss_dist 0.461, loss_coords 0.280, loss_res 0.009, : 100% 32/32 [00:24<00:00,  1.28it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.51it/s]\n",
            "Epoch 95, valid_edge_mae: 0.48026, Train_mae: 0.29580, Validation_mae: 0.29648, Validation_rmsd: 0.66010, res_acc: 1.00, kl_x: 0.00, kl_h: 0.00, elapse: 29.61875\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.6601014886469878, epoch: 95\n",
            "Best validation rec acc so far: 0.9952083230018616, epoch: 95\n",
            "=====Epoch 96\n",
            "Training...\n",
            "loss_dist 0.482, loss_coords 0.297, loss_res 0.017, : 100% 32/32 [00:24<00:00,  1.31it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.50it/s]\n",
            "Epoch 96, valid_edge_mae: 0.47872, Train_mae: 0.29404, Validation_mae: 0.29391, Validation_rmsd: 0.65685, res_acc: 0.99, kl_x: 0.00, kl_h: 0.00, elapse: 29.14235\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.6568542834190648, epoch: 96\n",
            "Best validation rec acc so far: 0.9952083230018616, epoch: 95\n",
            "=====Epoch 97\n",
            "Training...\n",
            "loss_dist 0.467, loss_coords 0.283, loss_res 0.015, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.52it/s]\n",
            "Epoch 97, valid_edge_mae: 0.47562, Train_mae: 0.29208, Validation_mae: 0.29313, Validation_rmsd: 0.65270, res_acc: 0.99, kl_x: 0.00, kl_h: 0.00, elapse: 29.20229\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Best validation RMSD so far: 0.652704807351133, epoch: 97\n",
            "Best validation rec acc so far: 0.9952083230018616, epoch: 95\n",
            "=====Epoch 98\n",
            "Training...\n",
            "loss_dist 0.473, loss_coords 0.291, loss_res 0.011, : 100% 32/32 [00:24<00:00,  1.32it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.53it/s]\n",
            "Epoch 98, valid_edge_mae: 0.47122, Train_mae: 0.28938, Validation_mae: 0.28796, Validation_rmsd: 0.64764, res_acc: 1.00, kl_x: 0.00, kl_h: 0.00, elapse: 28.84079\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.6476356221590689, epoch: 98\n",
            "Best validation rec acc so far: 0.9963541626930237, epoch: 98\n",
            "=====Epoch 99\n",
            "Training...\n",
            "loss_dist 0.470, loss_coords 0.288, loss_res 0.004, : 100% 32/32 [00:24<00:00,  1.30it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.50it/s]\n",
            "Epoch 99, valid_edge_mae: 0.46646, Train_mae: 0.28622, Validation_mae: 0.28607, Validation_rmsd: 0.64144, res_acc: 1.00, kl_x: 0.00, kl_h: 0.00, elapse: 29.26570\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.6414441611084305, epoch: 99\n",
            "Best validation rec acc so far: 0.9968055486679077, epoch: 99\n",
            "=====Epoch 100\n",
            "Training...\n",
            "loss_dist 0.469, loss_coords 0.283, loss_res 0.012, : 100% 32/32 [00:24<00:00,  1.31it/s]\n",
            "Evaluating...\n",
            "Iteration: 100% 7/7 [00:04<00:00,  1.52it/s]\n",
            "Epoch 100, valid_edge_mae: 0.46462, Train_mae: 0.28182, Validation_mae: 0.28377, Validation_rmsd: 0.63686, res_acc: 1.00, kl_x: 0.00, kl_h: 0.00, elapse: 29.09851\n",
            "Saving checkpoint...\n",
            "Analyzing...\n",
            "Saving checkpoint...\n",
            "Best validation RMSD so far: 0.6368603380458542, epoch: 100\n",
            "Best validation rec acc so far: 0.9973958134651184, epoch: 100\n"
          ]
        }
      ],
      "source": [
        "! python LatentLattice/train.py --mp_steps 3 --batch_size 32 --debug --layers 2 --edgeloss_weight 0.0 --epochs 100"
      ]
    }
  ],
  "metadata": {
    "accelerator": "GPU",
    "colab": {
      "gpuType": "A100",
      "machine_shape": "hm",
      "provenance": []
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}