Update demo NB to match audioLM v0.23.2

   "source": [

    "# !pip install audiolm-pytorch boto3 tensorboardX\n",

    "!pip install boto3 tensorboardX\n",

    "!pip install audiolm-pytorch==0.11.1\n",

    "!pip install audiolm-pytorch\n",

    "# !pip uninstall -y audiolm-pytorch\n",

    "raise AssertionError(\"don't forget to put in your patched version of audiolm and aws credentials!\")\n",

    "# raise AssertionError(\"don't forget to put in your patched version of audiolm and aws credentials!\")\n",

    "# tensorboardX required for lambda labs"

   ]

  },

    }

   ],

   "source": [

    "soundstream = SoundStream(\n",

    "from audiolm_pytorch import AudioLMSoundStream\n",

    "\n",

    "soundstream = AudioLMSoundStream(\n",

    "    codebook_size = 1024,\n",

    "    rq_num_quantizers = 8,\n",

    "    attn_window_size = 128,       # local attention receptive field at bottleneck\n",

    "    attn_depth = 2                # 2 local attention transformer blocks - the soundstream folks were not experts with attention, so i took the liberty to add some. encodec went with lstms, but attention should be better\n",

    ")\n",

    "\n",

    "actual_num_train_steps = 20001\n",

    "    lr=3e-4,\n",

    "    batch_size = 4,\n",

    "    grad_accum_every = 8, # effective batch size of batch_size * grad_accum_every = 32\n",

    "    data_max_length = 16000,\n",

    "    data_max_length_seconds = 2,  # train on 2 second audio\n",

    "    results_folder = \"soundstream_results\",\n",

    "    save_results_every = save_every,\n",

    "    save_model_every = save_every,\n",