4g-diabetes-binary-class.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "tags": [
     "skip"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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      "Requirement already satisfied: executing in /usr/local/lib/python3.8/dist-packages (from stack-data->ipython>=5.3.0->pyvis==0.3.1->-r requirements.txt (line 7)) (1.1.1)\n",
      "Requirement already satisfied: zipp>=0.5 in /usr/local/lib/python3.8/dist-packages (from importlib-metadata>=4.4->markdown>=2.6.8->tensorboard<2.12,>=2.11->tensorflow==2.11.0->-r requirements.txt (line 4)) (3.10.0)\n",
      "Requirement already satisfied: pyasn1<0.5.0,>=0.4.6 in /usr/local/lib/python3.8/dist-packages (from pyasn1-modules>=0.2.1->google-auth<3,>=1.6.3->tensorboard<2.12,>=2.11->tensorflow==2.11.0->-r requirements.txt (line 4)) (0.4.8)\n",
      "Requirement already satisfied: oauthlib>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from requests-oauthlib>=0.7.0->google-auth-oauthlib<0.5,>=0.4.1->tensorboard<2.12,>=2.11->tensorflow==2.11.0->-r requirements.txt (line 4)) (3.2.2)\n",
      "Building wheels for collected packages: jax, pyvis\n",
      "  Building wheel for jax (setup.py) ... \u001b[?25ldone\n",
      "\u001b[?25h  Created wheel for jax: filename=jax-0.4.1-py3-none-any.whl size=1338540 sha256=4dd3cdffd42fef2465a36f88c3a1f8f0c583bb5d18e9acac162e3b406958278f\n",
      "  Stored in directory: /home/jovyan/.cache/pip/wheels/e2/c2/cc/ac766a5c8ed28aec746fc292690d3e2e3790b554d2a6abacb7\n",
      "  Building wheel for pyvis (setup.py) ... \u001b[?25ldone\n",
      "\u001b[?25h  Created wheel for pyvis: filename=pyvis-0.3.1-py3-none-any.whl size=756330 sha256=1ff7c49e2edcdf87a7f258fe45b468ac830360ed57ebd9e906f804a0df3e03a5\n",
      "  Stored in directory: /home/jovyan/.cache/pip/wheels/a4/0c/61/8469ca276f96ab772c3acc7f47d71e9737cbdf6f446f017f48\n",
      "Successfully built jax pyvis\n",
      "Installing collected packages: tensorboard-plugin-wit, libclang, flatbuffers, werkzeug, tensorflow-io-gcs-filesystem, tensorflow-estimator, tensorboard-data-server, tenacity, pytzdata, protobuf, numpy, keras, google-pasta, gast, fonttools, astunparse, absl-py, scipy, plotly, pendulum, pandas, opt_einsum, markdown, h5py, contourpy, matplotlib, jaxlib, jax, google-auth-oauthlib, tensorboard, pyvis, tensorflow\n",
      "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
      "yellowbrick 1.3 requires numpy<1.20,>=1.16.0, but you have numpy 1.24.0 which is incompatible.\n",
      "ml-metadata 0.30.0 requires absl-py<0.13,>=0.9, but you have absl-py 1.3.0 which is incompatible.\n",
      "kubeflow-kale 2.0rc3.post0+6.g3f6dfd87b requires matplotlib<3.4.0, but you have matplotlib 3.6.2 which is incompatible.\n",
      "kubeflow-kale 2.0rc3.post0+6.g3f6dfd87b requires scipy<1.7, but you have scipy 1.10.0 which is incompatible.\n",
      "kserve 0.8.0 requires numpy~=1.19.2, but you have numpy 1.24.0 which is incompatible.\n",
      "kfp 1.7.post0+41.gb3589b6c6 requires absl-py<=0.11,>=0.9, but you have absl-py 1.3.0 which is incompatible.\u001b[0m\u001b[31m\n",
      "\u001b[0mSuccessfully installed absl-py-1.3.0 astunparse-1.6.3 contourpy-1.0.6 flatbuffers-23.1.4 fonttools-4.38.0 gast-0.4.0 google-auth-oauthlib-0.4.6 google-pasta-0.2.0 h5py-3.7.0 jax-0.4.1 jaxlib-0.4.1 keras-2.11.0 libclang-14.0.6 markdown-3.4.1 matplotlib-3.6.2 numpy-1.24.0 opt_einsum-3.3.0 pandas-1.5.2 pendulum-2.1.2 plotly-5.11.0 protobuf-3.19.6 pytzdata-2020.1 pyvis-0.3.1 scipy-1.10.0 tenacity-8.1.0 tensorboard-2.11.0 tensorboard-data-server-0.6.1 tensorboard-plugin-wit-1.8.1 tensorflow-2.11.0 tensorflow-estimator-2.11.0 tensorflow-io-gcs-filesystem-0.29.0 werkzeug-2.2.2\n",
      "\u001b[33mWARNING: You are using pip version 22.0.4; however, version 22.3.1 is available.\n",
      "You should consider upgrading via the '/usr/bin/python3 -m pip install --upgrade pip' command.\u001b[0m\u001b[33m\n",
      "\u001b[0m"
     ]
    }
   ],
   "source": [
    "\n",
    "! pip3 install -r requirements.txt\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "tags": [
     "skip"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'status': 'ok', 'restart': True}"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import sys\n",
    "import IPython\n",
    "app = IPython.Application.instance()\n",
    "app.kernel.do_shutdown(True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "tags": [
     "imports"
    ]
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2023-01-09 06:03:14.664523: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcudart.so.11.0'; dlerror: libcudart.so.11.0: cannot open shared object file: No such file or directory\n",
      "2023-01-09 06:03:15.564873: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer.so.7'; dlerror: libnvinfer.so.7: cannot open shared object file: No such file or directory\n",
      "2023-01-09 06:03:15.565008: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer_plugin.so.7'; dlerror: libnvinfer_plugin.so.7: cannot open shared object file: No such file or directory\n",
      "2023-01-09 06:03:15.565021: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Cannot dlopen some TensorRT libraries. If you would like to use Nvidia GPU with TensorRT, please make sure the missing libraries mentioned above are installed properly.\n",
      "2023-01-09 06:03:16.547872: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcuda.so.1'; dlerror: libcuda.so.1: cannot open shared object file: No such file or directory\n",
      "2023-01-09 06:03:16.547908: W tensorflow/compiler/xla/stream_executor/cuda/cuda_driver.cc:265] failed call to cuInit: UNKNOWN ERROR (303)\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "# from multiprocessing import Pool  # , Process\n",
    "from cerebros.simplecerebrosrandomsearch.simple_cerebros_random_search\\\n",
    "    import SimpleCerebrosRandomSearch\n",
    "import pendulum\n",
    "import pandas as pd\n",
    "import tensorflow as tf\n",
    "from cerebros.units.units import DenseUnit\n",
    "from cerebros.denseautomlstructuralcomponent.dense_automl_structural_component\\\n",
    "    import zero_7_exp_decay, zero_95_exp_decay, simple_sigmoid\n",
    "from ast import literal_eval"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "tags": [
     "pipeline-parameters"
    ]
   },
   "outputs": [],
   "source": [
    "\n",
    "activation = 'relu'\n",
    "predecessor_level_connection_affinity_factor_first = 2.0\n",
    "predecessor_level_connection_affinity_factor_main = 0.97\n",
    "max_consecutive_lateral_connections = 5\n",
    "p_lateral_connection = 0.97\n",
    "num_lateral_connection_tries_per_unit = 2\n",
    "learning_rate = 0.001\n",
    "epochs = 10 # [1, 100]\n",
    "batch_size = 100\n",
    "maximum_levels = 6 # [3,7]\n",
    "maximum_units_per_level = 4 # [2,10]\n",
    "maximum_neurons_per_unit = 4 # [2,20]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "tags": [
     "block:data_prep"
    ]
   },
   "outputs": [],
   "source": [
    "\n",
    "raw_data = pd.read_csv('diabetes.csv')\n",
    "label = raw_data.pop('Outcome').astype(int).values\n",
    "\n",
    "data_numeric = raw_data.astype(float)\n",
    "\n",
    "\n",
    "data_np = data_numeric.values\n",
    "\n",
    "# np.save('label', label, allow_pickle=True)\n",
    "# np.save('data', data_np, allow_pickle=True)\n",
    "\n",
    "TIME = pendulum.now(tz='America/New_York').__str__()[:16]\\\n",
    "    .replace('T', '_')\\\n",
    "    .replace(':', '_')\\\n",
    "    .replace('-', '_')\n",
    "PROJECT_NAME = f'{TIME}_cerebros_auto_ml_test'\n",
    "\n",
    "# data_np = np.load('data.npy', allow_pickle=True)\n",
    "# labels = np.load('labels.npy', allow_pickle=True)\n",
    "\n",
    "tensor_x =\\\n",
    "    tf.constant(data_np)\n",
    "\n",
    "training_x = [tensor_x]\n",
    "\n",
    "INPUT_SHAPES = [training_x[i].shape[1] for i in np.arange(len(training_x))]\n",
    "\n",
    "\n",
    "#alcohol_labels = tf.constant(pd.get_dummies(pd.cut(white['alcohol'], np.arange(\n",
    "#    white['alcohol'].min(), white['alcohol'].max()))).values)\n",
    "# quality_labels = tf.constant(pd.get_dummies(white['quality']).values)\n",
    "\n",
    "train_labels = [label]\n",
    "\n",
    "# OUTPUT_SHAPES = [1]  # [train_labels[i].shape[1]\n",
    "# for i in np.arange(len(train_labels))]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "tags": [
     "block:train",
     "prev:data_prep"
    ]
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "No GPU/TPU found, falling back to CPU. (Set TF_CPP_MIN_LOG_LEVEL=0 and rerun for more info.)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "nan\n",
      ">nnf>ceil\n",
      "k is: 0 value is: [{'1': <class 'cerebros.units.units.InputUnit'>}]\n",
      "0\n",
      "k is: 1 value is: [{'3': <class 'cerebros.units.units.DenseUnit'>}]\n",
      "1\n",
      "Trying to create level 1\n",
      "We think level 1's predecessors are: [0]\n",
      "k is: 2 value is: [{'4': <class 'cerebros.units.units.DenseUnit'>}, {'2': <class 'cerebros.units.units.DenseUnit'>}, {'2': <class 'cerebros.units.units.DenseUnit'>}, {'1': <class 'cerebros.units.units.DenseUnit'>}]\n",
      "2\n",
      "Trying to create level 2\n",
      "We think level 2's predecessors are: [0, 1]\n",
      "k is: 3 value is: [{'2': <class 'cerebros.units.units.DenseUnit'>}, {'3': <class 'cerebros.units.units.DenseUnit'>}, {'4': <class 'cerebros.units.units.DenseUnit'>}]\n",
      "3\n",
      "Trying to create level 3\n",
      "We think level 3's predecessors are: [0, 1, 2]\n",
      "k is: 4 value is: [{'1': <class 'cerebros.units.units.FinalDenseUnit'>}]\n",
      "4\n",
      "Trying to create Final level 4\n",
      "Trying to create level 4\n",
      "We think level final level 4's predecessors are: [0, 1, 2, 3]\n",
      "levels:\n",
      "[0, 1, 2, 3, 4]\n",
      "{'0': 'InputUnitModule'}\n",
      "{'3': <class 'cerebros.units.units.DenseUnit'>}\n",
      "{'4': <class 'cerebros.units.units.DenseUnit'>}\n",
      "{'2': <class 'cerebros.units.units.DenseUnit'>}\n",
      "{'2': <class 'cerebros.units.units.DenseUnit'>}\n",
      "{'1': <class 'cerebros.units.units.DenseUnit'>}\n",
      "{'2': <class 'cerebros.units.units.DenseUnit'>}\n",
      "{'3': <class 'cerebros.units.units.DenseUnit'>}\n",
      "{'4': <class 'cerebros.units.units.DenseUnit'>}\n",
      "Debug: I am 4 selecting 3\n",
      "debug: meta_level_number\n",
      "debug: meta_level_number\n",
      "debug: meta_level_number\n",
      "debug: meta_level_number\n",
      "debug: meta_level_number\n",
      "debug: meta_level_number\n",
      "debug: meta_level_number\n",
      "debug: meta_level_number\n",
      "debug: meta_level_number\n",
      "Setting levels_unmaterialized[0] level_number 0 to have first successor: levels_unmaterialized[:1], having level_numbers of [1, 2, 3, 4]\n",
      "Setting levels_unmaterialized[1] level_number 1 to have first successor: levels_unmaterialized[:2], having level_numbers of [2, 3, 4]\n",
      "Setting levels_unmaterialized[2] level_number 2 to have first successor: levels_unmaterialized[:3], having level_numbers of [3, 4]\n",
      "Setting levels_unmaterialized[3] level_number 3 to have first successor: levels_unmaterialized[:4], having level_numbers of [4]\n",
      "Debug: successor_connectivity_errors_2d []\n",
      "{'3': <class 'cerebros.units.units.DenseUnit'>}\n",
      "debug: meta_level_number\n",
      "Debug: successor_connectivity_errors_2d []\n",
      "materialize:_NeuralNetworkFuture_0000000000000nan_tr_0_DenseLevel_0000000000000001_tr_0_DenseUnit_0000000000000001_tr_0_0 called\n",
      "materialized network layers\n",
      "[<KerasTensor: shape=(None, 8) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_InputLevel_0000000000000000_tr_0_InputUnit_0000000000000000_tr_0_0_inp')>, <KerasTensor: shape=(None, 8) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_InputLevel_0000000000000000_tr_0_InputUnit_0000000000000000_tr_0_0_inp')>, <KerasTensor: shape=(None, 8) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_InputLevel_0000000000000000_tr_0_InputUnit_0000000000000000_tr_0_0_inp')>, <KerasTensor: shape=(None, 8) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_InputLevel_0000000000000000_tr_0_InputUnit_0000000000000000_tr_0_0_inp')>]\n",
      "{'4': <class 'cerebros.units.units.DenseUnit'>}\n",
      "{'2': <class 'cerebros.units.units.DenseUnit'>}\n",
      "{'2': <class 'cerebros.units.units.DenseUnit'>}\n",
      "{'1': <class 'cerebros.units.units.DenseUnit'>}\n",
      "debug: meta_level_number\n",
      "debug: meta_level_number\n",
      "debug: meta_level_number\n",
      "debug: meta_level_number\n",
      "Debug: successor_connectivity_errors_2d []\n",
      "Debug: successor_connectivity_errors_2d []\n",
      "Debug: successor_connectivity_errors_2d []\n",
      "Debug: successor_connectivity_errors_2d []\n",
      "materialize:_NeuralNetworkFuture_0000000000000nan_tr_0_DenseLevel_0000000000000002_tr_0_DenseUnit_0000000000000002_tr_0_0 called\n",
      "materialized network layers\n",
      "[<KerasTensor: shape=(None, 8) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_InputLevel_0000000000000000_tr_0_InputUnit_0000000000000000_tr_0_0_inp')>, <KerasTensor: shape=(None, 3) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_DenseLevel_0000000000000001_tr_0_DenseUnit_0000000000000001_tr_0_0_dns_')>, <KerasTensor: shape=(None, 8) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_InputLevel_0000000000000000_tr_0_InputUnit_0000000000000000_tr_0_0_inp')>, <KerasTensor: shape=(None, 3) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_DenseLevel_0000000000000001_tr_0_DenseUnit_0000000000000001_tr_0_0_dns_')>]\n",
      "materialize:_NeuralNetworkFuture_0000000000000nan_tr_0_DenseLevel_0000000000000002_tr_0_DenseUnit_0000000000000002_tr_0_1 called\n",
      "materialized network layers\n",
      "[<KerasTensor: shape=(None, 8) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_InputLevel_0000000000000000_tr_0_InputUnit_0000000000000000_tr_0_0_inp')>, <KerasTensor: shape=(None, 3) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_DenseLevel_0000000000000001_tr_0_DenseUnit_0000000000000001_tr_0_0_dns_')>, <KerasTensor: shape=(None, 8) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_InputLevel_0000000000000000_tr_0_InputUnit_0000000000000000_tr_0_0_inp')>, <KerasTensor: shape=(None, 3) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_DenseLevel_0000000000000001_tr_0_DenseUnit_0000000000000001_tr_0_0_dns_')>]\n",
      "materialize:_NeuralNetworkFuture_0000000000000nan_tr_0_DenseLevel_0000000000000002_tr_0_DenseUnit_0000000000000002_tr_0_2 called\n",
      "materialized network layers\n",
      "[<KerasTensor: shape=(None, 2) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_DenseLevel_0000000000000002_tr_0_DenseUnit_0000000000000002_tr_0_1_dns_')>, <KerasTensor: shape=(None, 8) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_InputLevel_0000000000000000_tr_0_InputUnit_0000000000000000_tr_0_0_inp')>, <KerasTensor: shape=(None, 3) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_DenseLevel_0000000000000001_tr_0_DenseUnit_0000000000000001_tr_0_0_dns_')>, <KerasTensor: shape=(None, 8) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_InputLevel_0000000000000000_tr_0_InputUnit_0000000000000000_tr_0_0_inp')>, <KerasTensor: shape=(None, 3) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_DenseLevel_0000000000000001_tr_0_DenseUnit_0000000000000001_tr_0_0_dns_')>]\n",
      "materialize:_NeuralNetworkFuture_0000000000000nan_tr_0_DenseLevel_0000000000000002_tr_0_DenseUnit_0000000000000002_tr_0_3 called\n",
