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inference using colab

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{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"colab": {
"provenance": [],
"gpuType": "T4"
},
"kernelspec": {
"name": "python3",
"display_name": "Python 3"
},
"language_info": {
"name": "python"
},
"accelerator": "GPU",
"gpuClass": "standard"
},
"cells": [
{
"cell_type": "markdown",
"source": [
"## 准备"
],
"metadata": {
"id": "qjTJUQsAHkrh"
}
},
{
"cell_type": "markdown",
"source": [
"运行`XrayGLM`，请选择GPU：\n",
"\n",
"`代码执行程序`->`更改运行时类型`->选择`GPU`->如果您是非会员你将不能在Colab中运行XrayGLM，如果您是Colab Pro用户请选择选择`A100`。"
],
"metadata": {
"id": "NGipWBjJG8Te"
}
},
{
"cell_type": "code",
"source": [
"!nvidia-smi"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "afequQCEIJjY",
"outputId": "7c5a2914-d12e-47b0-887e-5e29ea1b23e4"
},
"execution_count": 1,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Fri May 26 14:53:45 2023 \n",
"+-----------------------------------------------------------------------------+\n",
"| NVIDIA-SMI 525.85.12 Driver Version: 525.85.12 CUDA Version: 12.0 |\n",
"|-------------------------------+----------------------+----------------------+\n",
"| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |\n",
"| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |\n",
"| | | MIG M. |\n",
"|===============================+======================+======================|\n",
"| 0 Tesla T4 Off | 00000000:00:04.0 Off | 0 |\n",
"| N/A 36C P8 9W / 70W | 0MiB / 15360MiB | 0% Default |\n",
"| | | N/A |\n",
"+-------------------------------+----------------------+----------------------+\n",
" \n",
"+-----------------------------------------------------------------------------+\n",
"| Processes: |\n",
"| GPU GI CI PID Type Process name GPU Memory |\n",
"| ID ID Usage |\n",
"|=============================================================================|\n",
"| No running processes found |\n",
"+-----------------------------------------------------------------------------+\n"
]
}
]
},
{
"cell_type": "markdown",
"source": [
"## 克隆仓库"
],
"metadata": {
"id": "2l1xHYYvHiMb"
}
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "VC_rcAF9GxXy",
"outputId": "a48a6ab8-ef9f-4f5b-8892-a4b1eab0e0a0"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Cloning into 'XrayGLM'...\n",
"remote: Enumerating objects: 264, done.\u001b[K\n",
"remote: Counting objects: 100% (160/160), done.\u001b[K\n",
"remote: Compressing objects: 100% (102/102), done.\u001b[K\n",
"remote: Total 264 (delta 98), reused 104 (delta 55), pack-reused 104\u001b[K\n",
"Receiving objects: 100% (264/264), 8.95 MiB | 23.26 MiB/s, done.\n",
"Resolving deltas: 100% (105/105), done.\n"
]
}
],
"source": [
"!git clone https://github.com/WangRongsheng/XrayGLM.git"
]
},
{
"cell_type": "code",
"source": [
"%cd XrayGLM/"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "i7eNI-5pHqDi",
"outputId": "89f7955e-eff2-4d32-de96-4c0371f73b6a"
},
"execution_count": 3,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"/content/XrayGLM\n"
]
}
]
},
{
"cell_type": "markdown",
"source": [
"## 安装依赖"
],
"metadata": {
"id": "xFeQK3jGHySf"
}
},
{
"cell_type": "code",
"source": [
"!pip install -r requirements.txt"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "yP7Pb6bkHxbF",
"outputId": "db4d483c-e4c7-43fb-e27f-c85ca1c3e8a5"
},
"execution_count": 4,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
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" Building wheel for deepspeed (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
