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PipeModeDataset code block example improvements #346

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Merged
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Aug 14, 2018
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PipeModeDataset code block example improvements #346

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PipeModeDataset code block example improvements
nkconnor Aug 10, 2018
4803933
Merge branch 'master' into patch-2
ChoiByungWook Aug 14, 2018
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15 changes: 7 additions & 8 deletions src/sagemaker/tensorflow/README.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -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),
Expand All @@ -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:
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