      "materialized network layers\n",
      "[<KerasTensor: shape=(None, 2) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_DenseLevel_0000000000000002_tr_0_DenseUnit_0000000000000002_tr_0_2_dns_')>, <KerasTensor: shape=(None, 2) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_DenseLevel_0000000000000002_tr_0_DenseUnit_0000000000000002_tr_0_1_dns_')>, <KerasTensor: shape=(None, 2) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_DenseLevel_0000000000000002_tr_0_DenseUnit_0000000000000002_tr_0_1_dns_')>, <KerasTensor: shape=(None, 8) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_InputLevel_0000000000000000_tr_0_InputUnit_0000000000000000_tr_0_0_inp')>, <KerasTensor: shape=(None, 3) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_DenseLevel_0000000000000001_tr_0_DenseUnit_0000000000000001_tr_0_0_dns_')>, <KerasTensor: shape=(None, 8) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_InputLevel_0000000000000000_tr_0_InputUnit_0000000000000000_tr_0_0_inp')>, <KerasTensor: shape=(None, 3) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_DenseLevel_0000000000000001_tr_0_DenseUnit_0000000000000001_tr_0_0_dns_')>]\n",
      "{'2': <class 'cerebros.units.units.DenseUnit'>}\n",
      "{'3': <class 'cerebros.units.units.DenseUnit'>}\n",
      "{'4': <class 'cerebros.units.units.DenseUnit'>}\n",
      "debug: meta_level_number\n",
      "debug: meta_level_number\n",
      "debug: meta_level_number\n",
      "Debug: successor_connectivity_errors_2d []\n",
      "Debug: successor_connectivity_errors_2d []\n",
      "Debug: successor_connectivity_errors_2d []\n",
      "materialize:_NeuralNetworkFuture_0000000000000nan_tr_0_DenseLevel_0000000000000003_tr_0_DenseUnit_0000000000000003_tr_0_0 called\n",
      "materialized network layers\n",
      "[<KerasTensor: shape=(None, 8) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_InputLevel_0000000000000000_tr_0_InputUnit_0000000000000000_tr_0_0_inp')>, <KerasTensor: shape=(None, 3) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_DenseLevel_0000000000000001_tr_0_DenseUnit_0000000000000001_tr_0_0_dns_')>, <KerasTensor: shape=(None, 2) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_DenseLevel_0000000000000002_tr_0_DenseUnit_0000000000000002_tr_0_1_dns_')>, <KerasTensor: shape=(None, 4) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_DenseLevel_0000000000000002_tr_0_DenseUnit_0000000000000002_tr_0_0_dns_')>, <KerasTensor: shape=(None, 4) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_DenseLevel_0000000000000002_tr_0_DenseUnit_0000000000000002_tr_0_0_dns_')>, <KerasTensor: shape=(None, 8) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_InputLevel_0000000000000000_tr_0_InputUnit_0000000000000000_tr_0_0_inp')>, <KerasTensor: shape=(None, 3) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_DenseLevel_0000000000000001_tr_0_DenseUnit_0000000000000001_tr_0_0_dns_')>, <KerasTensor: shape=(None, 2) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_DenseLevel_0000000000000002_tr_0_DenseUnit_0000000000000002_tr_0_1_dns_')>, <KerasTensor: shape=(None, 4) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_DenseLevel_0000000000000002_tr_0_DenseUnit_0000000000000002_tr_0_0_dns_')>, <KerasTensor: shape=(None, 1) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_DenseLevel_0000000000000002_tr_0_DenseUnit_0000000000000002_tr_0_3_dns_')>]\n",
      "materialize:_NeuralNetworkFuture_0000000000000nan_tr_0_DenseLevel_0000000000000003_tr_0_DenseUnit_0000000000000003_tr_0_1 called\n",
      "materialized network layers\n",
      "[<KerasTensor: shape=(None, 8) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_InputLevel_0000000000000000_tr_0_InputUnit_0000000000000000_tr_0_0_inp')>, <KerasTensor: shape=(None, 3) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_DenseLevel_0000000000000001_tr_0_DenseUnit_0000000000000001_tr_0_0_dns_')>, <KerasTensor: shape=(None, 4) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_DenseLevel_0000000000000002_tr_0_DenseUnit_0000000000000002_tr_0_0_dns_')>, <KerasTensor: shape=(None, 2) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_DenseLevel_0000000000000002_tr_0_DenseUnit_0000000000000002_tr_0_2_dns_')>, <KerasTensor: shape=(None, 2) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_DenseLevel_0000000000000002_tr_0_DenseUnit_0000000000000002_tr_0_2_dns_')>, <KerasTensor: shape=(None, 8) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_InputLevel_0000000000000000_tr_0_InputUnit_0000000000000000_tr_0_0_inp')>, <KerasTensor: shape=(None, 3) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_DenseLevel_0000000000000001_tr_0_DenseUnit_0000000000000001_tr_0_0_dns_')>, <KerasTensor: shape=(None, 4) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_DenseLevel_0000000000000002_tr_0_DenseUnit_0000000000000002_tr_0_0_dns_')>, <KerasTensor: shape=(None, 1) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_DenseLevel_0000000000000002_tr_0_DenseUnit_0000000000000002_tr_0_3_dns_')>, <KerasTensor: shape=(None, 2) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_DenseLevel_0000000000000002_tr_0_DenseUnit_0000000000000002_tr_0_1_dns_')>]\n",
      "materialize:_NeuralNetworkFuture_0000000000000nan_tr_0_DenseLevel_0000000000000003_tr_0_DenseUnit_0000000000000003_tr_0_2 called\n",
      "materialized network layers\n",
      "[<KerasTensor: shape=(None, 3) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_DenseLevel_0000000000000003_tr_0_DenseUnit_0000000000000003_tr_0_1_dns_')>, <KerasTensor: shape=(None, 3) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_DenseLevel_0000000000000003_tr_0_DenseUnit_0000000000000003_tr_0_1_dns_')>, <KerasTensor: shape=(None, 8) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_InputLevel_0000000000000000_tr_0_InputUnit_0000000000000000_tr_0_0_inp')>, <KerasTensor: shape=(None, 3) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_DenseLevel_0000000000000001_tr_0_DenseUnit_0000000000000001_tr_0_0_dns_')>, <KerasTensor: shape=(None, 2) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_DenseLevel_0000000000000002_tr_0_DenseUnit_0000000000000002_tr_0_1_dns_')>, <KerasTensor: shape=(None, 1) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_DenseLevel_0000000000000002_tr_0_DenseUnit_0000000000000002_tr_0_3_dns_')>, <KerasTensor: shape=(None, 2) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_DenseLevel_0000000000000002_tr_0_DenseUnit_0000000000000002_tr_0_1_dns_')>, <KerasTensor: shape=(None, 8) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_InputLevel_0000000000000000_tr_0_InputUnit_0000000000000000_tr_0_0_inp')>, <KerasTensor: shape=(None, 3) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_DenseLevel_0000000000000001_tr_0_DenseUnit_0000000000000001_tr_0_0_dns_')>, <KerasTensor: shape=(None, 4) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_DenseLevel_0000000000000002_tr_0_DenseUnit_0000000000000002_tr_0_0_dns_')>, <KerasTensor: shape=(None, 4) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_DenseLevel_0000000000000002_tr_0_DenseUnit_0000000000000002_tr_0_0_dns_')>, <KerasTensor: shape=(None, 4) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_DenseLevel_0000000000000002_tr_0_DenseUnit_0000000000000002_tr_0_0_dns_')>]\n",
      "{'1': <class 'cerebros.units.units.FinalDenseUnit'>}\n",
      "debug: meta_level_number\n",
      "Debug: successor_connectivity_errors_2d []\n",
      "materialize:_NeuralNetworkFuture_0000000000000nan_tr_0_FinalDenseLevel_0000000000000004_tr_0_FinalDenseUnit_0000000000000004_tr_0_0 called\n",
      "materialized network layers\n",
      "[<KerasTensor: shape=(None, 3) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_DenseLevel_0000000000000003_tr_0_DenseUnit_0000000000000003_tr_0_1_dns_')>, <KerasTensor: shape=(None, 2) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_DenseLevel_0000000000000003_tr_0_DenseUnit_0000000000000003_tr_0_0_dns_')>, <KerasTensor: shape=(None, 2) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_DenseLevel_0000000000000003_tr_0_DenseUnit_0000000000000003_tr_0_0_dns_')>, <KerasTensor: shape=(None, 4) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_DenseLevel_0000000000000003_tr_0_DenseUnit_0000000000000003_tr_0_2_dns_')>, <KerasTensor: shape=(None, 4) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_DenseLevel_0000000000000003_tr_0_DenseUnit_0000000000000003_tr_0_2_dns_')>, <KerasTensor: shape=(None, 2) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_DenseLevel_0000000000000003_tr_0_DenseUnit_0000000000000003_tr_0_0_dns_')>, <KerasTensor: shape=(None, 8) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_InputLevel_0000000000000000_tr_0_InputUnit_0000000000000000_tr_0_0_inp')>, <KerasTensor: shape=(None, 3) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_DenseLevel_0000000000000001_tr_0_DenseUnit_0000000000000001_tr_0_0_dns_')>, <KerasTensor: shape=(None, 1) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_DenseLevel_0000000000000002_tr_0_DenseUnit_0000000000000002_tr_0_3_dns_')>, <KerasTensor: shape=(None, 1) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_DenseLevel_0000000000000002_tr_0_DenseUnit_0000000000000002_tr_0_3_dns_')>, <KerasTensor: shape=(None, 2) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_DenseLevel_0000000000000003_tr_0_DenseUnit_0000000000000003_tr_0_0_dns_')>, <KerasTensor: shape=(None, 3) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_DenseLevel_0000000000000003_tr_0_DenseUnit_0000000000000003_tr_0_1_dns_')>, <KerasTensor: shape=(None, 2) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_DenseLevel_0000000000000003_tr_0_DenseUnit_0000000000000003_tr_0_0_dns_')>, <KerasTensor: shape=(None, 8) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_InputLevel_0000000000000000_tr_0_InputUnit_0000000000000000_tr_0_0_inp')>, <KerasTensor: shape=(None, 3) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_DenseLevel_0000000000000001_tr_0_DenseUnit_0000000000000001_tr_0_0_dns_')>, <KerasTensor: shape=(None, 2) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_DenseLevel_0000000000000002_tr_0_DenseUnit_0000000000000002_tr_0_1_dns_')>, <KerasTensor: shape=(None, 1) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_DenseLevel_0000000000000002_tr_0_DenseUnit_0000000000000002_tr_0_3_dns_')>, <KerasTensor: shape=(None, 3) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_DenseLevel_0000000000000003_tr_0_DenseUnit_0000000000000003_tr_0_1_dns_')>, <KerasTensor: shape=(None, 2) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_DenseLevel_0000000000000003_tr_0_DenseUnit_0000000000000003_tr_0_0_dns_')>, <KerasTensor: shape=(None, 2) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_DenseLevel_0000000000000003_tr_0_DenseUnit_0000000000000003_tr_0_0_dns_')>]\n",
      "inputs\n",
      "KerasTensor(type_spec=TensorSpec(shape=(None, 8), dtype=tf.float32, name='NeuralNetworkFuture_0000000000000nan_tr_0_InputLevel_0000000000000000_tr_0_InputUnit_0000000000000000_tr_0_0_inp'), name='NeuralNetworkFuture_0000000000000nan_tr_0_InputLevel_0000000000000000_tr_0_InputUnit_0000000000000000_tr_0_0_inp', description=\"created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_InputLevel_0000000000000000_tr_0_InputUnit_0000000000000000_tr_0_0_inp'\")\n",
      "\n",
      "outputs\n",
      "KerasTensor(type_spec=TensorSpec(shape=(None, 1), dtype=tf.float32, name=None), name='NeuralNetworkFuture_0000000000000nan_tr_0_FinalDenseLevel_0000000000000004_tr_0_FinalDenseUnit_0000000000000004_tr_0_0_dns_/Sigmoid:0', description=\"created by layer 'NeuralNetworkFuture_0000000000000nan_tr_0_FinalDenseLevel_0000000000000004_tr_0_FinalDenseUnit_0000000000000004_tr_0_0_dns_'\")\n",
      "Model: \"NeuralNetworkFuture_0000000000000nan_tr_0_nn_materialized\"\n",
      "__________________________________________________________________________________________________\n",
      " Layer (type)                   Output Shape         Param #     Connected to                     \n",
      "==================================================================================================\n",
      " NeuralNetworkFuture_0000000000  [(None, 8)]         0           []                               \n",
      " 000nan_tr_0_InputLevel_0000000                                                                   \n",
      " 000000000_tr_0_InputUnit_00000                                                                   \n",
      " 00000000000_tr_0_0_inp (InputL                                                                   \n",
      " ayer)                                                                                            \n",
      "                                                                                                  \n",
      " NeuralNetworkFuture_0000000000  (None, 32)          0           ['NeuralNetworkFuture_00000000000\n",
      " 000nan_tr_0_DenseLevel_0000000                                  00nan_tr_0_InputLevel_00000000000\n",
      " 000000001_tr_0_DenseUnit_00000                                  00000_tr_0_InputUnit_000000000000\n",
      " 00000000001_tr_0_0_cat_ (Conca                                  0000_tr_0_0_inp[0][0]',          \n",
      " tenate)                                                          'NeuralNetworkFuture_00000000000\n",
      "                                                                 00nan_tr_0_InputLevel_00000000000\n",
      "                                                                 00000_tr_0_InputUnit_000000000000\n",
      "                                                                 0000_tr_0_0_inp[0][0]',          \n",
      "                                                                  'NeuralNetworkFuture_00000000000\n",
      "                                                                 00nan_tr_0_InputLevel_00000000000\n",
      "                                                                 00000_tr_0_InputUnit_000000000000\n",
      "                                                                 0000_tr_0_0_inp[0][0]',          \n",
      "                                                                  'NeuralNetworkFuture_00000000000\n",
      "                                                                 00nan_tr_0_InputLevel_00000000000\n",
      "                                                                 00000_tr_0_InputUnit_000000000000\n",
      "                                                                 0000_tr_0_0_inp[0][0]']          \n",
      "                                                                                                  \n",
      " NeuralNetworkFuture_0000000000  (None, 32)          128         ['NeuralNetworkFuture_00000000000\n",
      " 000nan_tr_0_DenseLevel_0000000                                  00nan_tr_0_DenseLevel_00000000000\n",
      " 000000001_tr_0_DenseUnit_00000                                  00001_tr_0_DenseUnit_000000000000\n",
      " 00000000001_tr_0_0_btn_ (Batch                                  0001_tr_0_0_cat_[0][0]']         \n",
      " Normalization)                                                                                   \n",
      "                                                                                                  \n",
      " NeuralNetworkFuture_0000000000  (None, 3)           99          ['NeuralNetworkFuture_00000000000\n",
      " 000nan_tr_0_DenseLevel_0000000                                  00nan_tr_0_DenseLevel_00000000000\n",
      " 000000001_tr_0_DenseUnit_00000                                  00001_tr_0_DenseUnit_000000000000\n",
      " 00000000001_tr_0_0_dns_ (Dense                                  0001_tr_0_0_btn_[0][0]']         \n",
