Add troubleshooting page for TF sessions used in predict method (#1141)

Co-authored-by: David Eliahu <deliahu@users.noreply.github.com>
(cherry picked from commit 54d3d26)

Author: deliahu

docs/summary.md

@@ -47,6 +47,7 @@
 
 * [API is stuck updating](troubleshooting/stuck-updating.md)
 * [NVIDIA runtime not found](troubleshooting/nvidia-container-runtime-not-found.md)
+* [TF session in predict()](troubleshooting/tf-session-in-predict.md)
 
 ## Guides
 

docs/troubleshooting/tf-session-in-predict.md

@@ -0,0 +1,18 @@
+# Using TensorFlow session in predict method
+
+When doing inferences with TensorFlow using the [Python Predictor](../deployments/predictors.md#python-predictor), it should be noted that your Python Predictor's `__init__()` constructor is only called on one thread, whereas its `predict()` method can run on any of the available threads (which is configured via the `threads_per_process` field in the API's `predictor` configuration). If `threads_per_process` is set to `1` (the default value), then there is no concern, since `__init__()` and `predict()` will run on the same thread. However, if `threads_per_process` is greater than `1`, then only one of the inference threads will have executed the `__init__()` function. This can cause issues with TensorFlow because the default graph is a property of the current thread, so if `__init__()` initializes the TensorFlow graph, only the thread that executed `__init__()` will have the default graph set.
+
+The error you may see if the default graph is not set (as a consequence of `__init__()` and `predict()` running in separate threads) is:
+
+```text
+TypeError: Cannot interpret feed_dict key as Tensor: Tensor Tensor("Placeholder:0", shape=(1, ?), dtype=int32) is not an element of this graph.
+```
+
+To avoid this error, you can set the default graph before running the prediction in the `predict()` method:
+
+```python
+
+def predict(self, payload):
+    with self.sess.graph.as_default():
+        # perform your inference here
+```