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26-Nov: Fixes to Issue #1800 and SDKv2 corrections #1801

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Nov 27, 2020
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26-Nov: Fixes to Issue #1800 and SDKv2 corrections #1801

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48 changes: 37 additions & 11 deletions introduction_to_amazon_algorithms/deepar_electricity/DeepAR-Electricity.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -16,11 +16,23 @@
"* Make requests to the deployed model to obtain forecasts interactively\n",
"* Illustrate advanced features of DeepAR: missing values, additional time features, non-regular frequencies and category information\n",
"\n",
"Running this notebook takes around 40 min on a ml.c4.2xlarge for the training, and inference is done on a ml.m4.xlarge (the usage time will depend on how long you leave your served model running).\n",
"Running this notebook takes around 40 min on a ml.c4.2xlarge for the training, and inference is done on a ml.m5.large (the usage time will depend on how long you leave your served model running).\n",
"\n",
"This notebook is tested using SageMaker Studio but using classic Notebook (From the SageMaker Menu, go to Help -> select `Launch Classic Notebook`). \n",
"\n",
"For more information see the DeepAR [documentation](https://docs.aws.amazon.com/sagemaker/latest/dg/deepar.html) or [paper](https://arxiv.org/abs/1704.04110), "
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import sys\n",
"!{sys.executable} -m pip install s3fs"
]
},
{
"cell_type": "code",
"execution_count": null,
Expand Down Expand Up @@ -116,7 +128,9 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"metadata": {
"scrolled": false
},
"outputs": [],
"source": [
"image_name = sagemaker.amazon.amazon_estimator.get_image_uri(region, \"forecasting-deepar\", \"latest\")"
Expand Down Expand Up @@ -424,8 +438,8 @@
"outputs": [],
"source": [
"estimator = sagemaker.estimator.Estimator(\n",
" image_uri=image_name,\n",
" sagemaker_session=sagemaker_session,\n",
" image_name=image_name,\n",
" role=role,\n",
" train_instance_count=1,\n",
" train_instance_type='ml.c4.2xlarge',\n",
Expand Down Expand Up @@ -530,10 +544,22 @@
"metadata": {},
"outputs": [],
"source": [
"class DeepARPredictor(sagemaker.predictor.RealTimePredictor):\n",
"from sagemaker.serializers import IdentitySerializer"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"class DeepARPredictor(sagemaker.predictor.Predictor):\n",
" \n",
" def __init__(self, *args, **kwargs):\n",
" super().__init__(*args, content_type=sagemaker.content_types.CONTENT_TYPE_JSON, **kwargs)\n",
" super().__init__(*args, \n",
" #serializer=JSONSerializer(),\n",
" serializer=IdentitySerializer(content_type=\"application/json\"),\n",
" **kwargs)\n",
" \n",
" def predict(self, ts, cat=None, dynamic_feat=None, \n",
" num_samples=100, return_samples=False, quantiles=[\"0.1\", \"0.5\", \"0.9\"]):\n",
Expand All @@ -556,7 +582,7 @@
" \n",
" def __encode_request(self, ts, cat, dynamic_feat, num_samples, return_samples, quantiles):\n",
" instance = series_to_dict(ts, cat if cat is not None else None, dynamic_feat if dynamic_feat else None)\n",
"\n",
" \n",
" configuration = {\n",
" \"num_samples\": num_samples,\n",
" \"output_types\": [\"quantiles\", \"samples\"] if return_samples else [\"quantiles\"],\n",
Expand Down Expand Up @@ -619,7 +645,7 @@
"source": [
"predictor = estimator.deploy(\n",
" initial_instance_count=1,\n",
" instance_type='ml.m4.xlarge',\n",
" instance_type='ml.m5.large',\n",
" predictor_cls=DeepARPredictor)"
]
},
Expand Down Expand Up @@ -984,8 +1010,8 @@
"source": [
"%%time\n",
"estimator_new_features = sagemaker.estimator.Estimator(\n",
" image_uri=image_name,\n",
" sagemaker_session=sagemaker_session,\n",
" image_name=image_name,\n",
" role=role,\n",
" train_instance_count=1,\n",
" train_instance_type='ml.c4.2xlarge',\n",
Expand Down Expand Up @@ -1030,7 +1056,7 @@
"%%time\n",
"predictor_new_features = estimator_new_features.deploy(\n",
" initial_instance_count=1,\n",
" instance_type='ml.m4.xlarge',\n",
" instance_type='ml.m5.large',\n",
" predictor_cls=DeepARPredictor)"
]
},
Expand Down Expand Up @@ -1115,9 +1141,9 @@
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"display_name": "Python 3 (Data Science)",
"language": "python",
"name": "python3"
"name": "python3__SAGEMAKER_INTERNAL__arn:aws:sagemaker:us-east-1:081325390199:image/datascience-1.0"
},
"language_info": {
"codemirror_mode": {
Expand Down