" Created wheel for deepspeed: filename=deepspeed-0.9.2-py3-none-any.whl size=811222 sha256=89c873a8ffd584d153855895a2077006b63f6fa644c57547bba5db5991dd7627\n",
" Stored in directory: /root/.cache/pip/wheels/a6/d2/b1/b15210b5dc024bab4eccbac2148db29959fe01fe6042557d07\n",
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" Stored in directory: /root/.cache/pip/wheels/0c/c2/0e/3b9c6845c6a4e35beb90910cc70d9ac9ab5d47402bd62af0df\n",
"Successfully built deepspeed ffmpy\n",
"Installing collected packages: tokenizers, sentencepiece, pydub, ninja, hjson, ffmpy, cpm-kernels, xxhash, websockets, uc-micro-py, tensorboardX, semantic-version, python-multipart, orjson, multidict, latex2mathml, h11, frozenlist, einops, dill, async-timeout, aiofiles, yarl, uvicorn, starlette, responses, multiprocess, mdtex2html, mdit-py-plugins, linkify-it-py, huggingface-hub, httpcore, aiosignal, transformers, httpx, fastapi, aiohttp, gradio-client, gradio, datasets, deepspeed, SwissArmyTransformer\n",
"Successfully installed SwissArmyTransformer-0.3.6 aiofiles-23.1.0 aiohttp-3.8.4 aiosignal-1.3.1 async-timeout-4.0.2 cpm-kernels-1.0.11 datasets-2.12.0 deepspeed-0.9.2 dill-0.3.6 einops-0.6.1 fastapi-0.95.2 ffmpy-0.3.0 frozenlist-1.3.3 gradio-3.32.0 gradio-client-0.2.5 h11-0.14.0 hjson-3.1.0 httpcore-0.17.2 httpx-0.24.1 huggingface-hub-0.14.1 latex2mathml-3.76.0 linkify-it-py-2.0.2 mdit-py-plugins-0.3.3 mdtex2html-1.2.0 multidict-6.0.4 multiprocess-0.70.14 ninja-1.11.1 orjson-3.8.14 pydub-0.25.1 python-multipart-0.0.6 responses-0.18.0 semantic-version-2.10.0 sentencepiece-0.1.99 starlette-0.27.0 tensorboardX-2.6 tokenizers-0.13.3 transformers-4.29.2 uc-micro-py-1.0.2 uvicorn-0.22.0 websockets-11.0.3 xxhash-3.2.0 yarl-1.9.2\n"
]
}
]
},
{
"cell_type": "markdown",
"source": [
"## 准备权重"
],
"metadata": {
"id": "KDx-WyWjMp1X"
}
},
{
"cell_type": "code",
"source": [
"%cd checkpoints/\n",
"!wget https://huggingface.co/wangrongsheng/XrayGLM-300/resolve/main/latest\n",
"!wget https://huggingface.co/wangrongsheng/XrayGLM-300/resolve/main/model_config.json\n",
"\n",
"!mkdir 300\n",
"%cd 300/\n",
"!wget https://huggingface.co/wangrongsheng/XrayGLM-300/resolve/main/300/mp_rank_00_model_states.pt\n",
"%cd .."
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "2bfV3mtPH24o",
"outputId": "02ca3948-5bc3-4c9c-87ba-3da3a49eeac8"
},
"execution_count": 5,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"/content/XrayGLM/checkpoints\n",
"--2023-05-26 14:55:00-- https://huggingface.co/wangrongsheng/XrayGLM-300/resolve/main/latest\n",
"Resolving huggingface.co (huggingface.co)... 99.84.191.118, 99.84.191.66, 99.84.191.42, ...\n",
"Connecting to huggingface.co (huggingface.co)|99.84.191.118|:443... connected.\n",
"HTTP request sent, awaiting response... 200 OK\n",
"Length: 3 [text/plain]\n",
"Saving to: ‘latest’\n",
"\n",
"\rlatest 0%[ ] 0 --.-KB/s \rlatest 100%[===================>] 3 --.-KB/s in 0s \n",
"\n",
"2023-05-26 14:55:00 (731 KB/s) - ‘latest’ saved [3/3]\n",
"\n",
"--2023-05-26 14:55:00-- https://huggingface.co/wangrongsheng/XrayGLM-300/resolve/main/model_config.json\n",
"Resolving huggingface.co (huggingface.co)... 99.84.191.118, 99.84.191.66, 99.84.191.42, ...\n",
"Connecting to huggingface.co (huggingface.co)|99.84.191.118|:443... connected.\n",
"HTTP request sent, awaiting response... 200 OK\n",
"Length: 1745 (1.7K) [text/plain]\n",
"Saving to: ‘model_config.json’\n",
"\n",
"model_config.json 100%[===================>] 1.70K --.-KB/s in 0s \n",
"\n",
"2023-05-26 14:55:00 (394 MB/s) - ‘model_config.json’ saved [1745/1745]\n",
"\n",
"/content/XrayGLM/checkpoints/300\n",
"--2023-05-26 14:55:00-- https://huggingface.co/wangrongsheng/XrayGLM-300/resolve/main/300/mp_rank_00_model_states.pt\n",
