jupyter_notebooks/regression/siren_reg_base_spec.ipynb

{"cells":[{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"5cc7AuO2pbRS","outputId":"54d98ae5-2d3f-4708-a435-8506d1df4cd0"},"outputs":[{"output_type":"stream","name":"stdout","text":["Requirement already satisfied: tensorflow_addons in /usr/local/lib/python3.10/dist-packages (0.23.0)\n","Requirement already satisfied: packaging in /usr/local/lib/python3.10/dist-packages (from tensorflow_addons) (23.2)\n","Requirement already satisfied: typeguard<3.0.0,>=2.7 in /usr/local/lib/python3.10/dist-packages (from tensorflow_addons) (2.13.3)\n","Requirement already satisfied: keras-tuner in /usr/local/lib/python3.10/dist-packages (1.4.6)\n","Requirement already satisfied: keras in /usr/local/lib/python3.10/dist-packages (from keras-tuner) (2.15.0)\n","Requirement already satisfied: packaging in /usr/local/lib/python3.10/dist-packages (from keras-tuner) (23.2)\n","Requirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (from keras-tuner) (2.31.0)\n","Requirement already satisfied: kt-legacy in /usr/local/lib/python3.10/dist-packages (from keras-tuner) (1.0.5)\n","Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests->keras-tuner) (3.3.2)\n","Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests->keras-tuner) (3.6)\n","Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests->keras-tuner) (2.0.7)\n","Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests->keras-tuner) (2024.2.2)\n","fatal: destination path 'Siren' already exists and is not an empty directory.\n"]}],"source":["!pip install --upgrade keras==2.15.0\n","!pip install --upgrade tensorflow==2.15.0.post1\n","!pip install --upgrade scipy==1.11.4\n","!pip install tensorflow-addons==0.21.0\n","!pip install keras-tuner --upgrade\n","\n","# clone siren repository, refresh folder to see the siren repository\n","# runtime -> change runtime -> choose a gpu/tpu\n","!git clone https://github.com/hubtru/Siren/"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"ptr8TjdKpakk","outputId":"8447e2d3-b49c-4702-d391-d958a19d832c"},"outputs":[{"output_type":"stream","name":"stderr","text":["/usr/local/lib/python3.10/dist-packages/tensorflow_addons/utils/tfa_eol_msg.py:23: UserWarning: \n","\n","TensorFlow Addons (TFA) has ended development and introduction of new features.\n","TFA has entered a minimal maintenance and release mode until a planned end of life in May 2024.\n","Please modify downstream libraries to take dependencies from other repositories in our TensorFlow community (e.g. Keras, Keras-CV, and Keras-NLP). \n","\n","For more information see: https://github.com/tensorflow/addons/issues/2807 \n","\n","  warnings.warn(\n"]}],"source":["import numpy as np\n","import pandas as pd\n","import tensorflow as tf\n","import tensorflow_addons as tfa\n","import matplotlib.pyplot as plt\n","import seaborn as sns\n","from tensorflow import keras as k\n","from keras import layers\n","from sklearn.model_selection import train_test_split\n","import cv2\n","import os\n","\n","os.environ[\"CUDA_VISIBLE_DEVICES\"]=\"1\""]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"gnZMlq8spakl","outputId":"090da619-e0d6-4a56-e4cb-09929bfa14ea"},"outputs":[{"output_type":"stream","name":"stdout","text":["Num GPUs Available:  0\n","GPUs:  []\n"]}],"source":["# ============================== gpu info ==============================\n","print(\"Num GPUs Available: \", len(tf.config.list_physical_devices(\"GPU\")))\n","print(\"GPUs: \", tf.config.list_physical_devices(\"GPU\"))"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"GJcTwDKRpakm"},"outputs":[],"source":["# ============================== variables ==============================\n","# architecture\n","image_size = 256\n","filters = 256\n","depth = 4\n","columns = 4\n","kernel_size = 5\n","patch_size = 16\n","num_classes = 3\n","\n","in_channel = 9\n","img_rows, img_cols = image_size, image_size\n","input_shape = (img_rows, img_cols, in_channel)\n","\n","learning_rate = 0.001\n","weight_decay = 0.0001\n","batch_size = 8\n","epochs = 100"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"HLFGU4Y3pakm"},"outputs":[],"source":["# ============================== paths ==============================\n","# needed for generate_data\n","modality = \"spec\"\n","exp_name = f\"siren_reg\"\n","sub_exp_name = f\"base\"\n","model_name = f\"{exp_name}_{sub_exp_name}_{modality}\"\n","model_save_path = f\"{model_name}.h5\"\n","\n","# dataset\n","csv_path = \"/content/Siren/dataset/labels_reg_sample.csv\"\n","spec_path = f\"/content/Siren/dataset/{modality}\""]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"VL4wfsGjpakm","outputId":"ef1965cd-7789-4503-c19d-edb5f7cb33d1"},"outputs":[{"output_type":"stream","name":"stdout","text":["size check train/test/val 14 3 3 20\n"]}],"source":["# ============================== load/prepare dataset ==============================\n","df = pd.read_csv(csv_path)\n","\n","# RANDOM DATASET: we switch to toolbased\n","# shuffle, need same state for tool/spec/chips/multi\n","np.random.seed(55)\n","df = df.iloc[np.random.permutation(len(df))]\n","# train/test/val : 70/15/15\n","train_df, test_df = train_test_split(df, test_size=0.3)\n","test_df, val_df = train_test_split(test_df, test_size=0.5)\n","\n","print(\n","    \"size check train/test/val\",\n","    len(train_df),\n","    len(test_df),\n","    len(val_df),\n","    (len(train_df) + len(test_df) + len(val_df)),\n",")\n","\n","train_df[\"spec_x\"] = train_df.id.map(lambda id: f\"{spec_path}/x/{id}.jpg\")\n","test_df[\"spec_x\"] = test_df.id.map(lambda id: f\"{spec_path}/x/{id}.jpg\")\n","val_df[\"spec_x\"] = val_df.id.map(lambda id: f\"{spec_path}/x/{id}.jpg\")\n","\n","train_df[\"spec_y\"] = train_df.id.map(lambda id: f\"{spec_path}/y/{id}.jpg\")\n","test_df[\"spec_y\"] = test_df.id.map(lambda id: f\"{spec_path}/y/{id}.jpg\")\n","val_df[\"spec_y\"] = val_df.id.map(lambda id: f\"{spec_path}/y/{id}.jpg\")\n","\n","train_df[\"spec_z\"] = train_df.id.map(lambda id: f\"{spec_path}/z/{id}.jpg\")\n","test_df[\"spec_z\"] = test_df.id.map(lambda id: f\"{spec_path}/z/{id}.jpg\")\n","val_df[\"spec_z\"] = val_df.id.map(lambda id: f\"{spec_path}/z/{id}.jpg\")\n"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":546},"id":"bCXzwXthpakm","outputId":"abbed54e-fcb6-44d0-82ed-831f6dc5ae6f"},"outputs":[{"output_type":"display_data","data":{"text/plain":["<Figure size 600x600 with 0 Axes>"]},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["<Figure size 500x500 with 1 Axes>"],"image/png":"iVBORw0KGgoAAAANSUhEUgAAAeoAAAIACAYAAABNWi9DAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/bCgiHAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAvBUlEQVR4nO3deVzVdb7H8fcR5IgKuKKi4FKuKGWiXlNHU8scl2zPUSMrmwpza5yixkwdQ6dcykyrW9rNzKyrZpaauzW5IOZCuZaKmUpugNvRON/7R+O5HsEUQn5f8PV8PM7j0e93fvzO50szvDq7yxhjBAAArFTM6QEAAMClEWoAACxGqAEAsBihBgDAYoQaAACLEWoAACxGqAEAsBihBgDAYoQaAACLEWogn+zZs0cul0uvvPJKvp1zxYoVcrlcWrFiRb6d87wXX3xRLpcr38+bk7Zt26pt27a+7fPr+uSTTwrk9h966CHVqFGjQG4LyG+EGte0adOmyeVyaf369U6P8oecX8f5S4kSJRQREaGOHTvqtddeU2ZmZr7czs8//6wXX3xRGzduzJfz5SebZwP+CEINFCEjRozQ+++/r8mTJ+upp56SJA0cOFCNGjXS5s2b/Y79xz/+odOnT+fq/D///LOGDx+e6xh++eWX+vLLL3P1M7n1e7O9/fbb2r59+1W9feBqCXR6AAD5p1OnToqNjfVtJyQkaNmyZerSpYu6deumrVu3Kjg4WJIUGBiowMCr+yfg1KlTKlmypIKCgq7q7VxO8eLFHb194I/gHjVwGWfPntULL7ygJk2aKCwsTKVKlVLr1q21fPnyS/7M+PHjVb16dQUHB6tNmzZKSUnJdsy2bdt0zz33qFy5cipRooRiY2M1b968fJ+/Xbt2Gjp0qPbu3avp06f79uf0HPXixYvVqlUrlSlTRqVLl1bdunX13HPPSfrteeWmTZtKkvr06eN7mH3atGmSfnseumHDhkpOTtaf/vQnlSxZ0vezFz9HfV5WVpaee+45Va5cWaVKlVK3bt20b98+v2Nq1Kihhx56KNvPXnjOy82W03PUJ0+e1NNPP63IyEi53W7VrVtXr7zyii7+QkGXy6V+/fpp7ty5atiwodxut6Kjo7Vw4cKcf+FAPuMeNXAZGRkZ+u///m/16NFDffv2VWZmpt555x117NhR69at04033uh3/P/8z/8oMzNT8fHxOnPmjF599VW1a9dOW7ZsUaVKlSRJ3333nVq2bKmqVavq2WefValSpTRr1ix1795d//u//6s777wzX9fQu3dvPffcc/ryyy/Vt2/fHI/57rvv1KVLF8XExGjEiBFyu93atWuX/v3vf0uS6tevrxEjRuiFF17QY489ptatW0uSbr75Zt85jhw5ok6dOumBBx5Qr169fOu9lFGjRsnlcumZZ55RWlqaJkyYoA4dOmjjxo2+e/5X4kpmu5AxRt26ddPy5cv1yCOP6MYbb9SiRYs0ZMgQ7d+/X+PHj/c7/uuvv9bs2bP15JNPKiQkRK+99pruvvtupaamqnz58lc8J5AnBriGTZ061UgySUlJlzzm119/NR6Px2/fsWPHTKVKlczDDz/s27d7924jyQQHB5uffvrJt3/t2rVGkhk0aJBvX/v27U2jRo3MmTNnfPu8Xq+5+eabTe3atX37li9fbiSZ5cuX/+F1hIWFmcaNG/u2hw0bZi78EzB+/Hgjyfzyyy+XPEdSUpKRZKZOnZrtujZt2hhJZsqUKTle16ZNm2zrqlq1qsnIyPDtnzVrlpFkXn31Vd++6tWrm7i4uMue8/dmi4uLM9WrV/dtz50710gy//znP/2Ou+eee4zL5TK7du3y7ZNkgoKC/PZt2rTJSDITJ07MdltAfuOhb+AyAgICfM+xer1eHT16VL/++qtiY2O1YcOGbMd3795dVatW9W03a9ZMzZs31xdffCFJOnr0qJYtW6b77rtPmZmZOnz4sA4fPqwjR46oY8eO2rlzp/bv35/v6yhduvTvvvq7TJkykqRPP/1UXq83T7fhdrvVp0+fKz7+wQcfVEhIiG/7nnvuUZUqVXy/q6vliy++UEBAgPr37++3/+mnn5YxRgsWLPDb36FDB1133XW+7ZiYGIWGhurHH3+8qnMCEs9RA1fkvffeU0xMjEqUKKHy5curYsWK+vzzz5Wenp7t2Nq1a2fbV6dOHe3Zs0eStGvXLhljNHToUFWsWNHvMmzYMElSWlpavq/hxIkTflG82P3336+WLVvq0UcfVaVKlfTAAw9o1qxZuYp21apVc/XCsYt/Vy6XS9dff73vd3W17N27VxEREdl+H/Xr1/ddf6GoqKhs5yhbtqyOHTt29YYE/oPnqIHLmD59uh566CF1795dQ4YMUXh4uAICApSYmKgffvgh1+c7H76//e1v6tixY47HXH/99X9o5ov99NNPSk9P/93zBgcHa9WqVVq+fLk+//xzLVy4UB999JHatWunL7/8UgEBAZe9ndw8r3ylLvWhLFlZWVc0U3641O2Yi154BlwNhBq4jE8++US1atXS7Nmz/aJx/t7vxXbu3Jlt344dO3yvOq5Vq5ak394y1KFDh/wfOAfvv/++JF3yPwzOK1asmNq3b6/27dtr3Lhxeumll/T8889r+fLl6tChQ75/ktnFvytjjHbt2qWYmBjfvrJly+r48ePZfnbv3r2+36V06aDnpHr16lqyZIkyMzP97lVv27bNdz1gCx76Bi7j/L2pC+89rV27VqtXr87x+Llz5/o9x7xu3TqtXbtWnTp1kiSFh4erbdu2evPNN3XgwIFsP//LL7/k5/hatmyZRo4cqZo1a6pnz56XPO7o0aPZ9p1/RbvH45EklSpVSpJyDGdenH+F/HmffPKJDhw44PtdSdJ1112nNWvW6OzZs7598+fPz/Y2rtzM9uc//1lZWVl6/fXX/faPHz9eLpfL7/YBp3GPGpD07rvv5vi+2AEDBqhLly6aPXu27rzzTnXu3Fm7d+/WlClT1KBBA504cSLbz1x//fVq1aqVnnjiCXk8Hk2YMEHly5fX3//+d98xkyZNUqtWrdSoUSP17dtXtWrV0qFDh7R69Wr99NNP2rRpU57WsWDBAm3btk2//vqrDh06pGXLlmnx4sWqXr265s2bpxIlSlzyZ0eMGKFVq1apc+fOql69utLS0vTGG2+oWrVqatWqlaTfolmmTBlNmTJFISEhKlWqlJo3b66aNWvmad5y5cqpVatW6tOnjw4dOqQJEybo+uuv93sL2aOPPqpPPvlEt99+u+677z798MMPmj59ut+Lu3I7W9euXXXLLbfo+eef1549e3TDDTfoyy+/1KeffqqBAwdmOzfgKEdfcw447Pzbmi512bdvn/F6veall14y1atXN2632zRu3NjMnz8/21t+zr896+WXXzZjx441kZGRxu12m9atW5tNmzZlu+0ffvjBPPjgg6Zy5cqmePHipmrVqqZLly7mk08+8R2T27dnnb8EBQWZypUrm1tvvdW8+uqrfm+BOu/it2ctXbrU3HHHHSYiIsIEBQWZiIgI06NHD7Njxw6/n/v0009NgwYNTGBgoN/bodq0aWOio6NznO9Sb8/68MMPTUJCggkPDzfBwcGmc+fOZu/evdl+fuzYsaZq1arG7Xabli1bmvXr12c75+/NdvG/K2OMyczMNIMGDTIRERGmePHipnbt2ubll182Xq/X7zhJJj4+PttMl3rbGJDfXMbwaggAAGzFc9QAAFiMUAMAYDFCDQCAxQg1AAAWI9QAAFiMUAMAYLFCHWpjjDIyMvi8XQBAkVWoQ52ZmamwsLDf/eo+AAAKs0IdagAAijpCDQCAxQg1AAAWI9QAAFiMUAMAYDFCDQCAxQg1AAAWI9QAAFiMUAMAYDFCDQCAxQg1AAAWI9QAAFiMUAMAYDFCDQCAxQg1AAAWczTUWVlZGjp0qGrWrKng4GBdd911GjlypIwxTo4FAIA1Ap288TFjxmjy5Ml67733FB0drfXr16tPnz4KCwtT//79nRwNAAArOBrqb775RnfccYc6d+4sSapRo4Y+/PBDrVu3zsmxAACwhqOhvvnmm/XWW29px44dqlOnjjZt2qSvv/5a48aNy/F4j8cjj8fj287IyMj3mVJTU3X48OF8P68kVahQQVFRUVfl3ACAosnRUD/77LPKyMhQvXr1FBAQoKysLI0aNUo9e/bM8fjExEQNHz78qs2TmpqqevXq6/TpU1fl/MHBJbVt21ZiDQC4Yo6GetasWfrggw80Y8YMRUdHa+PGjRo4cKAiIiIUFxeX7fiEhAQNHjzYt52RkaHIyMh8m+fw4cM6ffqUmj88TKFVauTbeSUp48AerX13uA4fPkyoAQBXzNFQDxkyRM8++6weeOABSVKjRo20d+9eJSYm5hhqt9stt9t91ecKrVJD5aLqXvXbAQDgchx9e9apU6dUrJj/CAEBAfJ6vQ5NBACAXRy9R921a1eNGjVKUVFRio6O1rfffqtx48bp4YcfdnIsAACs4WioJ06cqKFDh+rJJ59UWlqaIiIi9Ne//lUvvPCCk2MBAGANR0MdEhKiCRMmaMKECU6OAQCAtfisbwAALEaoAQCwGKEGAMBihBoAAIsRagAALEaoAQCwGKEGAMBihBoAAIsRagAALEaoAQCwGKEGAMBihBoAAIsRagAALEaoAQCwGKEGAMBihBoAAIsRagAALEaoAQCwGKEGAMBihBoAAIsRagAALEaoAQCwGKEGAMBihBoAAIsRagAALEaoAQCwGKEGAMBihBoAAIsRagAALEaoAQCwGKEGAMBihBoAAIsRagAALEaoAQCwGKEGAMBihBoAAIsRagAALEaoAQCwGKEGAMBihBoAAIs5GuoaNWrI5XJlu8THxzs5FgAA1gh08saTkpKUlZXl205JSdGtt96qe++918GpAACwh6Ohrlixot/26NGjdd1116lNmzYOTQQAgF0cDfWFzp49q+nTp2vw4MFyuVw5HuPxeOTxeHzbGRkZBTUeAACOsObFZHPnztXx48f10EMPXfKYxMREhYWF+S6RkZEFNyAAAA6wJtTvvPOOOnXqpIiIiEsek5CQoPT0dN9l3759BTghAAAFz4qHvvfu3aslS5Zo9uzZv3uc2+2W2+0uoKkAAHCeFfeop06dqvDwcHXu3NnpUQAAsIrjofZ6vZo6dari4uIUGGjFHXwAAKzheKiXLFmi1NRUPfzww06PAgCAdRy/C3vbbbfJGOP0GAAAWMnxe9QAAODSCDUAABYj1AAAWIxQAwBgMUINAIDFCDUAABYj1AAAWIxQAwBgMUINAIDFCDUAABYj1AAAWIxQAwBgMUINAIDFCDUAABYj1AAAWIxQAwBgMUINAIDFCDUAABYj1AAAWIxQAwBgMUINAIDFCDUAABYj1AAAWIxQAwBgMUINAIDFCDUAABYj1AAAWIxQAwBgMUINAIDFCDUAABYj1AAAWIxQAwBgMUINAIDFCDUAABYj1AAAWIxQAwBgMUINAIDFCDUAABYj1AAAWIxQAwBgMcdDvX//fvXq1Uvly5dXcHCwGjVqpPXr1zs9FgAAVgh08saPHTumli1b6pZbbtGCBQtUsWJF7dy5U2XLlnVyLAAArOFoqMeMGaPIyEhNnTrVt69mzZoOTgQAgF0cfeh73rx5io2N1b333qvw8HA1btxYb7/99iWP93g8ysjI8LsAAFCUORrqH3/8UZMnT1bt2rW1aNEiPfHEE+rfv7/ee++9HI9PTExUWFiY7xIZGVnAEwMAULAcDbXX69VNN92kl156SY0bN9Zjjz2mvn37asqUKTken5CQoPT0dN9l3759BTwxAAAFy9FQV6lSRQ0aNPDbV79+faWmpuZ4vNvtVmhoqN8FAICizNFQt2zZUtu3b/fbt2PHDlWvXt2hiQAAsIujoR40aJDWrFmjl156Sbt27dKMGTP01ltvKT4+3smxAACwhqOhbtq0qebMmaMPP/xQDRs21MiRIzVhwgT17NnTybEAALCGo++jlqQuXbqoS5cuTo8BAICVHP8IUQAAcGmEGgAAixFqAAAsRqgBALAYoQYAwGKEGgAAixFqAAAsRqgBALAYoQYAwGKEGgAAixFqAAAsRqgBALAYoQYAwGKEGgAAixFqAAAsRqgBALAYoQYAwGKEGgAAixFqAAAsRqgBALAYoQYAwGKEGgAAixFqAAAsRqgBALAYoQYAwGKEGgAAixFqAAAsRqgBALAYoQYAwGKEGgAAixFqAAAsRqgBALAYoQYAwGKEGgAAixFqAAAsRqgBALAYoQYAwGKEGgAAixFqAAAsRqgBALCYo6F+8cUX5XK5/C716tVzciQAAKwS6PQA0dHRWrJkiW87MNDxkQAAsIbjVQwMDFTlypWdHgMAACs5/hz1zp07FRERoVq1aqlnz55KTU295LEej0cZGRl+FwAAijJHQ928eXNNmzZNCxcu1OTJk7V79261bt1amZmZOR6fmJiosLAw3yUyMrKAJwYAoGA5GupOnTrp3nvvVUxMjDp27KgvvvhCx48f16xZs3I8PiEhQenp6b7Lvn37CnhiAAAKluPPUV+oTJkyqlOnjnbt2pXj9W63W263u4CnAgDAOY4/R32hEydO6IcfflCVKlWcHgUAACs4Guq//e1vWrlypfbs2aNvvvlGd955pwICAtSjRw8nxwIAwBqOPvT9008/qUePHjpy5IgqVqyoVq1aac2aNapYsaKTYwEAYA1HQz1z5kwnbx4AAOtZ9Rw1AADwR6gBALAYoQYAwGKEGgAAixFqAAAsRqgBALAYoQYAwGKEGgAAixFqAAAsRqgBALAYoQYAwGKEGgAAixFqAAAsRqgBALAYoQYAwGJ5CnWtWrV05MiRbPuPHz+uWrVq/eGhAADAb/IU6j179igrKyvbfo/Ho/379//hoQAAwG8Cc3PwvHnzfP+8aNEihYWF+bazsrK0dOlS1ahRI9+GAwDgWperUHfv3l2S5HK5FBcX53dd8eLFVaNGDY0dOzbfhgMA4FqXq1B7vV5JUs2aNZWUlKQKFSpclaEAAMBvchXq83bv3p3fcwAAgBzkKdSStHTpUi1dulRpaWm+e9rnvfvuu394MAAAkMdQDx8+XCNGjFBsbKyqVKkil8uV33MBAADlMdRTpkzRtGnT1Lt37/yeBwAAXCBP76M+e/asbr755vyeBQAAXCRPoX700Uc1Y8aM/J4FAABcJE8PfZ85c0ZvvfWWlixZopiYGBUvXtzv+nHjxuXLcAAAXOvyFOrNmzfrxhtvlCSlpKT4XccLywAAyD95CvXy5cvzew4AAJADvuYSAACL5eke9S233PK7D3EvW7YszwMBAID/l6dQn39++rxz585p48aNSklJyfZlHQAAIO/yFOrx48fnuP/FF1/UiRMn/tBAAADg/+Xrc9S9evXic74BAMhH+Rrq1atXq0SJEvl5SgAArml5euj7rrvu8ts2xujAgQNav369hg4dmi+DAQCAPIY6LCzMb7tYsWKqW7euRowYodtuuy1fBgMAAHkM9dSpU/N7DgAAkIM8hfq85ORkbd26VZIUHR2txo0b58tQAADgN3l6MVlaWpratWunpk2bqn///urfv7+aNGmi9u3b65dffsnTIKNHj5bL5dLAgQPz9PMAABRFeQr1U089pczMTH333Xc6evSojh49qpSUFGVkZKh///65Pl9SUpLefPNNxcTE5GUcAACKrDyFeuHChXrjjTdUv359374GDRpo0qRJWrBgQa7OdeLECfXs2VNvv/22ypYtm5dxAAAosvIUaq/Xm+07qCWpePHi8nq9uTpXfHy8OnfurA4dOuRlFAAAirQ8vZisXbt2GjBggD788ENFRERIkvbv369Bgwapffv2V3yemTNnasOGDUpKSrqi4z0ejzwej287IyMjd4Nb4PyL7/JbhQoVFBUVdVXODQBwTp5C/frrr6tbt26qUaOGIiMjJUn79u1Tw4YNNX369Cs6x759+zRgwAAtXrz4ij/NLDExUcOHD8/LyI47nX5Ekku9evW6KucPDi6pbdu2EmsAKGLyFOrIyEht2LBBS5Ys0bZt2yRJ9evXz9XD18nJyUpLS9NNN93k25eVlaVVq1bp9ddfl8fjUUBAgN/PJCQkaPDgwb7tjIwM338o2O7cqUxJRjf+5RlVrFkvX8+dcWCP1r47XIcPHybUAFDE5CrUy5YtU79+/bRmzRqFhobq1ltv1a233ipJSk9PV3R0tKZMmaLWrVtf9lzt27fXli1b/Pb16dNH9erV0zPPPJMt0pLkdrvldrtzM7J1SodHqVxUXafHAAAUErkK9YQJE9S3b1+FhoZmuy4sLEx//etfNW7cuCsKdUhIiBo2bOi3r1SpUipfvny2/QAAXKty9arvTZs26fbbb7/k9bfddpuSk5P/8FAAAOA3ubpHfejQoRzfluU7WWBgnj+ZTJJWrFiR558FAKAoytU96qpVqyolJeWS12/evFlVqlT5w0MBAIDf5CrUf/7znzV06FCdOXMm23WnT5/WsGHD1KVLl3wbDgCAa12uHvr+xz/+odmzZ6tOnTrq16+f6tb97dXL27Zt06RJk5SVlaXnn3/+qgwKAMC1KFehrlSpkr755hs98cQTSkhIkDFGkuRyudSxY0dNmjRJlSpVuiqDAgBwLcr1B55Ur15dX3zxhY4dO6Zdu3bJGKPatWvzhRoAAFwFefpkMkkqW7asmjZtmp+zAACAi+Tp27MAAEDBINQAAFiMUAMAYDFCDQCAxQg1AAAWI9QAAFiMUAMAYDFCDQCAxQg1AAAWI9QAAFiMUAMAYDFCDQCAxQg1AAAWI9QAAFiMUAMAYDFCDQCAxQg1AAAWI9QAAFiMUAMAYDFCDQCAxQg1AAAWI9QAAFiMUAMAYDFCDQCAxQg1AAAWI9QAAFiMUAMAYDFCDQCAxQg1AAAWI9QAAFiMUAMAYDFCDQCAxQg1AAAWI9QAAFjM0VBPnjxZMTExCg0NVWhoqFq0aKEFCxY4ORIAAFZxNNTVqlXT6NGjlZycrPXr16tdu3a644479N133zk5FgAA1gh08sa7du3qtz1q1ChNnjxZa9asUXR0tENTAQBgD0dDfaGsrCx9/PHHOnnypFq0aJHjMR6PRx6Px7edkZFRUOMBAOAIx19MtmXLFpUuXVput1uPP/645syZowYNGuR4bGJiosLCwnyXyMjIAp4WAICC5Xio69atq40bN2rt2rV64oknFBcXp++//z7HYxMSEpSenu677Nu3r4CnBQCgYDn+0HdQUJCuv/56SVKTJk2UlJSkV199VW+++Wa2Y91ut9xud0GPCACAYxy/R30xr9fr9zw0AADXMkfvUSckJKhTp06KiopSZmamZsyYoRUrVmjRokVOjgUAgDUcDXVaWpoefPBBHThwQGFhYYqJidGiRYt06623OjkWAADWcDTU77zzjpM3DwCA9ax7jhoAAPw/Qg0AgMUINQAAFiPUAABYjFADAGAxQg0AgMUINQAAFiPUAABYjFADAGAxQg0AgMUINQAAFiPUAABYjFADAGAxQg0AgMUINQAAFiPUAABYjFADAGAxQg0AgMUINQAAFiPUAABYjFADAGAxQg0AgMUINQAAFiPUAABYjFADAGAxQg0AgMUINQAAFiPUAABYjFADAGAxQg0AgMUINQAAFiPUAABYjFADAGAxQg0AgMUINQAAFiPUAABYjFADAGAxQg0AgMUINQAAFiPUAABYzNFQJyYmqmnTpgoJCVF4eLi6d++u7du3OzkSAABWcTTUK1euVHx8vNasWaPFixfr3Llzuu2223Ty5EknxwIAwBqBTt74woUL/banTZum8PBwJScn609/+pNDUwEAYA9HQ32x9PR0SVK5cuVyvN7j8cjj8fi2MzIyCmQuAACcYs2LybxerwYOHKiWLVuqYcOGOR6TmJiosLAw3yUyMrKApwQAoGBZE+r4+HilpKRo5syZlzwmISFB6enpvsu+ffsKcEIAAAqeFQ999+vXT/Pnz9eqVatUrVq1Sx7ndrvldrsLcDIAAJzlaKiNMXrqqac0Z84crVixQjVr1nRyHAAArONoqOPj4zVjxgx9+umnCgkJ0cGDByVJYWFhCg4OdnI0AACs4Ohz1JMnT1Z6erratm2rKlWq+C4fffSRk2MBAGANxx/6BgAAl2bNq74BAEB2hBoAAIsRagAALEaoAQCwGKEGAMBihBoAAIsRagAALEaoAQCwGKEGAMBihBoAAIsRagAALEaoAQCwGKEGAMBihBoAAIsRagAALEaoAQCwGKEGAMBihBoAAIsRagAALEaoAQCwGKEGAMBihBoAAIsRagAALEaoAQCwGKEGAMBihBoAAIsRagAALEaoAQCwGKEGAMBihBoAAIsRagAALEaoAQCwGKEGAMBihBoAAIsRagAALEaoAQCwGKEGAMBihBoAAIsRagAALEaoAQCwmKOhXrVqlbp27aqIiAi5XC7NnTvXyXEAALCOo6E+efKkbrjhBk2aNMnJMQAAsFagkzfeqVMnderUyckRAACwmqOhzi2PxyOPx+PbzsjIcHAa+2zduvWqnLdChQqKioq6KucGgPyUmpqqw4cPX5VzO/W3sFCFOjExUcOHD3d6DOucTj8iyaVevXpdlfMHB5fUtm1biTUAq6Wmpqpevfo6ffrUVTm/U38LC1WoExISNHjwYN92RkaGIiMjHZzIDudOZUoyuvEvz6hizXr5eu6MA3u09t3hOnz4MKEGYLXDhw/r9OlTav7wMIVWqZGv53byb2GhCrXb7Zbb7XZ6DGuVDo9Suai6To8BAI4KrVKjSP0t5H3UAABYzNF71CdOnNCuXbt827t379bGjRtVrlw5HmYFAEAOh3r9+vW65ZZbfNvnn3+Oi4vTtGnTHJoKAAB7OBrqtm3byhjj5AgAAFiN56gBALAYoQYAwGKEGgAAixFqAAAsRqgBALAYoQYAwGKEGgAAixFqAAAsRqgBALAYoQYAwGKEGgAAixFqAAAsRqgBALAYoQYAwGKEGgAAixFqAAAsRqgBALAYoQYAwGKEGgAAixFqAAAsRqgBALAYoQYAwGKEGgAAixFqAAAsRqgBALAYoQYAwGKEGgAAixFqAAAsRqgBALAYoQYAwGKEGgAAixFqAAAsRqgBALAYoQYAwGKEGgAAixFqAAAsRqgBALAYoQYAwGKEGgAAixFqAAAsZkWoJ02apBo1aqhEiRJq3ry51q1b5/RIAABYwfFQf/TRRxo8eLCGDRumDRs26IYbblDHjh2Vlpbm9GgAADjO8VCPGzdOffv2VZ8+fdSgQQNNmTJFJUuW1Lvvvuv0aAAAOC7QyRs/e/askpOTlZCQ4NtXrFgxdejQQatXr852vMfjkcfj8W2np6dLkjIyMvJlnhMnTkiSju7drl89p/PlnOdlHNgrSUrfv1PFA12F59wHUyVJycnJvt9PfipWrJi8Xm++n5dzO3N+zs25nTz39u3bJV2lv+H/+Vt44sSJfGuOJIWEhMjluszfbeOg/fv3G0nmm2++8ds/ZMgQ06xZs2zHDxs2zEjiwoULFy5cisQlPT39sq109B51biUkJGjw4MG+ba/Xq6NHj6p8+fKX/y+SK5CRkaHIyEjt27dPoaGhf/h8Nihqaypq65FYU2FR1NZU1NYjFc41hYSEXPYYR0NdoUIFBQQE6NChQ377Dx06pMqVK2c73u12y+12++0rU6ZMvs8VGhpaaP4lX6mitqaith6JNRUWRW1NRW09UtFbk6MvJgsKClKTJk20dOlS3z6v16ulS5eqRYsWDk4GAIAdHH/oe/DgwYqLi1NsbKyaNWumCRMm6OTJk+rTp4/TowEA4DjHQ33//ffrl19+0QsvvKCDBw/qxhtv1MKFC1WpUqUCn8XtdmvYsGHZHl4vzIramoraeiTWVFgUtTUVtfVIRXNNkuQyxhinhwAAADlz/ANPAADApRFqAAAsRqgBALAYoQYAwGKE+j8K81dtJiYmqmnTpgoJCVF4eLi6d+/u+8zb886cOaP4+HiVL19epUuX1t13353tg2ZsNXr0aLlcLg0cONC3rzCuZ//+/erVq5fKly+v4OBgNWrUSOvXr/ddb4zRCy+8oCpVqig4OFgdOnTQzp07HZz492VlZWno0KGqWbOmgoODdd1112nkyJG68PWptq9p1apV6tq1qyIiIuRyuTR37ly/669k/qNHj6pnz54KDQ1VmTJl9Mgjj1yVz8W/Ur+3pnPnzumZZ55Ro0aNVKpUKUVEROjBBx/Uzz//7HeOwrSmiz3++ONyuVyaMGGC337b1pQbhFqF/6s2V65cqfj4eK1Zs0aLFy/WuXPndNttt+nkyZO+YwYNGqTPPvtMH3/8sVauXKmff/5Zd911l4NTX5mkpCS9+eabiomJ8dtf2NZz7NgxtWzZUsWLF9eCBQv0/fffa+zYsSpbtqzvmH/961967bXXNGXKFK1du1alSpVSx44ddebMGQcnv7QxY8Zo8uTJev3117V161aNGTNG//rXvzRx4kTfMbav6eTJk7rhhhs0adKkHK+/kvl79uyp7777TosXL9b8+fO1atUqPfbYYwW1hGx+b02nTp3Shg0bNHToUG3YsEGzZ8/W9u3b1a1bN7/jCtOaLjRnzhytWbNGERER2a6zbU25kg/frVHoNWvWzMTHx/u2s7KyTEREhElMTHRwqrxLS0szkszKlSuNMcYcP37cFC9e3Hz88ce+Y7Zu3WokmdWrVzs15mVlZmaa2rVrm8WLF5s2bdqYAQMGGGMK53qeeeYZ06pVq0te7/V6TeXKlc3LL7/s23f8+HHjdrvNhx9+WBAj5lrnzp3Nww8/7LfvrrvuMj179jTGFL41STJz5szxbV/J/N9//72RZJKSknzHLFiwwLhcLrN///4Cm/1SLl5TTtatW2ckmb179xpjCu+afvrpJ1O1alWTkpJiqlevbsaPH++7zvY1Xc41f4/6/FdtdujQwbfv975qszA4//Wf5cqVk/TbV1SeO3fOb4316tVTVFSU1WuMj49X586d/eaWCud65s2bp9jYWN17770KDw9X48aN9fbbb/uu3717tw4ePOi3prCwMDVv3tzaNd18881aunSpduzYIUnatGmTvv76a3Xq1ElS4VzTha5k/tWrV6tMmTKKjY31HdOhQwcVK1ZMa9euLfCZ8yI9PV0ul8v3vQmFcU1er1e9e/fWkCFDFB0dne36wrimCzn+yWROO3z4sLKysrJ9ElqlSpW0bds2h6bKO6/Xq4EDB6ply5Zq2LChJOngwYMKCgrK9gUmlSpV0sGDBx2Y8vJmzpypDRs2KCkpKdt1hXE9P/74oyZPnqzBgwfrueeeU1JSkvr376+goCDFxcX55s7pf4e2runZZ59VRkaG6tWrp4CAAGVlZWnUqFHq2bOnJBXKNV3oSuY/ePCgwsPD/a4PDAxUuXLlCsUaz5w5o2eeeUY9evTwfYlFYVzTmDFjFBgYqP79++d4fWFc04Wu+VAXNfHx8UpJSdHXX3/t9Ch5tm/fPg0YMECLFy9WiRIlnB4nX3i9XsXGxuqll16SJDVu3FgpKSmaMmWK4uLiHJ4ub2bNmqUPPvhAM2bMUHR0tDZu3KiBAwcqIiKi0K7pWnLu3Dndd999MsZo8uTJTo+TZ8nJyXr11Ve1YcOGfPm6Yxtd8w995/arNm3Wr18/zZ8/X8uXL1e1atV8+ytXrqyzZ8/q+PHjfsfbusbk5GSlpaXppptuUmBgoAIDA7Vy5Uq99tprCgwMVKVKlQrVeiSpSpUqatCggd+++vXrKzU1VZJ8cxem/x0OGTJEzz77rB544AE1atRIvXv31qBBg5SYmCipcK7pQlcyf+XKlbO96PTXX3/V0aNHrV7j+Ujv3btXixcv9vtKyMK2pq+++kppaWmKiory/b3Yu3evnn76adWoUUNS4VvTxa75UBeFr9o0xqhfv36aM2eOli1bppo1a/pd36RJExUvXtxvjdu3b1dqaqqVa2zfvr22bNmijRs3+i6xsbHq2bOn758L03okqWXLltneMrdjxw5Vr15dklSzZk1VrlzZb00ZGRlau3attWs6deqUihXz/xMSEBAgr9crqXCu6UJXMn+LFi10/PhxJScn+45ZtmyZvF6vmjdvXuAzX4nzkd65c6eWLFmi8uXL+11f2NbUu3dvbd682e/vRUREhIYMGaJFixZJKnxrysbpV7PZYObMmcbtdptp06aZ77//3jz22GOmTJky5uDBg06PdkWeeOIJExYWZlasWGEOHDjgu5w6dcp3zOOPP26ioqLMsmXLzPr1602LFi1MixYtHJw6dy581bcxhW8969atM4GBgWbUqFFm586d5oMPPjAlS5Y006dP9x0zevRoU6ZMGfPpp5+azZs3mzvuuMPUrFnTnD592sHJLy0uLs5UrVrVzJ8/3+zevdvMnj3bVKhQwfz973/3HWP7mjIzM823335rvv32WyPJjBs3znz77be+V0Bfyfy33367ady4sVm7dq35+uuvTe3atU2PHj2cWtLvruns2bOmW7duplq1ambjxo1+fy88Hk+hXFNOLn7VtzH2rSk3CPV/TJw40URFRZmgoCDTrFkzs2bNGqdHumKScrxMnTrVd8zp06fNk08+acqWLWtKlixp7rzzTnPgwAHnhs6li0NdGNfz2WefmYYNGxq3223q1atn3nrrLb/rvV6vGTp0qKlUqZJxu92mffv2Zvv27Q5Ne3kZGRlmwIABJioqypQoUcLUqlXLPP/8835/8G1f0/Lly3P8/05cXJwx5srmP3LkiOnRo4cpXbq0CQ0NNX369DGZmZkOrOY3v7em3bt3X/LvxfLlywvlmnKSU6htW1Nu8DWXAABY7Jp/jhoAAJsRagAALEaoAQCwGKEGAMBihBoAAIsRagAALEaoAQCwGKEGAMBihBoAAIsRagAALEaogSIuMzNTPXv2VKlSpVSlShWNHz9ebdu21cCBAyVJ77//vmJjYxUSEqLKlSvrL3/5i99XAq5YsUIul0uff/65YmJiVKJECf3Xf/2XUlJSfMfs3btXXbt2VdmyZVWqVClFR0friy++KOilAkUSoQaKuMGDB+vf//635s2bp8WLF+urr77Shg0bfNefO3dOI0eO1KZNmzR37lzt2bNHDz30ULbzDBkyRGPHjlVSUpIqVqyorl276ty5c5Kk+Ph4eTwerVq1Slu2bNGYMWNUunTpgloiUKTxpRxAEZaZmany5ctrxowZuueeeyRJ6enpioiIUN++fTVhwoRsP7N+/Xo1bdpUmZmZKl26tFasWKFbbrlFM2fO1P333y9JOnr0qKpVq6Zp06bpvvvuU0xMjO6++24NGzasIJcHXBO4Rw0UYT/++KPOnTunZs2a+faFhYWpbt26vu3k5GR17dpVUVFRCgkJUZs2bSRJqampfudq0aKF75/LlSununXrauvWrZKk/v3765///KdatmypYcOGafPmzVdzWcA1hVAD17CTJ0+qY8eOCg0N1QcffKCkpCTNmTNHknT27NkrPs+jjz6qH3/8Ub1799aWLVsUGxuriRMnXq2xgWsKoQaKsFq1aql48eJKSkry7UtPT9eOHTskSdu2bdORI0c0evRotW7dWvXq1fN7IdmF1qxZ4/vnY8eOaceOHapfv75vX2RkpB5//HHNnj1bTz/9tN5+++2rtCrg2hLo9AAArp6QkBDFxcVpyJAhKleunMLDwzVs2DAVK1ZMLpdLUVFRCgoK0sSJE/X4448rJSVFI0eOzPFcI0aMUPny5VWpUiU9//zzqlChgrp37y5JGjhwoDp16qQ6dero2LFjWr58uV/EAeQd96iBIm7cuHFq0aKFunTpog4dOqhly5aqX7++SpQooYoVK2ratGn6+OOP1aBBA40ePVqvvPJKjucZPXq0BgwYoCZNmujgwYP67LPPFBQUJEnKyspSfHy86tevr9tvv1116tTRG2+8UZDLBIosXvUNXGNOnjypqlWrauzYsXrkkUcue/z5V30fO3ZMZcqUufoDAvDDQ99AEfftt99q27ZtatasmdLT0zVixAhJ0h133OHwZACuBKEGrgGvvPKKtm/frqCgIDVp0kRfffWVKlSo4PRYAK4AD30DAGAxXkwGAIDFCDUAABYj1AAAWIxQAwBgMUINAIDFCDUAABYj1AAAWIxQAwBgMUINAIDF/g+LU/sqAflXhwAAAABJRU5ErkJggg==\n"},"metadata":{}}],"source":["plt.figure(figsize=(6, 6))\n","sns.displot(train_df[\"gaps\"])\n","plt.title(\"Label Distribution\")\n","plt.show()"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":546},"id":"kumzui4Npakn","outputId":"a1ed109b-6156-4a4f-930d-5d2e6e43106c"},"outputs":[{"output_type":"display_data","data":{"text/plain":["<Figure size 600x600 with 0 Axes>"]},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["<Figure size 500x500 with 1 Axes>"],"image/png":"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\n"},"metadata":{}}],"source":["plt.figure(figsize=(6, 6))\n","sns.displot(train_df[\"flank_wear\"])\n","plt.title(\"Label Distribution\")\n","plt.show()"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":546},"id":"xEgILWOLpakn","outputId":"0fcd7a1b-3904-4746-9ade-2151c081d5fa"},"outputs":[{"output_type":"display_data","data":{"text/plain":["<Figure size 600x600 with 0 Axes>"]},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["<Figure size 500x500 with 1 Axes>"],"image/png":"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\n"},"metadata":{}}],"source":["plt.figure(figsize=(6, 6))\n","sns.displot(train_df[\"overhang\"])\n","plt.title(\"Label Distribution\")\n","plt.show()"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"xKTZ-9FCpakn","outputId":"efadfafa-4e94-45a1-f7ab-8caf5387a703"},"outputs":[{"output_type":"stream","name":"stdout","text":["check if permutation is same on all models\n","train_head          id   gaps  flank_wear  overhang  \\\n","14   T8R3B4   6.88       40.92     14.54   \n","10   T6R9B3  12.94       95.63     16.65   \n","0    T1R2B1   7.67       34.89     48.61   \n","3   T2R13B4   0.00      122.59     25.55   \n","1    T1R7B4  13.89       85.41     50.25   \n","\n","                                       spec_x  \\\n","14   /content/Siren/dataset/spec/x/T8R3B4.jpg   \n","10   /content/Siren/dataset/spec/x/T6R9B3.jpg   \n","0    /content/Siren/dataset/spec/x/T1R2B1.jpg   \n","3   /content/Siren/dataset/spec/x/T2R13B4.jpg   \n","1    /content/Siren/dataset/spec/x/T1R7B4.jpg   \n","\n","                                       spec_y  \\\n","14   /content/Siren/dataset/spec/y/T8R3B4.jpg   \n","10   /content/Siren/dataset/spec/y/T6R9B3.jpg   \n","0    /content/Siren/dataset/spec/y/T1R2B1.jpg   \n","3   /content/Siren/dataset/spec/y/T2R13B4.jpg   \n","1    /content/Siren/dataset/spec/y/T1R7B4.jpg   \n","\n","                                       spec_z  \n","14   /content/Siren/dataset/spec/z/T8R3B4.jpg  \n","10   /content/Siren/dataset/spec/z/T6R9B3.jpg  \n","0    /content/Siren/dataset/spec/z/T1R2B1.jpg  \n","3   /content/Siren/dataset/spec/z/T2R13B4.jpg  \n","1    /content/Siren/dataset/spec/z/T1R7B4.jpg  \n","test_head          id   gaps  flank_wear  overhang  \\\n","16   T9R7B4   0.00       94.62     17.05   \n","18  T10R3B4   0.00       44.26      7.10   \n","9   T5R12B1  21.79      334.39     16.14   \n","\n","                                       spec_x  \\\n","16   /content/Siren/dataset/spec/x/T9R7B4.jpg   \n","18  /content/Siren/dataset/spec/x/T10R3B4.jpg   \n","9   /content/Siren/dataset/spec/x/T5R12B1.jpg   \n","\n","                                       spec_y  \\\n","16   /content/Siren/dataset/spec/y/T9R7B4.jpg   \n","18  /content/Siren/dataset/spec/y/T10R3B4.jpg   \n","9   /content/Siren/dataset/spec/y/T5R12B1.jpg   \n","\n","                                       spec_z  \n","16   /content/Siren/dataset/spec/z/T9R7B4.jpg  \n","18  /content/Siren/dataset/spec/z/T10R3B4.jpg  \n","9   /content/Siren/dataset/spec/z/T5R12B1.jpg  \n","val_head          id   gaps  flank_wear  overhang  \\\n","5   T3R10B1   5.00      128.39     35.26   \n","13  T7R14B3  13.67      141.91     14.62   \n","12   T7R8B3   7.45       77.05     19.02   \n","\n","                                       spec_x  \\\n","5   /content/Siren/dataset/spec/x/T3R10B1.jpg   \n","13  /content/Siren/dataset/spec/x/T7R14B3.jpg   \n","12   /content/Siren/dataset/spec/x/T7R8B3.jpg   \n","\n","                                       spec_y  \\\n","5   /content/Siren/dataset/spec/y/T3R10B1.jpg   \n","13  /content/Siren/dataset/spec/y/T7R14B3.jpg   \n","12   /content/Siren/dataset/spec/y/T7R8B3.jpg   \n","\n","                                       spec_z  \n","5   /content/Siren/dataset/spec/z/T3R10B1.jpg  \n","13  /content/Siren/dataset/spec/z/T7R14B3.jpg  \n","12   /content/Siren/dataset/spec/z/T7R8B3.jpg  \n"]}],"source":["print(\"check if permutation is same on all models\")\n","print(\"train_head\", train_df.head())\n","print(\"test_head\", test_df.head())\n","print(\"val_head\", val_df.head())"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"YsduxGITpakn"},"outputs":[],"source":["def read_specs(file_paths_x, file_paths_y, file_paths_z, img_rows, img_cols, channels):\n","    \"\"\"\n","    Reads the spectogram files from disk and normalizes the pixel values\n","      @params:\n","        file_paths - Array of file paths to read from\n","        img_rows - The image height.