      " )                                                                                                \n",
      "                                                                                                  \n",
      " NeuralNetworkFuture_0000000000  (None, 22)          0           ['NeuralNetworkFuture_00000000000\n",
      " 000nan_tr_0_DenseLevel_0000000                                  00nan_tr_0_InputLevel_00000000000\n",
      " 000000002_tr_0_DenseUnit_00000                                  00000_tr_0_InputUnit_000000000000\n",
      " 00000000002_tr_0_1_cat_ (Conca                                  0000_tr_0_0_inp[0][0]',          \n",
      " tenate)                                                          'NeuralNetworkFuture_00000000000\n",
      "                                                                 00nan_tr_0_DenseLevel_00000000000\n",
      "                                                                 00001_tr_0_DenseUnit_000000000000\n",
      "                                                                 0001_tr_0_0_dns_[0][0]',         \n",
      "                                                                  'NeuralNetworkFuture_00000000000\n",
      "                                                                 00nan_tr_0_InputLevel_00000000000\n",
      "                                                                 00000_tr_0_InputUnit_000000000000\n",
      "                                                                 0000_tr_0_0_inp[0][0]',          \n",
      "                                                                  'NeuralNetworkFuture_00000000000\n",
      "                                                                 00nan_tr_0_DenseLevel_00000000000\n",
      "                                                                 00001_tr_0_DenseUnit_000000000000\n",
      "                                                                 0001_tr_0_0_dns_[0][0]']         \n",
      "                                                                                                  \n",
      " NeuralNetworkFuture_0000000000  (None, 22)          88          ['NeuralNetworkFuture_00000000000\n",
      " 000nan_tr_0_DenseLevel_0000000                                  00nan_tr_0_DenseLevel_00000000000\n",
      " 000000002_tr_0_DenseUnit_00000                                  00002_tr_0_DenseUnit_000000000000\n",
      " 00000000002_tr_0_1_btn_ (Batch                                  0002_tr_0_1_cat_[0][0]']         \n",
      " Normalization)                                                                                   \n",
      "                                                                                                  \n",
      " NeuralNetworkFuture_0000000000  (None, 2)           46          ['NeuralNetworkFuture_00000000000\n",
      " 000nan_tr_0_DenseLevel_0000000                                  00nan_tr_0_DenseLevel_00000000000\n",
      " 000000002_tr_0_DenseUnit_00000                                  00002_tr_0_DenseUnit_000000000000\n",
      " 00000000002_tr_0_1_dns_ (Dense                                  0002_tr_0_1_btn_[0][0]']         \n",
      " )                                                                                                \n",
      "                                                                                                  \n",
      " NeuralNetworkFuture_0000000000  (None, 24)          0           ['NeuralNetworkFuture_00000000000\n",
      " 000nan_tr_0_DenseLevel_0000000                                  00nan_tr_0_DenseLevel_00000000000\n",
      " 000000002_tr_0_DenseUnit_00000                                  00002_tr_0_DenseUnit_000000000000\n",
      " 00000000002_tr_0_2_cat_ (Conca                                  0002_tr_0_1_dns_[0][0]',         \n",
      " tenate)                                                          'NeuralNetworkFuture_00000000000\n",
      "                                                                 00nan_tr_0_InputLevel_00000000000\n",
      "                                                                 00000_tr_0_InputUnit_000000000000\n",
      "                                                                 0000_tr_0_0_inp[0][0]',          \n",
      "                                                                  'NeuralNetworkFuture_00000000000\n",
      "                                                                 00nan_tr_0_DenseLevel_00000000000\n",
      "                                                                 00001_tr_0_DenseUnit_000000000000\n",
      "                                                                 0001_tr_0_0_dns_[0][0]',         \n",
      "                                                                  'NeuralNetworkFuture_00000000000\n",
      "                                                                 00nan_tr_0_InputLevel_00000000000\n",
      "                                                                 00000_tr_0_InputUnit_000000000000\n",
      "                                                                 0000_tr_0_0_inp[0][0]',          \n",
      "                                                                  'NeuralNetworkFuture_00000000000\n",
      "                                                                 00nan_tr_0_DenseLevel_00000000000\n",
      "                                                                 00001_tr_0_DenseUnit_000000000000\n",
      "                                                                 0001_tr_0_0_dns_[0][0]']         \n",
      "                                                                                                  \n",
      " NeuralNetworkFuture_0000000000  (None, 24)          96          ['NeuralNetworkFuture_00000000000\n",
      " 000nan_tr_0_DenseLevel_0000000                                  00nan_tr_0_DenseLevel_00000000000\n",
      " 000000002_tr_0_DenseUnit_00000                                  00002_tr_0_DenseUnit_000000000000\n",
      " 00000000002_tr_0_2_btn_ (Batch                                  0002_tr_0_2_cat_[0][0]']         \n",
      " Normalization)                                                                                   \n",
      "                                                                                                  \n",
      " NeuralNetworkFuture_0000000000  (None, 2)           50          ['NeuralNetworkFuture_00000000000\n",
      " 000nan_tr_0_DenseLevel_0000000                                  00nan_tr_0_DenseLevel_00000000000\n",
      " 000000002_tr_0_DenseUnit_00000                                  00002_tr_0_DenseUnit_000000000000\n",
      " 00000000002_tr_0_2_dns_ (Dense                                  0002_tr_0_2_btn_[0][0]']         \n",
      " )                                                                                                \n",
      "                                                                                                  \n",
      " NeuralNetworkFuture_0000000000  (None, 22)          0           ['NeuralNetworkFuture_00000000000\n",
      " 000nan_tr_0_DenseLevel_0000000                                  00nan_tr_0_InputLevel_00000000000\n",
      " 000000002_tr_0_DenseUnit_00000                                  00000_tr_0_InputUnit_000000000000\n",
      " 00000000002_tr_0_0_cat_ (Conca                                  0000_tr_0_0_inp[0][0]',          \n",
      " tenate)                                                          'NeuralNetworkFuture_00000000000\n",
      "                                                                 00nan_tr_0_DenseLevel_00000000000\n",
      "                                                                 00001_tr_0_DenseUnit_000000000000\n",
      "                                                                 0001_tr_0_0_dns_[0][0]',         \n",
      "                                                                  'NeuralNetworkFuture_00000000000\n",
      "                                                                 00nan_tr_0_InputLevel_00000000000\n",
      "                                                                 00000_tr_0_InputUnit_000000000000\n",
      "                                                                 0000_tr_0_0_inp[0][0]',          \n",
      "                                                                  'NeuralNetworkFuture_00000000000\n",
      "                                                                 00nan_tr_0_DenseLevel_00000000000\n",
      "                                                                 00001_tr_0_DenseUnit_000000000000\n",
      "                                                                 0001_tr_0_0_dns_[0][0]']         \n",
      "                                                                                                  \n",
      " NeuralNetworkFuture_0000000000  (None, 28)          0           ['NeuralNetworkFuture_00000000000\n",
      " 000nan_tr_0_DenseLevel_0000000                                  00nan_tr_0_DenseLevel_00000000000\n",
      " 000000002_tr_0_DenseUnit_00000                                  00002_tr_0_DenseUnit_000000000000\n",
      " 00000000002_tr_0_3_cat_ (Conca                                  0002_tr_0_2_dns_[0][0]',         \n",
      " tenate)                                                          'NeuralNetworkFuture_00000000000\n",
      "                                                                 00nan_tr_0_DenseLevel_00000000000\n",
      "                                                                 00002_tr_0_DenseUnit_000000000000\n",
      "                                                                 0002_tr_0_1_dns_[0][0]',         \n",
      "                                                                  'NeuralNetworkFuture_00000000000\n",
      "                                                                 00nan_tr_0_DenseLevel_00000000000\n",
      "                                                                 00002_tr_0_DenseUnit_000000000000\n",
      "                                                                 0002_tr_0_1_dns_[0][0]',         \n",
      "                                                                  'NeuralNetworkFuture_00000000000\n",
      "                                                                 00nan_tr_0_InputLevel_00000000000\n",
      "                                                                 00000_tr_0_InputUnit_000000000000\n",
      "                                                                 0000_tr_0_0_inp[0][0]',          \n",
      "                                                                  'NeuralNetworkFuture_00000000000\n",
      "                                                                 00nan_tr_0_DenseLevel_00000000000\n",
      "                                                                 00001_tr_0_DenseUnit_000000000000\n",
      "                                                                 0001_tr_0_0_dns_[0][0]',         \n",
      "                                                                  'NeuralNetworkFuture_00000000000\n",
      "                                                                 00nan_tr_0_InputLevel_00000000000\n",
      "                                                                 00000_tr_0_InputUnit_000000000000\n",
      "                                                                 0000_tr_0_0_inp[0][0]',          \n",
      "                                                                  'NeuralNetworkFuture_00000000000\n",
      "                                                                 00nan_tr_0_DenseLevel_00000000000\n",
      "                                                                 00001_tr_0_DenseUnit_000000000000\n",
      "                                                                 0001_tr_0_0_dns_[0][0]']         \n",
      "                                                                                                  \n",
      " NeuralNetworkFuture_0000000000  (None, 22)          88          ['NeuralNetworkFuture_00000000000\n",
      " 000nan_tr_0_DenseLevel_0000000                                  00nan_tr_0_DenseLevel_00000000000\n",
      " 000000002_tr_0_DenseUnit_00000                                  00002_tr_0_DenseUnit_000000000000\n",
      " 00000000002_tr_0_0_btn_ (Batch                                  0002_tr_0_0_cat_[0][0]']         \n",
      " Normalization)                                                                                   \n",
      "                                                                                                  \n",
      " NeuralNetworkFuture_0000000000  (None, 28)          112         ['NeuralNetworkFuture_00000000000\n",
      " 000nan_tr_0_DenseLevel_0000000                                  00nan_tr_0_DenseLevel_00000000000\n",
      " 000000002_tr_0_DenseUnit_00000                                  00002_tr_0_DenseUnit_000000000000\n",
      " 00000000002_tr_0_3_btn_ (Batch                                  0002_tr_0_3_cat_[0][0]']         \n",
      " Normalization)                                                                                   \n",
      "                                                                                                  \n",
      " NeuralNetworkFuture_0000000000  (None, 4)           92          ['NeuralNetworkFuture_00000000000\n",
      " 000nan_tr_0_DenseLevel_0000000                                  00nan_tr_0_DenseLevel_00000000000\n",
      " 000000002_tr_0_DenseUnit_00000                                  00002_tr_0_DenseUnit_000000000000\n",
      " 00000000002_tr_0_0_dns_ (Dense                                  0002_tr_0_0_btn_[0][0]']         \n",
      " )                                                                                                \n",
      "                                                                                                  \n",
      " NeuralNetworkFuture_0000000000  (None, 1)           29          ['NeuralNetworkFuture_00000000000\n",
      " 000nan_tr_0_DenseLevel_0000000                                  00nan_tr_0_DenseLevel_00000000000\n",
      " 000000002_tr_0_DenseUnit_00000                                  00002_tr_0_DenseUnit_000000000000\n",
      " 00000000002_tr_0_3_dns_ (Dense                                  0002_tr_0_3_btn_[0][0]']         \n",
      " )                                                                                                \n",
      "                                                                                                  \n",
      " NeuralNetworkFuture_0000000000  (None, 37)          0           ['NeuralNetworkFuture_00000000000\n",
      " 000nan_tr_0_DenseLevel_0000000                                  00nan_tr_0_InputLevel_00000000000\n",
      " 000000003_tr_0_DenseUnit_00000                                  00000_tr_0_InputUnit_000000000000\n",
      " 00000000003_tr_0_1_cat_ (Conca                                  0000_tr_0_0_inp[0][0]',          \n",
      " tenate)                                                          'NeuralNetworkFuture_00000000000\n",
      "                                                                 00nan_tr_0_DenseLevel_00000000000\n",
      "                                                                 00001_tr_0_DenseUnit_000000000000\n",
      "                                                                 0001_tr_0_0_dns_[0][0]',         \n",
      "                                                                  'NeuralNetworkFuture_00000000000\n",