"Resolving huggingface.co (huggingface.co)... 99.84.191.118, 99.84.191.66, 99.84.191.42, ...\n",
"Connecting to huggingface.co (huggingface.co)|99.84.191.118|:443... connected.\n",
"HTTP request sent, awaiting response... 302 Found\n",
"Location: https://cdn-lfs.huggingface.co/repos/9c/1e/9c1e004e97461ba661c41154f31b5276e1fd0198e0c1b3b8d05ce1bd2097f010/07a39f495cfd8abe80c01e87bb5476823058df4e3a2fdbca21bcc38c52073f82?response-content-disposition=attachment%3B+filename*%3DUTF-8%27%27mp_rank_00_model_states.pt%3B+filename%3D%22mp_rank_00_model_states.pt%22%3B&Expires=1685372101&Policy=eyJTdGF0ZW1lbnQiOlt7IlJlc291cmNlIjoiaHR0cHM6Ly9jZG4tbGZzLmh1Z2dpbmdmYWNlLmNvL3JlcG9zLzljLzFlLzljMWUwMDRlOTc0NjFiYTY2MWM0MTE1NGYzMWI1Mjc2ZTFmZDAxOThlMGMxYjNiOGQwNWNlMWJkMjA5N2YwMTAvMDdhMzlmNDk1Y2ZkOGFiZTgwYzAxZTg3YmI1NDc2ODIzMDU4ZGY0ZTNhMmZkYmNhMjFiY2MzOGM1MjA3M2Y4Mj9yZXNwb25zZS1jb250ZW50LWRpc3Bvc2l0aW9uPSoiLCJDb25kaXRpb24iOnsiRGF0ZUxlc3NUaGFuIjp7IkFXUzpFcG9jaFRpbWUiOjE2ODUzNzIxMDF9fX1dfQ__&Signature=qtX2yPuGxGgkCvqIpT7zHKIaISvC6G7pOEfh9ihARwQ9Nitwrk8B8fZB77x3x732Jaf1DP8XrkdliXf0moA0LhCtyt5-6FSk%7ExitvvAC00pkGQ1tFj%7ET%7EGsyxgDivy3Iv2PtgQ8A-8RRDCucF8HOmxW-nbTnA4eTbVpGRaS-E5IJPwDcgoDEcN7nrMUOz24Pfg4UCPcjuFK0CxZBzwNnPTVXq6LIyHhV64xxCSMyz67EZWZBmE1qLQMr%7EayYuCLdeppdHlkbrRQt-TpXbpFpFAWumqk3Oo-CY4SF7KDB%7ECGPtbpyA8duy35iBleF0b%7ExU2eLaazC6QBwgNUt9Ivt-w__&Key-Pair-Id=KVTP0A1DKRTAX [following]\n",
"--2023-05-26 14:55:00-- https://cdn-lfs.huggingface.co/repos/9c/1e/9c1e004e97461ba661c41154f31b5276e1fd0198e0c1b3b8d05ce1bd2097f010/07a39f495cfd8abe80c01e87bb5476823058df4e3a2fdbca21bcc38c52073f82?response-content-disposition=attachment%3B+filename*%3DUTF-8%27%27mp_rank_00_model_states.pt%3B+filename%3D%22mp_rank_00_model_states.pt%22%3B&Expires=1685372101&Policy=eyJTdGF0ZW1lbnQiOlt7IlJlc291cmNlIjoiaHR0cHM6Ly9jZG4tbGZzLmh1Z2dpbmdmYWNlLmNvL3JlcG9zLzljLzFlLzljMWUwMDRlOTc0NjFiYTY2MWM0MTE1NGYzMWI1Mjc2ZTFmZDAxOThlMGMxYjNiOGQwNWNlMWJkMjA5N2YwMTAvMDdhMzlmNDk1Y2ZkOGFiZTgwYzAxZTg3YmI1NDc2ODIzMDU4ZGY0ZTNhMmZkYmNhMjFiY2MzOGM1MjA3M2Y4Mj9yZXNwb25zZS1jb250ZW50LWRpc3Bvc2l0aW9uPSoiLCJDb25kaXRpb24iOnsiRGF0ZUxlc3NUaGFuIjp7IkFXUzpFcG9jaFRpbWUiOjE2ODUzNzIxMDF9fX1dfQ__&Signature=qtX2yPuGxGgkCvqIpT7zHKIaISvC6G7pOEfh9ihARwQ9Nitwrk8B8fZB77x3x732Jaf1DP8XrkdliXf0moA0LhCtyt5-6FSk%7ExitvvAC00pkGQ1tFj%7ET%7EGsyxgDivy3Iv2PtgQ8A-8RRDCucF8HOmxW-nbTnA4eTbVpGRaS-E5IJPwDcgoDEcN7nrMUOz24Pfg4UCPcjuFK0CxZBzwNnPTVXq6LIyHhV64xxCSMyz67EZWZBmE1qLQMr%7EayYuCLdeppdHlkbrRQt-TpXbpFpFAWumqk3Oo-CY4SF7KDB%7ECGPtbpyA8duy35iBleF0b%7ExU2eLaazC6QBwgNUt9Ivt-w__&Key-Pair-Id=KVTP0A1DKRTAX\n",
"Resolving cdn-lfs.huggingface.co (cdn-lfs.huggingface.co)... 108.138.64.49, 108.138.64.121, 108.138.64.111, ...\n",
"Connecting to cdn-lfs.huggingface.co (cdn-lfs.huggingface.co)|108.138.64.49|:443... connected.\n",
"HTTP request sent, awaiting response... 200 OK\n",
"Length: 15622949761 (15G) [binary/octet-stream]\n",
"Saving to: ‘mp_rank_00_model_states.pt’\n",
"\n",
"mp_rank_00_model_st 100%[===================>] 14.55G 58.6MB/s in 4m 10s \n",
"\n",
"2023-05-26 14:59:10 (59.6 MB/s) - ‘mp_rank_00_model_states.pt’ saved [15622949761/15622949761]\n",
"\n",
"/content/XrayGLM/checkpoints\n"
]
}
]
},
{
"cell_type": "markdown",
"source": [
"模型较大，耐心等待下载完成即可。"
],
"metadata": {
"id": "EymbuKwFMZKZ"
}
},
{
"cell_type": "code",
"source": [
"ls"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "Bqda_17JIRiw",
"outputId": "6f413890-95c8-48b6-c135-7cd41e6c5473"
},
"execution_count": 6,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"\u001b[0m\u001b[01;34m300\u001b[0m/ latest model_config.json README.md\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"%cd .."
