diff --git a/src/sagemaker/chainer/README.rst b/src/sagemaker/chainer/README.rst index d7af76b500..248c4f82ff 100644 --- a/src/sagemaker/chainer/README.rst +++ b/src/sagemaker/chainer/README.rst @@ -158,7 +158,7 @@ The following are optional arguments. When you create a ``Chainer`` object, you - ``train_volume_size`` Size in GB of the EBS volume to use for storing input data during training. Must be large enough to store training data if input_mode='File' is used (which is the default). -- ``train_max_run`` Timeout in hours for training, after which Amazon +- ``train_max_run`` Timeout in seconds for training, after which Amazon SageMaker terminates the job regardless of its current status. - ``input_mode`` The input mode that the algorithm supports. Valid modes: 'File' - Amazon SageMaker copies the training dataset from the diff --git a/src/sagemaker/mxnet/README.rst b/src/sagemaker/mxnet/README.rst index 23ec1dd061..a297ab046c 100644 --- a/src/sagemaker/mxnet/README.rst +++ b/src/sagemaker/mxnet/README.rst @@ -136,7 +136,7 @@ The following are optional arguments. When you create an ``MXNet`` object, you c - ``train_volume_size`` Size in GB of the EBS volume to use for storing input data during training. Must be large enough to store training data if input_mode='File' is used (which is the default). -- ``train_max_run`` Timeout in hours for training, after which Amazon +- ``train_max_run`` Timeout in seconds for training, after which Amazon SageMaker terminates the job regardless of its current status. - ``input_mode`` The input mode that the algorithm supports. Valid modes: 'File' - Amazon SageMaker copies the training dataset from the diff --git a/src/sagemaker/pytorch/README.rst b/src/sagemaker/pytorch/README.rst index 9cc80e3da1..24cc270543 100644 --- a/src/sagemaker/pytorch/README.rst +++ b/src/sagemaker/pytorch/README.rst @@ -187,7 +187,7 @@ The following are optional arguments. When you create a ``PyTorch`` object, you - ``train_volume_size`` Size in GB of the EBS volume to use for storing input data during training. Must be large enough to store training data if input_mode='File' is used (which is the default). -- ``train_max_run`` Timeout in hours for training, after which Amazon +- ``train_max_run`` Timeout in seconds for training, after which Amazon SageMaker terminates the job regardless of its current status. - ``input_mode`` The input mode that the algorithm supports. Valid modes: 'File' - Amazon SageMaker copies the training dataset from the diff --git a/src/sagemaker/tensorflow/README.rst b/src/sagemaker/tensorflow/README.rst index 57fd202f73..d9c9c59df6 100644 --- a/src/sagemaker/tensorflow/README.rst +++ b/src/sagemaker/tensorflow/README.rst @@ -414,7 +414,7 @@ you can specify these as keyword arguments. - ``train_volume_size (int)`` Size in GB of the EBS volume to use for storing input data during training. Must be large enough to the store training data. -- ``train_max_run (int)`` Timeout in hours for training, after which Amazon +- ``train_max_run (int)`` Timeout in seconds for training, after which Amazon SageMaker terminates the job regardless of its current status. - ``output_path (str)`` S3 location where you want the training result (model artifacts and optional output files) saved. If not specified, results