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commit 24d50a3e7e6baee21e4801cfca8972d152cc4657\n","  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n","Requirement already satisfied: alpharelu in /usr/local/lib/python3.10/dist-packages (from ml-utility-loss==0.1.1) (1.1)\n","Requirement already satisfied: entmax in /usr/local/lib/python3.10/dist-packages (from ml-utility-loss==0.1.1) (1.1)\n","Requirement already satisfied: accelerate>=0.20.3 in /usr/local/lib/python3.10/dist-packages (from ml-utility-loss==0.1.1) (0.24.0)\n","Requirement already satisfied: catboost>=1.0.3 in /usr/local/lib/python3.10/dist-packages (from ml-utility-loss==0.1.1) (1.2.2)\n","Requirement already satisfied: category-encoders>=2.3.0 in /usr/local/lib/python3.10/dist-packages (from ml-utility-loss==0.1.1) (2.6.2)\n","Requirement already satisfied: datasets>=2.6.1 in /usr/local/lib/python3.10/dist-packages (from ml-utility-loss==0.1.1) (2.14.6)\n","Requirement already satisfied: delu==0.0.18 in /usr/local/lib/python3.10/dist-packages (from 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in /usr/local/lib/python3.10/dist-packages (from cffi>=1.0.1->argon2-cffi-bindings->argon2-cffi->notebook->jupyter>=1.0.0->ml-utility-loss==0.1.1) (2.21)\n","Collecting git+https://github.com/R-N/ml-utility-loss.git\n","  Cloning https://github.com/R-N/ml-utility-loss.git to /tmp/pip-req-build-99m4rbmk\n","  Running command git clone --filter=blob:none --quiet https://github.com/R-N/ml-utility-loss.git /tmp/pip-req-build-99m4rbmk\n","  Resolved https://github.com/R-N/ml-utility-loss.git to commit 24d50a3e7e6baee21e4801cfca8972d152cc4657\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=396570 sha256=f1a733056ddab47ed8572c2cf763404def3220b9dbc2c4cb9d19326196e76825\n","  Stored in directory: /tmp/pip-ephem-wheel-cache-ce0u6g3p/wheels/4c/bf/aa/7a48a646b041e8e425159fc8b8a571fe8fabcb1c6196eb94ad\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"]}]},{"cell_type":"code","source":["%cd /content\n","!rm -rf ml-utility-loss\n","!git clone https://github.com/R-N/ml-utility-loss\n","%cd ml-utility-loss\n","!rm -rf ml_utility_loss"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"qZbCP3H6zcpq","executionInfo":{"status":"ok","timestamp":1698341548860,"user_tz":-420,"elapsed":40021,"user":{"displayName":"Rizqi Nur","userId":"09644007964068789560"}},"outputId":"23812d78-85a2-487b-b2be-df16446a519f"},"execution_count":3,"outputs":[{"output_type":"stream","name":"stdout","text":["/content\n","Cloning into 'ml-utility-loss'...\n","remote: Enumerating objects: 56195, done.\u001b[K\n","remote: Counting objects: 100% (9108/9108), done.\u001b[K\n","remote: Compressing objects: 100% (3950/3950), done.\u001b[K\n","remote: Total 56195 (delta 5193), reused 9050 (delta 5135), pack-reused 47087\u001b[K\n","Receiving objects: 100% (56195/56195), 282.12 MiB | 14.52 MiB/s, done.\n","Resolving deltas: 100% (7241/7241), done.\n","Updating files: 100% (50924/50924), done.\n","/content/ml-utility-loss\n"]}]},{"cell_type":"code","source":["import os\n","datasets = [\n","    \"insurance\",\n","    \"treatment\",\n","    \"contraceptive\"\n","]\n","\n","data_dir = \"/content/drive/MyDrive/rizqinur2010/Documents/ITS/Tesis/Model/\"\n","model = \"realtabformer\"\n","data_dir = os.path.join(data_dir, model)\n","dataset_dir = \"datasets\""],"metadata":{"id":"vKq9n0J3wHH1","executionInfo":{"status":"ok","timestamp":1698341845922,"user_tz":-420,"elapsed":3,"user":{"displayName":"Rizqi Nur","userId":"09644007964068789560"}}},"execution_count":21,"outputs":[]},{"cell_type":"code","source":["for d in datasets:\n","    !ls {data_dir}/{d} | grep info"],"metadata":{"id":"5muTC284DH1D","executionInfo":{"status":"ok","timestamp":1698341847255,"user_tz":-420,"elapsed":562,"user":{"displayName":"Rizqi Nur","userId":"09644007964068789560"}}},"execution_count":22,"outputs":[]},{"cell_type":"code","source":["import json\n","import os\n","infos = {}\n","for dataset in datasets:\n","    with open(os.path.join(dataset_dir, f\"{dataset}.json\")) as f:\n","        info = json.load(f)\n","    infos[dataset] = info"],"metadata":{"id":"iMeMVZfs0f_X","executionInfo":{"status":"ok","timestamp":1698341847757,"user_tz":-420,"elapsed":504,"user":{"displayName":"Rizqi Nur","userId":"09644007964068789560"}}},"execution_count":23,"outputs":[]},{"cell_type":"code","source":["import os\n","from ml_utility_loss.loss_learning.estimator.pipeline import score_datasets\n","\n","for dataset in datasets:\n","    