      "                                                                 00nan_tr_0_DenseLevel_00000000000\n",
      "                                                                 00002_tr_0_DenseUnit_000000000000\n",
      "                                                                 0002_tr_0_0_dns_[0][0]',         \n",
      "                                                                  'NeuralNetworkFuture_00000000000\n",
      "                                                                 00nan_tr_0_DenseLevel_00000000000\n",
      "                                                                 00002_tr_0_DenseUnit_000000000000\n",
      "                                                                 0002_tr_0_2_dns_[0][0]',         \n",
      "                                                                  'NeuralNetworkFuture_00000000000\n",
      "                                                                 00nan_tr_0_DenseLevel_00000000000\n",
      "                                                                 00002_tr_0_DenseUnit_000000000000\n",
      "                                                                 0002_tr_0_2_dns_[0][0]',         \n",
      "                                                                  'NeuralNetworkFuture_00000000000\n",
      "                                                                 00nan_tr_0_InputLevel_00000000000\n",
      "                                                                 00000_tr_0_InputUnit_000000000000\n",
      "                                                                 0000_tr_0_0_inp[0][0]',          \n",
      "                                                                  'NeuralNetworkFuture_00000000000\n",
      "                                                                 00nan_tr_0_DenseLevel_00000000000\n",
      "                                                                 00001_tr_0_DenseUnit_000000000000\n",
      "                                                                 0001_tr_0_0_dns_[0][0]',         \n",
      "                                                                  'NeuralNetworkFuture_00000000000\n",
      "                                                                 00nan_tr_0_DenseLevel_00000000000\n",
      "                                                                 00002_tr_0_DenseUnit_000000000000\n",
      "                                                                 0002_tr_0_0_dns_[0][0]',         \n",
      "                                                                  'NeuralNetworkFuture_00000000000\n",
      "                                                                 00nan_tr_0_DenseLevel_00000000000\n",
      "                                                                 00002_tr_0_DenseUnit_000000000000\n",
      "                                                                 0002_tr_0_3_dns_[0][0]',         \n",
      "                                                                  'NeuralNetworkFuture_00000000000\n",
      "                                                                 00nan_tr_0_DenseLevel_00000000000\n",
      "                                                                 00002_tr_0_DenseUnit_000000000000\n",
      "                                                                 0002_tr_0_1_dns_[0][0]']         \n",
      "                                                                                                  \n",
      " NeuralNetworkFuture_0000000000  (None, 37)          148         ['NeuralNetworkFuture_00000000000\n",
      " 000nan_tr_0_DenseLevel_0000000                                  00nan_tr_0_DenseLevel_00000000000\n",
      " 000000003_tr_0_DenseUnit_00000                                  00003_tr_0_DenseUnit_000000000000\n",
      " 00000000003_tr_0_1_btn_ (Batch                                  0003_tr_0_1_cat_[0][0]']         \n",
      " Normalization)                                                                                   \n",
      "                                                                                                  \n",
      " NeuralNetworkFuture_0000000000  (None, 3)           114         ['NeuralNetworkFuture_00000000000\n",
      " 000nan_tr_0_DenseLevel_0000000                                  00nan_tr_0_DenseLevel_00000000000\n",
      " 000000003_tr_0_DenseUnit_00000                                  00003_tr_0_DenseUnit_000000000000\n",
      " 00000000003_tr_0_1_dns_ (Dense                                  0003_tr_0_1_btn_[0][0]']         \n",
      " )                                                                                                \n",
      "                                                                                                  \n",
      " NeuralNetworkFuture_0000000000  (None, 39)          0           ['NeuralNetworkFuture_00000000000\n",
      " 000nan_tr_0_DenseLevel_0000000                                  00nan_tr_0_InputLevel_00000000000\n",
      " 000000003_tr_0_DenseUnit_00000                                  00000_tr_0_InputUnit_000000000000\n",
      " 00000000003_tr_0_0_cat_ (Conca                                  0000_tr_0_0_inp[0][0]',          \n",
      " tenate)                                                          'NeuralNetworkFuture_00000000000\n",
      "                                                                 00nan_tr_0_DenseLevel_00000000000\n",
      "                                                                 00001_tr_0_DenseUnit_000000000000\n",
      "                                                                 0001_tr_0_0_dns_[0][0]',         \n",
      "                                                                  'NeuralNetworkFuture_00000000000\n",
      "                                                                 00nan_tr_0_DenseLevel_00000000000\n",
      "                                                                 00002_tr_0_DenseUnit_000000000000\n",
      "                                                                 0002_tr_0_1_dns_[0][0]',         \n",
      "                                                                  'NeuralNetworkFuture_00000000000\n",
      "                                                                 00nan_tr_0_DenseLevel_00000000000\n",
      "                                                                 00002_tr_0_DenseUnit_000000000000\n",
      "                                                                 0002_tr_0_0_dns_[0][0]',         \n",
      "                                                                  'NeuralNetworkFuture_00000000000\n",
      "                                                                 00nan_tr_0_DenseLevel_00000000000\n",
      "                                                                 00002_tr_0_DenseUnit_000000000000\n",
      "                                                                 0002_tr_0_0_dns_[0][0]',         \n",
      "                                                                  'NeuralNetworkFuture_00000000000\n",
      "                                                                 00nan_tr_0_InputLevel_00000000000\n",
      "                                                                 00000_tr_0_InputUnit_000000000000\n",
      "                                                                 0000_tr_0_0_inp[0][0]',          \n",
      "                                                                  'NeuralNetworkFuture_00000000000\n",
      "                                                                 00nan_tr_0_DenseLevel_00000000000\n",
      "                                                                 00001_tr_0_DenseUnit_000000000000\n",
      "                                                                 0001_tr_0_0_dns_[0][0]',         \n",
      "                                                                  'NeuralNetworkFuture_00000000000\n",
      "                                                                 00nan_tr_0_DenseLevel_00000000000\n",
      "                                                                 00002_tr_0_DenseUnit_000000000000\n",
      "                                                                 0002_tr_0_1_dns_[0][0]',         \n",
      "                                                                  'NeuralNetworkFuture_00000000000\n",
      "                                                                 00nan_tr_0_DenseLevel_00000000000\n",
      "                                                                 00002_tr_0_DenseUnit_000000000000\n",
      "                                                                 0002_tr_0_0_dns_[0][0]',         \n",
      "                                                                  'NeuralNetworkFuture_00000000000\n",
      "                                                                 00nan_tr_0_DenseLevel_00000000000\n",
      "                                                                 00002_tr_0_DenseUnit_000000000000\n",
      "                                                                 0002_tr_0_3_dns_[0][0]']         \n",
      "                                                                                                  \n",
      " NeuralNetworkFuture_0000000000  (None, 45)          0           ['NeuralNetworkFuture_00000000000\n",
      " 000nan_tr_0_DenseLevel_0000000                                  00nan_tr_0_DenseLevel_00000000000\n",
      " 000000003_tr_0_DenseUnit_00000                                  00003_tr_0_DenseUnit_000000000000\n",
      " 00000000003_tr_0_2_cat_ (Conca                                  0003_tr_0_1_dns_[0][0]',         \n",
      " tenate)                                                          'NeuralNetworkFuture_00000000000\n",
      "                                                                 00nan_tr_0_DenseLevel_00000000000\n",
      "                                                                 00003_tr_0_DenseUnit_000000000000\n",
      "                                                                 0003_tr_0_1_dns_[0][0]',         \n",
      "                                                                  'NeuralNetworkFuture_00000000000\n",
      "                                                                 00nan_tr_0_InputLevel_00000000000\n",
      "                                                                 00000_tr_0_InputUnit_000000000000\n",
      "                                                                 0000_tr_0_0_inp[0][0]',          \n",
      "                                                                  'NeuralNetworkFuture_00000000000\n",
      "                                                                 00nan_tr_0_DenseLevel_00000000000\n",
      "                                                                 00001_tr_0_DenseUnit_000000000000\n",
      "                                                                 0001_tr_0_0_dns_[0][0]',         \n",
      "                                                                  'NeuralNetworkFuture_00000000000\n",
      "                                                                 00nan_tr_0_DenseLevel_00000000000\n",
      "                                                                 00002_tr_0_DenseUnit_000000000000\n",
      "                                                                 0002_tr_0_1_dns_[0][0]',         \n",
      "                                                                  'NeuralNetworkFuture_00000000000\n",
      "                                                                 00nan_tr_0_DenseLevel_00000000000\n",
      "                                                                 00002_tr_0_DenseUnit_000000000000\n",
      "                                                                 0002_tr_0_3_dns_[0][0]',         \n",
      "                                                                  'NeuralNetworkFuture_00000000000\n",
      "                                                                 00nan_tr_0_DenseLevel_00000000000\n",
      "                                                                 00002_tr_0_DenseUnit_000000000000\n",
      "                                                                 0002_tr_0_1_dns_[0][0]',         \n",
      "                                                                  'NeuralNetworkFuture_00000000000\n",
      "                                                                 00nan_tr_0_InputLevel_00000000000\n",
      "                                                                 00000_tr_0_InputUnit_000000000000\n",
      "                                                                 0000_tr_0_0_inp[0][0]',          \n",
      "                                                                  'NeuralNetworkFuture_00000000000\n",
      "                                                                 00nan_tr_0_DenseLevel_00000000000\n",
      "                                                                 00001_tr_0_DenseUnit_000000000000\n",
      "                                                                 0001_tr_0_0_dns_[0][0]',         \n",
      "                                                                  'NeuralNetworkFuture_00000000000\n",
      "                                                                 00nan_tr_0_DenseLevel_00000000000\n",
      "                                                                 00002_tr_0_DenseUnit_000000000000\n",
      "                                                                 0002_tr_0_0_dns_[0][0]',         \n",
      "                                                                  'NeuralNetworkFuture_00000000000\n",
      "                                                                 00nan_tr_0_DenseLevel_00000000000\n",
      "                                                                 00002_tr_0_DenseUnit_000000000000\n",
      "                                                                 0002_tr_0_0_dns_[0][0]',         \n",
      "                                                                  'NeuralNetworkFuture_00000000000\n",
      "                                                                 00nan_tr_0_DenseLevel_00000000000\n",
      "                                                                 00002_tr_0_DenseUnit_000000000000\n",
      "                                                                 0002_tr_0_0_dns_[0][0]']         \n",
      "                                                                                                  \n",
      " NeuralNetworkFuture_0000000000  (None, 39)          156         ['NeuralNetworkFuture_00000000000\n",
      " 000nan_tr_0_DenseLevel_0000000                                  00nan_tr_0_DenseLevel_00000000000\n",
      " 000000003_tr_0_DenseUnit_00000                                  00003_tr_0_DenseUnit_000000000000\n",
      " 00000000003_tr_0_0_btn_ (Batch                                  0003_tr_0_0_cat_[0][0]']         \n",
      " Normalization)                                                                                   \n",
      "                                                                                                  \n",
      " NeuralNetworkFuture_0000000000  (None, 45)          180         ['NeuralNetworkFuture_00000000000\n",
      " 000nan_tr_0_DenseLevel_0000000                                  00nan_tr_0_DenseLevel_00000000000\n",
      " 000000003_tr_0_DenseUnit_00000                                  00003_tr_0_DenseUnit_000000000000\n",
