From 4baa4ec06571ec8f2d8cac08e9651436efc48c2f Mon Sep 17 00:00:00 2001 From: Nicholas Connor Date: Fri, 10 Aug 2018 10:30:32 -0400 Subject: [PATCH] PipeModeDataset code block example improvements * removed duplicate `PipeModeDataset` instantiation * wrap usage in `train_input_fn` to match other examples --- src/sagemaker/tensorflow/README.rst | 15 +++++++-------- 1 file changed, 7 insertions(+), 8 deletions(-) diff --git a/src/sagemaker/tensorflow/README.rst b/src/sagemaker/tensorflow/README.rst index d9c9c59df6..031a354401 100644 --- a/src/sagemaker/tensorflow/README.rst +++ b/src/sagemaker/tensorflow/README.rst @@ -779,8 +779,6 @@ In your ``entry_point`` script, you can use ``PipeModeDataset`` like a ``Dataset from sagemaker_tensorflow import PipeModeDataset - ds = PipeModeDataset(channel='training', record_format='TFRecord') - features = { 'data': tf.FixedLenFeature([], tf.string), 'labels': tf.FixedLenFeature([], tf.int64), @@ -792,12 +790,13 @@ In your ``entry_point`` script, you can use ``PipeModeDataset`` like a ``Dataset 'data': tf.decode_raw(parsed['data'], tf.float64) }, parsed['labels']) - ds = PipeModeDataset(channel='training', record_format='TFRecord') - num_epochs = 20 - ds = ds.repeat(num_epochs) - ds = ds.prefetch(10) - ds = ds.map(parse, num_parallel_calls=10) - ds = ds.batch(64) + def train_input_fn(training_dir, hyperparameters): + ds = PipeModeDataset(channel='training', record_format='TFRecord') + ds = ds.repeat(20) + ds = ds.prefetch(10) + ds = ds.map(parse, num_parallel_calls=10) + ds = ds.batch(64) + return ds To run training job with Pipe input mode, pass in ``input_mode='Pipe'`` to your TensorFlow Estimator: