From 2cf6e7a07967f063775b53f7e49d54bbe11e2e6a Mon Sep 17 00:00:00 2001 From: Varuna Jayasiri Date: Thu, 14 Jan 2021 10:18:27 +0530 Subject: [PATCH] colab notebook --- labml_nn/transformers/gpt/__init__.py | 5 + labml_nn/transformers/gpt/experiment.ipynb | 624 +++++++++++++++++++++ 2 files changed, 629 insertions(+) create mode 100644 labml_nn/transformers/gpt/experiment.ipynb diff --git a/labml_nn/transformers/gpt/__init__.py b/labml_nn/transformers/gpt/__init__.py index 4bef688b..ade65bac 100644 --- a/labml_nn/transformers/gpt/__init__.py +++ b/labml_nn/transformers/gpt/__init__.py @@ -24,6 +24,11 @@ Main differences of this to a standard autoregressive transformer are the parameter initialization, weight decay, and learning rate schedule. For the transformer we reuse the [existing labml/nn transformer implementation](https://lab-ml.com/labml_nn/transformers/). + +Here's a notebook for training a GPT mode on Tiny Shakespeare dataset. + +[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/lab-ml/nn/blob/master/labml_nn/transformers/gpt/experiment.ipynb) +[![View Run](https://img.shields.io/badge/labml-experiment-brightgreen)](https://web.lab-ml.com/run?uuid=0324c6d0562111eba65d0242ac1c0002) """ import torch diff --git a/labml_nn/transformers/gpt/experiment.ipynb b/labml_nn/transformers/gpt/experiment.ipynb new file mode 100644 index 00000000..459aa10d --- /dev/null +++ b/labml_nn/transformers/gpt/experiment.ipynb @@ -0,0 +1,624 @@ +{ + "nbformat": 4, + "nbformat_minor": 0, + "metadata": { + "colab": { + "name": "GPT", + "provenance": [], + "collapsed_sections": [] + }, + "kernelspec": { + "name": "python3", + "display_name": "Python 3" + }, + "accelerator": "GPU" + }, + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "AYV_dMVDxyc2" + }, + "source": [ + "[![Github](https://img.shields.io/github/stars/lab-ml/nn?style=social)](https://github.com/lab-ml/nn)\n", + "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/lab-ml/nn/blob/master/labml_nn/transformers/gpt/experiment.ipynb) \n", + "\n", + "## Training a model with GPT architecture\n", + "\n", + "This is an experiment training Tiny Shakespeare dataset with GPT architecture model." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "AahG_i2y5tY9" + }, + "source": [ + "Install the `labml-nn` package" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "ZCzmCrAIVg0L", + "colab": { + "base_uri": "https://localhost:8080/" + }, + "outputId": "9c544df4-3fc7-4152-b50d-07919dbfb9de" + }, + "source": [ + "!pip install labml-nn" + ], + "execution_count": 1, + "outputs": [ + { + "output_type": "stream", + "text": [ + "Collecting labml-nn\n", + "\u001b[?25l Downloading https://files.pythonhosted.org/packages/f5/92/c454c38d613449e9cfee59809b83589bfc5463ebcf39a72126c268e31a77/labml_nn-0.4.78-py3-none-any.whl (111kB)\n", + "\u001b[K |████████████████████████████████| 112kB 8.4MB/s \n", + "\u001b[?25hCollecting labml>=0.4.86\n", + "\u001b[?25l Downloading https://files.pythonhosted.org/packages/a7/d3/f8708934e0062e6403faa2a36d97e1677097740c94f90fd7c04ea986d7cf/labml-0.4.89-py3-none-any.whl (97kB)\n", + "\u001b[K |████████████████████████████████| 102kB 6.1MB/s \n", + "\u001b[?25hRequirement already satisfied: numpy in /usr/local/lib/python3.6/dist-packages (from labml-nn) (1.19.5)\n", + "Requirement already satisfied: torch in /usr/local/lib/python3.6/dist-packages (from labml-nn) (1.7.0+cu101)\n", + "Collecting einops\n", + " Downloading https://files.pythonhosted.org/packages/5d/a0/9935e030634bf60ecd572c775f64ace82ceddf2f504a5fd3902438f07090/einops-0.3.0-py2.py3-none-any.whl\n", + "Collecting labml-helpers>=0.4.72\n", + " Downloading https://files.pythonhosted.org/packages/ec/58/2b7dcfde4565134ad97cdfe96ad7070fef95c37be2cbc066b608c9ae5c1d/labml_helpers-0.4.72-py3-none-any.whl\n", + "Collecting