      " 00000000003_tr_0_2_btn_ (Batch                                  0003_tr_0_2_cat_[0][0]']         \n",
      " Normalization)                                                                                   \n",
      "                                                                                                  \n",
      " NeuralNetworkFuture_0000000000  (None, 2)           80          ['NeuralNetworkFuture_00000000000\n",
      " 000nan_tr_0_DenseLevel_0000000                                  00nan_tr_0_DenseLevel_00000000000\n",
      " 000000003_tr_0_DenseUnit_00000                                  00003_tr_0_DenseUnit_000000000000\n",
      " 00000000003_tr_0_0_dns_ (Dense                                  0003_tr_0_0_btn_[0][0]']         \n",
      " )                                                                                                \n",
      "                                                                                                  \n",
      " NeuralNetworkFuture_0000000000  (None, 4)           184         ['NeuralNetworkFuture_00000000000\n",
      " 000nan_tr_0_DenseLevel_0000000                                  00nan_tr_0_DenseLevel_00000000000\n",
      " 000000003_tr_0_DenseUnit_00000                                  00003_tr_0_DenseUnit_000000000000\n",
      " 00000000003_tr_0_2_dns_ (Dense                                  0003_tr_0_2_btn_[0][0]']         \n",
      " )                                                                                                \n",
      "                                                                                                  \n",
      " NeuralNetworkFuture_0000000000  (None, 58)          0           ['NeuralNetworkFuture_00000000000\n",
      " 000nan_tr_0_FinalDenseLevel_00                                  00nan_tr_0_DenseLevel_00000000000\n",
      " 00000000000004_tr_0_FinalDense                                  00003_tr_0_DenseUnit_000000000000\n",
      " Unit_0000000000000004_tr_0_0_c                                  0003_tr_0_1_dns_[0][0]',         \n",
      " at_ (Concatenate)                                                'NeuralNetworkFuture_00000000000\n",
      "                                                                 00nan_tr_0_DenseLevel_00000000000\n",
      "                                                                 00003_tr_0_DenseUnit_000000000000\n",
      "                                                                 0003_tr_0_0_dns_[0][0]',         \n",
      "                                                                  'NeuralNetworkFuture_00000000000\n",
      "                                                                 00nan_tr_0_DenseLevel_00000000000\n",
      "                                                                 00003_tr_0_DenseUnit_000000000000\n",
      "                                                                 0003_tr_0_0_dns_[0][0]',         \n",
      "                                                                  'NeuralNetworkFuture_00000000000\n",
      "                                                                 00nan_tr_0_DenseLevel_00000000000\n",
      "                                                                 00003_tr_0_DenseUnit_000000000000\n",
      "                                                                 0003_tr_0_2_dns_[0][0]',         \n",
      "                                                                  'NeuralNetworkFuture_00000000000\n",
      "                                                                 00nan_tr_0_DenseLevel_00000000000\n",
      "                                                                 00003_tr_0_DenseUnit_000000000000\n",
      "                                                                 0003_tr_0_2_dns_[0][0]',         \n",
      "                                                                  'NeuralNetworkFuture_00000000000\n",
      "                                                                 00nan_tr_0_DenseLevel_00000000000\n",
      "                                                                 00003_tr_0_DenseUnit_000000000000\n",
      "                                                                 0003_tr_0_0_dns_[0][0]',         \n",
      "                                                                  'NeuralNetworkFuture_00000000000\n",
      "                                                                 00nan_tr_0_InputLevel_00000000000\n",
      "                                                                 00000_tr_0_InputUnit_000000000000\n",
      "                                                                 0000_tr_0_0_inp[0][0]',          \n",
      "                                                                  'NeuralNetworkFuture_00000000000\n",
      "                                                                 00nan_tr_0_DenseLevel_00000000000\n",
      "                                                                 00001_tr_0_DenseUnit_000000000000\n",
      "                                                                 0001_tr_0_0_dns_[0][0]',         \n",
      "                                                                  'NeuralNetworkFuture_00000000000\n",
      "                                                                 00nan_tr_0_DenseLevel_00000000000\n",
      "                                                                 00002_tr_0_DenseUnit_000000000000\n",
      "                                                                 0002_tr_0_3_dns_[0][0]',         \n",
      "                                                                  'NeuralNetworkFuture_00000000000\n",
      "                                                                 00nan_tr_0_DenseLevel_00000000000\n",
      "                                                                 00002_tr_0_DenseUnit_000000000000\n",
      "                                                                 0002_tr_0_3_dns_[0][0]',         \n",
      "                                                                  'NeuralNetworkFuture_00000000000\n",
      "                                                                 00nan_tr_0_DenseLevel_00000000000\n",
      "                                                                 00003_tr_0_DenseUnit_000000000000\n",
      "                                                                 0003_tr_0_0_dns_[0][0]',         \n",
      "                                                                  'NeuralNetworkFuture_00000000000\n",
      "                                                                 00nan_tr_0_DenseLevel_00000000000\n",
      "                                                                 00003_tr_0_DenseUnit_000000000000\n",
      "                                                                 0003_tr_0_1_dns_[0][0]',         \n",
      "                                                                  'NeuralNetworkFuture_00000000000\n",
      "                                                                 00nan_tr_0_DenseLevel_00000000000\n",
      "                                                                 00003_tr_0_DenseUnit_000000000000\n",
      "                                                                 0003_tr_0_0_dns_[0][0]',         \n",
      "                                                                  'NeuralNetworkFuture_00000000000\n",
      "                                                                 00nan_tr_0_InputLevel_00000000000\n",
      "                                                                 00000_tr_0_InputUnit_000000000000\n",
      "                                                                 0000_tr_0_0_inp[0][0]',          \n",
      "                                                                  'NeuralNetworkFuture_00000000000\n",
      "                                                                 00nan_tr_0_DenseLevel_00000000000\n",
      "                                                                 00001_tr_0_DenseUnit_000000000000\n",
      "                                                                 0001_tr_0_0_dns_[0][0]',         \n",
      "                                                                  'NeuralNetworkFuture_00000000000\n",
      "                                                                 00nan_tr_0_DenseLevel_00000000000\n",
      "                                                                 00002_tr_0_DenseUnit_000000000000\n",
      "                                                                 0002_tr_0_1_dns_[0][0]',         \n",
      "                                                                  'NeuralNetworkFuture_00000000000\n",
      "                                                                 00nan_tr_0_DenseLevel_00000000000\n",
      "                                                                 00002_tr_0_DenseUnit_000000000000\n",
      "                                                                 0002_tr_0_3_dns_[0][0]',         \n",
      "                                                                  'NeuralNetworkFuture_00000000000\n",
      "                                                                 00nan_tr_0_DenseLevel_00000000000\n",
      "                                                                 00003_tr_0_DenseUnit_000000000000\n",
      "                                                                 0003_tr_0_1_dns_[0][0]',         \n",
      "                                                                  'NeuralNetworkFuture_00000000000\n",
      "                                                                 00nan_tr_0_DenseLevel_00000000000\n",
      "                                                                 00003_tr_0_DenseUnit_000000000000\n",
      "                                                                 0003_tr_0_0_dns_[0][0]',         \n",
      "                                                                  'NeuralNetworkFuture_00000000000\n",
      "                                                                 00nan_tr_0_DenseLevel_00000000000\n",
      "                                                                 00003_tr_0_DenseUnit_000000000000\n",
      "                                                                 0003_tr_0_0_dns_[0][0]']         \n",
      "                                                                                                  \n",
      " NeuralNetworkFuture_0000000000  (None, 58)          232         ['NeuralNetworkFuture_00000000000\n",
      " 000nan_tr_0_FinalDenseLevel_00                                  00nan_tr_0_FinalDenseLevel_000000\n",
      " 00000000000004_tr_0_FinalDense                                  0000000004_tr_0_FinalDenseUnit_00\n",
      " Unit_0000000000000004_tr_0_0_b                                  00000000000004_tr_0_0_cat_[0][0]'\n",
      " tn_ (BatchNormalization)                                        ]                                \n",
      "                                                                                                  \n",
      " NeuralNetworkFuture_0000000000  (None, 1)           59          ['NeuralNetworkFuture_00000000000\n",
      " 000nan_tr_0_FinalDenseLevel_00                                  00nan_tr_0_FinalDenseLevel_000000\n",
      " 00000000000004_tr_0_FinalDense                                  0000000004_tr_0_FinalDenseUnit_00\n",
      " Unit_0000000000000004_tr_0_0_d                                  00000000000004_tr_0_0_btn_[0][0]'\n",
      " ns_ (Dense)                                                     ]                                \n",
      "                                                                                                  \n",
      "==================================================================================================\n",
      "Total params: 1,981\n",
      "Trainable params: 1,367\n",
      "Non-trainable params: 614\n",
      "__________________________________________________________________________________________________\n",
      "None\n",
      "Epoch 1/10\n",
      "5/5 [==============================] - 14s 1s/step - loss: 0.9234 - binary_accuracy: 0.4529 - precision: 0.3333 - recall: 0.5000 - val_loss: 12.9753 - val_binary_accuracy: 0.3197 - val_precision: 0.3184 - val_recall: 0.9884\n",
      "Epoch 2/10\n",
      "5/5 [==============================] - 0s 12ms/step - loss: 0.8253 - binary_accuracy: 0.5190 - precision: 0.3849 - recall: 0.5330 - val_loss: 11.1958 - val_binary_accuracy: 0.3197 - val_precision: 0.3184 - val_recall: 0.9884\n",
      "Epoch 3/10\n",
      "5/5 [==============================] - 0s 13ms/step - loss: 0.7588 - binary_accuracy: 0.5631 - precision: 0.4224 - recall: 0.5385 - val_loss: 10.3022 - val_binary_accuracy: 0.3234 - val_precision: 0.3209 - val_recall: 1.0000\n",
      "Epoch 4/10\n",
      "5/5 [==============================] - 0s 13ms/step - loss: 0.7099 - binary_accuracy: 0.6032 - precision: 0.4619 - recall: 0.5330 - val_loss: 9.4562 - val_binary_accuracy: 0.3234 - val_precision: 0.3209 - val_recall: 1.0000\n",
      "Epoch 5/10\n",
      "5/5 [==============================] - 0s 17ms/step - loss: 0.6660 - binary_accuracy: 0.6273 - precision: 0.4897 - recall: 0.5220 - val_loss: 8.7083 - val_binary_accuracy: 0.3234 - val_precision: 0.3209 - val_recall: 1.0000\n",
      "Epoch 6/10\n",
      "5/5 [==============================] - 0s 12ms/step - loss: 0.6332 - binary_accuracy: 0.6593 - precision: 0.5309 - recall: 0.5659 - val_loss: 7.9648 - val_binary_accuracy: 0.3234 - val_precision: 0.3209 - val_recall: 1.0000\n",
      "Epoch 7/10\n",
      "5/5 [==============================] - 0s 11ms/step - loss: 0.6041 - binary_accuracy: 0.7014 - precision: 0.5922 - recall: 0.5824 - val_loss: 7.2415 - val_binary_accuracy: 0.3234 - val_precision: 0.3209 - val_recall: 1.0000\n",
      "Epoch 8/10\n",
      "5/5 [==============================] - 0s 13ms/step - loss: 0.5885 - binary_accuracy: 0.6814 - precision: 0.5650 - recall: 0.5495 - val_loss: 6.5367 - val_binary_accuracy: 0.3234 - val_precision: 0.3209 - val_recall: 1.0000\n",
      "Epoch 9/10\n",
      "5/5 [==============================] - 0s 12ms/step - loss: 0.5648 - binary_accuracy: 0.7214 - precision: 0.6287 - recall: 0.5769 - val_loss: 5.9177 - val_binary_accuracy: 0.3197 - val_precision: 0.3184 - val_recall: 0.9884\n",
      "Epoch 10/10\n",
      "5/5 [==============================] - 0s 14ms/step - loss: 0.5565 - binary_accuracy: 0.7134 - precision: 0.6102 - recall: 0.5934 - val_loss: 5.3821 - val_binary_accuracy: 0.3197 - val_precision: 0.3184 - val_recall: 0.9884\n",
      "this is neural_network_spec_file 2023_01_09_01_03_cerebros_auto_ml_test_meta_776979558490/model_architectures/tr_0000000000000000_subtrial_0000000000000000.txt\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:absl:Function `_wrapped_model` contains input name(s) NeuralNetworkFuture_0000000000000nan_tr_0_InputLevel_0000000000000000_tr_0_InputUnit_0000000000000000_tr_0_0_inp with unsupported characters which will be renamed to neuralnetworkfuture_0000000000000nan_tr_0_inputlevel_0000000000000000_tr_0_inputunit_0000000000000000_tr_0_0_inp in the SavedModel.\n",
      "WARNING:absl:Found untraced functions such as _update_step_xla while saving (showing 1 of 1). These functions will not be directly callable after loading.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: 2023_01_09_01_03_cerebros_auto_ml_test_meta_776979558490/models/tr_0000000000000000_subtrial_0000000000000000/assets\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: 2023_01_09_01_03_cerebros_auto_ml_test_meta_776979558490/models/tr_0000000000000000_subtrial_0000000000000000/assets\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "returning trial 0 oracles\n",
