google-research

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{
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  "cells": [
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    {
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      "cell_type": "markdown",
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      "metadata": {
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        "colab_type": "text",
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        "id": "p9DgAr1jFJhp"
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      },
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      "source": [
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        "Copyright 2020 The Google Research Authors. All Rights Reserved.\n",
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        "Licensed under the Apache License, Version 2.0 (the \"License\"); you may not use this file except in compliance with the License. You may obtain a copy of the License at\n",
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        "\n",
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        "http://www.apache.org/licenses/LICENSE-2.0\n",
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        "\n",
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        "Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an \"AS IS\" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License."
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      ]
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    },
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    {
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      "cell_type": "markdown",
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      "metadata": {
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        "colab_type": "text",
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        "id": "B-Wnu7pjFl-N"
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      },
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      "source": [
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        "**NOTE: Executing the code (training or evaluation) for the first time will download the full CLEVR dataset (17.7GB).**"
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      ]
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    },
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    {
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      "cell_type": "code",
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      "execution_count": null,
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      "metadata": {
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        "colab": {},
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        "colab_type": "code",
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        "id": "T0AC86o61DIT"
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      },
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      "outputs": [],
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      "source": [
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        "# Requirements: Python 3.x, TensorFlow 2.x, TensorFlow Datasets\n",
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        "\n",
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        "from absl import logging\n",
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        "import tensorflow as tf\n",
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        "import tensorflow_datasets as tfds\n",
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        "import matplotlib.pyplot as plt\n",
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        "\n",
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        "# When executing this notebook out of a subfolder, use the command below to\n",
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        "# change to the project's root folder (required for imports):\n",
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        "# %cd ..\n",
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        "\n",
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        "import slot_attention.data as data_utils\n",
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        "import slot_attention.model as model_utils"
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      ]
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    },
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    {
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      "cell_type": "code",
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      "execution_count": null,
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      "metadata": {
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        "colab": {},
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        "colab_type": "code",
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        "id": "ES0x4gql8Mig"
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      },
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      "outputs": [],
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      "source": [
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        "# Hyperparameters.\n",
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        "seed = 0\n",
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        "batch_size = 1\n",
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        "num_slots = 7\n",
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        "num_iterations = 3\n",
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        "resolution = (128, 128)\n",
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        "ckpt_path = \"/tmp/object_discovery/\"  # Path to model checkpoint."
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      ]
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    },
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    {
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      "cell_type": "code",
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      "execution_count": null,
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      "metadata": {
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        "colab": {},
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        "colab_type": "code",
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        "id": "G60O3E3B_c-e"
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      },
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      "outputs": [],
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      "source": [
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        "def load_model(checkpoint_dir, num_slots=11, num_iters=3, batch_size=16):\n",
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        "  resolution = (128, 128)\n",
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        "  model = model_utils.build_model(\n",
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        "      resolution, batch_size, num_slots, num_iters,\n",
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        "      model_type=\"object_discovery\")\n",
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        "\n",
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        "  ckpt = tf.train.Checkpoint(network=model)\n",
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        "  ckpt_manager = tf.train.CheckpointManager(\n",
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        "      ckpt, directory=checkpoint_dir, max_to_keep=5)\n",
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        "\n",
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        "  if ckpt_manager.latest_checkpoint:\n",
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        "    ckpt.restore(ckpt_manager.latest_checkpoint)\n",
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        "    logging.info(\"Restored from %s\", ckpt_manager.latest_checkpoint)\n",
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        "\n",
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        "  return model"
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      ]
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    },
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    {
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      "cell_type": "code",
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      "execution_count": null,
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      "metadata": {
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        "colab": {},
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        "colab_type": "code",
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        "id": "XrWNKCSq59Qn"
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      },
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      "outputs": [],
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      "source": [
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        "# Build dataset iterators, optimizers and model.\n",
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        "tf.random.set_seed(seed)\n",
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        "data_iterator = data_utils.build_clevr_iterator(\n",
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        "    batch_size, split=\"validation\", resolution=resolution, shuffle=True,\n",
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        "    max_n_objects=6, get_properties=False, apply_crop=True)\n",
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        "\n",
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        "model = load_model(ckpt_path, num_slots=num_slots, num_iters=num_iterations,\n",
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        "                   batch_size=batch_size)"
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      ]
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    },
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    {
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      "cell_type": "code",
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      "execution_count": null,
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      "metadata": {
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        "colab": {},
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        "colab_type": "code",
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        "id": "mcqHuS9pjvzY"
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      },
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      "outputs": [],
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      "source": [
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        "def renormalize(x):\n",
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        "  \"\"\"Renormalize from [-1, 1] to [0, 1].\"\"\"\n",
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        "  return x / 2. + 0.5\n",
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        "\n",
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        "def get_prediction(model, batch, idx=0):\n",
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        "  recon_combined, recons, masks, slots = model(batch[\"image\"])\n",
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        "  image = renormalize(batch[\"image\"])[idx]\n",
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        "  recon_combined = renormalize(recon_combined)[idx]\n",
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        "  recons = renormalize(recons)[idx]\n",
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        "  masks = masks[idx]\n",
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        "  return image, recon_combined, recons, masks, slots"
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      ]
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    },
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    {
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      "cell_type": "code",
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      "execution_count": null,
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      "metadata": {
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        "colab": {},
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        "colab_type": "code",
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        "id": "Bddz5KwJIRac"
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      },
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      "outputs": [],
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      "source": [
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        "# Get new batch.\n",
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        "batch = next(data_iterator)"
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      ]
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    },
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    {
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      "cell_type": "code",
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      "execution_count": null,
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      "metadata": {
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        "colab": {},
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        "colab_type": "code",
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        "id": "vLKytvW0mrbz"
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      },
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      "outputs": [],
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      "source": [
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        "# Predict.\n",
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        "image, recon_combined, recons, masks, slots = get_prediction(model, batch)"
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      ]
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    },
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    {
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      "cell_type": "code",
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      "execution_count": null,
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      "metadata": {
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        "colab": {
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          "height": 143
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        },
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        "colab_type": "code",
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        "id": "Lcsylkf_3FQM",
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        "outputId": "f196c2fe-3e1d-4165-c5a0-35d2947430f8"
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      },
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      "outputs": [
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        {
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          "data": {
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73ArCd94SSSkHyoEHthP5qGzC4BJQDggaONmDNwlK8KlvCFNEVhICXG0kVGMQ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\nIYQQQgjZMP8Dg/hHHduYdYoAAAAASUVORK5CYII=\n",
185
            "text/plain": [
186
              "\u003cFigure size 1500x200 with 9 Axes\u003e"
187
            ]
188
          },
189
          "metadata": {
190
            "tags": []
191
          },
192
          "output_type": "display_data"
193
        }
194
      ],
195
      "source": [
196
        "# Visualize.\n",
197
        "num_slots = len(masks)\n",
198
        "fig, ax = plt.subplots(1, num_slots + 2, figsize=(15, 2))\n",
199
        "ax[0].imshow(image)\n",
200
        "ax[0].set_title('Image')\n",
201
        "ax[1].imshow(recon_combined)\n",
202
        "ax[1].set_title('Recon.')\n",
203
        "for i in range(num_slots):\n",
204
        "  ax[i + 2].imshow(recons[i] * masks[i] + (1 - masks[i]))\n",
205
        "  ax[i + 2].set_title('Slot %s' % str(i + 1))\n",
206
        "for i in range(len(ax)):\n",
207
        "  ax[i].grid(False)\n",
208
        "  ax[i].axis('off')"
209
      ]
210
    }
211
  ],
212
  "metadata": {
213
    "colab": {
214
      "collapsed_sections": [],
215
      "name": "eval.ipynb",
216
      "provenance": []
217
    },
218
    "kernelspec": {
219
      "display_name": "Python 3",
220
      "name": "python3"
221
    }
222
  },
223
  "nbformat": 4,
224
  "nbformat_minor": 0
225
}
226

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