pyyaml>=5.3.1\n", + "\u001b[?25l Downloading https://files.pythonhosted.org/packages/64/c2/b80047c7ac2478f9501676c988a5411ed5572f35d1beff9cae07d321512c/PyYAML-5.3.1.tar.gz (269kB)\n", + "\u001b[K |████████████████████████████████| 276kB 11.7MB/s \n", + "\u001b[?25hCollecting gitpython\n", + "\u001b[?25l Downloading https://files.pythonhosted.org/packages/d7/cb/ec98155c501b68dcb11314c7992cd3df6dce193fd763084338a117967d53/GitPython-3.1.12-py3-none-any.whl (159kB)\n", + "\u001b[K |████████████████████████████████| 163kB 13.8MB/s \n", + "\u001b[?25hRequirement already satisfied: typing-extensions in /usr/local/lib/python3.6/dist-packages (from torch->labml-nn) (3.7.4.3)\n", + "Requirement already satisfied: dataclasses in /usr/local/lib/python3.6/dist-packages (from torch->labml-nn) (0.8)\n", + "Requirement already satisfied: future in /usr/local/lib/python3.6/dist-packages (from torch->labml-nn) (0.16.0)\n", + "Collecting gitdb<5,>=4.0.1\n", + "\u001b[?25l Downloading https://files.pythonhosted.org/packages/48/11/d1800bca0a3bae820b84b7d813ad1eff15a48a64caea9c823fc8c1b119e8/gitdb-4.0.5-py3-none-any.whl (63kB)\n", + "\u001b[K |████████████████████████████████| 71kB 8.7MB/s \n", + "\u001b[?25hCollecting smmap<4,>=3.0.1\n", + " Downloading https://files.pythonhosted.org/packages/b0/9a/4d409a6234eb940e6a78dfdfc66156e7522262f5f2fecca07dc55915952d/smmap-3.0.4-py2.py3-none-any.whl\n", + "Building wheels for collected packages: pyyaml\n", + " Building wheel for pyyaml (setup.py) ... \u001b[?25l\u001b[?25hdone\n", + " Created wheel for pyyaml: filename=PyYAML-5.3.1-cp36-cp36m-linux_x86_64.whl size=44621 sha256=8a5f1cee9425b47a5677f6229a8cdaea31a4c0c52473052981369bc0f865efe2\n", + " Stored in directory: /root/.cache/pip/wheels/a7/c1/ea/cf5bd31012e735dc1dfea3131a2d5eae7978b251083d6247bd\n", + "Successfully built pyyaml\n", + "Installing collected packages: pyyaml, smmap, gitdb, gitpython, labml, einops, labml-helpers, labml-nn\n", + " Found existing installation: PyYAML 3.13\n", + " Uninstalling PyYAML-3.13:\n", + " Successfully uninstalled PyYAML-3.13\n", + "Successfully installed einops-0.3.0 gitdb-4.0.5 gitpython-3.1.12 labml-0.4.89 labml-helpers-0.4.72 labml-nn-0.4.78 pyyaml-5.3.1 smmap-3.0.4\n" + ], + "name": "stdout" + } + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "SE2VUQ6L5zxI" + }, + "source": [ + "Imports" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "0hJXx_g0wS2C" + }, + "source": [ + "import torch\n", + "import torch.nn as nn\n", + "\n", + "from labml import experiment\n", + "from labml.configs import option\n", + "from labml_helpers.module import Module\n", + "from labml_nn.transformers.gpt import Configs" + ], + "execution_count": 2, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "Lpggo0wM6qb-" + }, + "source": [ + "Create an experiment" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "bFcr9k-l4cAg" + }, + "source": [ + "experiment.create(name=\"gpt\")" + ], + "execution_count": 3, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "-OnHLi626tJt" + }, + "source": [ + "Initialize [GPT configurations](https://lab-ml.com/labml_nn/transformers/gpt/)" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "Piz0c5f44hRo" + }, + "source": [ + "conf = Configs()" + ], + "execution_count": 4, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "wwMzCqpD6vkL" + }, + "source": [ + "Set experiment configurations and assign a configurations dictionary to override configurations" + ] + }, + { + "cell_type": "code", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 17 + }, + "id": "e6hmQhTw4nks", + "outputId": "018b39d7-7d84-4651-8b33-80de77d58ace" + }, + "source": [ + "experiment.configs(conf, {\n", + " # Use character level tokenizer\n", + " 'tokenizer': 'character',\n", + " # Prompt separator is blank\n", + " 'prompt_separator': '',\n", + " # Starting prompt for sampling\n", + " 'prompt': 'It is ',\n", + " # Use Tiny Shakespeare dataset\n", + " 'text': 'tiny_shakespeare',\n", + "\n", + " # Use a context size of $128$\n", + " 'seq_len': 128,\n", + " # Train for $32$ epochs\n", + " 'epochs': 32,\n", + " # Batch size $128$\n", + " 'batch_size': 128,\n", + " # Switch between training and validation for $10$ times\n", + " # per epoch\n", + " 'inner_iterations': 10,\n", + "\n", + " # Transformer configurations\n", + " 'transformer.d_model': 512,\n", + " 'transformer.d_ff': 2048,\n", + " 'transformer.n_heads': 8,\n", + " 'transformer.n_layers': 6\n", + "})" + ], + "execution_count": 5, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/html": [ + "
"
+            ],
+            "text/plain": [
+              ""
+            ]
+          },
+          "metadata": {
+            "tags": []
+          }
+        }
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "EvI7MtgJ61w5"
+      },
+      "source": [
+        "Set PyTorch models for loading and saving"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 459
+        },
+        "id": "GDlt7dp-5ALt",
+        "outputId": "e7768185-4a3c-4fec-f688-73c0463db015"
+      },
+      "source": [
+        "experiment.add_pytorch_models({'model': conf.model})"
+      ],
+      "execution_count": 6,
+      "outputs": [
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/html": [
+              "
Prepare model...\n",
+              "  Prepare transformer...\n",
+              "    Prepare n_tokens...\n",
+              "      Prepare text...\n",
+              "        Prepare tokenizer...[DONE]\t4.91ms\n",
+              "        Download...[DONE]\t261.22ms\n",
+              "        Load data...[DONE]\t7.26ms\n",
+              "        Tokenize...[DONE]\t27.96ms\n",
+              "        Build vocabulary...[DONE]\t137.31ms\n",
+              "      Prepare text...[DONE]\t458.67ms\n",
+              "    Prepare n_tokens...[DONE]\t465.05ms\n",
+              "  Prepare transformer...[DONE]\t472.81ms\n",
+              "  Prepare encoder...\n",
+              "    Prepare encoder_layer...\n",
+              "      Prepare encoder_attn...[DONE]\t46.65ms\n",
+              "      Prepare feed_forward...\n",
+              "        Prepare feed_forward_activation...[DONE]\t4.62ms\n",
+              "      Prepare feed_forward...[DONE]\t25.12ms\n",
+              "    Prepare encoder_layer...[DONE]\t115.91ms\n",
+              "  Prepare encoder...[DONE]\t165.88ms\n",
+              "  Prepare src_embed...[DONE]\t76.85ms\n",
+              "  Prepare generator...[DONE]\t3.92ms\n",
+              "  Prepare device...\n",
+              "    Prepare device_info...[DONE]\t63.02ms\n",
+              "  Prepare device...[DONE]\t66.20ms\n",
+              "Prepare model...[DONE]\t11,075.54ms\n",
+              "
"
+            ],
+            "text/plain": [
+              ""
+            ]
+          },
+          "metadata": {
+            "tags": []
+          }
+        }
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "KJZRf8527GxL"
+      },
+      "source": [
+        "Start the experiment and run the training loop."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 1000
+        },
+        "id": "aIAWo7Fw5DR8",
+        "outputId": "d4ca5ae0-6a97-439e-a318-010cb3f288cd"
+      },
+      "source": [
+        "# Start the experiment\n",
+        "with experiment.start():\n",
+        "    conf.run()"
+      ],
+      "execution_count": 7,
+      "outputs": [