      "       loss  binary_accuracy  precision    recall   val_loss  \\\n",
      "0  0.923414         0.452906   0.333333  0.500000  12.975286   \n",
      "1  0.825317         0.519038   0.384921  0.532967  11.195849   \n",
      "2  0.758754         0.563126   0.422414  0.538462  10.302246   \n",
      "3  0.709852         0.603206   0.461905  0.532967   9.456187   \n",
      "4  0.665995         0.627254   0.489691  0.521978   8.708330   \n",
      "5  0.633213         0.659319   0.530928  0.565934   7.964751   \n",
      "6  0.604129         0.701403   0.592179  0.582418   7.241508   \n",
      "7  0.588480         0.681363   0.564972  0.549451   6.536664   \n",
      "8  0.564812         0.721443   0.628743  0.576923   5.917686   \n",
      "9  0.556482         0.713427   0.610169  0.593407   5.382143   \n",
      "\n",
      "   val_binary_accuracy  val_precision  val_recall  trial_number  \\\n",
      "0             0.319703       0.318352    0.988372             0   \n",
      "1             0.319703       0.318352    0.988372             0   \n",
      "2             0.323420       0.320896    1.000000             0   \n",
      "3             0.323420       0.320896    1.000000             0   \n",
      "4             0.323420       0.320896    1.000000             0   \n",
      "5             0.323420       0.320896    1.000000             0   \n",
      "6             0.323420       0.320896    1.000000             0   \n",
      "7             0.323420       0.320896    1.000000             0   \n",
      "8             0.319703       0.318352    0.988372             0   \n",
      "9             0.319703       0.318352    0.988372             0   \n",
      "\n",
      "   subtrial_number                                         model_name  \n",
      "0                0  2023_01_09_01_03_cerebros_auto_ml_test_meta_77...  \n",
      "1                0  2023_01_09_01_03_cerebros_auto_ml_test_meta_77...  \n",
      "2                0  2023_01_09_01_03_cerebros_auto_ml_test_meta_77...  \n",
      "3                0  2023_01_09_01_03_cerebros_auto_ml_test_meta_77...  \n",
      "4                0  2023_01_09_01_03_cerebros_auto_ml_test_meta_77...  \n",
      "5                0  2023_01_09_01_03_cerebros_auto_ml_test_meta_77...  \n",
      "6                0  2023_01_09_01_03_cerebros_auto_ml_test_meta_77...  \n",
      "7                0  2023_01_09_01_03_cerebros_auto_ml_test_meta_77...  \n",
      "8                0  2023_01_09_01_03_cerebros_auto_ml_test_meta_77...  \n",
      "9                0  2023_01_09_01_03_cerebros_auto_ml_test_meta_77...  \n",
      "nan\n",
      ">nnf>ceil\n",
      "k is: 0 value is: [{'1': <class 'cerebros.units.units.InputUnit'>}]\n",
      "0\n",
      "k is: 1 value is: [{'1': <class 'cerebros.units.units.DenseUnit'>}, {'2': <class 'cerebros.units.units.DenseUnit'>}, {'3': <class 'cerebros.units.units.DenseUnit'>}, {'1': <class 'cerebros.units.units.DenseUnit'>}]\n",
      "1\n",
      "Trying to create level 1\n",
      "We think level 1's predecessors are: [0]\n",
      "k is: 2 value is: [{'2': <class 'cerebros.units.units.DenseUnit'>}]\n",
      "2\n",
      "Trying to create level 2\n",
      "We think level 2's predecessors are: [0, 1]\n",
      "k is: 3 value is: [{'3': <class 'cerebros.units.units.DenseUnit'>}, {'3': <class 'cerebros.units.units.DenseUnit'>}, {'1': <class 'cerebros.units.units.DenseUnit'>}, {'3': <class 'cerebros.units.units.DenseUnit'>}]\n",
      "3\n",
      "Trying to create level 3\n",
      "We think level 3's predecessors are: [0, 1, 2]\n",
      "k is: 4 value is: [{'1': <class 'cerebros.units.units.DenseUnit'>}]\n",
      "4\n",
      "Trying to create level 4\n",
      "We think level 4's predecessors are: [0, 1, 2, 3]\n",
      "k is: 5 value is: [{'1': <class 'cerebros.units.units.DenseUnit'>}, {'2': <class 'cerebros.units.units.DenseUnit'>}, {'3': <class 'cerebros.units.units.DenseUnit'>}, {'4': <class 'cerebros.units.units.DenseUnit'>}]\n",
      "5\n",
      "Trying to create level 5\n",
      "We think level 5's predecessors are: [0, 1, 2, 3, 4]\n",
      "k is: 6 value is: [{'1': <class 'cerebros.units.units.FinalDenseUnit'>}]\n",
      "6\n",
      "Trying to create Final level 6\n",
      "Trying to create level 6\n",
      "We think level final level 6's predecessors are: [0, 1, 2, 3, 4, 5]\n",
      "levels:\n",
      "[0, 1, 2, 3, 4, 5, 6]\n",
      "{'0': 'InputUnitModule'}\n",
      "{'1': <class 'cerebros.units.units.DenseUnit'>}\n",
      "{'2': <class 'cerebros.units.units.DenseUnit'>}\n",
      "{'3': <class 'cerebros.units.units.DenseUnit'>}\n",
      "{'1': <class 'cerebros.units.units.DenseUnit'>}\n",
      "{'2': <class 'cerebros.units.units.DenseUnit'>}\n",
      "{'3': <class 'cerebros.units.units.DenseUnit'>}\n",
      "{'3': <class 'cerebros.units.units.DenseUnit'>}\n",
      "{'1': <class 'cerebros.units.units.DenseUnit'>}\n",
      "{'3': <class 'cerebros.units.units.DenseUnit'>}\n",
      "{'1': <class 'cerebros.units.units.DenseUnit'>}\n",
      "{'1': <class 'cerebros.units.units.DenseUnit'>}\n",
      "{'2': <class 'cerebros.units.units.DenseUnit'>}\n",
      "{'3': <class 'cerebros.units.units.DenseUnit'>}\n",
      "{'4': <class 'cerebros.units.units.DenseUnit'>}\n",
      "Debug: I am 6 selecting 5\n",
      "debug: meta_level_number\n",
      "debug: meta_level_number\n",
      "debug: meta_level_number\n",
      "debug: meta_level_number\n",
      "debug: meta_level_number\n",
      "debug: meta_level_number\n",
      "debug: meta_level_number\n",
      "debug: meta_level_number\n",
      "debug: meta_level_number\n",
      "debug: meta_level_number\n",
      "debug: meta_level_number\n",
      "debug: meta_level_number\n",
      "debug: meta_level_number\n",
      "debug: meta_level_number\n",
      "debug: meta_level_number\n",
      "Setting levels_unmaterialized[0] level_number 0 to have first successor: levels_unmaterialized[:1], having level_numbers of [1, 2, 3, 4, 5, 6]\n",
      "Setting levels_unmaterialized[1] level_number 1 to have first successor: levels_unmaterialized[:2], having level_numbers of [2, 3, 4, 5, 6]\n",
      "Setting levels_unmaterialized[2] level_number 2 to have first successor: levels_unmaterialized[:3], having level_numbers of [3, 4, 5, 6]\n",
      "Setting levels_unmaterialized[3] level_number 3 to have first successor: levels_unmaterialized[:4], having level_numbers of [4, 5, 6]\n",
      "Setting levels_unmaterialized[4] level_number 4 to have first successor: levels_unmaterialized[:5], having level_numbers of [5, 6]\n",
      "Setting levels_unmaterialized[5] level_number 5 to have first successor: levels_unmaterialized[:6], having level_numbers of [6]\n",
      "Debug: successor_connectivity_errors_2d []\n",
      "{'1': <class 'cerebros.units.units.DenseUnit'>}\n",
      "{'2': <class 'cerebros.units.units.DenseUnit'>}\n",
      "{'3': <class 'cerebros.units.units.DenseUnit'>}\n",
      "{'1': <class 'cerebros.units.units.DenseUnit'>}\n",
      "debug: meta_level_number\n",
      "debug: meta_level_number\n",
      "debug: meta_level_number\n",
      "debug: meta_level_number\n",
      "Debug: successor_connectivity_errors_2d []\n",
      "Debug: successor_connectivity_errors_2d []\n",
      "Debug: successor_connectivity_errors_2d []\n",
      "Debug: successor_connectivity_errors_2d []\n",
      "materialize:_NeuralNetworkFuture_0000000000000nan_tr_1_DenseLevel_0000000000000001_tr_1_DenseUnit_0000000000000001_tr_1_0 called\n",
      "materialized network layers\n",
      "[<KerasTensor: shape=(None, 8) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_1_InputLevel_0000000000000000_tr_1_InputUnit_0000000000000000_tr_1_0_inp')>, <KerasTensor: shape=(None, 8) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_1_InputLevel_0000000000000000_tr_1_InputUnit_0000000000000000_tr_1_0_inp')>, <KerasTensor: shape=(None, 8) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_1_InputLevel_0000000000000000_tr_1_InputUnit_0000000000000000_tr_1_0_inp')>, <KerasTensor: shape=(None, 8) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_1_InputLevel_0000000000000000_tr_1_InputUnit_0000000000000000_tr_1_0_inp')>]\n",
      "materialize:_NeuralNetworkFuture_0000000000000nan_tr_1_DenseLevel_0000000000000001_tr_1_DenseUnit_0000000000000001_tr_1_1 called\n",
      "materialized network layers\n",
      "[<KerasTensor: shape=(None, 8) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_1_InputLevel_0000000000000000_tr_1_InputUnit_0000000000000000_tr_1_0_inp')>, <KerasTensor: shape=(None, 8) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_1_InputLevel_0000000000000000_tr_1_InputUnit_0000000000000000_tr_1_0_inp')>, <KerasTensor: shape=(None, 8) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_1_InputLevel_0000000000000000_tr_1_InputUnit_0000000000000000_tr_1_0_inp')>, <KerasTensor: shape=(None, 8) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_1_InputLevel_0000000000000000_tr_1_InputUnit_0000000000000000_tr_1_0_inp')>]\n",
      "materialize:_NeuralNetworkFuture_0000000000000nan_tr_1_DenseLevel_0000000000000001_tr_1_DenseUnit_0000000000000001_tr_1_2 called\n",
      "materialized network layers\n",
      "[<KerasTensor: shape=(None, 2) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_1_DenseLevel_0000000000000001_tr_1_DenseUnit_0000000000000001_tr_1_1_dns_')>, <KerasTensor: shape=(None, 2) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_1_DenseLevel_0000000000000001_tr_1_DenseUnit_0000000000000001_tr_1_1_dns_')>, <KerasTensor: shape=(None, 8) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_1_InputLevel_0000000000000000_tr_1_InputUnit_0000000000000000_tr_1_0_inp')>, <KerasTensor: shape=(None, 8) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_1_InputLevel_0000000000000000_tr_1_InputUnit_0000000000000000_tr_1_0_inp')>, <KerasTensor: shape=(None, 8) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_1_InputLevel_0000000000000000_tr_1_InputUnit_0000000000000000_tr_1_0_inp')>, <KerasTensor: shape=(None, 8) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_1_InputLevel_0000000000000000_tr_1_InputUnit_0000000000000000_tr_1_0_inp')>]\n",
      "materialize:_NeuralNetworkFuture_0000000000000nan_tr_1_DenseLevel_0000000000000001_tr_1_DenseUnit_0000000000000001_tr_1_3 called\n",
      "materialized network layers\n",
      "[<KerasTensor: shape=(None, 3) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_1_DenseLevel_0000000000000001_tr_1_DenseUnit_0000000000000001_tr_1_2_dns_')>, <KerasTensor: shape=(None, 2) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_1_DenseLevel_0000000000000001_tr_1_DenseUnit_0000000000000001_tr_1_1_dns_')>, <KerasTensor: shape=(None, 2) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_1_DenseLevel_0000000000000001_tr_1_DenseUnit_0000000000000001_tr_1_1_dns_')>, <KerasTensor: shape=(None, 8) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_1_InputLevel_0000000000000000_tr_1_InputUnit_0000000000000000_tr_1_0_inp')>, <KerasTensor: shape=(None, 8) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_1_InputLevel_0000000000000000_tr_1_InputUnit_0000000000000000_tr_1_0_inp')>, <KerasTensor: shape=(None, 8) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_1_InputLevel_0000000000000000_tr_1_InputUnit_0000000000000000_tr_1_0_inp')>, <KerasTensor: shape=(None, 8) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_1_InputLevel_0000000000000000_tr_1_InputUnit_0000000000000000_tr_1_0_inp')>]\n",
      "{'2': <class 'cerebros.units.units.DenseUnit'>}\n",
      "debug: meta_level_number\n",
      "Debug: successor_connectivity_errors_2d []\n",
      "materialize:_NeuralNetworkFuture_0000000000000nan_tr_1_DenseLevel_0000000000000002_tr_1_DenseUnit_0000000000000002_tr_1_0 called\n",
      "materialized network layers\n",
      "[<KerasTensor: shape=(None, 8) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_1_InputLevel_0000000000000000_tr_1_InputUnit_0000000000000000_tr_1_0_inp')>, <KerasTensor: shape=(None, 3) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_1_DenseLevel_0000000000000001_tr_1_DenseUnit_0000000000000001_tr_1_2_dns_')>, <KerasTensor: shape=(None, 3) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_1_DenseLevel_0000000000000001_tr_1_DenseUnit_0000000000000001_tr_1_2_dns_')>, <KerasTensor: shape=(None, 1) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_1_DenseLevel_0000000000000001_tr_1_DenseUnit_0000000000000001_tr_1_3_dns_')>, <KerasTensor: shape=(None, 8) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_1_InputLevel_0000000000000000_tr_1_InputUnit_0000000000000000_tr_1_0_inp')>, <KerasTensor: shape=(None, 3) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_1_DenseLevel_0000000000000001_tr_1_DenseUnit_0000000000000001_tr_1_2_dns_')>, <KerasTensor: shape=(None, 3) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_1_DenseLevel_0000000000000001_tr_1_DenseUnit_0000000000000001_tr_1_2_dns_')>, <KerasTensor: shape=(None, 1) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_1_DenseLevel_0000000000000001_tr_1_DenseUnit_0000000000000001_tr_1_3_dns_')>]\n",
      "{'3': <class 'cerebros.units.units.DenseUnit'>}\n",
      "{'3': <class 'cerebros.units.units.DenseUnit'>}\n",
      "{'1': <class 'cerebros.units.units.DenseUnit'>}\n",
      "{'3': <class 'cerebros.units.units.DenseUnit'>}\n",
      "debug: meta_level_number\n",
      "debug: meta_level_number\n",
      "debug: meta_level_number\n",
      "debug: meta_level_number\n",
      "Debug: successor_connectivity_errors_2d []\n",
      "Debug: successor_connectivity_errors_2d []\n",
      "Debug: successor_connectivity_errors_2d []\n",
      "Debug: successor_connectivity_errors_2d []\n",
      "materialize:_NeuralNetworkFuture_0000000000000nan_tr_1_DenseLevel_0000000000000003_tr_1_DenseUnit_0000000000000003_tr_1_0 called\n",
      "materialized network layers\n",
      "[<KerasTensor: shape=(None, 8) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_1_InputLevel_0000000000000000_tr_1_InputUnit_0000000000000000_tr_1_0_inp')>, <KerasTensor: shape=(None, 1) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_1_DenseLevel_0000000000000001_tr_1_DenseUnit_0000000000000001_tr_1_3_dns_')>, <KerasTensor: shape=(None, 2) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_1_DenseLevel_0000000000000001_tr_1_DenseUnit_0000000000000001_tr_1_1_dns_')>, <KerasTensor: shape=(None, 2) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_1_DenseLevel_0000000000000002_tr_1_DenseUnit_0000000000000002_tr_1_0_dns_')>, <KerasTensor: shape=(None, 8) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_1_InputLevel_0000000000000000_tr_1_InputUnit_0000000000000000_tr_1_0_inp')>, <KerasTensor: shape=(None, 1) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_1_DenseLevel_0000000000000001_tr_1_DenseUnit_0000000000000001_tr_1_0_dns_')>, <KerasTensor: shape=(None, 2) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_1_DenseLevel_0000000000000001_tr_1_DenseUnit_0000000000000001_tr_1_1_dns_')>, <KerasTensor: shape=(None, 2) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_1_DenseLevel_0000000000000002_tr_1_DenseUnit_0000000000000002_tr_1_0_dns_')>]\n",
      "materialize:_NeuralNetworkFuture_0000000000000nan_tr_1_DenseLevel_0000000000000003_tr_1_DenseUnit_0000000000000003_tr_1_1 called\n",
      "materialized network layers\n",