\n","        img_cols - The image width.\n","        as_grey - Read the image as Greyscale or RGB.\n","        channels - Number of channels.\n","      @returns:\n","        The created and compiled model (Model)\n","    \"\"\"\n","    images = []\n","    for i in range(file_paths_x.size):\n","        img = []\n","        img_x = cv2.imread(file_paths_x[i])\n","        res_x = cv2.resize(\n","            img_x, dsize=(img_rows, img_cols), interpolation=cv2.INTER_CUBIC\n","        )\n","        img.append(res_x)\n","\n","        img_y = cv2.imread(file_paths_y[i])\n","        res_y = cv2.resize(\n","            img_y, dsize=(img_rows, img_cols), interpolation=cv2.INTER_CUBIC\n","        )\n","        img.append(res_y)\n","\n","        img_z = cv2.imread(file_paths_z[i])\n","        res_z = cv2.resize(\n","            img_z, dsize=(img_rows, img_cols), interpolation=cv2.INTER_CUBIC\n","        )\n","        img.append(res_z)\n","        img = np.concatenate(img, axis=2)\n","        images.append(img)\n","\n","    images = np.asarray(images, dtype=np.float32)\n","\n","    # normalize\n","    images = images / 255.0\n","\n","    return images"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"_u9XVx3Rpako"},"outputs":[],"source":["x_train_spec = read_specs(\n","    train_df.spec_x.values,\n","    train_df.spec_y.values,\n","    train_df.spec_z.values,\n","    img_rows,\n","    img_cols,\n","    in_channel,\n",")\n","x_test_spec = read_specs(\n","    test_df.spec_x.values,\n","    test_df.spec_y.values,\n","    test_df.spec_z.values,\n","    img_rows,\n","    img_cols,\n","    in_channel,\n",")\n","x_val_spec = read_specs(\n","    val_df.spec_x.values,\n","    val_df.spec_y.values,\n","    val_df.spec_z.values,\n","    img_rows,\n","    img_cols,\n","    in_channel,\n",")"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"hhSBGwDIpako","outputId":"a28a49a2-8039-46af-a850-3e38ff89af94"},"outputs":[{"output_type":"execute_result","data":{"text/plain":["(14, 256, 256, 9)"]},"metadata":{},"execution_count":13}],"source":["x_train_spec.shape"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":310},"id":"CSDW_BSsJrPT","outputId":"c4eefd92-a9b3-4c10-fd28-4674fbd88862"},"outputs":[{"output_type":"execute_result","data":{"text/plain":["[]"]},"metadata":{},"execution_count":14},{"output_type":"display_data","data":{"text/plain":["<Figure size 1000x3000 with 3 Axes>"],"image/png":"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\n"},"metadata":{}}],"source":["# Split the last dimension into 3 separate spectrograms\n","spectrogram1 = x_train_spec[0, :, :, 0:3]  # First spectrogram (channels 0-2)\n","spectrogram2 = x_train_spec[0, :, :, 3:6]  # Second spectrogram (channels 3-5)\n","spectrogram3 = x_train_spec[0, :, :, 6:9]  # Third spectrogram (channels 6-8)\n","# Convert arrays to images\n","pil_img1 = tf.keras.utils.array_to_img(spectrogram1)\n","pil_img2 = tf.keras.utils.array_to_img(spectrogram2)\n","pil_img3 = tf.keras.utils.array_to_img(spectrogram3)\n","# Display the images\n","fig, ax = plt.subplots(1,3, figsize=(10,30))\n","ax[0].imshow(pil_img1)\n","ax[1].imshow(pil_img2)\n","ax[2].imshow(pil_img3)\n","plt.plot()"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"u0O4CdCvpako"},"outputs":[],"source":["labels_train = train_df[[\"gaps\", \"flank_wear\", \"overhang\"]]\n","labels_test = test_df[[\"gaps\", \"flank_wear\", \"overhang\"]]\n","labels_val = val_df[[\"gaps\", \"flank_wear\", \"overhang\"]]"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"CMjqCA2Upako"},"outputs":[],"source":["train_dataset = tf.data.Dataset.from_tensor_slices((x_train_spec, labels_train))\n","test_dataset = tf.data.Dataset.from_tensor_slices((x_test_spec, labels_test))\n","val_dataset = tf.data.Dataset.from_tensor_slices((x_val_spec, labels_val))"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"EZU0UsXApakp"},"outputs":[],"source":["# ============================== augment ==============================\n","auto = tf.data.AUTOTUNE\n","\n","data_augmentation = k.Sequential(\n","    [\n","        k.layers.RandomBrightness(factor=(-0.2, 0.2), value_range=(0, 1)),\n","        k.layers.RandomContrast(factor=0.2),\n","        k.layers.GaussianNoise(stddev=0.2),\n","    ],\n","    name=\"data_augmentation\",\n",")"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"4jUf9z-epakp"},"outputs":[],"source":["def generate_datasets(images, is_train=False, shuffle=False):\n","    dataset = images\n","    if shuffle:\n","        dataset = dataset.shuffle(batch_size * 10)\n","    dataset = dataset.batch(batch_size)\n","    if is_train:\n","        dataset = dataset.map(\n","            lambda x, y: (data_augmentation(x), y), num_parallel_calls=auto\n","        )\n","    return dataset.prefetch(auto)"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"-Lis2MsCpakp"},"outputs":[],"source":["train_ds = generate_datasets(train_dataset, is_train=True, shuffle=True)\n","val_ds = generate_datasets(val_dataset)\n","test_ds = generate_datasets(test_dataset)"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"stxaru8cpakp","outputId":"e63f1af5-b706-4314-d4da-978ba5de4ab1"},"outputs":[{"output_type":"execute_result","data":{"text/plain":["<_PrefetchDataset element_spec=(TensorSpec(shape=(None, 256, 256, 9), dtype=tf.float32, name=None), TensorSpec(shape=(None, 3), dtype=tf.float64, name=None))>"]},"metadata":{},"execution_count":20}],"source":["train_ds"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"_1Y5r3Jvpakp"},"outputs":[],"source":["def activation_module(x):\n","    x = layers.Activation(\"gelu\")(x)\n","    return layers.BatchNormalization()(x)\n","\n","\n","def base_module(x, filters: int, patch_size: int):\n","    x = layers.Conv2D(filters, kernel_size=patch_size, strides=patch_size)(x)\n","    return activation_module(x)\n","\n","\n","def depth_point_module(\n","    x, pe_block, column, level, depth, r_arr, filters: int, kernel_size: int\n","):\n","    if column == 0:\n","        # Depthwise convolution.\n","        x0 = x\n","        x = layers.DepthwiseConv2D(kernel_size=kernel_size, padding=\"same\")(x)\n","        x = layers.Add()([activation_module(x), x0])  # Residual.\n","\n","        # Pointwise convolution.\n","        x = layers.Conv2D(filters, kernel_size=1)(x)\n","        x = activation_module(x)\n","\n","        r_arr = reverasable_output_array(x, r_arr, column, level)\n","        return x, r_arr\n","    else:\n","        if level == 0:\n","            x0 = fusion_block_double(r_arr[column - 1][level + 1], pe_block)\n","        elif level < len(r_arr[0]) - 1 and level != 0:\n","            x0 = fusion_block_double(r_arr[column - 1][level + 1], x)\n","        else:\n","            x0 = x\n","        x = layers.DepthwiseConv2D(kernel_size=kernel_size, padding=\"same\")(x0)\n","        x = layers.Add()([activation_module(x), x0])  # Residual.\n","\n","        # Pointwise convolution.\n","        x = layers.Conv2D(filters, kernel_size=1)(x)\n","        x = activation_module(x)\n","\n","        if column != 0:\n","            x = fusion_block_double(r_arr[column - 1][level], x)\n","\n","        r_arr = reverasable_output_array(x, r_arr, column, level)\n","\n","        return x, r_arr\n","\n","\n","def fusion_block_double(x, y):\n","    return layers.Add()([x, y])\n","\n","\n","def reverasable_output_array(x, r_arr, column, level):\n","    r_arr[column][level] = x\n","    return r_arr\n","\n","\n","def load_siren(\n","    image_size=image_size,\n","    filters=filters,\n","    depth=depth,\n","    columns=columns,\n","    kernel_size=kernel_size,\n","    patch_size=patch_size,\n","    num_classes=num_classes,\n","):\n","    r_arr = [[None for _ in range(depth)] for _ in range(columns)]\n","\n","    inputs = k.Input(input_shape)\n","    # x = layers.Rescaling(scale=1.0 / 255)(inputs)         # already rescaled\n","\n","    # Extract patch embeddings.\n","    x = base_module(inputs, filters, patch_size)\n","    pe_block = x\n","\n","    # Siren blocks.\n","    for column in range(columns):\n","        for level in range(depth):\n","            x, r_arr = depth_point_module(\n","                x, pe_block, column, level, depth, r_arr, filters, kernel_size\n","            )\n","\n","    # Classification block.\n","    x = layers.GlobalAvgPool2D()(x)\n","    outputs = layers.Dense(num_classes, activation=\"linear\")(x)\n","\n","    return k.Model(inputs, outputs)"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"HeWj3PvFpakq"},"outputs":[],"source":["def launch_experiment(model):\n","    optimizer = tfa.optimizers.AdamW(\n","        learning_rate=learning_rate, weight_decay=weight_decay\n","    )\n","\n","    model.compile(\n","        optimizer=optimizer, loss=\"mse\", metrics=[tf.keras.metrics.MeanSquaredError()]\n","    )\n","\n","    history = model.fit(\n","        train_ds,\n","        validation_data=val_ds,\n","        epochs=epochs,\n","    )\n","\n","    _, accuracy = model.evaluate(test_ds)\n","    print(f\"Test error: {round(accuracy, 2)}\")\n","\n","    return history, model"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"KU_KLV_Ypakq","outputId":"f060041f-8389-43a2-9283-19e3fa371c04"},"outputs":[{"output_type":"stream","name":"stdout","text":["Model: \"model\"\n","__________________________________________________________________________________________________\n"," Layer (type)                Output Shape                 Param #   Connected to                  \n","==================================================================================================\n"," input_1 (InputLayer)        [(None, 256, 256, 9)]        0         []                            \n","                                                                                                  \n"," conv2d (Conv2D)             (None, 16, 16, 256)          590080    ['input_1[0][0]']             \n","                                                                                                  \n"," activation (Activation)     (None, 16, 16, 256)          0         ['conv2d[0][0]']              \n","                                                                                                  \n"," batch_normalization (Batch  (None, 16, 16, 256)          1024      ['activation[0][0]']          \n"," Normalization)                                                                                   \n","                                                                                                  \n"," depthwise_conv2d (Depthwis  (None, 16, 16, 256)          6656      ['batch_normalization[0][0]'] \n"," eConv2D)                                                                                         \n","                                                                                                  \n"," activation_1 (Activation)   (None, 16, 16, 256)          0         ['depthwise_conv2d[0][0]']    \n","                                                                                                  \n"," batch_normalization_1 (Bat  (None, 16, 16, 256)          1024      ['activation_1[0][0]']        \n"," chNormalization)                                                                                 \n","                                                                                                  \n"," add (Add)                   (None, 16, 16, 256)          0         ['batch_normalization_1[0][0]'\n","                                                                    , 'batch_normalization[0][0]']\n","                                                                                                  \n"," conv2d_1 (Conv2D)           (None, 16, 16, 256)          65792     ['add[0][0]']                 \n","                                                                                                  \n"," activation_2 (Activation)   (None, 16, 16, 256)          0         ['conv2d_1[0][0]']            \n","                                                                                                  \n"," batch_normalization_2 (Bat  (None, 16, 16, 256)          1024      ['activation_2[0][0]']        \n"," chNormalization)                                                                                 \n","                                                                                                  \n"," depthwise_conv2d_1 (Depthw  (None, 16, 16, 256)          6656      ['batch_normalization_2[0][0]'\n"," iseConv2D)                                                         ]                             \n","                                                                                                  \n"," activation_3 (Activation)   (None, 16, 16, 256)          0         ['depthwise_conv2d_1[0][0]']  \n","                                                                                                  \n"," batch_normalization_3 (Bat  (None, 16, 16, 256)          1024      ['activation_3[0][0]']        \n"," chNormalization)                                                                                 \n","                                                                                                  \n"," add_1 (Add)                 (None, 16, 16, 256)          0         ['batch_normalization_3[0][0]'\n","                                                                    , 'batch_normalization_2[0][0]\n","                                                                    ']                            \n","                                                                                                  \n"," conv2d_2 (Conv2D)           (None, 16, 16, 256)          65792     ['add_1[0][0]']               \n","                                                                                                  \n"," activation_4 (Activation)   (None, 16, 16, 256)          0         ['conv2d_2[0][0]']            \n","                                                                                                  \n"," batch_normalization_4 (Bat  (None, 16, 16, 256)          1024      ['activation_4[0][0]']        \n"," chNormalization)                                                                                 \n","                                                                                                  \n"," add_4 (Add)                 (None, 16, 16, 256)          0         ['batch_normalization_4[0][0]'\n","                                                                    , 'batch_normalization[0][0]']\n","                                                                                                  \n"," depthwise_conv2d_4 (Depthw  (None, 16, 16, 256)          6656      ['add_4[0][0]']               \n"," iseConv2D)                                                                                       \n","                                                                                                  \n"," depthwise_conv2d_2 (Depthw  (None, 16, 16, 256)          6656      ['batch_normalization_4[0][0]'\n"," iseConv2D)                                                         ]                             \n","                                                                                                  \n"," activation_9 (Activation)   (None, 16, 16, 256)          0         ['depthwise_conv2d_4[0][0]']  \n","                                                                                                  \n"," activation_5 (Activation)   (None, 16, 16, 256)          0         ['depthwise_conv2d_2[0][0]']  \n","                                                                                                  \n"," batch_normalization_9 (Bat  (None, 16, 16, 256)          1024      ['activation_9[0][0]']        \n"," chNormalization)                                                                                 \n","                                                                                                  \n"," batch_normalization_5 (Bat  (None, 16, 16, 256)          1024      ['activation_5[0][0]']        \n"," chNormalization)                                                                                 \n","                                                                                                  \n"," add_5 (Add)                 (None, 16, 16, 256)          0         ['batch_normalization_9[0][0]'\n","                                                                    , 'add_4[0][0]']              \n","                                                                                                  \n"," add_2 (Add)                 (None, 16, 16, 256)          0         ['batch_normalization_5[0][0]'\n","                                                                    , 'batch_normalization_4[0][0]\n","                                                                    ']                            \n","                                                                                                  \n"," conv2d_5 (Conv2D)           (None, 16, 16, 256)          65792     ['add_5[0][0]']               \n","                                                                                                  \n"," conv2d_3 (Conv2D)           (None, 16, 16, 256)          65792     ['add_2[0][0]']               \n","                                                                                                  \n"," activation_10 (Activation)  (None, 16, 16, 256)          0         ['conv2d_5[0][0]']            \n","                                                                                                  \n"," activation_6 (Activation)   (None, 16, 16, 256)          0         ['conv2d_3[0][0]']            \n","                                                                                                  \n"," batch_normalization_10 (Ba  (None, 16, 16, 256)          1024      ['activation_10[0][0]']       \n"," tchNormalization)                                                                                \n","                                                                                                  \n"," batch_normalization_6 (Bat  (None, 16, 16, 256)          1024      ['activation_6[0][0]']        \n"," chNormalization)                                                                                 \n","                                                                                                  \n"," add_6 (Add)                 (None, 16, 16, 256)          0         ['batch_normalization_2[0][0]'\n","                                                                    , 'batch_normalization_10[0][0\n","                                                                    ]']                           \n","                                                                                                  \n"," add_7 (Add)                 (None, 16, 16, 256)          0         ['batch_normalization_6[0][0]'\n","                                                                    , 'add_6[0][0]']              \n","                                                                                                  \n"," depthwise_conv2d_5 (Depthw  (None, 16, 16, 256)          6656      ['add_7[0][0]']               \n"," iseConv2D)                                                                                       \n","                                                                                                  \n"," depthwise_conv2d_3 (Depthw  (None, 16, 16, 256)          6656      ['batch_normalization_6[0][0]'\n"," iseConv2D)                                                         ]                             \n","                                                                                                  \n"," activation_11 (Activation)  (None, 16, 16, 256)          0         ['depthwise_conv2d_5[0][0]']  \n","                                                                                                  \n"," activation_7 (Activation)   (None, 16, 16, 256)          0         ['depthwise_conv2d_3[0][0]']  \n","                                                                                                  \n"," batch_normalization_11 (Ba  (None, 16, 16, 256)          1024      ['activation_11[0][0]']       \n"," tchNormalization)                                                                                \n","                                                                                                  \n"," batch_normalization_7 (Bat  (None, 16, 16, 256)          1024      ['activation_7[0][0]']        \n"," chNormalization)                                                                                 \n","                                                                                                  \n"," add_8 (Add)                 (None, 16, 16, 256)          0         ['batch_normalization_11[0][0]\n","                                                                    ',                            \n","                                                                     'add_7[0][0]']               \n","                                                                                                  \n"," add_3 (Add)                 (None, 16, 16, 256)          0         ['batch_normalization_7[0][0]'\n","                                                                    , 'batch_normalization_6[0][0]\n","                                                                    ']                            \n","                                                                                                  \n"," conv2d_6 (Conv2D)           (None, 16, 16, 256)          65792     ['add_8[0][0]']               \n","                                                                                                  \n"," conv2d_4 (Conv2D)           (None, 16, 16, 256)          65792     ['add_3[0][0]']               \n","                                                                                                  \n"," activation_12 (Activation)  (None, 16, 16, 256)          0         ['conv2d_6[0][0]']            \n","                                                                                                  \n"," activation_8 (Activation)   (None, 16, 16, 256)          0         ['conv2d_4[0][0]']            \n","                                                                                                  \n"," batch_normalization_12 (Ba  (None, 16, 16, 256)          1024      ['activation_12[0][0]']       \n"," tchNormalization)                                                                                \n","                                                                                                  \n"," batch_normalization_8 (Bat  (None, 16, 16, 256)          1024      ['activation_8[0][0]']        \n"," chNormalization)                                                                                 \n","                                                                                                  \n"," add_9 (Add)                 (None, 16, 16, 256)          0         ['batch_normalization_4[0][0]'\n","                                                                    , 'batch_normalization_12[0][0\n","                                                                    ]']                           \n","                                                                                                  \n"," add_10 (Add)                (None, 16, 16, 256)          0         ['batch_normalization_8[0][0]'\n","                                                                    , 'add_9[0][0]']              \n","                                                                                                  \n"," add_15 (Add)                (None, 16, 16, 256)          0         ['add_9[0][0]',               \n","                                                                     'batch_normalization[0][0]'] \n","                                                                                                  \n"," depthwise_conv2d_6 (Depthw  (None, 16, 16, 256)          6656      ['add_10[0][0]']              \n"," iseConv2D)                                                                                       \n","                                                                                                  \n"," depthwise_conv2d_8 (Depthw  (None, 16, 16, 256)          6656      ['add_15[0][0]']              \n"," iseConv2D)                                                                                       \n","                                                                                                  \n"," activation_13 (Activation)  (None, 16, 16, 256)          0         ['depthwise_conv2d_6[0][0]']  \n","                                                                                                  \n"," activation_17 (Activation)  (None, 16, 16, 256)          0         ['depthwise_conv2d_8[0][0]']  \n","                                                                                                  \n"," batch_normalization_13 (Ba  (None, 16, 16, 256)          1024      ['activation_13[0][0]']       \n"," tchNormalization)                                                                                \n","                                                                                                  \n"," batch_normalization_17 (Ba  (None, 16, 16, 256)          1024      ['activation_17[0][0]']       \n"," tchNormalization)                                                                                \n","                                                                                                  \n"," add_11 (Add)                (None, 16, 16, 256)          0         ['batch_normalization_13[0][0]\n","                                                                    ',                            \n","                                                                     'add_10[0][0]']              \n","                                                                                                  \n"," add_16 (Add)                (None, 16, 16, 256)          0         ['batch_normalization_17[0][0]\n","                                                                    ',                            \n","                                                                     'add_15[0][0]']              \n","                                                                                                  \n"," conv2d_7 (Conv2D)           (None, 16, 16, 256)          65792     ['add_11[0][0]']              \n","                                                                                                  \n"," conv2d_9 (Conv2D)           (None, 16, 16, 256)          65792     ['add_16[0][0]']              \n","                                                                                                  \n"," activation_14 (Activation)  (None, 16, 16, 256)          0         ['conv2d_7[0][0]']            \n","                                                                                                  \n"," activation_18 (Activation)  (None, 16, 16, 256)          0         ['conv2d_9[0][0]']            \n","                                                                                                  \n"," batch_normalization_14 (Ba  (None, 16, 16, 256)          1024      ['activation_14[0][0]']       \n"," tchNormalization)                                                                                \n","                                                                                                  \n"," batch_normalization_18 (Ba  (None, 16, 16, 256)          1024      ['activation_18[0][0]']       \n"," tchNormalization)                                                                                \n","                                                                                                  \n"," add_12 (Add)                (None, 16, 16, 256)          0         ['batch_normalization_6[0][0]'\n","                                                                    , 'batch_normalization_14[0][0\n","                                                                    ]']                           \n","                                                                                                  \n"," add_17 (Add)                (None, 16, 16, 256)          0         ['add_6[0][0]',               \n","                                                                     'batch_normalization_18[0][0]\n","                                                                    ']                            \n","                                                                                                  \n"," add_18 (Add)                (None, 16, 16, 256)          0         ['add_12[0][0]',              \n","                                                                     'add_17[0][0]']              \n","                                                                                                  \n"," depthwise_conv2d_7 (Depthw  (None, 16, 16, 256)          6656      ['add_12[0][0]']              \n"," iseConv2D)                                                                                       \n","                                                                                                  \n"," depthwise_conv2d_9 (Depthw  (None, 16, 16, 256)          6656      ['add_18[0][0]']              \n"," iseConv2D)                                                                                       \n","                                                                                                  \n"," activation_15 (Activation)  (None, 16, 16, 256)          0         ['depthwise_conv2d_7[0][0]']  \n","                                                                                                  \n"," activation_19 (Activation)  (None, 16, 16, 256)          0         ['depthwise_conv2d_9[0][0]']  \n","                                                                                                  \n"," batch_normalization_15 (Ba  (None, 16, 16, 256)          1024      ['activation_15[0][0]']       \n"," tchNormalization)                                                                                \n","                                                                                                  \n"," batch_normalization_19 (Ba  (None, 16, 16, 256)          1024      ['activation_19[0][0]']       \n"," tchNormalization)                                                                                \n","                                                                                                  \n"," add_13 (Add)                (None, 16, 16, 256)          0         ['batch_normalization_15[0][0]\n","                                                                    ',                            \n","                                                                     'add_12[0][0]']              \n","                                                                                                  \n"," add_19 (Add)                (None, 16, 16, 256)          0         ['batch_normalization_19[0][0]\n","                                                                    ',                            \n","                                                                     'add_18[0][0]']              \n","                                                                                                  \n"," conv2d_8 (Conv2D)           (None, 16, 16, 256)          65792     ['add_13[0][0]']              \n","                                                                                                  \n"," conv2d_10 (Conv2D)          (None, 16, 16, 256)          65792     ['add_19[0][0]']              \n","                                                                                                  \n"," activation_16 (Activation)  (None, 16, 16, 256)          0         ['conv2d_8[0][0]']            \n","                                                                                                  \n"," activation_20 (Activation)  (None, 16, 16, 256)          0         ['conv2d_10[0][0]']           \n","                                                                                                  \n"," batch_normalization_16 (Ba  (None, 16, 16, 256)          1024      ['activation_16[0][0]']       \n"," tchNormalization)                                                                                \n","                                                                                                  \n"," batch_normalization_20 (Ba  (None, 16, 16, 256)          1024      ['activation_20[0][0]']       \n"," tchNormalization)                                                                                \n","                                                                                                  \n"," add_14 (Add)                (None, 16, 16, 256)          0         ['batch_normalization_8[0][0]'\n","                                                                    , 'batch_normalization_16[0][0\n","                                                                    ]']                           \n","                                                                                                  \n"," add_20 (Add)                (None, 16, 16, 256)          0         ['add_9[0][0]',               \n","                                                                     'batch_normalization_20[0][0]\n","                                                                    ']                            \n","                                                                                                  \n"," add_21 (Add)                (None, 16, 16, 256)          0         ['add_14[0][0]',              \n","                                                                     'add_20[0][0]']              \n","                                                                                                  \n"," add_26 (Add)                (None, 16, 16, 256)          0         ['add_20[0][0]',              \n","                                                                     'batch_normalization[0][0]'] \n","                                                                                                  \n"," depthwise_conv2d_10 (Depth  (None, 16, 16, 256)          6656      ['add_21[0][0]']              \n"," wiseConv2D)                                                                                      \n","                                                                                                  \n"," depthwise_conv2d_12 (Depth  (None, 16, 16, 256)          6656      ['add_26[0][0]']              \n"," wiseConv2D)                                                                                      \n","                                                                                                  \n"," activation_21 (Activation)  (None, 16, 16, 256)          0         ['depthwise_conv2d_10[0][0]'] \n","                                                                                                  \n"," activation_25 (Activation)  (None, 16, 16, 256)          0         ['depthwise_conv2d_12[0][0]'] \n","                                                                                                  \n"," batch_normalization_21 (Ba  (None, 16, 16, 256)          1024      ['activation_21[0][0]']       \n"," tchNormalization)                                                                                \n","                                                                                                  \n"," batch_normalization_25 (Ba  (None, 16, 16, 256)          1024      ['activation_25[0][0]']       \n"," tchNormalization)                                                                                \n","                                                                                                  \n"," add_22 (Add)                (None, 16, 16, 256)          0         ['batch_normalization_21[0][0]\n","                                                                    ',                            \n","                                                                     'add_21[0][0]']              \n","                                                                                                  \n"," add_27 (Add)                (None, 16, 16, 256)          0         ['batch_normalization_25[0][0]\n","                                                                    ',                            \n","                                                                     'add_26[0][0]']              \n","                                                                                                  \n"," conv2d_11 (Conv2D)          (None, 16, 16, 256)          65792     ['add_22[0][0]']              \n","                                                                                                  \n"," conv2d_13 (Conv2D)          (None, 16, 16, 256)          65792     ['add_27[0][0]']              \n","                                                                                                  \n"," activation_22 (Activation)  (None, 16, 16, 256)          0         ['conv2d_11[0][0]']           \n","                                                                                                  \n"," activation_26 (Activation)  (None, 16, 16, 256)          0         ['conv2d_13[0][0]']           \n","                                                                                                  \n"," batch_normalization_22 (Ba  (None, 16, 16, 256)          1024      ['activation_22[0][0]']       \n"," tchNormalization)                                                                                \n","                                                                                                  \n"," batch_normalization_26 (Ba  (None, 16, 16, 256)          1024      ['activation_26[0][0]']       \n"," tchNormalization)                                                                                \n","                                                                                                  \n"," add_23 (Add)                (None, 16, 16, 256)          0         ['add_12[0][0]',              \n","                                                                     'batch_normalization_22[0][0]\n","                                                                    ']                            \n","                                                                                                  \n"," add_28 (Add)                (None, 16, 16, 256)          0         ['add_17[0][0]',              \n","                                                                     'batch_normalization_26[0][0]\n","                                                                    ']                            \n","                                                                                                  \n"," add_29 (Add)                (None, 16, 16, 256)          0         ['add_23[0][0]',              \n","                                                                     'add_28[0][0]']              \n","                                                                                                  \n"," depthwise_conv2d_11 (Depth  (None, 16, 16, 256)          6656      ['add_23[0][0]']              \n"," wiseConv2D)                                                                                      \n","                                                                                                  \n"," depthwise_conv2d_13 (Depth  (None, 16, 16, 256)          6656      ['add_29[0][0]']              \n"," wiseConv2D)                                                                                      \n","                                                                                                  \n"," activation_23 (Activation)  (None, 16, 16, 256)          0         ['depthwise_conv2d_11[0][0]'] \n","                                                                                                  \n"," activation_27 (Activation)  (None, 16, 16, 256)          0         ['depthwise_conv2d_13[0][0]'] \n","                                                                                                  \n"," batch_normalization_23 (Ba  (None, 16, 16, 256)          1024      ['activation_23[0][0]']       \n"," tchNormalization)                                                                                \n","                                                                                                  \n"," batch_normalization_27 (Ba  (None, 16, 16, 256)          1024      ['activation_27[0][0]']       \n"," tchNormalization)                                                                                \n","                                                                                                  \n"," add_24 (Add)                (None, 16, 16, 256)          0         ['batch_normalization_23[0][0]\n","                                                                    ',                            \n","                                                                     'add_23[0][0]']              \n","                                                                                                  \n"," add_30 (Add)                (None, 16, 16, 256)          0         ['batch_normalization_27[0][0]\n","                                                                    ',                            \n","                                                                     'add_29[0][0]']              \n","                                                                                                  \n"," conv2d_12 (Conv2D)          (None, 16, 16, 256)          65792     ['add_24[0][0]']              \n","                                                                                                  \n"," conv2d_14 (Conv2D)          (None, 16, 16, 256)          65792     ['add_30[0][0]']              \n","                                                                                                  \n"," activation_24 (Activation)  (None, 16, 16, 256)          0         ['conv2d_12[0][0]']           \n","                                                                                                  \n"," activation_28 (Activation)  (None, 16, 16, 256)          0         ['conv2d_14[0][0]']           \n","                                                                                                  \n"," batch_normalization_24 (Ba  (None, 16, 16, 256)          1024      ['activation_24[0][0]']       \n"," tchNormalization)                                                                                \n","                                                                                                  \n"," batch_normalization_28 (Ba  (None, 16, 16, 256)          1024      ['activation_28[0][0]']       \n"," tchNormalization)                                                                                \n","                                                                                                  \n"," add_25 (Add)                (None, 16, 16, 256)          0         ['add_14[0][0]',              \n","                                                                     'batch_normalization_24[0][0]\n","                                                                    ']                            \n","                                                                                                  \n"," add_31 (Add)                (None, 16, 16, 256)          0         ['add_20[0][0]',              \n","                                                                     'batch_normalization_28[0][0]\n","                                                                    ']                            \n","                                                                                                  \n"," add_32 (Add)                (None, 16, 16, 256)          0         ['add_25[0][0]',              \n","                                                                     'add_31[0][0]']              \n","                                                                                                  \n"," depthwise_conv2d_14 (Depth  (None, 16, 16, 256)          6656      ['add_32[0][0]']              \n"," wiseConv2D)                                                                                      \n","                                                                                                  \n"," activation_29 (Activation)  (None, 16, 16, 256)          0         ['depthwise_conv2d_14[0][0]'] \n","                                                                                                  \n"," batch_normalization_29 (Ba  (None, 16, 16, 256)          1024      ['activation_29[0][0]']       \n"," tchNormalization)                                                                                \n","                                                                                                  \n"," add_33 (Add)                (None, 16, 16, 256)          0         ['batch_normalization_29[0][0]\n","                                                                    ',                            \n","                                                                     'add_32[0][0]']              \n","                                                                                                  \n"," conv2d_15 (Conv2D)          (None, 16, 16, 256)          65792     ['add_33[0][0]']              \n","                                                                                                  \n"," activation_30 (Activation)  (None, 16, 16, 256)          0         ['conv2d_15[0][0]']           \n","                                                                                                  \n"," batch_normalization_30 (Ba  (None, 16, 16, 256)          1024      ['activation_30[0][0]']       \n"," tchNormalization)                                                                                \n","                                                                                                  \n"," add_34 (Add)                (None, 16, 16, 256)          0         ['add_23[0][0]',              \n","                                                                     'batch_normalization_30[0][0]\n","                                                                    ']                            \n","                                                                                                  \n"," depthwise_conv2d_15 (Depth  (None, 16, 16, 256)          6656      ['add_34[0][0]']              \n"," wiseConv2D)                                                                                      \n","                                                                                                  \n"," activation_31 (Activation)  (None, 16, 16, 256)          0         ['depthwise_conv2d_15[0][0]'] \n","                                                                                                  \n"," batch_normalization_31 (Ba  (None, 16, 16, 256)          1024      ['activation_31[0][0]']       \n"," tchNormalization)                                                                                \n","                                                                                                  \n"," add_35 (Add)                (None, 16, 16, 256)          0         ['batch_normalization_31[0][0]\n","                                                                    ',                            \n","                                                                     'add_34[0][0]']              \n","                                                                                                  \n"," conv2d_16 (Conv2D)          (None, 16, 16, 256)          65792     ['add_35[0][0]']              \n","                                                                                                  \n"," activation_32 (Activation)  (None, 16, 16, 256)          0         ['conv2d_16[0][0]']           \n","                                                                                                  \n"," batch_normalization_32 (Ba  (None, 16, 16, 256)          1024      ['activation_32[0][0]']       \n"," tchNormalization)                                                                                \n","                                                                                                  \n"," add_36 (Add)                (None, 16, 16, 256)          0         ['add_25[0][0]',              \n","                                                                     'batch_normalization_32[0][0]\n","                                                                    ']                            \n","                                                                                                  \n"," global_average_pooling2d (  (None, 256)                  0         ['add_36[0][0]']              \n"," GlobalAveragePooling2D)                                                                          \n","                                                                                                  \n"," dense (Dense)               (None, 3)                    771       ['global_average_pooling2d[0][\n","                                                                    0]']                          \n","                                                                                                  \n","==================================================================================================\n","Total