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update xgboost version to 1.5-1 in notebooks #3439

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merged 5 commits into from
Jun 16, 2022
Merged

update xgboost version to 1.5-1 in notebooks #3439

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60fad45
Merge pull request #1 from aws/main
haixiw May 19, 2022
7376291
update xgboost to 1.5-1
Jun 2, 2022
dd41b3e
add time stamp to endpoint configuration
Jun 3, 2022
01041fb
fix typo
Jun 3, 2022
11cdce8
code formatting change
Jun 16, 2022
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10 changes: 6 additions & 4 deletions ...unctionality/multi_model_xgboost_home_value/xgboost_multi_model_endpoint_home_value.ipynb
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Expand Up @@ -101,6 +101,7 @@
],
"source": [
"import sagemaker\n",
"\n",
"print(sagemaker.__version__)"
]
},
Expand Down Expand Up @@ -338,6 +339,7 @@
"from sagemaker import get_execution_role\n",
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Line #27.    ENDPOINT_NAME = f'mme-xgboost-housing-{strftime("%Y-%m-%d-%H-%M-%S", gmtime())}'

Please run black-nb -l 100 {notebook-name}.ipynb for each notebook to apply code formatting - the standard is double quotes.


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Thanks, I used this command and with new commits it passed the code-formatting check

