{"cells":[{"cell_type":"code","execution_count":null,"metadata":{"id":"COkMuAOy2J5o"},"outputs":[],"source":["%load_ext autoreload\n","%autoreload 2"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":2788,"status":"ok","timestamp":1699424405111,"user":{"displayName":"Rizqi Nur","userId":"09644007964068789560"},"user_tz":-420},"id":"HfqAIvK1iGpA","outputId":"c07c4737-5255-407b-eee4-2af7aefdbcd3"},"outputs":[{"name":"stdout","output_type":"stream","text":["Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n"]}],"source":["from google.colab import drive\n","drive.mount('/content/drive')"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":385631,"status":"ok","timestamp":1699423886508,"user":{"displayName":"Rizqi Nur","userId":"09644007964068789560"},"user_tz":-420},"id":"lqNWRhS42u4P","outputId":"9d54b617-f5cd-4b9f-9c52-59963705de9b"},"outputs":[{"name":"stdout","output_type":"stream","text":["Collecting optuna\n","  Downloading optuna-3.4.0-py3-none-any.whl (409 kB)\n","\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m409.6/409.6 kB\u001b[0m \u001b[31m4.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n","\u001b[?25hCollecting optuna-dashboard\n","  Downloading optuna_dashboard-0.13.0-py3-none-any.whl (5.8 MB)\n","\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m5.8/5.8 MB\u001b[0m \u001b[31m60.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n","\u001b[?25hCollecting alembic>=1.5.0 (from optuna)\n","  Downloading alembic-1.12.1-py3-none-any.whl (226 kB)\n","\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m226.8/226.8 kB\u001b[0m \u001b[31m17.9 MB/s\u001b[0m eta 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(from cffi>=1.0.1->argon2-cffi-bindings->argon2-cffi->notebook->jupyter>=1.0.0->ml-utility-loss==0.1.1) (2.21)\n","Building wheels for collected packages: ml-utility-loss, alpharelu, torchtext\n","  Building wheel for ml-utility-loss (setup.py) ... \u001b[?25l\u001b[?25hdone\n","  Created wheel for ml-utility-loss: filename=ml_utility_loss-0.1.1-py3-none-any.whl size=435424 sha256=29c698559cc3e0ae7eea0c27b4ed0e357213590e94d01d243fd5afd41e3cfafb\n","  Stored in directory: /tmp/pip-ephem-wheel-cache-4gs049zg/wheels/54/30/38/31c28079b5f07b6c793211d38f72e7f0be6764bfdfe016df74\n","  Building wheel for alpharelu (setup.py) ... \u001b[?25l\u001b[?25hdone\n","  Created wheel for alpharelu: filename=alpharelu-1.1-py3-none-any.whl size=3843 sha256=714546f19a87d883352607e45de8591855f9ac4a36b013eca8eced4fccdae472\n","  Stored in directory: /root/.cache/pip/wheels/19/f4/8b/4d08773d0281d53fe80057c78ca51371bcbe8859a469fba852\n","  Building wheel for torchtext (setup.py) ... \u001b[?25l\u001b[?25hdone\n","  Created wheel for torchtext: filename=torchtext-0.6.1-py3-none-any.whl size=64352 sha256=8eb8ec6526604f0211823a39793269b13a93a89e636a168eaa3045480b821a92\n","  Stored in directory: /tmp/pip-ephem-wheel-cache-4gs049zg/wheels/61/f8/1f/28b8e145b4451f1ae42f92d412bc90463e90f560f41e4d00c8\n","Successfully built ml-utility-loss alpharelu torchtext\n","Installing collected packages: tokenizers, sentencepiece, torchinfo, tomli-w, qtpy, pynvml, nvidia-cuda-runtime-cu11, nvidia-cuda-nvrtc-cu11, nvidia-cublas-cu11, numpy, jedi, executing, dill, colorama, asttokens, nvidia-cudnn-cu11, multiprocess, icecream, huggingface-hub, Faker, transformers, torch, torchvision, torchtext, skorch, scikit-plot, rtdl, rdt, qtconsole, pytorch-ranger, libzero, entmax, delu, datasets, category-encoders, catboost, alpharelu, accelerate, torch_optimizer, dython, jupyter, ml-utility-loss\n","  Attempting uninstall: numpy\n","    Found existing installation: numpy 1.23.5\n","    Uninstalling numpy-1.23.5:\n","      Successfully uninstalled numpy-1.23.5\n","  Attempting uninstall: torch\n","    Found existing installation: torch 2.1.0+cu118\n","    Uninstalling torch-2.1.0+cu118:\n","      Successfully uninstalled torch-2.1.0+cu118\n","  Attempting uninstall: torchvision\n","    Found existing installation: torchvision 0.16.0+cu118\n","    Uninstalling torchvision-0.16.0+cu118:\n","      Successfully uninstalled torchvision-0.16.0+cu118\n","  Attempting uninstall: torchtext\n","    Found existing installation: torchtext 0.16.0\n","    Uninstalling torchtext-0.16.0:\n","      Successfully uninstalled torchtext-0.16.0\n","\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n","lida 0.0.10 requires fastapi, which is not installed.\n","lida 0.0.10 requires kaleido, which is not installed.\n","lida 0.0.10 requires python-multipart, which is not installed.\n","lida 0.0.10 requires uvicorn, which is not installed.\n","cupy-cuda11x 11.0.0 requires numpy<1.26,>=1.20, but you have numpy 1.26.1 which is incompatible.\n","torchaudio 2.1.0+cu118 requires torch==2.1.0, but you have torch 1.13.1 which is incompatible.\n","torchdata 0.7.0 requires torch==2.1.0, but you have torch 1.13.1 which is incompatible.\u001b[0m\u001b[31m\n","\u001b[0mSuccessfully installed Faker-19.13.0 accelerate-0.24.1 alpharelu-1.1 asttokens-2.4.1 catboost-1.2.2 category-encoders-2.6.3 colorama-0.4.6 datasets-2.14.6 delu-0.0.18 dill-0.3.7 dython-0.6.8 entmax-1.1 executing-2.0.1 huggingface-hub-0.18.0 icecream-2.1.3 jedi-0.19.1 jupyter-1.0.0 libzero-0.0.8 ml-utility-loss-0.1.1 multiprocess-0.70.15 numpy-1.26.1 nvidia-cublas-cu11-11.10.3.66 nvidia-cuda-nvrtc-cu11-11.7.99 nvidia-cuda-runtime-cu11-11.7.99 nvidia-cudnn-cu11-8.5.0.96 pynvml-11.5.0 pytorch-ranger-0.1.1 qtconsole-5.5.0 qtpy-2.4.1 rdt-1.8.0 rtdl-0.0.13 scikit-plot-0.3.7 sentencepiece-0.1.99 skorch-0.15.0 tokenizers-0.13.3 tomli-w-1.0.0 torch-1.13.1 torch_optimizer-0.3.0 torchinfo-1.8.0 torchtext-0.6.1 torchvision-0.14.1 transformers-4.28.0\n","Collecting git+https://github.com/R-N/ml-utility-loss\n","  Cloning https://github.com/R-N/ml-utility-loss to /tmp/pip-req-build-67ndixnd\n","  Running command git clone --filter=blob:none --quiet https://github.com/R-N/ml-utility-loss /tmp/pip-req-build-67ndixnd\n","  Resolved https://github.com/R-N/ml-utility-loss to commit 88cad1fe670a454c22556ffab0b88ff417a72048\n","  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n","Building wheels for collected packages: ml-utility-loss\n","  Building wheel for ml-utility-loss (setup.py) ... \u001b[?25l\u001b[?25hdone\n","  Created wheel for ml-utility-loss: filename=ml_utility_loss-0.1.1-py3-none-any.whl size=435424 sha256=210f7ff00596fab3624b9cbbde601e202f0467572831bffb9d4c78d6d9075fd9\n","  Stored in directory: /tmp/pip-ephem-wheel-cache-7f3thfcw/wheels/54/30/38/31c28079b5f07b6c793211d38f72e7f0be6764bfdfe016df74\n","Successfully built ml-utility-loss\n","Installing collected packages: ml-utility-loss\n","  Attempting uninstall: ml-utility-loss\n","    Found existing installation: ml-utility-loss 0.1.1\n","    Uninstalling ml-utility-loss-0.1.1:\n","      Successfully uninstalled ml-utility-loss-0.1.1\n","Successfully installed ml-utility-loss-0.1.1\n"]}],"source":["!pip install optuna optuna-dashboard\n","!pip install git+https://github.com/R-N/ml-utility-loss\n","!pip install git+https://github.com/R-N/ml-utility-loss --force-reinstall --no-deps"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":1724,"status":"ok","timestamp":1699424406827,"user":{"displayName":"Rizqi Nur","userId":"09644007964068789560"},"user_tz":-420},"id":"nrYplK5Rkgcn","outputId":"1c2ed5da-2d6c-40a9-ad4f-b969109dc8b5"},"outputs":[{"name":"stdout","output_type":"stream","text":["/content\n","  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current\n","                                 Dload  Upload   Total   Spent    Left  Speed\n","  0     0    0     0    0     0      0      0 --:--:-- --:--:-- --:--:--     0\n","  0     0    0     0    0     0      0      0 --:--:-- --:--:-- --:--:--     0\n","100 34.7M  100 34.7M    0     0  50.0M      0 --:--:-- --:--:-- --:--:--  104M\n"]}],"source":["%cd /content\n","!curl -Ls https://github.com/ekzhang/bore/releases/download/v0.4.0/bore-v0.4.0-x86_64-unknown-linux-musl.tar.gz | tar zx -C /usr/bin\n","!curl -Lo /usr/bin/cloudflared https://github.com/cloudflare/cloudflared/releases/latest/download/cloudflared-linux-amd64 && chmod +x /usr/bin/cloudflared"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"ns5hFcVL2yvs"},"outputs":[],"source":["datasets = [\n","    \"insurance\",\n","    \"treatment\",\n","    \"contraceptive\"\n","]\n","\n","model_dir = \"/content/drive/MyDrive/rizqinur2010/Documents/ITS/Tesis/Model/\""]},{"cell_type":"code","execution_count":null,"metadata":{"id":"UdvXYv3c3LXy"},"outputs":[],"source":["import pandas as pd\n","import numpy as np\n","import json\n","import os\n","\n","dataset_dir = \"datasets\"\n","dataset_name = \"treatment\"\n"]},{"cell_type":"code","execution_count":409,"metadata":{"executionInfo":{"elapsed":363,"status":"ok","timestamp":1699431279191,"user":{"displayName":"Rizqi Nur","userId":"09644007964068789560"},"user_tz":-420},"id":"a-SjylvlYl7i"},"outputs":[],"source":["from ml_utility_loss.util import mkdir\n","\n","model_name = \"realtabformer\"\n","df_name = \"4\"\n","model_subdir = \"mean-best-disc-model\"\n","#model_name_2 = f\"{model_name}_{dataset_name}_{df_name}\"\n","model_dir_2 = os.path.join(model_dir, model_name, dataset_name, str(df_name))\n","mkdir(model_dir_2)\n","params_path = os.path.join(model_dir_2, f\"params.json\")"]},{"cell_type":"code","execution_count":410,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":1539,"status":"ok","timestamp":1699431282047,"user":{"displayName":"Rizqi Nur","userId":"09644007964068789560"},"user_tz":-420},"id":"-YDZUU9QUCwx","outputId":"a3290331-ba34-4283-b12c-fe26143693f9"},"outputs":[{"output_type":"stream","name":"stdout","text":["/content/drive/MyDrive/rizqinur2010/Documents/ITS/Tesis/Model/realtabformer/treatment/4\n"]}],"source":["print(model_dir_2)"]},{"cell_type":"code","execution_count":411,"metadata":{"executionInfo":{"elapsed":7,"status":"ok","timestamp":1699431282047,"user":{"displayName":"Rizqi Nur","userId":"09644007964068789560"},"user_tz":-420},"id":"NgahtU1q9uLO"},"outputs":[],"source":["\n","from ml_utility_loss.tuning import create_objective\n","import ml_utility_loss.synthesizers.realtabformer.params as PARAMS\n","from ml_utility_loss.util import filter_dict_2, filter_dict\n","from copy import deepcopy\n","\n","params = getattr(PARAMS, dataset_name).BEST\n","\n","model_params={\n","    **params,\n","}\n","\n","model_params[\"epochs\"] = min(model_params.pop(\"epochs\", 100), 100)\n","\n","model_params_ = deepcopy(model_params)"]},{"cell_type":"code","execution_count":412,"metadata":{"executionInfo":{"elapsed":7,"status":"ok","timestamp":1699431282048,"user":{"displayName":"Rizqi Nur","userId":"09644007964068789560"},"user_tz":-420},"id":"wGsDQTlk8Zl1"},"outputs":[],"source":["from ml_utility_loss.synthesizers.realtabformer.wrapper import REaLTabFormer\n","from ml_utility_loss.synthesizers.realtabformer.params.default import GPT2_PARAMS, REALTABFORMER_PARAMS\n","\n","from transformers.models.gpt2 import GPT2Config\n","\n","num_bootstrap = model_params.pop(\"num_bootstrap\", 100)\n","\n","gpt2_params = filter_dict(model_params, GPT2_PARAMS)\n","realtabformer_params = filter_dict(model_params, REALTABFORMER_PARAMS)\n","\n","# Non-relational or parent table.\n","rtf_model = REaLTabFormer(\n","    tabular_config=GPT2Config(**gpt2_params),\n","    **realtabformer_params\n",")\n","\n","rtf_model.experiment_id = str(df_name)\n"]},{"cell_type":"code","execution_count":413,"metadata":{"id":"nB724X33v4Qd","executionInfo":{"status":"ok","timestamp":1699431298162,"user_tz":-420,"elapsed":16120,"user":{"displayName":"Rizqi Nur","userId":"09644007964068789560"}}},"outputs":[],"source":["model_dir_3 = f\"{model_dir_2}/{df_name}\"\n","rtf_model = rtf_model.load_from_dir(\n","    model_dir_3,\n","    config_file=\"rtf_config.json\",\n","    model_file=f\"{model_subdir}/pytorch_model.bin\"\n",")"]},{"cell_type":"code","execution_count":414,"metadata":{"id":"5S-S8SKlbaZE","executionInfo":{"status":"ok","timestamp":1699431298162,"user_tz":-420,"elapsed":5,"user":{"displayName":"Rizqi Nur","userId":"09644007964068789560"}}},"outputs":[],"source":["text_embedding = rtf_model.model.transformer.wte\n","position_embedding = rtf_model.model.transformer.wpe"]},{"cell_type":"code","execution_count":415,"metadata":{"id":"83txVTxksE7V","executionInfo":{"status":"ok","timestamp":1699431298162,"user_tz":-420,"elapsed":5,"user":{"displayName":"Rizqi Nur","userId":"09644007964068789560"}}},"outputs":[],"source":["model_dir_4 = f\"{model_dir_3}/{model_subdir}\""]},{"cell_type":"code","execution_count":416,"metadata":{"id":"hbIV6cI4bf5f","executionInfo":{"status":"ok","timestamp":1699431299504,"user_tz":-420,"elapsed":1346,"user":{"displayName":"Rizqi Nur","userId":"09644007964068789560"}}},"outputs":[],"source":["import torch\n","import os\n","from copy import deepcopy\n","\n","torch.save(text_embedding, os.path.join(model_dir_4, \"text_embedding.pt\"))\n","torch.save(deepcopy(text_embedding.state_dict()), os.path.join(model_dir_4, \"text_embedding.states.pt\"))"]},{"cell_type":"code","execution_count":417,"metadata":{"id":"16Ot4B7Zrumx","executionInfo":{"status":"ok","timestamp":1699431299504,"user_tz":-420,"elapsed":6,"user":{"displayName":"Rizqi Nur","userId":"09644007964068789560"}}},"outputs":[],"source":["import torch\n","import os\n","from copy import deepcopy\n","\n","torch.save(position_embedding, os.path.join(model_dir_4, \"position_embedding.pt\"))\n","torch.save(deepcopy(position_embedding.state_dict()), os.path.join(model_dir_4, \"position_embedding.states.pt\"))"]},{"cell_type":"code","execution_count":418,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"lPJcW_9psoYR","executionInfo":{"status":"ok","timestamp":1699431299504,"user_tz":-420,"elapsed":6,"user":{"displayName":"Rizqi Nur","userId":"09644007964068789560"}},"outputId":"3396842a-4b26-4927-ed43-25ebf330d34d"},"outputs":[{"output_type":"execute_result","data":{"text/plain":["768"]},"metadata":{},"execution_count":418}],"source":["text_embedding.weight.shape[-1]"]},{"cell_type":"code","execution_count":418,"metadata":{"id":"axQZ1NOWuPIE","executionInfo":{"status":"ok","timestamp":1699431299504,"user_tz":-420,"elapsed":5,"user":{"displayName":"Rizqi Nur","userId":"09644007964068789560"}}},"outputs":[],"source":[]}],"metadata":{"colab":{"provenance":[]},"kernelspec":{"display_name":"Python 3","name":"python3"},"language_info":{"name":"python"}},"nbformat":4,"nbformat_minor":0}