params: 1783811 (6.80 MB)\n","Trainable params: 1766915 (6.74 MB)\n","Non-trainable params: 16896 (66.00 KB)\n","__________________________________________________________________________________________________\n"]}],"source":["model = load_siren()\n","model.summary()"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"KXJng1w2pakq","outputId":"271a6b8a-5d32-47c3-8927-718077d4b1bb"},"outputs":[{"output_type":"stream","name":"stdout","text":["Epoch 1/100\n","2/2 [==============================] - 26s 3s/step - loss: 3880.3591 - mean_squared_error: 3880.3591 - val_loss: 4875.9541 - val_mean_squared_error: 4875.9541\n","Epoch 2/100\n","2/2 [==============================] - 1s 668ms/step - loss: 3908.3679 - mean_squared_error: 3908.3679 - val_loss: 4559.4316 - val_mean_squared_error: 4559.4316\n","Epoch 3/100\n","2/2 [==============================] - 2s 704ms/step - loss: 3822.4270 - mean_squared_error: 3822.4270 - val_loss: 4188.1167 - val_mean_squared_error: 4188.1167\n","Epoch 4/100\n","2/2 [==============================] - 2s 722ms/step - loss: 3621.4419 - mean_squared_error: 3621.4419 - val_loss: 4138.5928 - val_mean_squared_error: 4138.5928\n","Epoch 5/100\n","2/2 [==============================] - 2s 728ms/step - loss: 3490.9368 - mean_squared_error: 3490.9363 - val_loss: 4082.9075 - val_mean_squared_error: 4082.9075\n","Epoch 6/100\n","2/2 [==============================] - 2s 926ms/step - loss: 3472.8074 - mean_squared_error: 3472.8074 - val_loss: 3629.4656 - val_mean_squared_error: 3629.4656\n","Epoch 7/100\n","2/2 [==============================] - 2s 922ms/step - loss: 3456.2708 - mean_squared_error: 3456.2708 - val_loss: 3107.9558 - val_mean_squared_error: 3107.9558\n","Epoch 8/100\n","2/2 [==============================] - 1s 680ms/step - loss: 3318.4783 - mean_squared_error: 3318.4783 - val_loss: 3142.3330 - val_mean_squared_error: 3142.3330\n","Epoch 9/100\n","2/2 [==============================] - 2s 707ms/step - loss: 3536.9817 - mean_squared_error: 3536.9817 - val_loss: 3252.8210 - val_mean_squared_error: 3252.8210\n","Epoch 10/100\n","2/2 [==============================] - 2s 716ms/step - loss: 3435.4734 - mean_squared_error: 3435.4734 - val_loss: 3439.6443 - val_mean_squared_error: 3439.6443\n","Epoch 11/100\n","2/2 [==============================] - 1s 646ms/step - loss: 3343.6958 - mean_squared_error: 3343.6958 - val_loss: 3474.1091 - val_mean_squared_error: 3474.1091\n","Epoch 12/100\n","2/2 [==============================] - 2s 681ms/step - loss: 3266.2219 - mean_squared_error: 3266.2219 - val_loss: 3532.7737 - val_mean_squared_error: 3532.7737\n","Epoch 13/100\n","2/2 [==============================] - 2s 901ms/step - loss: 3253.5659 - mean_squared_error: 3253.5659 - val_loss: 3642.1367 - val_mean_squared_error: 3642.1367\n","Epoch 14/100\n","2/2 [==============================] - 1s 707ms/step - loss: 3379.8789 - mean_squared_error: 3379.8789 - val_loss: 3806.8826 - val_mean_squared_error: 3806.8826\n","Epoch 15/100\n","2/2 [==============================] - 1s 716ms/step - loss: 3197.4700 - mean_squared_error: 3197.4700 - val_loss: 3808.1963 - val_mean_squared_error: 3808.1963\n","Epoch 16/100\n","2/2 [==============================] - 1s 650ms/step - loss: 3273.2595 - mean_squared_error: 3273.2595 - val_loss: 4028.0164 - val_mean_squared_error: 4028.0164\n","Epoch 17/100\n","2/2 [==============================] - 2s 709ms/step - loss: 3132.1160 - mean_squared_error: 3132.1160 - val_loss: 4540.4673 - val_mean_squared_error: 4540.4673\n","Epoch 18/100\n","2/2 [==============================] - 1s 670ms/step - loss: 3245.8113 - mean_squared_error: 3245.8113 - val_loss: 4642.9502 - val_mean_squared_error: 4642.9502\n","Epoch 19/100\n","2/2 [==============================] - 2s 1s/step - loss: 3225.5583 - mean_squared_error: 3225.5583 - val_loss: 4481.3286 - val_mean_squared_error: 4481.3286\n","Epoch 20/100\n","2/2 [==============================] - 1s 657ms/step - loss: 3211.5234 - mean_squared_error: 3211.5234 - val_loss: 4395.4331 - val_mean_squared_error: 4395.4331\n","Epoch 21/100\n","2/2 [==============================] - 2s 708ms/step - loss: 3437.9565 - mean_squared_error: 3437.9565 - val_loss: 4700.0850 - val_mean_squared_error: 4700.0850\n","Epoch 22/100\n","2/2 [==============================] - 1s 670ms/step - loss: 3126.9514 - mean_squared_error: 3126.9514 - val_loss: 5114.5356 - val_mean_squared_error: 5114.5356\n","Epoch 23/100\n","2/2 [==============================] - 2s 713ms/step - loss: 2958.3745 - mean_squared_error: 2958.3745 - val_loss: 5255.9111 - val_mean_squared_error: 5255.9111\n","Epoch 24/100\n","2/2 [==============================] - 2s 734ms/step - loss: 3101.5320 - mean_squared_error: 3101.5320 - val_loss: 5262.1978 - val_mean_squared_error: 5262.1978\n","Epoch 25/100\n","2/2 [==============================] - 2s 664ms/step - loss: 3144.5261 - mean_squared_error: 3144.5261 - val_loss: 5616.7524 - val_mean_squared_error: 5616.7524\n","Epoch 26/100\n","2/2 [==============================] - 1s 721ms/step - loss: 2918.9497 - mean_squared_error: 2918.9497 - val_loss: 5999.9688 - val_mean_squared_error: 5999.9688\n","Epoch 27/100\n","2/2 [==============================] - 1s 655ms/step - loss: 3028.0149 - mean_squared_error: 3028.0149 - val_loss: 5855.6675 - val_mean_squared_error: 5855.6675\n","Epoch 28/100\n","2/2 [==============================] - 2s 730ms/step - loss: 2943.0503 - mean_squared_error: 2943.0503 - val_loss: 5666.4067 - val_mean_squared_error: 5666.4067\n","Epoch 29/100\n","2/2 [==============================] - 1s 651ms/step - loss: 2819.8113 - mean_squared_error: 2819.8113 - val_loss: 5546.2700 - val_mean_squared_error: 5546.2700\n","Epoch 30/100\n","2/2 [==============================] - 2s 1s/step - loss: 3095.4314 - mean_squared_error: 3095.4314 - val_loss: 5945.0854 - val_mean_squared_error: 5945.0854\n","Epoch 31/100\n","2/2 [==============================] - 2s 655ms/step - loss: 2833.9280 - mean_squared_error: 2833.9280 - val_loss: 6434.3594 - val_mean_squared_error: 6434.3594\n","Epoch 32/100\n","2/2 [==============================] - 2s 711ms/step - loss: 2863.2327 - mean_squared_error: 2863.2327 - val_loss: 6287.4712 - val_mean_squared_error: 6287.4712\n","Epoch 33/100\n","2/2 [==============================] - 1s 729ms/step - loss: 2920.8376 - mean_squared_error: 2920.8376 - val_loss: 5758.3633 - val_mean_squared_error: 5758.3633\n","Epoch 34/100\n","2/2 [==============================] - 1s 645ms/step - loss: 2702.0142 - mean_squared_error: 2702.0142 - val_loss: 5635.5171 - val_mean_squared_error: 5635.5171\n","Epoch 35/100\n","2/2 [==============================] - 1s 656ms/step - loss: 2660.8181 - mean_squared_error: 2660.8181 - val_loss: 5803.8384 - val_mean_squared_error: 5803.8384\n","Epoch 36/100\n","2/2 [==============================] - 2s 963ms/step - loss: 2559.0403 - mean_squared_error: 2559.0403 - val_loss: 6037.3765 - val_mean_squared_error: 6037.3765\n","Epoch 37/100\n","2/2 [==============================] - 1s 652ms/step - loss: 2754.1133 - mean_squared_error: 2754.1133 - val_loss: 6421.2812 - val_mean_squared_error: 6421.2812\n","Epoch 38/100\n","2/2 [==============================] - 2s 729ms/step - loss: 2688.5920 - mean_squared_error: 2688.5920 - val_loss: 6563.5474 - val_mean_squared_error: 6563.5474\n","Epoch 39/100\n","2/2 [==============================] - 1s 661ms/step - loss: 2784.3677 - mean_squared_error: 2784.3677 - val_loss: 6001.1177 - val_mean_squared_error: 6001.1177\n","Epoch 40/100\n","2/2 [==============================] - 1s 729ms/step - loss: 2685.4604 - mean_squared_error: 2685.4604 - val_loss: 5618.3906 - val_mean_squared_error: 5618.3906\n","Epoch 41/100\n","2/2 [==============================] - 2s 927ms/step - loss: 2682.4285 - mean_squared_error: 2682.4285 - val_loss: 5886.0317 - val_mean_squared_error: 5886.0317\n","Epoch 42/100\n","2/2 [==============================] - 1s 664ms/step - loss: 2350.6836 - mean_squared_error: 2350.6836 - val_loss: 6315.9790 - val_mean_squared_error: 6315.9790\n","Epoch 43/100\n","2/2 [==============================] - 1s 665ms/step - loss: 2552.6052 - mean_squared_error: 2552.6052 - val_loss: 6674.0547 - val_mean_squared_error: 6674.0547\n","Epoch 44/100\n","2/2 [==============================] - 1s 657ms/step - loss: 2333.1721 - mean_squared_error: 2333.1721 - val_loss: 6366.7153 - val_mean_squared_error: 6366.7153\n","Epoch 45/100\n","2/2 [==============================] - 2s 1s/step - loss: 2492.5715 - mean_squared_error: 2492.5715 - val_loss: 5306.5464 - val_mean_squared_error: 5306.5464\n","Epoch 46/100\n","2/2 [==============================] - 1s 677ms/step - loss: 2601.1365 - mean_squared_error: 2601.1365 - val_loss: 5177.3403 - val_mean_squared_error: 5177.3403\n","Epoch 47/100\n","2/2 [==============================] - 2s 1s/step - loss: 2413.9553 - mean_squared_error: 2413.9553 - val_loss: 5741.2603 - val_mean_squared_error: 5741.2603\n","Epoch 48/100\n","2/2 [==============================] - 2s 669ms/step - loss: 2586.1580 - mean_squared_error: 2586.1580 - val_loss: 6098.2437 - val_mean_squared_error: 6098.2437\n","Epoch 49/100\n","2/2 [==============================] - 2s 720ms/step - loss: 2340.5530 - mean_squared_error: 2340.5530 - val_loss: 6019.0161 - val_mean_squared_error: 6019.0161\n","Epoch 50/100\n","2/2 [==============================] - 2s 722ms/step - loss: 2304.3774 - mean_squared_error: 2304.3774 - val_loss: 5953.3384 - val_mean_squared_error: 5953.3384\n","Epoch 51/100\n","2/2 [==============================] - 1s 655ms/step - loss: 2242.7437 - mean_squared_error: 2242.7437 - val_loss: 6098.7534 - val_mean_squared_error: 6098.7534\n","Epoch 52/100\n","2/2 [==============================] - 2s 727ms/step - loss: 2117.9270 - mean_squared_error: 2117.9272 - val_loss: 6290.5645 - val_mean_squared_error: 6290.5645\n","Epoch 53/100\n","2/2 [==============================] - 2s 734ms/step - loss: 2105.0066 - mean_squared_error: 2105.0066 - val_loss: 6222.7944 - val_mean_squared_error: 6222.7944\n","Epoch 54/100\n","2/2 [==============================] - 2s 1s/step - loss: 1989.3015 - mean_squared_error: 1989.3015 - val_loss: 6247.2104 - val_mean_squared_error: 6247.2104\n","Epoch 55/100\n","2/2 [==============================] - 1s 723ms/step - loss: 2331.0801 - mean_squared_error: 2331.0801 - val_loss: 6233.0991 - val_mean_squared_error: 6233.0991\n","Epoch 56/100\n","2/2 [==============================] - 1s 667ms/step - loss: 2035.0924 - mean_squared_error: 2035.0924 - val_loss: 6222.0415 - val_mean_squared_error: 6222.0415\n","Epoch 57/100\n","2/2 [==============================] - 2s 718ms/step - loss: 1964.8500 - mean_squared_error: 1964.8500 - val_loss: 6270.8374 - val_mean_squared_error: 6270.8374\n","Epoch 58/100\n","2/2 [==============================] - 1s 707ms/step - loss: 1858.0452 - mean_squared_error: 1858.0452 - val_loss: 5928.4414 - val_mean_squared_error: 5928.4414\n","Epoch 59/100\n","2/2 [==============================] - 2s 1s/step - loss: 1948.7904 - mean_squared_error: 1948.7904 - val_loss: 5331.8755 - val_mean_squared_error: 5331.8755\n","Epoch 60/100\n","2/2 [==============================] - 2s 712ms/step - loss: 1898.0530 - mean_squared_error: 1898.0530 - val_loss: 5097.2114 - val_mean_squared_error: 5097.2114\n","Epoch 61/100\n","2/2 [==============================] - 1s 665ms/step - loss: 1951.6495 - mean_squared_error: 1951.6497 - val_loss: 5328.5308 - val_mean_squared_error: 5328.5308\n","Epoch 62/100\n","2/2 [==============================] - 1s 642ms/step - loss: 2071.0071 - mean_squared_error: 2071.0071 - val_loss: 4801.5728 - val_mean_squared_error: 4801.5728\n","Epoch 63/100\n","2/2 [==============================] - 1s 666ms/step - loss: 1815.4147 - mean_squared_error: 1815.4147 - val_loss: 4535.0659 - val_mean_squared_error: 4535.0659\n","Epoch 64/100\n","2/2 [==============================] - 2s 723ms/step - loss: 1641.0701 - mean_squared_error: 1641.0701 - val_loss: 4662.2231 - val_mean_squared_error: 4662.2231\n","Epoch 65/100\n","2/2 [==============================] - 1s 708ms/step - loss: 1558.1404 - mean_squared_error: 1558.1404 - val_loss: 3973.6191 - val_mean_squared_error: 3973.6191\n","Epoch 66/100\n","2/2 [==============================] - 2s 1s/step - loss: 1672.6290 - mean_squared_error: 1672.6290 - val_loss: 3198.7747 - val_mean_squared_error: 3198.7747\n","Epoch 67/100\n","2/2 [==============================] - 2s 716ms/step - loss: 1577.4314 - mean_squared_error: 1577.4314 - val_loss: 3057.9695 - val_mean_squared_error: 3057.9695\n","Epoch 68/100\n","2/2 [==============================] - 1s 665ms/step - loss: 1464.0262 - mean_squared_error: 1464.0262 - val_loss: 3350.6379 - val_mean_squared_error: 3350.6379\n","Epoch 69/100\n","2/2 [==============================] - 1s 712ms/step - loss: 1513.4590 - mean_squared_error: 1513.4590 - val_loss: 