"from sagemaker.amazon.amazon_estimator import image_uris\n",
"import boto3\n",
"from time import gmtime, strftime\n",
"\n",
"from sklearn.model_selection import train_test_split\n",
"\n",
Expand All @@ -350,7 +352,7 @@
"\n",
"# This is references the AWS managed XGBoost container\n",
"XGBOOST_IMAGE = image_uris.retrieve(\n",
" region=boto3.Session().region_name, framework=\"xgboost\", version=\"1.0-1\"\n",
" region=boto3.Session().region_name, framework=\"xgboost\", version=\"1.5-1\"\n",
")\n",
"\n",
"DATA_PREFIX = \"XGBOOST_BOSTON_HOUSING\"\n",
Expand All @@ -359,7 +361,7 @@
"TRAIN_INSTANCE_TYPE = \"ml.m4.xlarge\"\n",
"ENDPOINT_INSTANCE_TYPE = \"ml.m4.xlarge\"\n",
"\n",
"ENDPOINT_NAME = \"mme-xgboost-housing\"\n",
"ENDPOINT_NAME = f'mme-xgboost-housing-{strftime(\"%Y-%m-%d-%H-%M-%S\", gmtime())}'\n",
"\n",
"MODEL_NAME = ENDPOINT_NAME"
]
Expand Down Expand Up @@ -506,9 +508,9 @@
" gamma=4,\n",
" min_child_weight=6,\n",
" subsample=0.8,\n",
" silent=0,\n",
" verbosity=0,\n",
" early_stopping_rounds=5,\n",
" objective=\"reg:linear\",\n",
" objective=\"reg:squarederror\",\n",
" num_round=25,\n",
" )\n",
"\n",
Expand Down
17 changes: 9 additions & 8 deletions ...maker_neo_compilation_jobs/xgboost_customer_churn/xgboost_customer_churn_neo_studio.ipynb
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Expand Up @@ -316,7 +316,7 @@
"from sagemaker import image_uris\n",
"\n",
"container = image_uris.retrieve(\n",
" framework=\"xgboost\", region=boto3.Session().region_name, version=\"1.0-1\"\n",
" framework=\"xgboost\", region=boto3.Session().region_name, version=\"1.5-1\"\n",
")"
]
},
Expand Down Expand Up @@ -377,7 +377,7 @@
" gamma=4,\n",
" min_child_weight=6,\n",
" subsample=0.8,\n",
" silent=0,\n",
" verbosity=0,\n",
" objective=\"binary:logistic\",\n",
" num_round=100,\n",
")\n",
Expand Down Expand Up @@ -437,9 +437,9 @@
" split_array = np.array_split(data, int(data.shape[0] / float(rows) + 1))\n",
" predictions = \"\"\n",
" for array in split_array:\n",
" predictions = \",\".join([predictions, xgb_predictor.predict(array).decode(\"utf-8\")])\n",
" predictions = \"\".join([predictions, xgb_predictor.predict(array).decode(\"utf-8\")])\n",
"\n",
" return np.fromstring(predictions[1:], sep=\",\")\n",
" return predictions.split(\"\\n\")[:-1]\n",
"\n",
"\n",
"predictions = predict(test_data.values[:, 1:])"
Expand All @@ -458,6 +458,7 @@
"metadata": {},
"outputs": [],
"source": [
"predictions = np.array([float(num) for num in predictions])\n",
"pd.crosstab(\n",
" index=test_data.iloc[:, 0],\n",
" columns=np.round(predictions),\n",
Expand Down Expand Up @@ -621,7 +622,7 @@
" input_shape={\"data\": [1, 69]},\n",
" role=role,\n",
" framework=\"xgboost\",\n",
" framework_version=\"latest\",\n",
" framework_version=\"1.5-1\",\n",
" output_path=output_path,\n",
")"
]
Expand Down Expand Up @@ -670,9 +671,9 @@
" split_array = np.array_split(data, int(data.shape[0] / float(rows) + 1))\n",
" predictions = \"\"\n",
" for array in split_array:\n",
" predictions = \",\".join([predictions, compiled_predictor.predict(array).decode(\"utf-8\")])\n",
" predictions = \"\".join([predictions, xgb_predictor.predict(array).decode(\"utf-8\")])\n",
"\n",
" return np.fromstring(predictions[1:], sep=\",\")\n",
" return predictions.split(\"\\n\")[:-1]\n",
"\n",
"\n",
"predictions = optimized_predict(test_data.values[:, 1:])"
Expand Down Expand Up @@ -721,4 +722,4 @@
},
"nbformat": 4,
"nbformat_minor": 4
}
}
2 changes: 1 addition & 1 deletion ...rameter_tuning/xgboost_direct_marketing/hpo_xgboost_direct_marketing_sagemaker_APIs.ipynb
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Expand Up @@ -383,7 +383,7 @@
"source": [
"from sagemaker.image_uris import retrieve\n",
"\n",
"training_image = retrieve(framework=\"xgboost\", region=region, version=\"latest\")\n",
"training_image = retrieve(framework=\"xgboost\", region=region, version=\"1.5-1\")\n",
"\n",
"s3_input_train = \"s3://{}/{}/train\".format(bucket, prefix)\n",
"s3_input_validation = \"s3://{}/{}/validation/\".format(bucket, prefix)\n",
Expand Down
6 changes: 3 additions & 3 deletions introduction_to_amazon_algorithms/xgboost_mnist/xgboost_mnist.ipynb
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Expand Up @@ -255,7 +255,7 @@
"source": [
"from sagemaker.image_uris import retrieve\n",
"\n",
"container = retrieve(framework=\"xgboost\", region=region, version=\"1.0-1\")"
"container = retrieve(framework=\"xgboost\", region=region, version=\"1.5-1\")"
]
},
{
Expand All @@ -275,7 +275,7 @@
" \"eta\": \"0.2\",\n",
" \"gamma\": \"4\",\n",
" \"min_child_weight\": \"6\",\n",
" \"silent\": \"0\",\n",
" \"verbosity\": \"0\",\n",
" \"objective\": \"multi:softmax\",\n",
" \"num_class\": \"10\",\n",
" \"num_round\": \"10\",\n",
Expand Down Expand Up @@ -636,7 +636,7 @@
" EndpointName=endpoint_name, ContentType=content_type, Body=payload\n",
" )\n",
" result = response[\"Body\"].read().decode(\"ascii\")\n",
" preds = [float(num) for num in result.split(\",\")]\n",
" preds = [float(num) for num in result.split(\"\\n\")[:-1]]\n",
" return preds\n",
"\n",
"\n",
Expand Down
9 changes: 5 additions & 4 deletions ...oduction_to_applying_machine_learning/xgboost_customer_churn/xgboost_customer_churn.ipynb
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Expand Up @@ -677,7 +677,7 @@
},
"outputs": [],
"source": [
"container = sagemaker.image_uris.retrieve(\"xgboost\", sess.boto_region_name, \"latest\")\n",
"container = sagemaker.image_uris.retrieve(\"xgboost\", sess.boto_region_name, \"1.5-1\")\n",
"display(container)"
]
},
Expand Down Expand Up @@ -790,7 +790,7 @@
" gamma=4,\n",
" min_child_weight=6,\n",
" subsample=0.8,\n",
" silent=0,\n",
" verbosity=0,\n",
" objective=\"binary:logistic\",\n",
" num_round=100,\n",
")\n",
Expand Down Expand Up @@ -900,9 +900,9 @@
" split_array = np.array_split(data, int(data.shape[0] / float(rows) + 1))\n",
" predictions = \"\"\n",
" for array in split_array:\n",
" predictions = \",\".join([predictions, xgb_predictor.predict(array).decode(\"utf-8\")])\n",
" predictions = \"\".join([predictions, xgb_predictor.predict(array).decode(\"utf-8\")])\n",
"\n",
" return np.fromstring(predictions[1:], sep=\",\")\n",
" return predictions.split(\"\\n\")[:-1]\n",
"\n",
"\n",
"predictions = predict(test_data.to_numpy()[:, 1:])"
Expand All @@ -915,6 +915,7 @@
"metadata": {},
"outputs": [],
"source": [
"predictions = np.array([float(num) for num in predictions])\n",
"print(predictions)"
]
},
Expand Down
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