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/html": [
+              "
\n",
+              "gpt: 0324c6d0562111eba65d0242ac1c0002\n",
+              "\t[dirty]: \"\"\n",
+              "Initialize...\n",
+              "  Prepare mode...[DONE]\t2.91ms\n",
+              "Initialize...[DONE]\t105.13ms\n",
+              "Prepare validator...\n",
+              "  Prepare valid_loader...[DONE]\t112.67ms\n",
+              "Prepare validator...[DONE]\t259.72ms\n",
+              "\n",
+              "--------------------------------------------------\n",
+              "LABML WARNING\n",
+              "LabML App Warning: empty_token: Please create a valid token at https://web.lab-ml.com.\n",
+              "Click on the experiment link to monitor the experiment and add it to your experiments list.\n",
+              "--------------------------------------------------\n",
+              "Monitor experiment at https://web.lab-ml.com/run?uuid=0324c6d0562111eba65d0242ac1c0002\n",
+              "\n",
+              "  Prepare train_loader...[DONE]\t105.04ms\n",
+              "Prepare trainer...[DONE]\t207.61ms\n",
+              "Prepare training_loop...\n",
+              "  Prepare loop_count...[DONE]\t51.30ms\n",
+              "Prepare training_loop...[DONE]\t374.91ms\n",
+              "It is LmBsuuwsdtUUQUHHHs\n",
+              "\n",
+              "\n",
+              "BsYh\n",
+              "It is s s an s t a a a s t the \n",
+              "It is t the t the t t t t t the\n",
+              "It is the the the the the t the\n",
+              "It is the the the the the the t\n",
+              "It is the the the the the the t\n",
+              "It is the the the the the the t\n",
+              "It is the the the the the the t\n",
+              "It is the the the the the the t\n",
+              "It is the and the and and the a\n",
+              "1,003,776:  Sample: 100%   303ms  Train: 100%  53,938ms  Valid: 100% 1,973ms   loss.train:  2.38163 accuracy.train: 0.250702 loss.valid:  2.36796 accuracy.valid: 0.269186  61,419ms  0:01m/  0:31m  \n",
+              "It is the an the the the the th\n",
+              "It is the the the the the the t\n",
+              "It is the the the the the the t\n",
+              "It is the the the the the the t\n",
+              "It is the the the the the the t\n",
+              "It is the the the the the the t\n",
+              "It is man the the the the the t\n",
+              "It is an the the the the the th\n",
+              "It is the the the the the the t\n",
+              "It is the the the the the the t\n",
+              "2,007,552:  Sample: 100%   320ms  Train: 100%  50,987ms  Valid: 100% 2,146ms   loss.train:  2.11509 accuracy.train: 0.343499 loss.valid:  2.17901 accuracy.valid: 0.343077  59,401ms  0:01m/  0:29m  \n",
+              "It is the to the the the the th\n",
+              "It is the to the the the the th\n",
+              "It is and the the the the the t\n",
+              "It is and the thee thee the the\n",
+              "It is and the the the the she s\n",
+              "It is the so the so dee the son\n",
+              "It is to the the with the and t\n",
+              "It is and the so sould the soul\n",
+              "It is and the the thee strees t\n",
+              "It is the the with so the with \n",
+              "3,011,328:  Sample: 100%   326ms  Train: 100%  51,276ms  Valid: 100% 2,203ms   loss.train:  1.86443 accuracy.train: 0.415378 loss.valid:  1.99342 accuracy.valid: 0.396061  58,651ms  0:02m/  0:28m  \n",
+              "It is the the would the with th\n",
+              "It is the shall so thee the sha\n",
+              "It is the the the the the the t\n",
