Typo in READMEs regarding train_max_run parameter

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

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

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

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