{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"name":"python","version":"3.10.12","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"},"kaggle":{"accelerator":"none","dataSources":[{"sourceId":53666,"databundleVersionId":6589269,"sourceType":"competition"}],"dockerImageVersionId":30558,"isInternetEnabled":true,"language":"python","sourceType":"notebook","isGpuEnabled":false}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"code","source":"from pathlib import Path\n\nfrom google.cloud import storage\n\nproject_name = \"layerone-dpf-ml-sbx-00000-dev\"\nbucket_name = \"kaggle_cmi\"\n\nclient = storage.Client(project_name)\nbucket = client.get_bucket(bucket_name)\n\nPath(\"models/\").mkdir(exist_ok=True)\n\n# stacking model (Boosting)\nfor run_name in [\n            \"stacking_exp013_009_1minute_sampling\",\n            \"stacking_exp028_021_from_016_192step\",\n            \"stacking_exp029_021_from_028_catboost\",\n            \"stacking_exp059_030_truncate_lgbm\",\n            \"stacking_exp061_030_truncate_cat\",\n        ]:\n    model_dir = Path(\"models/\") / run_name\n    model_dir.mkdir(exist_ok=True)\n    for blob in bucket.list_blobs(prefix=f\"shimacos/{run_name}/model/\"):\n        file_name = Path(blob.name).name\n        blob.download_to_filename(filename=str(model_dir / file_name))\n    for blob in bucket.list_blobs(prefix=f\"shimacos/{run_name}/.hydra/\"):\n        file_name = Path(blob.name).name\n        blob.download_to_filename(filename=str(model_dir / file_name))\n# stacking model (NN)\nfor run_name in [\"stacking_exp030_021_chink_gru\", \"stacking_exp060_030_truncate_small\"]:\n    (Path(\"models/\") / run_name).mkdir(exist_ok=True)\n    for i in range(5):\n        model_dir = Path(\"models/\") / run_name / f'fold{i}'\n        model_dir.mkdir(exist_ok=True)\n        for blob in bucket.list_blobs(prefix=f\"shimacos/{run_name}/fold{i}/model/\"):\n            file_name = Path(blob.name).name\n            blob.download_to_filename(filename=str(model_dir / 'nn.ckpt'))\n        for blob in bucket.list_blobs(prefix=f\"shimacos/{run_name}/fold{i}/.hydra/\"):\n            file_name = Path(blob.name).name\n            blob.download_to_filename(filename=str(model_dir / file_name))\n\n\nprint([str(path) for path in Path(\".\").iterdir() if not str(path).startswith(\".\")])\nprint([str(path) for path in model_dir.iterdir() if not str(path).startswith(\".\")])","metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","execution":{"iopub.status.busy":"2023-12-05T10:44:19.636254Z","iopub.execute_input":"2023-12-05T10:44:19.636911Z","iopub.status.idle":"2023-12-05T10:44:51.954609Z","shell.execute_reply.started":"2023-12-05T10:44:19.636875Z","shell.execute_reply":"2023-12-05T10:44:51.953436Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"","metadata":{},"execution_count":null,"outputs":[]}]}