File size: 4,721 Bytes
db8a108
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "machine_shape": "hm",
      "authorship_tag": "ABX9TyMmemQnx6G7GOnn6XBdjgxY",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "gpuClass": "standard",
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/sgoodfriend/rl-algo-impls/blob/main/colab_train.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# [sgoodfriend/rl-algo-impls](https://github.com/sgoodfriend/rl-algo-impls) in Google Colaboratory\n",
        "## Parameters\n",
        "\n",
        "\n",
        "1.   Wandb\n",
        "\n"
      ],
      "metadata": {
        "id": "S-tXDWP8WTLc"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from getpass import getpass\n",
        "import os\n",
        "os.environ[\"WANDB_API_KEY\"] = getpass(\"Wandb API key to upload metrics, videos, and models: \")"
      ],
      "metadata": {
        "id": "1ZtdYgxWNGwZ"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "2. train run parameters"
      ],
      "metadata": {
        "id": "ao0nAh3MOdN7"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "ALGO = \"ppo\"\n",
        "ENV = \"CartPole-v1\"\n",
        "SEED = 1"
      ],
      "metadata": {
        "id": "jKL_NFhVOjSc"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Setup\n",
        "Clone [sgoodfriend/rl-algo-impls](https://github.com/sgoodfriend/rl-algo-impls) "
      ],
      "metadata": {
        "id": "bsG35Io0hmKG"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "%%capture\n",
        "!git clone https://github.com/sgoodfriend/rl-algo-impls.git"
      ],
      "metadata": {
        "id": "k5ynTV25hdAf"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "Installing the correct packages:\n",
        "\n",
        "While conda and poetry are generally used for package management, the mismatch in Python versions (3.10 in the project file vs 3.8 in Colab) makes using the package yml files difficult to use. For now, instead I'm going to specify the list of requirements manually below:"
      ],
      "metadata": {
        "id": "jKxGok-ElYQ7"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "%%capture\n",
        "!apt install python-opengl\n",
        "!apt install ffmpeg\n",
        "!apt install xvfb\n",
        "!apt install swig"
      ],
      "metadata": {
        "id": "nn6EETTc2Ewf"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "%%capture\n",
        "%cd /content/rl-algo-impls\n",
        "python -m pip install ."
      ],
      "metadata": {
        "id": "AfZh9rH3yQii"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Run Once Per Runtime"
      ],
      "metadata": {
        "id": "4o5HOLjc4wq7"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import wandb\n",
        "wandb.login()"
      ],
      "metadata": {
        "id": "PCXa5tdS2qFX"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Restart Session beteween runs"
      ],
      "metadata": {
        "id": "AZBZfSUV43JQ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "%%capture\n",
        "from pyvirtualdisplay import Display\n",
        "\n",
        "virtual_display = Display(visible=0, size=(1400, 900))\n",
        "virtual_display.start()"
      ],
      "metadata": {
        "id": "VzemeQJP2NO9"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "%cd /content/rl-algo-impls\n",
        "!python train.py --algo {ALGO} --env {ENV} --seed {SEED}"
      ],
      "metadata": {
        "id": "07aHYFH1zfXa"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}