3163.6257 - val_mean_squared_error: 3163.6257\n","Epoch 70/100\n","2/2 [==============================] - 1s 726ms/step - loss: 1496.0785 - mean_squared_error: 1496.0785 - val_loss: 3312.7854 - val_mean_squared_error: 3312.7854\n","Epoch 71/100\n","2/2 [==============================] - 1s 696ms/step - loss: 1368.9303 - mean_squared_error: 1368.9303 - val_loss: 3580.0168 - val_mean_squared_error: 3580.0168\n","Epoch 72/100\n","2/2 [==============================] - 2s 864ms/step - loss: 1265.7002 - mean_squared_error: 1265.7002 - val_loss: 3808.1633 - val_mean_squared_error: 3808.1633\n","Epoch 73/100\n","2/2 [==============================] - 2s 644ms/step - loss: 1203.6229 - mean_squared_error: 1203.6229 - val_loss: 4024.4128 - val_mean_squared_error: 4024.4128\n","Epoch 74/100\n","2/2 [==============================] - 1s 661ms/step - loss: 1211.9738 - mean_squared_error: 1211.9738 - val_loss: 3895.5508 - val_mean_squared_error: 3895.5508\n","Epoch 75/100\n","2/2 [==============================] - 1s 702ms/step - loss: 1147.9855 - mean_squared_error: 1147.9855 - val_loss: 3648.2722 - val_mean_squared_error: 3648.2722\n","Epoch 76/100\n","2/2 [==============================] - 2s 719ms/step - loss: 1094.7274 - mean_squared_error: 1094.7274 - val_loss: 3485.2910 - val_mean_squared_error: 3485.2910\n","Epoch 77/100\n","2/2 [==============================] - 1s 709ms/step - loss: 1048.7224 - mean_squared_error: 1048.7224 - val_loss: 3417.6482 - val_mean_squared_error: 3417.6482\n","Epoch 78/100\n","2/2 [==============================] - 1s 673ms/step - loss: 1061.5748 - mean_squared_error: 1061.5748 - val_loss: 3380.8115 - val_mean_squared_error: 3380.8115\n","Epoch 79/100\n","2/2 [==============================] - 2s 683ms/step - loss: 976.7926 - mean_squared_error: 976.7926 - val_loss: 3230.6868 - val_mean_squared_error: 3230.6868\n","Epoch 80/100\n","2/2 [==============================] - 2s 725ms/step - loss: 1114.7720 - mean_squared_error: 1114.7720 - val_loss: 3041.2126 - val_mean_squared_error: 3041.2126\n","Epoch 81/100\n","2/2 [==============================] - 2s 727ms/step - loss: 969.4302 - mean_squared_error: 969.4302 - val_loss: 2916.9734 - val_mean_squared_error: 2916.9734\n","Epoch 82/100\n","2/2 [==============================] - 2s 737ms/step - loss: 855.7783 - mean_squared_error: 855.7783 - val_loss: 2873.7395 - val_mean_squared_error: 2873.7395\n","Epoch 83/100\n","2/2 [==============================] - 1s 676ms/step - loss: 866.9525 - mean_squared_error: 866.9525 - val_loss: 3041.2410 - val_mean_squared_error: 3041.2410\n","Epoch 84/100\n","2/2 [==============================] - 2s 672ms/step - loss: 993.6716 - mean_squared_error: 993.6716 - val_loss: 3296.4021 - val_mean_squared_error: 3296.4021\n","Epoch 85/100\n","2/2 [==============================] - 1s 727ms/step - loss: 875.3380 - mean_squared_error: 875.3380 - val_loss: 3575.1953 - val_mean_squared_error: 3575.1953\n","Epoch 86/100\n","2/2 [==============================] - 1s 652ms/step - loss: 771.4354 - mean_squared_error: 771.4354 - val_loss: 3747.6160 - val_mean_squared_error: 3747.6160\n","Epoch 87/100\n","2/2 [==============================] - 1s 719ms/step - loss: 757.6100 - mean_squared_error: 757.6100 - val_loss: 3939.4629 - val_mean_squared_error: 3939.4629\n","Epoch 88/100\n","2/2 [==============================] - 1s 647ms/step - loss: 722.4261 - mean_squared_error: 722.4261 - val_loss: 4175.7666 - val_mean_squared_error: 4175.7666\n","Epoch 89/100\n","2/2 [==============================] - 2s 1s/step - loss: 724.5212 - mean_squared_error: 724.5212 - val_loss: 4226.5220 - val_mean_squared_error: 4226.5220\n","Epoch 90/100\n","2/2 [==============================] - 2s 681ms/step - loss: 1022.5958 - mean_squared_error: 1022.5958 - val_loss: 4071.5256 - val_mean_squared_error: 4071.5256\n","Epoch 91/100\n","2/2 [==============================] - 1s 703ms/step - loss: 732.5883 - mean_squared_error: 732.5883 - val_loss: 3731.2861 - val_mean_squared_error: 3731.2861\n","Epoch 92/100\n","2/2 [==============================] - 1s 724ms/step - loss: 590.4905 - mean_squared_error: 590.4905 - val_loss: 3569.9426 - val_mean_squared_error: 3569.9426\n","Epoch 93/100\n","2/2 [==============================] - 1s 658ms/step - loss: 571.0239 - mean_squared_error: 571.0239 - val_loss: 3575.6348 - val_mean_squared_error: 3575.6348\n","Epoch 94/100\n","2/2 [==============================] - 1s 670ms/step - loss: 639.4352 - mean_squared_error: 639.4352 - val_loss: 3631.6970 - val_mean_squared_error: 3631.6970\n","Epoch 95/100\n","2/2 [==============================] - 2s 987ms/step - loss: 507.0977 - mean_squared_error: 507.0977 - val_loss: 3724.3665 - val_mean_squared_error: 3724.3665\n","Epoch 96/100\n","2/2 [==============================] - 2s 888ms/step - loss: 511.5831 - mean_squared_error: 511.5831 - val_loss: 3660.9675 - val_mean_squared_error: 3660.9675\n","Epoch 97/100\n","2/2 [==============================] - 1s 642ms/step - loss: 607.3203 - mean_squared_error: 607.3203 - val_loss: 3457.7571 - val_mean_squared_error: 3457.7571\n","Epoch 98/100\n","2/2 [==============================] - 2s 716ms/step - loss: 502.6704 - mean_squared_error: 502.6704 - val_loss: 3388.1602 - val_mean_squared_error: 3388.1602\n","Epoch 99/100\n","2/2 [==============================] - 1s 665ms/step - loss: 435.9974 - mean_squared_error: 435.9974 - val_loss: 3419.8347 - val_mean_squared_error: 3419.8347\n","Epoch 100/100\n","2/2 [==============================] - 2s 907ms/step - loss: 564.8565 - mean_squared_error: 564.8565 - val_loss: 3420.9299 - val_mean_squared_error: 3420.9299\n","1/1 [==============================] - 0s 98ms/step - loss: 12064.5557 - mean_squared_error: 12064.5557\n","Test error: 12064.56\n"]}],"source":["history, model = launch_experiment(model)"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"lbe8bvP0pakq","outputId":"ff9b641e-2202-4a55-b643-052cdd4cdb59"},"outputs":[{"output_type":"stream","name":"stderr","text":["/usr/local/lib/python3.10/dist-packages/keras/src/engine/training.py:3103: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n","  saving_api.save_model(\n"]}],"source":["model.save(model_save_path)"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"f68Wvisypakq","outputId":"91489a81-3caf-487f-8b53-9ea7d9a32cef"},"outputs":[{"output_type":"stream","name":"stdout","text":["1/1 [==============================] - 2s 2s/step\n"]}],"source":["pred = model.predict(test_ds)"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"6S2XmLTVpakq"},"outputs":[],"source":["# ============================== generate data ==============================\n","import os\n","import numpy as np\n","import matplotlib.pyplot as plt\n","from scipy import interp\n","from itertools import cycle\n","from sklearn.metrics import roc_curve, auc\n","from sklearn.metrics import classification_report\n","from sklearn.metrics import PredictionErrorDisplay\n","from sklearn import metrics\n","import tensorflow as tf\n","from tensorflow import keras as k"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"N1US9W-3pakr"},"outputs":[],"source":["multi_pred = pred\n","gaps_pred, flank_wear_pred, overhang_pred = multi_pred.T\n","\n","multi_true = labels_test.to_numpy()\n","gaps_true, flank_wear_true, overhang_true = multi_true.T"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"ZabUzvzKpakr"},"outputs":[],"source":["labels_list = [\n","    \"gaps\",\n","    \"flank_wear\",\n","    \"overhang\",\n","    \"multi\",\n","]\n","pred_list = [\n","    gaps_pred,\n","    flank_wear_pred,\n","    overhang_pred,\n","    multi_pred,\n","]\n","true_list = [\n","    gaps_true,\n","    flank_wear_true,\n","    overhang_true,\n","    multi_true,\n","]"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":472},"id":"ewSUhAjvpakr","outputId":"8f0024bd-f29d-4fdb-e859-707b705649f2"},"outputs":[{"output_type":"display_data","data":{"text/plain":["<Figure size 640x480 with 1 Axes>"],"image/png":"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\n"},"metadata":{}}],"source":["# loss\n","plt.plot(history.history[\"loss\"])\n","plt.plot(history.history[\"val_loss\"])\n","plt.title(\"model loss\")\n","plt.ylabel(\"loss\")\n","plt.xlabel(\"epoch\")\n","plt.legend([\"train\", \"val\"], loc=\"upper left\")\n","plt.show()"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":1000},"id":"SSbH568Vpakr","outputId":"a41b8153-e7aa-4037-9c89-a581f1bbeb86"},"outputs":[{"output_type":"display_data","data":{"text/plain":["<Figure size 800x400 with 2 Axes>"],"image/png":"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\n"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["<Figure 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\n"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["<Figure 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\n"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["<Figure 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\n"},"metadata":{}}],"source":["for label, y_pred, y_true in zip(labels_list, pred_list, true_list):\n","    # https://scikit-learn.org/stable/auto_examples/model_selection/plot_cv_predict.html#sphx-glr-auto-examples-model-selection-plot-cv-predict-py\n","    fig, axs = plt.subplots(ncols=2, figsize=(8, 4))\n","    PredictionErrorDisplay.from_predictions(\n","        y_true=y_true,\n","        y_pred=y_pred,\n","        kind=\"actual_vs_predicted\",\n","        subsample=100,\n","        ax=axs[0],\n","        random_state=0,\n","    )\n","    axs[0].set_title(\"Actual vs. Predicted values\")\n","    PredictionErrorDisplay.from_predictions(\n","        y_true=y_true,\n","        y_pred=y_pred,\n","        kind=\"residual_vs_predicted\",\n","        subsample=100,\n","        ax=axs[1],\n","        random_state=0,\n","    )\n","    axs[1].set_title(\"Residuals vs. Predicted Values\")\n","    fig.suptitle(\"Plotting cross-validated predictions \" + label)\n","    plt.tight_layout()\n","    plt.show()"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"6cYEfpMZpakr"},"outputs":[],"source":["def min_shift(list1, list2):\n","    list1 = np.array(list1)\n","    list2 = np.array(list2)\n","    if list1.ndim == 2:\n","        for i in range(len(list1)):\n","            if np.min([list1, list2]) > 0:\n","                continue\n","            min = np.min([list1[i], list2[i]])\n","            list1[i] -= min\n","            list2[i] -= min\n","        return list1, list2\n","\n","    min = np.min([list1, list2])\n","    list1 = list1 - min\n","    list2 = list1 - min\n","\n","    return list1, list2"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"zYsvsYrdpaks","outputId":"279c3dd4-2a9b-4215-a037-272dcf533a7a"},"outputs":[{"output_type":"stream","name":"stdout","text":["===== gaps results =====\n","MAE:  26.6913410949707\n","MSE:  803.0404192960414\n","RMSE:  28.33796780462638\n","r2_score:  -6.610890232060309\n","MSLE_min_shifted:  0.3490041309634699\n","MAPE:  5.994959446754372e+16\n","===== flank_wear results =====\n","MAE:  149.16858514785767\n","MSE:  35137.350160727285\n","RMSE:  187.44959365313994\n","r2_score:  -1.1930202575454136\n","MSLE_min_shifted:  0.0055041684213141566\n","MAPE:  1.0001396589268292\n","===== overhang results =====\n","MAE:  15.273324635823565\n","MSE:  253.2762692476615\n","RMSE:  15.914655800477165\n","r2_score:  -11.55554283136725\n","MSLE:  0.7404336044759451\n","MAPE:  1.4915682599168785\n","===== multi results =====\n","MAE:  63.71108362621732\n","MSE:  12064.555616423662\n","RMSE:  77.23407241941449\n","r2_score:  -6.453151106990991\n","MSLE_min_shifted:  4.601355923169783\n","MAPE:  1.9983198155847908e+16\n"]}],"source":["for label, y_pred, y_true in zip(labels_list, pred_list, true_list):\n","    print(f\"===== {label} results =====\")\n","    print(\"MAE: \", metrics.mean_absolute_error(y_true, y_pred))\n","    print(\"MSE: \", metrics.mean_squared_error(y_true, y_pred))\n","    print(\"RMSE: \", metrics.mean_squared_error(y_true, y_pred, squared=False))\n","    print(\"r2_score: \", metrics.r2_score(y_true, y_pred))\n","    try:\n","        print(\"MSLE: \", metrics.mean_squared_log_error(y_true, y_pred))\n","    except ValueError as err:\n","        y_true_shift, y_pred_shift = min_shift(y_true, y_pred)\n","        print(\n","            \"MSLE_min_shifted: \",\n","            metrics.mean_squared_log_error(y_true_shift, y_pred_shift),\n","        )\n","    print(\"MAPE: \", metrics.mean_absolute_percentage_error(y_true, y_pred))"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"2vrCvRRwpaks"},"outputs":[],"source":[]}],"metadata":{"colab":{"provenance":[]},"kernelspec":{"display_name":"Python 3","name":"python3"},"language_info":{"codemirror_mode":{"name":"ipython","version":3},"file_extension":".py","mimetype":"text/x-python","name":"python","nbconvert_exporter":"python","pygments_lexer":"ipython3","version":"3.9.17"},"orig_nbformat":4},"nbformat":4,"nbformat_minor":0}