operate.ipynb

{
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   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[nltk_data] Downloading package averaged_perceptron_tagger to\n",
      "[nltk_data]     /Users/melkor/nltk_data...\n",
      "[nltk_data]   Package averaged_perceptron_tagger is already up-to-\n",
      "[nltk_data]       date!\n",
      "[Taichi] version 1.7.0, llvm 15.0.7, commit 7b58b0ff, osx, python 3.9.13\n",
      "start the image domain training session.\n"
     ]
    }
   ],
   "source": [
    "!/Users/melkor/miniforge3/envs/Melkor/bin/python AutoLearner/main.py --name=\"VKY\" \\\n",
    " --dataset=\"Sprites\" --domain=\"sprites\" --perception=\"valkyr\" --training_mode=\"query\" --batch_size=2 --lr=0.0002 \n",
    " "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "--checkpoint_dir=\"SceneGraphLearner/checkpoints/sprites_temp.ckpt\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[nltk_data] Downloading package averaged_perceptron_tagger to\n",
      "[nltk_data]     /Users/melkor/nltk_data...\n",
      "[nltk_data]   Package averaged_perceptron_tagger is already up-to-\n",
      "[nltk_data]       date!\n",
      "[Taichi] version 1.7.0, llvm 15.0.7, commit 7b58b0ff, osx, python 3.9.13\n",
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      "Figure(640x480)\n",
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      "Figure(640x480)\n",
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      "Figure(640x480)\n",
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      "Figure(640x480)\n",
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      "Figure(640x480)\n",
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      "Figure(640x480)\n",
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      "Figure(640x480)\n",
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      "Figure(640x480)\n",
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      "Figure(640x480)\n",
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      "Figure(640x480)\n",
      "p: tensor(0.9431, grad_fn=<SigmoidBackward0>)\n",
      "Figure(640x480)\n",
      "p: tensor(0.9502, grad_fn=<SigmoidBackward0>)\n",
      "Figure(640x480)\n",
      "p: tensor(0.9564, grad_fn=<SigmoidBackward0>)\n",
      "Figure(640x480)\n",
      "p: tensor(0.9620, grad_fn=<SigmoidBackward0>)\n",
      "Figure(640x480)\n",
      "p: tensor(0.9669, grad_fn=<SigmoidBackward0>)\n",
      "Figure(640x480)\n",
      "p: tensor(0.9713, grad_fn=<SigmoidBackward0>)\n",
      "Figure(640x480)\n",
      "p: tensor(0.9751, grad_fn=<SigmoidBackward0>)\n",
      "Figure(640x480)\n",
      "p: tensor(0.9785, grad_fn=<SigmoidBackward0>)\n",
      "Figure(640x480)\n",
      "p: tensor(0.9815, grad_fn=<SigmoidBackward0>)\n",
      "Figure(640x480)\n",
      "p: tensor(0.9841, grad_fn=<SigmoidBackward0>)\n",
      "Figure(640x480)\n",
      "p: tensor(0.9863, grad_fn=<SigmoidBackward0>)\n",
      "Figure(640x480)\n",
      "p: tensor(0.9883, grad_fn=<SigmoidBackward0>)\n",
      "Figure(640x480)\n",
      "p: tensor(0.9900, grad_fn=<SigmoidBackward0>)\n",
      "Figure(640x480)\n",
      "p: tensor(0.9915, grad_fn=<SigmoidBackward0>)\n",
      "Figure(640x480)\n",
      "p: tensor(0.9928, grad_fn=<SigmoidBackward0>)\n",
      "Figure(640x480)\n",
      "^C\n",
      "Traceback (most recent call last):\n",
      "  File \"/Users/melkor/Documents/GitHub/AutoLearner/AutoLearner/demo.py\", line 108, in <module>\n",
      "    plt.pause(0.01)\n",
      "  File \"/Users/melkor/miniforge3/envs/Melkor/lib/python3.9/site-packages/matplotlib/pyplot.py\", line 581, in pause\n",
      "    canvas.start_event_loop(interval)\n",
      "  File \"/Users/melkor/miniforge3/envs/Melkor/lib/python3.9/site-packages/matplotlib/backend_bases.py\", line 2549, in start_event_loop\n",
      "    time.sleep(timestep)\n",
      "KeyboardInterrupt\n"
     ]
    }
   ],
   "source": [
    "!/Users/melkor/miniforge3/envs/Melkor/bin/python \\\n",
    "    AutoLearner/demo.py --concept_type=\"cone\""
   ]
  }
 ],
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