+              "It is the shall the the come th\n",
+              "It is the the his shall the sha\n",
+              "It is the sould the storrow the\n",
+              "It is the soul the word the so \n",
+              "It is the so so me to mee the s\n",
+              "It is the so the stay the shall\n",
+              "It is the so the so the so the \n",
+              "4,015,104:  Sample: 100%   341ms  Train: 100%  51,141ms  Valid: 100% 2,202ms   loss.train:  1.74658 accuracy.train: 0.464521 loss.valid:  1.86725 accuracy.valid: 0.433598  58,268ms  0:03m/  0:27m  \n",
+              "It is the so so he her heart th\n",
+              "It is the the counter the so th\n",
+              "It is the seep the word the wor\n",
+              "It is and the cannot to the can\n",
+              "It is a the shall the was the d\n",
+              "It is a say a say a so the soun\n",
+              "It is the shall the hands and t\n",
+              "It is the sounder the shall the\n",
+              "It is the shall be the dear to \n",
+              "It is a the come to the sould o\n",
+              "5,018,880:  Sample: 100%   351ms  Train: 100%  51,208ms  Valid: 100% 2,213ms   loss.train:  1.67815 accuracy.train: 0.499096 loss.valid:  1.76973 accuracy.valid: 0.463422  58,122ms  0:04m/  0:26m  \n",
+              "It is the have the be the have \n",
+              "It is the so so so him him him \n",
+              "It is the the send the will the\n",
+              "It is the soul to the the the c\n",
+              "It is the stand the come of the\n",
+              "It is the heart the so the see \n",
+              "It is the would the world the w\n",
+              "It is the served the service th\n",
+              "It is the shall the shout shalt\n",
+              "It is the should be so the for \n",
+              "6,022,656:  Sample: 100%   354ms  Train: 100%  50,986ms  Valid: 100% 2,220ms   loss.train:  1.54598 accuracy.train: 0.521924 loss.valid:  1.66606 accuracy.valid: 0.481630  57,965ms  0:05m/  0:25m  \n",
+              "It is the see the sent the to t\n",
+              "It is the her shall the world.\n",
+              "\n",
+              "It is a strain.\n",
+              "\n",
+              "COMINIUS:\n",
+              "I wi\n",
+              "It is the should the hand the b\n",
+              "It is the sent of the shall be \n",
+              "It is the sentery the stander t\n",
+              "It is the shall be the see the \n",
+              "It is not to the should be so s\n",
+              "It is the such a man the world \n",
+              "It is the shall be the shall be\n",
+              "7,026,432:  Sample: 100%   360ms  Train: 100%  51,237ms  Valid: 100% 2,235ms   loss.train:  1.46728 accuracy.train: 0.540290 loss.valid:  1.66135 accuracy.valid: 0.495802  57,923ms  0:06m/  0:24m  \n",
+              "It is not the son of the see th\n",
+              "It is then the should of the co\n",
+              "It is not the so so so my son\n",
+              "A\n",
+              "It is the world to the world of\n",
+              "It is the send the death of the\n",
+              "It is the present the to mad be\n",
+              "It is the send the to him the h\n",
+              "It is the profater of the sea s\n",
+              "It is not the shall be strike o\n",
+              "It is the some to the some of t\n",
+              "8,030,208:  Sample: 100%   371ms  Train: 100%  51,149ms  Valid: 100% 2,215ms   loss.train:  1.42535 accuracy.train: 0.554010 loss.valid:  1.63348 accuracy.valid: 0.507633  57,901ms  0:07m/  0:23m  \n",
+              "It is the come of the sons,\n",
+              "The\n",
+              "It is not the strike of the sou\n",
