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261 lines
17 KiB
261 lines
17 KiB
{ |
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"cells": [ |
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{ |
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"cell_type": "code", |
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"execution_count": 1, |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"import sagemaker\n", |
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"import boto3\n", |
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"from sagemaker import get_execution_role\n", |
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"\n", |
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"boto_session = boto3.Session(profile_name='bonitoo', region_name='eu-central-1')\n", |
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"sagemaker_session = sagemaker.LocalSession(boto_session=boto_session)\n", |
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"#sagemaker_session = sagemaker.Session()" |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": 2, |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"# Get a SageMaker-compatible role used by this Notebook Instance.\n", |
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"#role = get_execution_role()\n", |
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"role = 'Bonitoo_SageMaker_Execution'\n", |
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"region = boto_session.region_name" |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": 14, |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"train_input = 'file:///home/ehp/soukrome/git/bonitoo/var/data'\n", |
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"#train_input = 's3://customers-bonitoo-cachettl/sagemaker/data/export.csv'\n" |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": 25, |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"from sagemaker.xgboost.estimator import XGBoost\n", |
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"\n", |
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"tf = XGBoost(\n", |
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" entry_point='train_model.py',\n", |
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" source_dir='./src',\n", |
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" train_instance_type='local',\n", |
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" train_instance_count=1,\n", |
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" role=role,\n", |
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" sagemaker_session=sagemaker_session,\n", |
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" framework_version='0.90-1',\n", |
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" py_version='py3',\n", |
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" hyperparameters={\n", |
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" 'bonitoo_price_pos_abs': 1000,\n", |
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" 'bonitoo_price_neg_abs': 200,\n", |
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" 'bonitoo_price_pos_perc': 0.05,\n", |
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" 'bonitoo_price_neg_perc': 0.05,\n", |
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" 'num_round': 10,\n", |
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" 'max_depth': 15,\n", |
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" 'eta': 0.5,\n", |
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" 'num_class': 8,\n", |
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" 'objective': 'multi:softprob',\n", |
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" 'eval_metric': 'mlogloss'\n", |
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" })" |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": 26, |
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"metadata": { |
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"scrolled": true |
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}, |
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"outputs": [ |
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{ |
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"name": "stdout", |
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"output_type": "stream", |
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"text": [ |
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"Creating tmp_3oe6esm_algo-1-z7zik_1 ... \n", |
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"\u001b[1BAttaching to tmp_3oe6esm_algo-1-z7zik_12mdone\u001b[0m\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m INFO:sagemaker-containers:Imported framework sagemaker_xgboost_container.training\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m INFO:sagemaker-containers:No GPUs detected (normal if no gpus installed)\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m INFO:sagemaker_xgboost_container.training:Invoking user training script.\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m INFO:sagemaker-containers:Module train_model does not provide a setup.py. \n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m Generating setup.py\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m INFO:sagemaker-containers:Generating setup.cfg\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m INFO:sagemaker-containers:Generating MANIFEST.in\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m INFO:sagemaker-containers:Installing module with the following command:\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m /miniconda3/bin/python -m pip install . -r requirements.txt\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m Processing /opt/ml/code\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m Requirement already satisfied: pandas in /miniconda3/lib/python3.7/site-packages (from -r requirements.txt (line 1)) (0.25.1)\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m Requirement already satisfied: numpy in /miniconda3/lib/python3.7/site-packages (from -r requirements.txt (line 2)) (1.17.2)\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m Requirement already satisfied: python-dateutil>=2.6.1 in /miniconda3/lib/python3.7/site-packages (from pandas->-r requirements.txt (line 1)) (2.8.0)\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m Requirement already satisfied: pytz>=2017.2 in /miniconda3/lib/python3.7/site-packages (from pandas->-r requirements.txt (line 1)) (2019.3)\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m Requirement already satisfied: six>=1.5 in /miniconda3/lib/python3.7/site-packages (from python-dateutil>=2.6.1->pandas->-r requirements.txt (line 1)) (1.12.0)\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m Building wheels for collected packages: train-model\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m Building wheel for train-model (setup.py) ... \u001b[?25ldone\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m \u001b[?25h Created wheel for train-model: filename=train_model-1.0.0-py2.py3-none-any.whl size=12858 sha256=cbbc20f68f0e136ef85c4050e540996d0f98c89e6b741b5260e7e9873b23ebf7\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m Stored in directory: /tmp/pip-ephem-wheel-cache-zrodcnfl/wheels/35/24/16/37574d11bf9bde50616c67372a334f94fa8356bc7164af8ca3\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m Successfully built train-model\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m