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Use log_artifact in notebook. #194

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Merged
daavoo merged 1 commit into from
Apr 13, 2023
Merged

Use log_artifact in notebook. #194

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48 changes: 28 additions & 20 deletions example-get-started-experiments/code/notebooks/TrainSegModel.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -158,7 +158,28 @@
" intersection = 2.0 * np.sum(y_true * y_pred)\n",
" dice = intersection / (np.sum(y_true) + np.sum(y_pred) + eps)\n",
" dice_list.append(dice)\n",
" return np.mean(dice_list)"
" return np.mean(dice_list)\n",
"\n",
"def evaluate(learn):\n",
" test_img_fpaths = get_files(DATA / \"test_data\", extensions=\".jpg\")\n",
" test_dl = learn.dls.test_dl(test_img_fpaths)\n",
" preds, _ = learn.get_preds(dl=test_dl)\n",
" masks_pred = np.array(preds[:, 1, :] > 0.5, dtype=np.uint8)\n",
" test_mask_fpaths = [\n",
" get_mask_path(fpath, DATA / \"test_data\") for fpath in test_img_fpaths\n",
" ]\n",
" masks_true = [Image.open(mask_path) for mask_path in test_mask_fpaths]\n",
" dice_multi = 0.0\n",
" for ii in range(len(masks_true)):\n",
" mask_pred, mask_true = masks_pred[ii], masks_true[ii]\n",
" width, height = mask_true.shape[1], mask_true.shape[0]\n",
" mask_pred = np.array(\n",
" Image.fromarray(mask_pred).resize((width, height)),\n",
" dtype=int\n",
" )\n",
" mask_true = np.array(mask_true, dtype=int)\n",
" dice_multi += dice(mask_true, mask_pred) / len(masks_true)\n",
" return dice_multi"
]
},
{
Expand All @@ -168,6 +189,8 @@
"outputs": [],
"source": [
"train_arch = 'resnet18'\n",
"models_dir = ROOT / \"models\"\n",
"models_dir.mkdir(exist_ok=True)\n",
"\n",
"for base_lr in [0.001, 0.005, 0.01]:\n",
" with Live(str(ROOT / \"results\" / \"train\"), save_dvc_exp=True) as live:\n",
Expand All @@ -185,26 +208,11 @@
" **fine_tune_args,\n",
" cbs=[DVCLiveCallback(live=live)])\n",
"\n",
" learn.export(fname=(models_dir / \"model.pkl\").absolute())\n",
"\n",
" live.summary[\"evaluate/dice_multi\"] = evaluate(learn)\n",
"\n",
" test_img_fpaths = get_files(DATA / \"test_data\", extensions=\".jpg\")\n",
" test_dl = learn.dls.test_dl(test_img_fpaths)\n",
" preds, _ = learn.get_preds(dl=test_dl)\n",
" masks_pred = np.array(preds[:, 1, :] > 0.5, dtype=np.uint8)\n",
" test_mask_fpaths = [\n",
" get_mask_path(fpath, DATA / \"test_data\") for fpath in test_img_fpaths\n",
" ]\n",
" masks_true = [Image.open(mask_path) for mask_path in test_mask_fpaths]\n",
" dice_multi = 0.0\n",
" for ii in range(len(masks_true)):\n",
" mask_pred, mask_true = masks_pred[ii], masks_true[ii]\n",
" width, height = mask_true.shape[1], mask_true.shape[0]\n",
" mask_pred = np.array(\n",
" Image.fromarray(mask_pred).resize((width, height)),\n",
" dtype=int\n",
" )\n",
" mask_true = np.array(mask_true, dtype=int)\n",
" dice_multi += dice(mask_true, mask_pred) / len(masks_true)\n",
" live.summary[\"evaluate/dice_multi\"] = dice_multi"
" live.log_artifact(str(models_dir / \"model.pkl\"))"
]
},
{
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1 change: 1 addition & 0 deletions example-get-started-experiments/generate.sh
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Expand Up @@ -95,6 +95,7 @@ cp -r $HERE/code/src .
cp $HERE/code/params.yaml .
sed -e "s/base_lr: 0.01/base_lr: $BEST_EXP_BASE_LR/" -i".bkp" params.yaml
rm params.yaml.bkp
dvc remove models/model.pkl.dvc
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@shcheklein shcheklein Apr 13, 2023

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not sure I understand the logic here, could you describe the workflow? do we transition from dvc add to log_artifact at some stage?

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@daavoo daavoo Apr 13, 2023

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We transition from log_artifact which is dvc add to stage output in the dvc.yaml.

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@shcheklein shcheklein Apr 13, 2023

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got it ... and what it was before the log_artifact where and how did we save the model?

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@daavoo daavoo Apr 13, 2023

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what it was before the log_artifact where and how did we save the model?

We didn't save it at all during the notebook state, that was the motivation for the P.R.

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@shcheklein shcheklein Apr 13, 2023

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got it!


dvc stage add -n data_split \
-p base,data_split \
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