+              "It is not so so so make the see\n",
+              "It is not the stand of the stan\n",
+              "It is the so offend the seat of\n",
+              "It is the strike of the strike \n",
+              "It is the country the worling o\n",
+              "It is the strike a man and the \n",
+              "It is the strike a more of the \n",
+              "It is not the season of the way\n",
+              "9,033,984:  Sample: 100%   382ms  Train: 100%  51,031ms  Valid: 100% 2,218ms   loss.train:  1.39141 accuracy.train: 0.565689 loss.valid:  1.65321 accuracy.valid: 0.512145  57,884ms  0:08m/  0:22m  \n",
+              "It is not so may so more to sta\n",
+              "It is the soul be so man of the\n",
+              "It is not so so so so dead and \n",
+              "It is not so much a so so so so\n",
+              "It is the death of the comes an\n",
+              "It is the desire the death,\n",
+              "And\n",
+              "It is not so more that thou was\n",
+              "It is not so so much a some to \n",
+              "It is the son of the souls of t\n",
+              "It is not the senate of the cou\n",
+              "10,037,760:  Sample: 100%   394ms  Train: 100%  51,195ms  Valid: 100% 2,231ms   loss.train:  1.33575 accuracy.train: 0.575717 loss.valid:  1.61892 accuracy.valid: 0.519455  57,919ms  0:09m/  0:21m  \n",
+              "It is the fair of the season.\n",
+              "\n",
+              "\n",
+              "It is not the comple of the cou\n",
+              "It is not the senate of the cou\n",
+              "It is the straight and the worl\n",
+              "It is a man a more of that have\n",
+              "It is the man of my soul stand \n",
+              "It is the senators of the state\n",
+              "It is the content the seal of t\n",
+              "It is the content to the provok\n",
+              "It is the sense of the prince o\n",
+              "11,041,536:  Sample: 100%   402ms  Train: 100%  51,201ms  Valid: 100% 2,238ms   loss.train:  1.32079 accuracy.train: 0.585922 loss.valid:  1.54672 accuracy.valid: 0.521141  57,958ms  0:10m/  0:20m  \n",
+              "It is not to see him to him.\n",
+              "\n",
+              "L\n",
+              "It is not the consent to the co\n",
+              "It is the death of the day of t\n",
+              "It is the soon of the court of \n",
+              "It is the senators of the strea\n",
+              "It is the compless of the world\n",
+              "It is not the command of my sou\n",
+              "It is the senate of the state o\n",
+              "It is not a sorrraw to him.\n",
+              "\n",
+              "AU\n",
+              "It is not the sound of the cour\n",
+              "12,045,312:  Sample: 100%   418ms  Train: 100%  51,201ms  Valid: 100% 2,240ms   loss.train:  1.29904 accuracy.train: 0.594461 loss.valid:  1.58210 accuracy.valid: 0.524935  58,013ms  0:11m/  0:19m  \n",
+              "It is not so man is my soul sou\n",
+              "It is the strong and the straig\n",
+              "It is the world the field of th\n",
+              "It is the death of the state,\n",
+              "A\n",
+              "It is not the sorrow of the dea\n",
+              "It is the strange the sea of th\n",
+              "It is the present of the house \n",
+              "It is not the son of the should\n",
+              "It is the contract that he will\n",
+              "It is not the seas of the monta\n",
+              "13,049,088:  Sample: 100%   437ms  Train: 100%  51,117ms  Valid: 100% 2,237ms   loss.train:  1.26697 accuracy.train: 0.603765 loss.valid:  1.57502 accuracy.valid: 0.526765  58,092ms  0:12m/  0:18m  \n",