Installing collected packages: train-model\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m Successfully installed train-model-1.0.0\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m INFO:sagemaker-containers:No GPUs detected (normal if no gpus installed)\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m INFO:sagemaker-containers:Invoking user script\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m \n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m Training Env:\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m \n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m {\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m \"additional_framework_parameters\": {},\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m \"channel_input_dirs\": {\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m \"training\": \"/opt/ml/input/data/training\"\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m },\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m \"current_host\": \"algo-1-z7zik\",\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m \"framework_module\": \"sagemaker_xgboost_container.training:main\",\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m \"hosts\": [\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m \"algo-1-z7zik\"\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m ],\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m \"hyperparameters\": {\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m \"bonitoo_price_pos_abs\": 1000,\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m \"bonitoo_price_neg_abs\": 200,\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m \"bonitoo_price_pos_perc\": 0.05,\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m \"bonitoo_price_neg_perc\": 0.05,\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m \"num_round\": 10,\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m \"max_depth\": 15,\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m \"eta\": 0.5,\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m \"num_class\": 8,\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m \"objective\": \"multi:softprob\",\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m \"eval_metric\": \"mlogloss\"\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m },\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m \"input_config_dir\": \"/opt/ml/input/config\",\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m \"input_data_config\": {\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m \"training\": {\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m \"TrainingInputMode\": \"File\"\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m }\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m },\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m \"input_dir\": \"/opt/ml/input\",\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m \"is_master\": true,\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m \"job_name\": \"sagemaker-xgboost-2019-10-26-08-41-25-312\",\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m \"log_level\": 20,\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m \"master_hostname\": \"algo-1-z7zik\",\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m \"model_dir\": \"/opt/ml/model\",\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m \"module_dir\": \"s3://sagemaker-eu-central-1-029917565482/sagemaker-xgboost-2019-10-26-08-41-25-312/source/sourcedir.tar.gz\",\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m \"module_name\": \"train_model\",\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m \"network_interface_name\": \"eth0\",\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m \"num_cpus\": 4,\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m \"num_gpus\": 0,\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m \"output_data_dir\": \"/opt/ml/output/data\",\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m \"output_dir\": \"/opt/ml/output\",\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m \"output_intermediate_dir\": \"/opt/ml/output/intermediate\",\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m \"resource_config\": {\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m \"current_host\": \"algo-1-z7zik\",\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m \"hosts\": [\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m \"algo-1-z7zik\"\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m ]\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m },\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m \"user_entry_point\": \"train_model.py\"\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m }\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m \n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m Environment variables:\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m \n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m SM_HOSTS=[\"algo-1-z7zik\"]\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m SM_NETWORK_INTERFACE_NAME=eth0\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m SM_HPS={\"bonitoo_price_neg_abs\":200,\"bonitoo_price_neg_perc\":0.05,\"bonitoo_price_pos_abs\":1000,\"bonitoo_price_pos_perc\":0.05,\"eta\":0.5,\"eval_metric\":\"mlogloss\",\"max_depth\":15,\"num_class\":8,\"num_round\":10,\"objective\":\"multi:softprob\"}\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m SM_USER_ENTRY_POINT=train_model.py\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m SM_FRAMEWORK_PARAMS={}\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m SM_RESOURCE_CONFIG={\"current_host\":\"algo-1-z7zik\",\"hosts\":[\"algo-1-z7zik\"]}\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m SM_INPUT_DATA_CONFIG={\"training\":{\"TrainingInputMode\":\"File\"}}\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m SM_OUTPUT_DATA_DIR=/opt/ml/output/data\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m SM_CHANNELS=[\"training\"]\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m SM_CURRENT_HOST=algo-1-z7zik\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m SM_MODULE_NAME=train_model\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m SM_LOG_LEVEL=20\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m SM_FRAMEWORK_MODULE=sagemaker_xgboost_container.training:main\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m SM_INPUT_DIR=/opt/ml/input\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m SM_INPUT_CONFIG_DIR=/opt/ml/input/config\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m SM_OUTPUT_DIR=/opt/ml/output\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m SM_NUM_CPUS=4\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m SM_NUM_GPUS=0\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m SM_MODEL_DIR=/opt/ml/model\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m SM_MODULE_DIR=s3://sagemaker-eu-central-1-029917565482/sagemaker-xgboost-2019-10-26-08-41-25-312/source/sourcedir.tar.gz\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m