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "pJZq1jLpMTZ6",
"outputId": "fe6106d8-e51a-4ff0-8284-cef133041121"
},
"execution_count": 7,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"/content/XrayGLM\n"
]
}
]
},
{
"cell_type": "markdown",
"source": [
"## 准备测试图"
],
"metadata": {
"id": "yStNQ5FZMs-_"
}
},
{
"cell_type": "code",
"source": [
"!wget https://github.com/WangRongsheng/XrayGLM/blob/main/data/Xray/2577_1.png"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "tWaunnTRMsNu",
"outputId": "c46d7dc3-2e3c-48f7-85f5-092f43a57018"
},
"execution_count": 8,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"--2023-05-26 14:59:30-- https://github.com/WangRongsheng/XrayGLM/blob/main/data/Xray/2577_1.png\n",
"Resolving github.com (github.com)... 140.82.114.4\n",
"Connecting to github.com (github.com)|140.82.114.4|:443... connected.\n",
"HTTP request sent, awaiting response... 200 OK\n",
"Length: unspecified [text/html]\n",
"Saving to: ‘2577_1.png’\n",
"\n",
"\r2577_1.png [<=> ] 0 --.-KB/s \r2577_1.png [ <=> ] 137.73K --.-KB/s in 0.009s \n",
"\n",
"2023-05-26 14:59:30 (14.5 MB/s) - ‘2577_1.png’ saved [141038]\n",
"\n"
]
}
]
},
{
"cell_type": "markdown",
"source": [
"## 运行XrayGLM"
],
"metadata": {
"id": "LlK7hlr1MyPm"
}
},
{
"cell_type": "code",
"source": [
"import os\n",
"os.environ['SAT_HOME'] = '/content/XrayGLM'"
],
"metadata": {
"id": "dfIIr7dKoaEG"
},
"execution_count": 26,
"outputs": []
},
{
"cell_type": "code",
"source": [
"!echo $SAT_HOME"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "15UYh3l-mbAg",
"outputId": "eb2ff6ae-2ab1-41a1-d67b-528d877fb2fc"
},
"execution_count": 27,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"/content/XrayGLM\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"!python cli_demo.py --from_pretrained checkpoints/ --prompt_zh '详细描述这张胸部X光片的诊断结果' --quant 8"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "OvBOxfB5Mm4D",
"outputId": "4e75b683-7cda-4322-a81d-f22429792eed"
},
"execution_count": 50,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"[2023-05-26 15:23:19,629] [INFO] building FineTuneVisualGLMModel model ...\n",
"56929\n",
"[2023-05-26 15:23:19,657] [INFO] [RANK 0] > initializing model parallel with size 1\n",
"[2023-05-26 15:23:19,659] [INFO] [RANK 0] You are using model-only mode.\n",
"For torch.distributed users or loading model parallel models, set environment variables RANK, WORLD_SIZE and LOCAL_RANK.\n",
"/usr/local/lib/python3.10/dist-packages/torch/nn/init.py:405: UserWarning: Initializing zero-element tensors is a no-op\n",
" warnings.warn(\"Initializing zero-element tensors is a no-op\")\n",
"[2023-05-26 15:23:35,330] [INFO] [RANK 0] > number of parameters on model parallel rank 0: 7811237376\n",
"[2023-05-26 15:23:37,980] [INFO] [RANK 0] global rank 0 is loading checkpoint checkpoints/300/mp_rank_00_model_states.pt\n",
"^C\n"
]
}
]
},
{
"cell_type": "code",
"source": [],
"metadata": {
"id": "Bt1RxhqdpFeR"
},
"execution_count": null,
"outputs": []
}
]
}
\ No newline at end of file
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