+              "It is not the man of the man of\n",
+              "It is not the stand of the cour\n",
+              "It is the prisoner of the head,\n",
+              "It is not the singled of his so\n",
+              "It is a man the heavens of the \n",
+              "It is not the stands of the sid\n",
+              "It is not the senators of the c\n",
+              "It is the sense that the presen\n",
+              "It is the dead of the court of \n",
+              "It is not the common of the com\n",
+              "14,052,864:  Sample: 100%   443ms  Train: 100%  51,152ms  Valid: 100% 2,223ms   loss.train:  1.21225 accuracy.train: 0.612812 loss.valid:  1.58159 accuracy.valid: 0.528407  58,138ms  0:13m/  0:17m  \n",
+              "It is not to the senate of the \n",
+              "It is not but the duke of death\n",
+              "It is not the stand of the stat\n",
+              "It is not the season of the par\n",
+              "It is not the langue of the fat\n",
+              "It is not a subject to the coul\n",
+              "It is not the duke of the death\n",
+              "It is not the side of the state\n",
+              "It is not the standed to the st\n",
+              "It is not the duke of the duke \n",
+              "15,056,640:  Sample: 100%   452ms  Train: 100%  51,115ms  Valid: 100% 2,240ms   loss.train:  1.22173 accuracy.train: 0.622129 loss.valid:  1.58946 accuracy.valid: 0.527285  58,204ms  0:14m/  0:16m  \n",
+              "It is not so sorrried to him ha\n",
+              "It is not a man of the prince o\n",
+              "It is not to the beloned and de\n",
+              "It is not the sorrow of my soul\n",
+              "It is the seated of the death a\n",
+              "It is not the sorrow of your ho\n",
+              "It is not the stand of my son,\n",
+              "\n",
+              "It is the sense of the deep of \n",
+              "It is not the soldiers of the h\n",
+              "It is the conqueror of the deat\n",
+              "16,060,416:  Sample: 100%   457ms  Train: 100%  51,418ms  Valid: 100% 2,239ms   loss.train:  1.17331 accuracy.train: 0.630410 loss.valid:  1.63163 accuracy.valid: 0.527393  58,299ms  0:15m/  0:15m  \n",
+              "It is the world and the sea of \n",
+              "It is not the court of the coll\n",
+              "It is not to the more of the fa\n",
+              "It is not the sore of the more \n",
+              "It is a sorrow in a last a grea\n",
+              "It is not the sun that have mad\n",
+              "It is not to see him to him to \n",
+              "It is not the sun of the deed i\n",
+              "It is the dead?\n",
+              "\n",
+              "DUKE OF YORK:\n",
+              "\n",
+              "It is not the soldiers of the c\n",
+              "17,064,192:  Sample: 100%   480ms  Train: 100%  51,259ms  Valid: 100% 2,239ms   loss.train:  1.16549 accuracy.train: 0.639204 loss.valid:  1.60157 accuracy.valid: 0.527572  58,395ms  0:16m/  0:14m  \n",
+              "It is the foot of all,\n",
+              "That I m\n",
+              "It is not the sea that the man \n",
+              "It is the deep and death death \n",
+              "It is not the sea,\n",
+              "That make th\n",
+              "It is not to be a power of the \n",
+              "17,522,944:  Sample: 100%   491ms  Train:  43%  52,020ms  Valid:  28% 2,205ms   loss.train:  1.12190 accuracy.train: 0.650947 loss.valid:  1.63582 accuracy.valid: 0.532135  58,395ms  0:16m/  0:14m  \n",
+              "Saving model...\n",
+              "Killing loop...\n",
+              "Still updating LabML App, please wait for it to complete...
