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merged 2 commits into from
May 30, 2018
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fix link to npy #202

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fix link to npy
May 29, 2018
cf9ce91
Merge branch 'master' into readme-link-fix
winstonaws May 30, 2018
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6 changes: 2 additions & 4 deletions README.rst
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Expand Up @@ -1957,12 +1957,10 @@ You can provide your own implementations for these functions in your hosting scr
If you omit any definition then the SageMaker Chainer model server will use its default implementation for that
function.

The ``RealTimePredictor`` used by Chainer in the SageMaker Python SDK serializes NumPy arrays to the NPY_ format
The ``RealTimePredictor`` used by Chainer in the SageMaker Python SDK serializes NumPy arrays to the `NPY <https://docs.scipy.org/doc/numpy/neps/npy-format.html>`_ format
by default, with Content-Type ``application/x-npy``. The SageMaker Chainer model server can deserialize NPY-formatted
data (along with JSON and CSV data).

.. _NPY https://docs.scipy.org/doc/numpy/neps/npy-format.html

If you rely solely on the SageMaker Chainer model server defaults, you get the following functionality:

- Prediction on models that implement the ``__call__`` method
Expand Down Expand Up @@ -1998,7 +1996,7 @@ Where ``request_body`` is a byte buffer and ``request_content_type`` is a Python
The SageMaker Chainer model server provides a default implementation of ``input_fn``.
This function deserializes JSON, CSV, or NPY encoded data into a NumPy array.

Default NPY deserialization requires ``request_body`` to follow the NPY_ format. For Chainer, the Python SDK
Default NPY deserialization requires ``request_body`` to follow the `NPY <https://docs.scipy.org/doc/numpy/neps/npy-format.html>`_ format. For Chainer, the Python SDK
defaults to sending prediction requests with this format.

Default json deserialization requires ``request_body`` contain a single json list.
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