commit 43bedcd860ce829a9690011984e142fec8c152ca
parent b3723fd9f1d12dd441f6fa4267c1fbc6c33e5619
Author: Marcel <MTRNord@users.noreply.github.com>
Date: Fri, 10 Mar 2023 16:22:59 +0000
Trying to get gpu working in codespace
Diffstat:
2 files changed, 11 insertions(+), 6 deletions(-)
diff --git a/.devcontainer/devcontainer.json b/.devcontainer/devcontainer.json
@@ -1,5 +1,9 @@
{
"image": "mcr.microsoft.com/devcontainers/universal:2",
+ "runArgs": [
+ "--gpus",
+ "all"
+ ],
"hostRequirements": {
"cpus": 4
},
@@ -16,6 +20,7 @@
"features": {
"ghcr.io/devcontainers/features/nvidia-cuda:1": {
"installCudnn": true,
+ "installNvtx": true,
"cudaVersion": "11.7",
"cudnnVersion": "8.5.0.96"
}
diff --git a/model.ipynb b/model.ipynb
@@ -2,7 +2,7 @@
"cells": [
{
"cell_type": "code",
- "execution_count": 2,
+ "execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
@@ -13,7 +13,7 @@
},
{
"cell_type": "code",
- "execution_count": 3,
+ "execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
@@ -25,7 +25,7 @@
},
{
"cell_type": "code",
- "execution_count": 4,
+ "execution_count": 3,
"metadata": {},
"outputs": [
{
@@ -34,7 +34,7 @@
"(#4) [Path('/workspaces/spam-ml-mx-v2/.fastai/imdb/train/pos'),Path('/workspaces/spam-ml-mx-v2/.fastai/imdb/train/unsupBow.feat'),Path('/workspaces/spam-ml-mx-v2/.fastai/imdb/train/labeledBow.feat'),Path('/workspaces/spam-ml-mx-v2/.fastai/imdb/train/neg')]"
]
},
- "execution_count": 4,
+ "execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
@@ -46,7 +46,7 @@
},
{
"cell_type": "code",
- "execution_count": 5,
+ "execution_count": 4,
"metadata": {},
"outputs": [
{
@@ -63,7 +63,7 @@
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mRuntimeError\u001b[0m Traceback (most recent call last)",
- "Cell \u001b[0;32mIn[5], line 2\u001b[0m\n\u001b[1;32m 1\u001b[0m source \u001b[39m=\u001b[39m untar_data(URLs\u001b[39m.\u001b[39mIMDB, data\u001b[39m=\u001b[39mp)\n\u001b[0;32m----> 2\u001b[0m dls \u001b[39m=\u001b[39m TextDataLoaders\u001b[39m.\u001b[39;49mfrom_folder(source, valid\u001b[39m=\u001b[39;49m\u001b[39m\"\u001b[39;49m\u001b[39mtest\u001b[39;49m\u001b[39m\"\u001b[39;49m, bs\u001b[39m=\u001b[39;49m\u001b[39m64\u001b[39;49m,\n\u001b[1;32m 3\u001b[0m device\u001b[39m=\u001b[39;49mtorch\u001b[39m.\u001b[39;49mdevice(\u001b[39m'\u001b[39;49m\u001b[39mcuda\u001b[39;49m\u001b[39m'\u001b[39;49m))\n\u001b[1;32m 4\u001b[0m dls\u001b[39m.\u001b[39mshow_batch()\n",
+ "Cell \u001b[0;32mIn[4], line 2\u001b[0m\n\u001b[1;32m 1\u001b[0m source \u001b[39m=\u001b[39m untar_data(URLs\u001b[39m.\u001b[39mIMDB, data\u001b[39m=\u001b[39mp)\n\u001b[0;32m----> 2\u001b[0m dls \u001b[39m=\u001b[39m TextDataLoaders\u001b[39m.\u001b[39;49mfrom_folder(source, valid\u001b[39m=\u001b[39;49m\u001b[39m\"\u001b[39;49m\u001b[39mtest\u001b[39;49m\u001b[39m\"\u001b[39;49m, bs\u001b[39m=\u001b[39;49m\u001b[39m64\u001b[39;49m,\n\u001b[1;32m 3\u001b[0m device\u001b[39m=\u001b[39;49mtorch\u001b[39m.\u001b[39;49mdevice(\u001b[39m'\u001b[39;49m\u001b[39mcuda\u001b[39;49m\u001b[39m'\u001b[39;49m))\n\u001b[1;32m 4\u001b[0m dls\u001b[39m.\u001b[39mshow_batch()\n",