SM_TRAINING_ENV={\"additional_framework_parameters\":{},\"channel_input_dirs\":{\"training\":\"/opt/ml/input/data/training\"},\"current_host\":\"algo-1-z7zik\",\"framework_module\":\"sagemaker_xgboost_container.training:main\",\"hosts\":[\"algo-1-z7zik\"],\"hyperparameters\":{\"bonitoo_price_neg_abs\":200,\"bonitoo_price_neg_perc\":0.05,\"bonitoo_price_pos_abs\":1000,\"bonitoo_price_pos_perc\":0.05,\"eta\":0.5,\"eval_metric\":\"mlogloss\",\"max_depth\":15,\"num_class\":8,\"num_round\":10,\"objective\":\"multi:softprob\"},\"input_config_dir\":\"/opt/ml/input/config\",\"input_data_config\":{\"training\":{\"TrainingInputMode\":\"File\"}},\"input_dir\":\"/opt/ml/input\",\"is_master\":true,\"job_name\":\"sagemaker-xgboost-2019-10-26-08-41-25-312\",\"log_level\":20,\"master_hostname\":\"algo-1-z7zik\",\"model_dir\":\"/opt/ml/model\",\"module_dir\":\"s3://sagemaker-eu-central-1-029917565482/sagemaker-xgboost-2019-10-26-08-41-25-312/source/sourcedir.tar.gz\",\"module_name\":\"train_model\",\"network_interface_name\":\"eth0\",\"num_cpus\":4,\"num_gpus\":0,\"output_data_dir\":\"/opt/ml/output/data\",\"output_dir\":\"/opt/ml/output\",\"output_intermediate_dir\":\"/opt/ml/output/intermediate\",\"resource_config\":{\"current_host\":\"algo-1-z7zik\",\"hosts\":[\"algo-1-z7zik\"]},\"user_entry_point\":\"train_model.py\"}\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m SM_USER_ARGS=[\"--bonitoo_price_neg_abs\",\"200\",\"--bonitoo_price_neg_perc\",\"0.05\",\"--bonitoo_price_pos_abs\",\"1000\",\"--bonitoo_price_pos_perc\",\"0.05\",\"--eta\",\"0.5\",\"--eval_metric\",\"mlogloss\",\"--max_depth\",\"15\",\"--num_class\",\"8\",\"--num_round\",\"10\",\"--objective\",\"multi:softprob\"]\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m SM_OUTPUT_INTERMEDIATE_DIR=/opt/ml/output/intermediate\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m SM_CHANNEL_TRAINING=/opt/ml/input/data/training\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m SM_HP_BONITOO_PRICE_POS_ABS=1000\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m SM_HP_BONITOO_PRICE_NEG_ABS=200\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m SM_HP_BONITOO_PRICE_POS_PERC=0.05\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m SM_HP_BONITOO_PRICE_NEG_PERC=0.05\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m SM_HP_NUM_ROUND=10\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m SM_HP_MAX_DEPTH=15\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m SM_HP_ETA=0.5\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m SM_HP_NUM_CLASS=8\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m SM_HP_OBJECTIVE=multi:softprob\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m SM_HP_EVAL_METRIC=mlogloss\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m PYTHONPATH=/miniconda3/bin:/:/usr/local/lib/python3.5/dist-packages/xgboost/dmlc-core/tracker:/miniconda3/lib/python37.zip:/miniconda3/lib/python3.7:/miniconda3/lib/python3.7/lib-dynload:/miniconda3/lib/python3.7/site-packages\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m \n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m Invoking script with the following command:\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m \n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m /miniconda3/bin/python -m train_model --bonitoo_price_neg_abs 200 --bonitoo_price_neg_perc 0.05 --bonitoo_price_pos_abs 1000 --bonitoo_price_pos_perc 0.05 --eta 0.5 --eval_metric mlogloss --max_depth 15 --num_class 8 --num_round 10 --objective multi:softprob\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m \n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m \n" |
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] |
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}, |
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{ |
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"name": "stdout", |
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"output_type": "stream", |
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"text": [ |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m [0]\ttrain-mlogloss:0.929483\tvalidation-mlogloss:1.0241\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m [1]\ttrain-mlogloss:0.645144\tvalidation-mlogloss:0.796067\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m [2]\ttrain-mlogloss:0.478228\tvalidation-mlogloss:0.672454\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m [3]\ttrain-mlogloss:0.369705\tvalidation-mlogloss:0.599333\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m [4]\ttrain-mlogloss:0.297172\tvalidation-mlogloss:0.556288\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m [5]\ttrain-mlogloss:0.247464\tvalidation-mlogloss:0.528165\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m [6]\ttrain-mlogloss:0.213406\tvalidation-mlogloss:0.509508\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m [7]\ttrain-mlogloss:0.186961\tvalidation-mlogloss:0.498194\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m [8]\ttrain-mlogloss:0.168055\tvalidation-mlogloss:0.490675\n", |
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"\u001b[36malgo-1-z7zik_1 |\u001b[0m [9]\ttrain-mlogloss:0.153464\tvalidation-mlogloss:0.485999\n", |
|
"\u001b[36mtmp_3oe6esm_algo-1-z7zik_1 exited with code 0\n", |
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"\u001b[0mAborting on container exit...\n", |
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"===== Job Complete =====\n" |
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] |
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} |
|
], |
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"source": [ |
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"estimator = tf.fit({'training': train_input})\n", |
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"#estimator = sklearn.attach('sagemaker-scikit-learn-2019-01-25-16-34-38-829')" |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": null, |
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"metadata": {}, |
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"outputs": [], |
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"source": [] |
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} |
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], |
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"metadata": { |
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"kernelspec": { |
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"display_name": "Python 3", |
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"language": "python", |
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"name": "python3" |
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}, |
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"language_info": { |
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"codemirror_mode": { |
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"name": "ipython", |
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"version": 3 |
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}, |
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"file_extension": ".py", |
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"mimetype": "text/x-python", |
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"name": "python", |
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"nbconvert_exporter": "python", |
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"pygments_lexer": "ipython3", |
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"version": "3.7.3" |
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} |
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}, |
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"nbformat": 4, |
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"nbformat_minor": 2 |
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}
|
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|