      "[<KerasTensor: shape=(None, 8) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_1_InputLevel_0000000000000000_tr_1_InputUnit_0000000000000000_tr_1_0_inp')>, <KerasTensor: shape=(None, 3) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_1_DenseLevel_0000000000000001_tr_1_DenseUnit_0000000000000001_tr_1_2_dns_')>, <KerasTensor: shape=(None, 1) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_1_DenseLevel_0000000000000001_tr_1_DenseUnit_0000000000000001_tr_1_3_dns_')>, <KerasTensor: shape=(None, 2) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_1_DenseLevel_0000000000000002_tr_1_DenseUnit_0000000000000002_tr_1_0_dns_')>, <KerasTensor: shape=(None, 8) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_1_InputLevel_0000000000000000_tr_1_InputUnit_0000000000000000_tr_1_0_inp')>, <KerasTensor: shape=(None, 3) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_1_DenseLevel_0000000000000001_tr_1_DenseUnit_0000000000000001_tr_1_2_dns_')>, <KerasTensor: shape=(None, 1) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_1_DenseLevel_0000000000000001_tr_1_DenseUnit_0000000000000001_tr_1_0_dns_')>, <KerasTensor: shape=(None, 2) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_1_DenseLevel_0000000000000002_tr_1_DenseUnit_0000000000000002_tr_1_0_dns_')>]\n",
      "materialize:_NeuralNetworkFuture_0000000000000nan_tr_1_DenseLevel_0000000000000003_tr_1_DenseUnit_0000000000000003_tr_1_2 called\n",
      "materialized network layers\n",
      "[<KerasTensor: shape=(None, 3) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_1_DenseLevel_0000000000000003_tr_1_DenseUnit_0000000000000003_tr_1_1_dns_')>, <KerasTensor: shape=(None, 3) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_1_DenseLevel_0000000000000003_tr_1_DenseUnit_0000000000000003_tr_1_1_dns_')>, <KerasTensor: shape=(None, 8) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_1_InputLevel_0000000000000000_tr_1_InputUnit_0000000000000000_tr_1_0_inp')>, <KerasTensor: shape=(None, 3) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_1_DenseLevel_0000000000000001_tr_1_DenseUnit_0000000000000001_tr_1_2_dns_')>, <KerasTensor: shape=(None, 3) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_1_DenseLevel_0000000000000001_tr_1_DenseUnit_0000000000000001_tr_1_2_dns_')>, <KerasTensor: shape=(None, 2) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_1_DenseLevel_0000000000000002_tr_1_DenseUnit_0000000000000002_tr_1_0_dns_')>, <KerasTensor: shape=(None, 8) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_1_InputLevel_0000000000000000_tr_1_InputUnit_0000000000000000_tr_1_0_inp')>, <KerasTensor: shape=(None, 1) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_1_DenseLevel_0000000000000001_tr_1_DenseUnit_0000000000000001_tr_1_0_dns_')>, <KerasTensor: shape=(None, 1) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_1_DenseLevel_0000000000000001_tr_1_DenseUnit_0000000000000001_tr_1_3_dns_')>, <KerasTensor: shape=(None, 2) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_1_DenseLevel_0000000000000002_tr_1_DenseUnit_0000000000000002_tr_1_0_dns_')>]\n",
      "materialize:_NeuralNetworkFuture_0000000000000nan_tr_1_DenseLevel_0000000000000003_tr_1_DenseUnit_0000000000000003_tr_1_3 called\n",
      "materialized network layers\n",
      "[<KerasTensor: shape=(None, 1) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_1_DenseLevel_0000000000000003_tr_1_DenseUnit_0000000000000003_tr_1_2_dns_')>, <KerasTensor: shape=(None, 3) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_1_DenseLevel_0000000000000003_tr_1_DenseUnit_0000000000000003_tr_1_1_dns_')>, <KerasTensor: shape=(None, 3) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_1_DenseLevel_0000000000000003_tr_1_DenseUnit_0000000000000003_tr_1_1_dns_')>, <KerasTensor: shape=(None, 8) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_1_InputLevel_0000000000000000_tr_1_InputUnit_0000000000000000_tr_1_0_inp')>, <KerasTensor: shape=(None, 1) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_1_DenseLevel_0000000000000001_tr_1_DenseUnit_0000000000000001_tr_1_0_dns_')>, <KerasTensor: shape=(None, 2) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_1_DenseLevel_0000000000000001_tr_1_DenseUnit_0000000000000001_tr_1_1_dns_')>, <KerasTensor: shape=(None, 2) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_1_DenseLevel_0000000000000002_tr_1_DenseUnit_0000000000000002_tr_1_0_dns_')>, <KerasTensor: shape=(None, 8) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_1_InputLevel_0000000000000000_tr_1_InputUnit_0000000000000000_tr_1_0_inp')>, <KerasTensor: shape=(None, 2) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_1_DenseLevel_0000000000000001_tr_1_DenseUnit_0000000000000001_tr_1_1_dns_')>, <KerasTensor: shape=(None, 1) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_1_DenseLevel_0000000000000001_tr_1_DenseUnit_0000000000000001_tr_1_0_dns_')>, <KerasTensor: shape=(None, 2) dtype=float32 (created by layer 'NeuralNetworkFuture_0000000000000nan_tr_1_DenseLevel_0000000000000002_tr_1_DenseUnit_0000000000000002_tr_1_0_dns_')>]\n",
      "{'1': <class 'cerebros.units.units.DenseUnit'>}\n",
      "debug: meta_level_number\n"
     ]
    },
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "Cell \u001b[0;32mIn [4], line 52\u001b[0m\n\u001b[1;32m      5\u001b[0m meta_trial_number \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mstr\u001b[39m(\u001b[38;5;28mint\u001b[39m(np\u001b[38;5;241m.\u001b[39mrandom\u001b[38;5;241m.\u001b[39mrandom() \u001b[38;5;241m*\u001b[39m \u001b[38;5;241m10\u001b[39m \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39m \u001b[38;5;241m12\u001b[39m))\n\u001b[1;32m      8\u001b[0m cerebros_automl \u001b[38;5;241m=\u001b[39m SimpleCerebrosRandomSearch(\n\u001b[1;32m      9\u001b[0m     unit_type\u001b[38;5;241m=\u001b[39mDenseUnit,\n\u001b[1;32m     10\u001b[0m     input_shapes\u001b[38;5;241m=\u001b[39mINPUT_SHAPES,\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m     50\u001b[0m     batch_size\u001b[38;5;241m=\u001b[39mbatch_size,\n\u001b[1;32m     51\u001b[0m     meta_trial_number\u001b[38;5;241m=\u001b[39mmeta_trial_number)\n\u001b[0;32m---> 52\u001b[0m val_binary_accuracy \u001b[38;5;241m=\u001b[39m \u001b[43mcerebros_automl\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrun_random_search\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/cerebros-core-algorithm-alpha/cerebros/simplecerebrosrandomsearch/simple_cerebros_random_search.py:514\u001b[0m, in \u001b[0;36mSimpleCerebrosRandomSearch.run_random_search\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    510\u001b[0m lock \u001b[38;5;241m=\u001b[39m Lock()\n\u001b[1;32m    511\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m i \u001b[38;5;129;01min\u001b[39;00m np\u001b[38;5;241m.\u001b[39marange(\n\u001b[1;32m    512\u001b[0m         \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mnumber_of_tries_per_architecture_moity):\n\u001b[1;32m    513\u001b[0m     processes\u001b[38;5;241m.\u001b[39mappend(\n\u001b[0;32m--> 514\u001b[0m         Process(target\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrun_moity_permutations\u001b[49m\u001b[43m(\u001b[49m\u001b[43mspec\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mspec\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43msubtrial_number\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43msubtrial_number\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mlock\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mlock\u001b[49m\u001b[43m)\u001b[49m))\n\u001b[1;32m    515\u001b[0m     subtrial_number \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1\u001b[39m\n\u001b[1;32m    516\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mseed \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1\u001b[39m\n",
      "File \u001b[0;32m~/cerebros-core-algorithm-alpha/cerebros/simplecerebrosrandomsearch/simple_cerebros_random_search.py:465\u001b[0m, in \u001b[0;36mSimpleCerebrosRandomSearch.run_moity_permutations\u001b[0;34m(self, spec, subtrial_number, lock)\u001b[0m\n\u001b[1;32m    436\u001b[0m \u001b[38;5;66;03m#with STRATEGY.scope():\u001b[39;00m\n\u001b[1;32m    437\u001b[0m nnf \u001b[38;5;241m=\u001b[39m NeuralNetworkFuture(\n\u001b[1;32m    438\u001b[0m     input_shapes\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39minput_shapes,\n\u001b[1;32m    439\u001b[0m     output_shapes\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39moutput_shapes,\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    463\u001b[0m     model_graph_file\u001b[38;5;241m=\u001b[39mmodel_graph_file\n\u001b[1;32m    464\u001b[0m     )\n\u001b[0;32m--> 465\u001b[0m \u001b[43mnnf\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmaterialize\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    466\u001b[0m nnf\u001b[38;5;241m.\u001b[39mcompile_neural_network()\n\u001b[1;32m    467\u001b[0m neural_network \u001b[38;5;241m=\u001b[39m nnf\u001b[38;5;241m.\u001b[39mmaterialized_neural_network\n",
      "File \u001b[0;32m~/cerebros-core-algorithm-alpha/cerebros/neuralnetworkfuture/neural_network_future.py:284\u001b[0m, in \u001b[0;36mNeuralNetworkFuture.materialize\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    281\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mutil_set_predecessor_connectivity_metadata()\n\u001b[1;32m    283\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m level \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mlevels_unmaterialized:\n\u001b[0;32m--> 284\u001b[0m     \u001b[43mlevel\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmaterialize\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    285\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mlevels_unmaterialized[\u001b[38;5;241m0\u001b[39m]\u001b[38;5;241m.\u001b[39mparallel_units) \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m1\u001b[39m:\n\u001b[1;32m    286\u001b[0m     materialized_neural_network_inputs \u001b[38;5;241m=\u001b[39m\\\n\u001b[1;32m    287\u001b[0m         [unit_0\u001b[38;5;241m.\u001b[39mneural_network_layer\n\u001b[1;32m    288\u001b[0m          \u001b[38;5;28;01mfor\u001b[39;00m unit_0 \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mlevels_unmaterialized[\u001b[38;5;241m0\u001b[39m]\u001b[38;5;241m.\u001b[39mparallel_units]\n",
      "File \u001b[0;32m~/cerebros-core-algorithm-alpha/cerebros/levels/levels.py:557\u001b[0m, in \u001b[0;36mDenseLevel.materialize\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    555\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mparse_units()\n\u001b[1;32m    556\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mset_connectivity_future_prototype()\n\u001b[0;32m--> 557\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mparse_meta_predecessor_connectivity\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    558\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mset_successor_levels()\n\u001b[1;32m    559\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdetect_successor_connectivity_errors()\n",
      "File \u001b[0;32m~/cerebros-core-algorithm-alpha/cerebros/levels/levels.py:542\u001b[0m, in \u001b[0;36mDenseLevel.parse_meta_predecessor_connectivity\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    532\u001b[0m     meta_level_number \u001b[38;5;241m=\u001b[39m\\\n\u001b[1;32m    533\u001b[0m         jnp\u001b[38;5;241m.\u001b[39mconcatenate(\n\u001b[1;32m    534\u001b[0m             [meta_level_number,\n\u001b[1;32m    535\u001b[0m              unit_0\u001b[38;5;241m.\u001b[39mmeta_predecessor_connectivity_level_number],\n\u001b[1;32m    536\u001b[0m             dtype\u001b[38;5;241m=\u001b[39mjnp\u001b[38;5;241m.\u001b[39mint32)\n\u001b[1;32m    537\u001b[0m     meta_unit_id \u001b[38;5;241m=\u001b[39m\\\n\u001b[1;32m    538\u001b[0m         jnp\u001b[38;5;241m.\u001b[39mconcatenate(\n\u001b[1;32m    539\u001b[0m             [meta_unit_id,\n\u001b[1;32m    540\u001b[0m              unit_0\u001b[38;5;241m.\u001b[39mmeta_predecessor_connectivity_unit_id],\n\u001b[1;32m    541\u001b[0m             dtype\u001b[38;5;241m=\u001b[39mjnp\u001b[38;5;241m.\u001b[39mint32)\n\u001b[0;32m--> 542\u001b[0m check_unique_units \u001b[38;5;241m=\u001b[39m \u001b[43mjnp\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcolumn_stack\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    543\u001b[0m \u001b[43m    \u001b[49m\u001b[43m[\u001b[49m\u001b[43mmeta_level_number\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmeta_unit_id\u001b[49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    544\u001b[0m unique_units \u001b[38;5;241m=\u001b[39m jnp\u001b[38;5;241m.\u001b[39munique(check_unique_units, axis\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m0\u001b[39m)\n\u001b[1;32m    546\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mmeta_predecessor_connectivity_level_number \u001b[38;5;241m=\u001b[39m unique_units[:, \u001b[38;5;241m0\u001b[39m]\n",
      "File \u001b[0;32m~/.local/lib/python3.8/site-packages/jax/_src/numpy/lax_numpy.py:1842\u001b[0m, in \u001b[0;36mcolumn_stack\u001b[0;34m(tup)\u001b[0m\n\u001b[1;32m   1840\u001b[0m   arrs \u001b[38;5;241m=\u001b[39m jax\u001b[38;5;241m.\u001b[39mvmap(\u001b[38;5;28;01mlambda\u001b[39;00m x: atleast_2d(x)\u001b[38;5;241m.\u001b[39mT)(tup) \u001b[38;5;28;01mif\u001b[39;00m tup\u001b[38;5;241m.\u001b[39mndim \u001b[38;5;241m<\u001b[39m \u001b[38;5;241m3\u001b[39m \u001b[38;5;28;01melse\u001b[39;00m tup\n\u001b[1;32m   1841\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m-> 1842\u001b[0m   arrs \u001b[38;5;241m=\u001b[39m [atleast_2d(arr)\u001b[38;5;241m.\u001b[39mT \u001b[38;5;28;01mif\u001b[39;00m arr\u001b[38;5;241m.\u001b[39mndim \u001b[38;5;241m<\u001b[39m \u001b[38;5;241m2\u001b[39m \u001b[38;5;28;01melse\u001b[39;00m arr \u001b[38;5;28;01mfor\u001b[39;00m arr \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mmap\u001b[39m(asarray, tup)]\n\u001b[1;32m   1843\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m concatenate(arrs, \u001b[38;5;241m1\u001b[39m)\n",
      "File \u001b[0;32m~/.local/lib/python3.8/site-packages/jax/_src/numpy/lax_numpy.py:1842\u001b[0m, in \u001b[0;36m<listcomp>\u001b[0;34m(.0)\u001b[0m\n\u001b[1;32m   1840\u001b[0m   arrs \u001b[38;5;241m=\u001b[39m jax\u001b[38;5;241m.\u001b[39mvmap(\u001b[38;5;28;01mlambda\u001b[39;00m x: atleast_2d(x)\u001b[38;5;241m.\u001b[39mT)(tup) \u001b[38;5;28;01mif\u001b[39;00m tup\u001b[38;5;241m.\u001b[39mndim \u001b[38;5;241m<\u001b[39m \u001b[38;5;241m3\u001b[39m \u001b[38;5;28;01melse\u001b[39;00m tup\n\u001b[1;32m   1841\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m-> 1842\u001b[0m   arrs \u001b[38;5;241m=\u001b[39m [\u001b[43matleast_2d\u001b[49m\u001b[43m(\u001b[49m\u001b[43marr\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241m.\u001b[39mT \u001b[38;5;28;01mif\u001b[39;00m arr\u001b[38;5;241m.\u001b[39mndim \u001b[38;5;241m<\u001b[39m \u001b[38;5;241m2\u001b[39m \u001b[38;5;28;01melse\u001b[39;00m arr \u001b[38;5;28;01mfor\u001b[39;00m arr \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mmap\u001b[39m(asarray, tup)]\n\u001b[1;32m   1843\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m concatenate(arrs, \u001b[38;5;241m1\u001b[39m)\n",
      "    \u001b[0;31m[... skipping hidden 1 frame]\u001b[0m\n",