"File \u001b[0;32m~/.local/lib/python3.10/site-packages/fastai/text/data.py:262\u001b[0m, in \u001b[0;36mTextDataLoaders.from_folder\u001b[0;34m(cls, path, train, valid, valid_pct, seed, vocab, text_vocab, is_lm, tok_tfm, seq_len, splitter, backwards, **kwargs)\u001b[0m\n\u001b[1;32m 257\u001b[0m get_items \u001b[39m=\u001b[39m partial(get_text_files, folders\u001b[39m=\u001b[39m[train,valid]) \u001b[39mif\u001b[39;00m valid_pct \u001b[39mis\u001b[39;00m \u001b[39mNone\u001b[39;00m \u001b[39melse\u001b[39;00m get_text_files\n\u001b[1;32m 258\u001b[0m dblock \u001b[39m=\u001b[39m DataBlock(blocks\u001b[39m=\u001b[39mblocks,\n\u001b[1;32m 259\u001b[0m get_items\u001b[39m=\u001b[39mget_items,\n\u001b[1;32m 260\u001b[0m splitter\u001b[39m=\u001b[39msplitter,\n\u001b[1;32m 261\u001b[0m get_y\u001b[39m=\u001b[39m\u001b[39mNone\u001b[39;00m \u001b[39mif\u001b[39;00m is_lm \u001b[39melse\u001b[39;00m parent_label)\n\u001b[0;32m--> 262\u001b[0m \u001b[39mreturn\u001b[39;00m \u001b[39mcls\u001b[39;49m\u001b[39m.\u001b[39;49mfrom_dblock(dblock, path, path\u001b[39m=\u001b[39;49mpath, seq_len\u001b[39m=\u001b[39;49mseq_len, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkwargs)\n",
"File \u001b[0;32m~/.local/lib/python3.10/site-packages/fastai/data/core.py:284\u001b[0m, in \u001b[0;36mDataLoaders.from_dblock\u001b[0;34m(cls, dblock, source, path, bs, val_bs, shuffle, device, **kwargs)\u001b[0m\n\u001b[1;32m 273\u001b[0m \u001b[39m@classmethod\u001b[39m\n\u001b[1;32m 274\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mfrom_dblock\u001b[39m(\u001b[39mcls\u001b[39m, \n\u001b[1;32m 275\u001b[0m dblock, \u001b[39m# `DataBlock` object\u001b[39;00m\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 282\u001b[0m \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mkwargs\n\u001b[1;32m 283\u001b[0m ):\n\u001b[0;32m--> 284\u001b[0m \u001b[39mreturn\u001b[39;00m dblock\u001b[39m.\u001b[39;49mdataloaders(source, path\u001b[39m=\u001b[39;49mpath, bs\u001b[39m=\u001b[39;49mbs, val_bs\u001b[39m=\u001b[39;49mval_bs, shuffle\u001b[39m=\u001b[39;49mshuffle, device\u001b[39m=\u001b[39;49mdevice, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkwargs)\n",
"File \u001b[0;32m~/.local/lib/python3.10/site-packages/fastai/data/block.py:157\u001b[0m, in \u001b[0;36mDataBlock.dataloaders\u001b[0;34m(self, source, path, verbose, **kwargs)\u001b[0m\n\u001b[1;32m 155\u001b[0m dsets \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mdatasets(source, verbose\u001b[39m=\u001b[39mverbose)\n\u001b[1;32m 156\u001b[0m kwargs \u001b[39m=\u001b[39m {\u001b[39m*\u001b[39m\u001b[39m*\u001b[39m\u001b[39mself\u001b[39m\u001b[39m.\u001b[39mdls_kwargs, \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mkwargs, \u001b[39m'\u001b[39m\u001b[39mverbose\u001b[39m\u001b[39m'\u001b[39m: verbose}\n\u001b[0;32m--> 157\u001b[0m \u001b[39mreturn\u001b[39;00m dsets\u001b[39m.\u001b[39;49mdataloaders(path\u001b[39m=\u001b[39;49mpath, after_item\u001b[39m=\u001b[39;49m\u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mitem_tfms, after_batch\u001b[39m=\u001b[39;49m\u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mbatch_tfms, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkwargs)\n",
