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Shashank Suhas
seminar-breakout
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ba855cdb
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ba855cdb
authored
Dec 14, 2017
by
Yuxin Wu
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docs/tutorial/inference.md
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@@ -28,7 +28,11 @@ But sometimes you need a different one for inference.
For example, you may need a different data layout for CPU inference,
or you may need placeholders in the inference graph, or the training graph contains multi-GPU replication
which you want to remove.
In this case, you can always create a new graph with pure TensorFlow.
In this case, you can always construct a new graph by simply:
```
python
a
,
b
=
tf
.
placeholder
(
...
),
tf
.
placeholder
(
...
)
# call symbolic functions on a, b
```
The only tool tensorpack has for after-training inference is
`OfflinePredictor`
,
a simple function to build the graph and return a callable for you.
...
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