      "File \u001b[0;32m~/.local/lib/python3.8/site-packages/jax/_src/api.py:622\u001b[0m, in \u001b[0;36m_cpp_jit.<locals>.cache_miss\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m    619\u001b[0m execute \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m    620\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(top_trace, core\u001b[38;5;241m.\u001b[39mEvalTrace) \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m (\n\u001b[1;32m    621\u001b[0m     jax\u001b[38;5;241m.\u001b[39mconfig\u001b[38;5;241m.\u001b[39mjax_debug_nans \u001b[38;5;129;01mor\u001b[39;00m jax\u001b[38;5;241m.\u001b[39mconfig\u001b[38;5;241m.\u001b[39mjax_debug_infs):\n\u001b[0;32m--> 622\u001b[0m   execute \u001b[38;5;241m=\u001b[39m \u001b[43mdispatch\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_xla_call_impl_lazy\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfun_\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mtracers\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mparams\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    623\u001b[0m   out_flat \u001b[38;5;241m=\u001b[39m call_bind_continuation(execute(\u001b[38;5;241m*\u001b[39margs_flat))\n\u001b[1;32m    624\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n",
      "File \u001b[0;32m~/.local/lib/python3.8/site-packages/jax/_src/dispatch.py:241\u001b[0m, in \u001b[0;36m_xla_call_impl_lazy\u001b[0;34m(***failed resolving arguments***)\u001b[0m\n\u001b[1;32m    239\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mNotImplementedError\u001b[39;00m(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mDynamic shapes do not work with Array.\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[1;32m    240\u001b[0m   arg_specs \u001b[38;5;241m=\u001b[39m [(\u001b[38;5;28;01mNone\u001b[39;00m, \u001b[38;5;28mgetattr\u001b[39m(x, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124m_device\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;28;01mNone\u001b[39;00m)) \u001b[38;5;28;01mfor\u001b[39;00m x \u001b[38;5;129;01min\u001b[39;00m args]\n\u001b[0;32m--> 241\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mxla_callable\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfun\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdevice\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mbackend\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mname\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdonated_invars\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mkeep_unused\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    242\u001b[0m \u001b[43m                    \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43marg_specs\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/.local/lib/python3.8/site-packages/jax/linear_util.py:303\u001b[0m, in \u001b[0;36mcache.<locals>.memoized_fun\u001b[0;34m(fun, *args)\u001b[0m\n\u001b[1;32m    301\u001b[0m   fun\u001b[38;5;241m.\u001b[39mpopulate_stores(stores)\n\u001b[1;32m    302\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m--> 303\u001b[0m   ans \u001b[38;5;241m=\u001b[39m \u001b[43mcall\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfun\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    304\u001b[0m   cache[key] \u001b[38;5;241m=\u001b[39m (ans, fun\u001b[38;5;241m.\u001b[39mstores)\n\u001b[1;32m    306\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m ans\n",
      "File \u001b[0;32m~/.local/lib/python3.8/site-packages/jax/_src/dispatch.py:359\u001b[0m, in \u001b[0;36m_xla_callable_uncached\u001b[0;34m(fun, device, backend, name, donated_invars, keep_unused, *arg_specs)\u001b[0m\n\u001b[1;32m    356\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m config\u001b[38;5;241m.\u001b[39mjax_array:\n\u001b[1;32m    357\u001b[0m   computation \u001b[38;5;241m=\u001b[39m sharded_lowering(fun, device, backend, name, donated_invars,\n\u001b[1;32m    358\u001b[0m                                  \u001b[38;5;28;01mFalse\u001b[39;00m, keep_unused, \u001b[38;5;241m*\u001b[39marg_specs)\n\u001b[0;32m--> 359\u001b[0m   \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mcomputation\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcompile\u001b[49m\u001b[43m(\u001b[49m\u001b[43m_allow_propagation_to_outputs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m)\u001b[49m\u001b[38;5;241m.\u001b[39munsafe_call\n\u001b[1;32m    360\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m    361\u001b[0m   \u001b[38;5;28;01mreturn\u001b[39;00m lower_xla_callable(fun, device, backend, name, donated_invars, \u001b[38;5;28;01mFalse\u001b[39;00m,\n\u001b[1;32m    362\u001b[0m                             keep_unused, \u001b[38;5;241m*\u001b[39marg_specs)\u001b[38;5;241m.\u001b[39mcompile()\u001b[38;5;241m.\u001b[39munsafe_call\n",
      "File \u001b[0;32m~/.local/lib/python3.8/site-packages/jax/interpreters/pxla.py:3202\u001b[0m, in \u001b[0;36mMeshComputation.compile\u001b[0;34m(self, _allow_propagation_to_outputs, _allow_compile_replicated)\u001b[0m\n\u001b[1;32m   3198\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mcompile\u001b[39m(\u001b[38;5;28mself\u001b[39m,\n\u001b[1;32m   3199\u001b[0m             _allow_propagation_to_outputs : \u001b[38;5;28mbool\u001b[39m \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mFalse\u001b[39;00m,\n\u001b[1;32m   3200\u001b[0m             _allow_compile_replicated : \u001b[38;5;28mbool\u001b[39m \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mTrue\u001b[39;00m) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m MeshExecutable:\n\u001b[1;32m   3201\u001b[0m   \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_executable \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m-> 3202\u001b[0m     executable \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_compile_unloaded\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m   3203\u001b[0m \u001b[43m        \u001b[49m\u001b[43m_allow_propagation_to_outputs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m_allow_compile_replicated\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   3204\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(executable, UnloadedMeshExecutable):\n\u001b[1;32m   3205\u001b[0m       executable \u001b[38;5;241m=\u001b[39m executable\u001b[38;5;241m.\u001b[39mload()\n",
      "File \u001b[0;32m~/.local/lib/python3.8/site-packages/jax/interpreters/pxla.py:3170\u001b[0m, in \u001b[0;36mMeshComputation._compile_unloaded\u001b[0;34m(self, _allow_propagation_to_outputs, _allow_compile_replicated)\u001b[0m\n\u001b[1;32m   3168\u001b[0m   \u001b[38;5;28;01mreturn\u001b[39;00m MeshExecutable\u001b[38;5;241m.\u001b[39mfrom_trivial_jaxpr(\u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mcompile_args)\n\u001b[1;32m   3169\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m-> 3170\u001b[0m   \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mUnloadedMeshExecutable\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfrom_hlo\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m   3171\u001b[0m \u001b[43m      \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_name\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   3172\u001b[0m \u001b[43m      \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_hlo\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   3173\u001b[0m \u001b[43m      \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcompile_args\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   3174\u001b[0m \u001b[43m      \u001b[49m\u001b[43m_allow_propagation_to_outputs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m_allow_propagation_to_outputs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   3175\u001b[0m \u001b[43m      \u001b[49m\u001b[43m_allow_compile_replicated\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m_allow_compile_replicated\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/.local/lib/python3.8/site-packages/jax/interpreters/pxla.py:3439\u001b[0m, in \u001b[0;36mUnloadedMeshExecutable.from_hlo\u001b[0;34m(name, computation, mesh, global_in_avals, global_out_avals, in_shardings, out_shardings, spmd_lowering, tuple_args, in_is_global, auto_spmd_lowering, _allow_propagation_to_outputs, _allow_compile_replicated, unordered_effects, ordered_effects, host_callbacks, keepalive, kept_var_idx, backend, device_assignment, committed, pmap_nreps)\u001b[0m\n\u001b[1;32m   3435\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m   3436\u001b[0m   \u001b[38;5;28;01mwith\u001b[39;00m dispatch\u001b[38;5;241m.\u001b[39mlog_elapsed_time(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mFinished XLA compilation of \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mname\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m   3437\u001b[0m                                  \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124min \u001b[39m\u001b[38;5;132;01m{elapsed_time}\u001b[39;00m\u001b[38;5;124m sec\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[1;32m   3438\u001b[0m                                  event\u001b[38;5;241m=\u001b[39mdispatch\u001b[38;5;241m.\u001b[39mBACKEND_COMPILE_EVENT):\n\u001b[0;32m-> 3439\u001b[0m     xla_executable \u001b[38;5;241m=\u001b[39m \u001b[43mdispatch\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcompile_or_get_cached\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m   3440\u001b[0m \u001b[43m        \u001b[49m\u001b[43mbackend\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcomputation\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcompile_options\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mhost_callbacks\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   3442\u001b[0m   \u001b[38;5;28;01mif\u001b[39;00m auto_spmd_lowering:\n\u001b[1;32m   3443\u001b[0m     \u001b[38;5;28;01massert\u001b[39;00m mesh \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n",
      "File \u001b[0;32m~/.local/lib/python3.8/site-packages/jax/_src/dispatch.py:1079\u001b[0m, in \u001b[0;36mcompile_or_get_cached\u001b[0;34m(backend, computation, compile_options, host_callbacks)\u001b[0m\n\u001b[1;32m   1075\u001b[0m     _cache_write(serialized_computation, compile_time, module_name,\n\u001b[1;32m   1076\u001b[0m                  compile_options, backend, compiled)\n\u001b[1;32m   1077\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m compiled\n\u001b[0;32m-> 1079\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mbackend_compile\u001b[49m\u001b[43m(\u001b[49m\u001b[43mbackend\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mserialized_computation\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcompile_options\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1080\u001b[0m \u001b[43m                       \u001b[49m\u001b[43mhost_callbacks\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/.local/lib/python3.8/site-packages/jax/_src/profiler.py:314\u001b[0m, in \u001b[0;36mannotate_function.<locals>.wrapper\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m    311\u001b[0m \u001b[38;5;129m@wraps\u001b[39m(func)\n\u001b[1;32m    312\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mwrapper\u001b[39m(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[1;32m    313\u001b[0m   \u001b[38;5;28;01mwith\u001b[39;00m TraceAnnotation(name, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mdecorator_kwargs):\n\u001b[0;32m--> 314\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    315\u001b[0m   \u001b[38;5;28;01mreturn\u001b[39;00m wrapper\n",
      "File \u001b[0;32m~/.local/lib/python3.8/site-packages/jax/_src/dispatch.py:1014\u001b[0m, in \u001b[0;36mbackend_compile\u001b[0;34m(backend, built_c, options, host_callbacks)\u001b[0m\n\u001b[1;32m   1009\u001b[0m   \u001b[38;5;28;01mreturn\u001b[39;00m backend\u001b[38;5;241m.\u001b[39mcompile(built_c, compile_options\u001b[38;5;241m=\u001b[39moptions,\n\u001b[1;32m   1010\u001b[0m                          host_callbacks\u001b[38;5;241m=\u001b[39mhost_callbacks)\n\u001b[1;32m   1011\u001b[0m \u001b[38;5;66;03m# Some backends don't have `host_callbacks` option yet\u001b[39;00m\n\u001b[1;32m   1012\u001b[0m \u001b[38;5;66;03m# TODO(sharadmv): remove this fallback when all backends allow `compile`\u001b[39;00m\n\u001b[1;32m   1013\u001b[0m \u001b[38;5;66;03m# to take in `host_callbacks`\u001b[39;00m\n\u001b[0;32m-> 1014\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mbackend\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcompile\u001b[49m\u001b[43m(\u001b[49m\u001b[43mbuilt_c\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcompile_options\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43moptions\u001b[49m\u001b[43m)\u001b[49m\n",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "\n",
    "\n",
    "INPUT_SHAPES = [training_x[i].shape[1] for i in np.arange(len(training_x))]\n",
    "\n",
    "OUTPUT_SHAPES = [1]\n",
    "\n",
    "meta_trial_number = str(int(np.random.random() * 10 ** 12))\n",
    "\n",
    "\n",
    "cerebros_automl = SimpleCerebrosRandomSearch(\n",
    "    unit_type=DenseUnit,\n",
    "    input_shapes=INPUT_SHAPES,\n",
    "    output_shapes=OUTPUT_SHAPES,\n",
    "    training_data=training_x,\n",
    "    labels=train_labels,\n",
    "    validation_split=0.35,\n",
    "    direction='maximize',\n",
    "    metric_to_rank_by=\"val_binary_accuracy\",\n",
    "    minimum_levels=2,\n",
    "    maximum_levels=maximum_levels,\n",
    "    minimum_units_per_level=1,\n",
    "    maximum_units_per_level=maximum_units_per_level,\n",
    "    minimum_neurons_per_unit=1,\n",
    "    maximum_neurons_per_unit=maximum_neurons_per_unit,\n",
    "    activation=activation,\n",
    "    final_activation='sigmoid',\n",
    "    number_of_architecture_moities_to_try=7,\n",
    "    number_of_tries_per_architecture_moity=1,\n",
    "    minimum_skip_connection_depth=1,\n",
    "    maximum_skip_connection_depth=7,\n",
    "    predecessor_level_connection_affinity_factor_first=predecessor_level_connection_affinity_factor_first,\n",
    "    predecessor_level_connection_affinity_factor_first_rounding_rule='ceil',\n",
    "    predecessor_level_connection_affinity_factor_main=predecessor_level_connection_affinity_factor_main,\n",
    "    predecessor_level_connection_affinity_factor_main_rounding_rule='ceil',\n",
    "    predecessor_level_connection_affinity_factor_decay_main=zero_7_exp_decay,\n",
    "    seed=8675309,\n",
    "    max_consecutive_lateral_connections=max_consecutive_lateral_connections,\n",
    "    gate_after_n_lateral_connections=3,\n",
    "    gate_activation_function=simple_sigmoid,\n",
    "    p_lateral_connection=p_lateral_connection,\n",
    "    p_lateral_connection_decay=zero_95_exp_decay,\n",
    "    num_lateral_connection_tries_per_unit=num_lateral_connection_tries_per_unit,\n",
    "    learning_rate=learning_rate,\n",
    "    loss=tf.keras.losses.BinaryCrossentropy(),\n",
    "    metrics=[tf.keras.metrics.BinaryAccuracy(),\n",
    "             tf.keras.metrics.Precision(),\n",
    "             tf.keras.metrics.Recall()],\n",
    "    epochs=epochs,\n",
    "    project_name=f\"{PROJECT_NAME}_meta_{meta_trial_number}\",\n",
    "    # use_multiprocessing_for_multiple_neural_networks=False,  # pull this param\n",
    "    model_graphs='model_graphs',\n",
    "    batch_size=batch_size,\n",
    "    meta_trial_number=meta_trial_number)\n",
    "val_binary_accuracy = cerebros_automl.run_random_search()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "tags": [
     "pipeline-metrics"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1\n"
     ]
    }
   ],
   "source": [
    "print(val_binary_accuracy)"
   ]
  }
 ],
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   "katib_metadata": {
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     "algorithmSettings": [
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       "value": "GP"
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     "goal": 1,
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      "parameterType": "categorical"
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   "katib_run": true,
   "pipeline_description": "Predicting whether a patient has diabetes.",
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