From f36c5b64cfe151fbb0e7383c6da04d5859d2baec Mon Sep 17 00:00:00 2001 From: Lauren Yu <6631887+laurenyu@users.noreply.github.com> Date: Wed, 6 Feb 2019 12:47:34 -0800 Subject: [PATCH 1/2] Switch ReadTheDocs link to stable --- README.rst | 16 ++++++++-------- 1 file changed, 8 insertions(+), 8 deletions(-) diff --git a/README.rst b/README.rst index b9534e5c82..4b545b11f0 100644 --- a/README.rst +++ b/README.rst @@ -708,8 +708,8 @@ For more detailed examples of running hyperparameter tuning jobs, see: For more detailed explanations of the classes that this library provides for automatic model tuning, see: -- `API docs for HyperparameterTuner and parameter range classes `__ -- `API docs for analytics classes `__ +- `API docs for HyperparameterTuner and parameter range classes `__ +- `API docs for analytics classes `__ SageMaker Batch Transform @@ -734,7 +734,7 @@ Alternatively, if you already have a SageMaker model, you can create an instance instance_count=1, instance_type='ml.m4.xlarge') -For a full list of the possible options to configure by using either of these methods, see the API docs for `Estimator `__ or `Transformer `__. +For a full list of the possible options to configure by using either of these methods, see the API docs for `Estimator `__ or `Transformer `__. After you create a ``Transformer`` object, you can invoke ``transform()`` to start a batch transform job with the S3 location of your data. You can also specify other attributes of your data, such as the content type. @@ -743,7 +743,7 @@ You can also specify other attributes of your data, such as the content type. transformer.transform('s3://my-bucket/batch-transform-input') -For more details about what can be specified here, see `API docs `__. +For more details about what can be specified here, see `API docs `__. Secure Training and Inference with VPC @@ -864,11 +864,11 @@ then call its ``predict()`` method with your input. You can use either the generic ``RealTimePredictor`` class, which by default does not perform any serialization/deserialization transformations on your input, but can be configured to do so through constructor arguments: -http://sagemaker.readthedocs.io/en/latest/predictors.html +http://sagemaker.readthedocs.io/en/stable/predictors.html Or you can use the TensorFlow / MXNet specific predictor classes, which have default serialization/deserialization logic: -http://sagemaker.readthedocs.io/en/latest/sagemaker.tensorflow.html#tensorflow-predictor -http://sagemaker.readthedocs.io/en/latest/sagemaker.mxnet.html#mxnet-predictor +http://sagemaker.readthedocs.io/en/stable/sagemaker.tensorflow.html#tensorflow-predictor +http://sagemaker.readthedocs.io/en/stable/sagemaker.mxnet.html#mxnet-predictor Example code using the TensorFlow predictor: @@ -887,7 +887,7 @@ That is, you can bring your own model: First, package the files for the trained model into a ``.tar.gz`` file, and upload the archive to S3. -Next, create a ``Model`` object that corresponds to the framework that you are using: `MXNetModel `__ or `TensorFlowModel `__. +Next, create a ``Model`` object that corresponds to the framework that you are using: `MXNetModel `__ or `TensorFlowModel `__. Example code using ``MXNetModel``: From c732bd1fa705741c387faf5d8dfca2bb247d4ea1 Mon Sep 17 00:00:00 2001 From: Lauren Yu <6631887+laurenyu@users.noreply.github.com> Date: Wed, 6 Feb 2019 12:49:36 -0800 Subject: [PATCH 2/2] changelog --- CHANGELOG.rst | 1 + 1 file changed, 1 insertion(+) diff --git a/CHANGELOG.rst b/CHANGELOG.rst index 187317cf64..ba53a7c879 100644 --- a/CHANGELOG.rst +++ b/CHANGELOG.rst @@ -6,6 +6,7 @@ CHANGELOG ========== * doc-fix: update information about saving models in the MXNet README +* doc-fix: change ReadTheDocs links from latest to stable 1.18.2 ======