From b7ae0d56947bd981c7abcdc18ff69b9f01bc2480 Mon Sep 17 00:00:00 2001 From: Faith Xu Date: Sun, 7 Jul 2019 21:56:18 -0700 Subject: [PATCH] Fix link (#1351) * Fix link * Update PyOp.md --- docs/PyOp.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/PyOp.md b/docs/PyOp.md index 4f30a33e42..e82d7b6995 100644 --- a/docs/PyOp.md +++ b/docs/PyOp.md @@ -2,7 +2,7 @@ The Python Operator provides the capability to easily invoke any custom Python code within a single node of an ONNX graph using ONNX Runtime. This can be useful for quicker experimentation when a model requires operators that are not officially supported in ONNX and ONNX Runtime, particularly if there is already a Python implementation for the required functionality. This should be used with discretion in production scenarios, and all security or other risks should be considered. ## Design Overview -The feature can be found under [onnxruntime/core/language_interop_ops](onnxruntime/core/language_interop_ops). +The feature can be found under [onnxruntime/core/language_interop_ops](../onnxruntime/core/language_interop_ops). All Python C API dependent code are compiled into a dynamic linked library named pywrapper. Before calling into Python script, pywrapper will convert onnxruntime tensor(s) to numpy(s), which is converted back when completed.

Here is a chart illustrating the calling sequence: