From 0498c93619bb7413e3651d73105e46d1c6461ea2 Mon Sep 17 00:00:00 2001 From: Zach Wolfe Date: Mon, 27 Nov 2017 11:21:16 -0800 Subject: [PATCH] Replace s3_input with s3_data parameter in xgboost_customer_churn Related: https://github.com/awslabs/amazon-sagemaker-examples/pull/74 I have not run this notebook, but I ran the related notebook above. Help on class s3_input in module sagemaker.session: class s3_input(builtins.object) | Amazon SageMaker channel configurations for S3 data sources. | | Attributes: | config (dict[str, dict]): A SageMaker ``DataSource`` referencing a SageMaker ``S3DataSource``. | | Methods defined here: | | __init__(self, s3_data, distribution='FullyReplicated', compression=None, content_type=None, record_wrapping=None, s3_data_type='S3Prefix') | Create a definition for input data used by an SageMaker training job. | | See AWS documentation on the ``CreateTrainingJob`` API for more details on the parameters. | | Args: | s3_data (str): Defines the location of s3 data to train on. | distribution (str): Valid values: 'FullyReplicated', 'ShardedByS3Key' | (default: 'FullyReplicated'). | compression (str): Valid values: 'Gzip', 'Bzip2', 'Lzop' (default: None). | content_type (str): MIME type of the input data (default: None). | record_wrapping (str): Valid values: 'RecordIO' (default: None). | s3_data_type (str): Value values: 'S3Prefix', 'ManifestFile'. If 'S3Prefix', ``s3_data`` defines | a prefix of s3 objects to train on. All objects with s3 keys beginning with ``s3_data`` will | be used to train. If 'ManifestFile', then ``s3_data`` defines a single s3 manifest file, listing | each s3 object to train on. The Manifest file format is described in the SageMaker API documentation: | https://aws.amazon.com/sagemaker/latest/dg/API_S3DataSource.html | --- .../xgboost_customer_churn/xgboost_customer_churn.ipynb | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/introduction_to_applying_machine_learning/xgboost_customer_churn/xgboost_customer_churn.ipynb b/introduction_to_applying_machine_learning/xgboost_customer_churn/xgboost_customer_churn.ipynb index b69b8b380c..f3002c6f47 100644 --- a/introduction_to_applying_machine_learning/xgboost_customer_churn/xgboost_customer_churn.ipynb +++ b/introduction_to_applying_machine_learning/xgboost_customer_churn/xgboost_customer_churn.ipynb @@ -343,8 +343,8 @@ "metadata": {}, "outputs": [], "source": [ - "s3_input_train = sagemaker.s3_input(s3_prefix='s3://{}/{}/train'.format(bucket, prefix), content_type='csv')\n", - "s3_input_validation = sagemaker.s3_input(s3_prefix='s3://{}/{}/validation/'.format(bucket, prefix), content_type='csv')" + "s3_input_train = sagemaker.s3_input(s3_data='s3://{}/{}/train'.format(bucket, prefix), content_type='csv')\n", + "s3_input_validation = sagemaker.s3_input(s3_data='s3://{}/{}/validation/'.format(bucket, prefix), content_type='csv')" ] }, {