score_datasets(os.path.join(data_dir, dataset), list(range(5)), infos[dataset])"],"metadata":{"id":"YpS3ifzNHpE6","colab":{"base_uri":"https://localhost:8080/","height":0,"referenced_widgets":["3945695bc81740fcb1ede9059bab0138","533d63c2846940dba53e3df30c6e63fe","d995077ff55145a5babe4300304d68ae","15bb4fb9dcd14a408bd3cd55e3e3eca9","6487ffd39d8d4be6826ae9266310d649","2e15dcde9df14a6da8a759b6c025526b","31d967962f77486fb4a1441c521b25b1","e984b333f4a24fed8a23fdc4a42468c7","dd588bbf80b245a48401c28af3129f43","00fd0b55767046969ea63559e6c7c3e3","fcb8b579ebed438bbcf76bf58a389b0c","aa330ce2cac047898db25f45c21dae2b","3a919208a2c44b22b707c24713e48847","1c750c7166e14aa18071887329c55221","138d5ef5cfa34c04a7befeb7ee2c13f5","f5af6264df2f4be88faf3e79e22d32ec","677b438df17f4e9e9af9a19e4aba2281","887a28ea3253495f8548ae7dbdb206f0","5fb506abd363435d8dbacec0b19a7c8e","847a88b78e7d47bd8054905001aa3de1","f6af4ea3867f47f5a4b80d6b72bc9677","fd82db433ed248b7bef76a2bce69cb49","ceb64ac1fb4d49f5a16d682e38598f85","a87e26896b4a48d5abdb537f25032f95","4c6a58496cc549e8b9299d2506b367ca","c0c1ff73acba412194679007a1de5d4d","3eac61bf6d0d4d1b89a340a98803a0cb","001b0286842e4e54a66f0c7520ed4140","aaa66eea7184443baa9734aeb7da90d5","d6364d0755be44a0a63678470a97b9d8"]},"outputId":"591ffa2b-559c-4db8-df99-bb4c90bcdbc6","executionInfo":{"status":"ok","timestamp":1698341862200,"user_tz":-420,"elapsed":14445,"user":{"displayName":"Rizqi Nur","userId":"09644007964068789560"}}},"execution_count":24,"outputs":[{"output_type":"display_data","data":{"text/plain":["MetricVisualizer(layout=Layout(align_self='stretch', height='500px'))"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"3945695bc81740fcb1ede9059bab0138"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["MetricVisualizer(layout=Layout(align_self='stretch', height='500px'))"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"533d63c2846940dba53e3df30c6e63fe"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["MetricVisualizer(layout=Layout(align_self='stretch', height='500px'))"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"d995077ff55145a5babe4300304d68ae"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["MetricVisualizer(layout=Layout(align_self='stretch', height='500px'))"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"15bb4fb9dcd14a408bd3cd55e3e3eca9"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["MetricVisualizer(layout=Layout(align_self='stretch', height='500px'))"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"6487ffd39d8d4be6826ae9266310d649"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["MetricVisualizer(layout=Layout(align_self='stretch', height='500px'))"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"2e15dcde9df14a6da8a759b6c025526b"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["MetricVisualizer(layout=Layout(align_self='stretch', height='500px'))"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"31d967962f77486fb4a1441c521b25b1"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["MetricVisualizer(layout=Layout(align_self='stretch', height='500px'))"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"e984b333f4a24fed8a23fdc4a42468c7"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["MetricVisualizer(layout=Layout(align_self='stretch', height='500px'))"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"dd588bbf80b245a48401c28af3129f43"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["MetricVisualizer(layout=Layout(align_self='stretch', height='500px'))"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"00fd0b55767046969ea63559e6c7c3e3"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["MetricVisualizer(layout=Layout(align_self='stretch', height='500px'))"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"fcb8b579ebed438bbcf76bf58a389b0c"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["MetricVisualizer(layout=Layout(align_self='stretch', height='500px'))"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"aa330ce2cac047898db25f45c21dae2b"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["MetricVisualizer(layout=Layout(align_self='stretch', height='500px'))"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"3a919208a2c44b22b707c24713e48847"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["MetricVisualizer(layout=Layout(align_self='stretch', height='500px'))"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"1c750c7166e14aa18071887329c55221"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["MetricVisualizer(layout=Layout(align_self='stretch', height='500px'))"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"138d5ef5cfa34c04a7befeb7ee2c13f5"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["MetricVisualizer(layout=Layout(align_self='stretch', 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