"
+            ],
+            "text/plain": [
+              ""
+            ]
+          },
+          "metadata": {
+            "tags": []
+          }
+        },
+        {
+          "output_type": "error",
+          "ename": "KeyboardInterrupt",
+          "evalue": "ignored",
+          "traceback": [
+            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+            "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
+            "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;31m# Start the experiment\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0;32mwith\u001b[0m \u001b[0mexperiment\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstart\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m     \u001b[0mconf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrun\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
+            "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/labml_helpers/train_valid.py\u001b[0m in \u001b[0;36mrun\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    238\u001b[0m         \u001b[0m_\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtrainer\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    239\u001b[0m         \u001b[0;32mfor\u001b[0m \u001b[0m_\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtraining_loop\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 240\u001b[0;31m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrun_step\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    241\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    242\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0msample\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+            "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/labml_helpers/train_valid.py\u001b[0m in \u001b[0;36mrun_step\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    226\u001b[0m             \u001b[0;32mwith\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmode\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mupdate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mis_train\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    227\u001b[0m                 \u001b[0;32mwith\u001b[0m \u001b[0mtracker\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnamespace\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'train'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 228\u001b[0;31m                     \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtrainer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    229\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalidator\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    230\u001b[0m                 \u001b[0;32mwith\u001b[0m \u001b[0mtracker\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnamespace\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'valid'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+            "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/labml_helpers/train_valid.py\u001b[0m in \u001b[0;36m__call__\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    130\u001b[0m                 \u001b[0msm\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mon_epoch_start\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    131\u001b[0m         \u001b[0;32mwith\u001b[0m \u001b[0mtorch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mset_grad_enabled\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmode\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mis_train\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 132\u001b[0;31m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__iterate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    133\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    134\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_batch_index\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcompleted\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+            "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/labml_helpers/train_valid.py\u001b[0m in \u001b[0;36m__iterate\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    143\u001b[0m                 \u001b[0mbatch\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnext\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__iterable\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    144\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 145\u001b[0;31m                 \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstep\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mbatch\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_batch_index\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    146\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    147\u001b[0m                 \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_batch_index\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstep\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+            "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/labml_nn/experiments/nlp_autoregression.py\u001b[0m in \u001b[0;36mstep\u001b[0;34m(self, batch, batch_idx)\u001b[0m\n\u001b[1;32m    125\u001b[0m         \u001b[0;31m# Calculate and log loss\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    126\u001b[0m         \u001b[0mloss\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mloss_func\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0moutput\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtarget\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 127\u001b[0;31m         \u001b[0mtracker\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0madd\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"loss.\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mloss\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    128\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    129\u001b[0m         \u001b[0;31m# Calculate and log accuracy\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+            "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/labml/tracker.py\u001b[0m in \u001b[0;36madd\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m    131\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstr\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    132\u001b[0m             \u001b[0;32mraise\u001b[0m \u001b[0mTypeError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'tracker.add should be called as add(name, value), add(dictionary) or add(k=v,k2=v2...)'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 133\u001b[0;31m         \u001b[0m_internal\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstore\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0margs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    134\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    135\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
+            "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/labml/internal/tracker/__init__.py\u001b[0m in \u001b[0;36mstore\u001b[0;34m(self, key, value)\u001b[0m\n\u001b[1;32m    166\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    167\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_create_indicator\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 168\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mindicators\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcollect_value\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mvalue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    169\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    170\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mnew_line\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+            "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/labml/internal/tracker/indicators/numeric.py\u001b[0m in \u001b[0;36mcollect_value\u001b[0;34m(self, value)\u001b[0m\n\u001b[1;32m     79\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     80\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mcollect_value\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 81\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_values\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mto_numpy\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mvalue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mravel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     82\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     83\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mclear\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+            "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/labml/internal/util/values.py\u001b[0m in \u001b[0;36mto_numpy\u001b[0;34m(value)\u001b[0m\n\u001b[1;32m     20\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcpu\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnumpy\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     21\u001b[0m         \u001b[0;32melif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mvalue\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtorch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mTensor\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 22\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcpu\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnumpy\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     23\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     24\u001b[0m     \u001b[0;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34mf\"Unknown type {type(value)}\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+            "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/labml_helpers/training_loop.py\u001b[0m in \u001b[0;36m__handler\u001b[0;34m(self, sig, frame)\u001b[0m\n\u001b[1;32m    162\u001b[0m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__finish\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    163\u001b[0m             \u001b[0mlogger\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlog\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'Killing loop...'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mText\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdanger\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 164\u001b[0;31m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mold_handler\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msig\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mframe\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    165\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    166\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m__str__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+            "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
+          ]
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/html": [
+              "
Updating App. Please wait...
"
+            ],
+            "text/plain": [
+              ""
+            ]
+          },
+          "metadata": {
+            "tags": []
+          }
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "oBXXlP2b7XZO"
+      },
+      "source": [
+        ""
+      ],
+      "execution_count": null,
+      "outputs": []
+    }
+  ]
+}
\ No newline at end of file