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-rw-r--r--tensorflow/docs_src/extend/adding_an_op.md6
1 files changed, 3 insertions, 3 deletions
diff --git a/tensorflow/docs_src/extend/adding_an_op.md b/tensorflow/docs_src/extend/adding_an_op.md
index 99933b75b4..3586794418 100644
--- a/tensorflow/docs_src/extend/adding_an_op.md
+++ b/tensorflow/docs_src/extend/adding_an_op.md
@@ -42,7 +42,7 @@ To incorporate your custom op you'll need to:
Python @{tf.test.compute_gradient_error$gradient checker}.
See
[`relu_op_test.py`](https://www.tensorflow.org/code/tensorflow/python/kernel_tests/relu_op_test.py) as
- an example that does tests the forward functions of Relu-like operators and
+ an example that tests the forward functions of Relu-like operators and
their gradients.
PREREQUISITES:
@@ -345,7 +345,7 @@ building the `.so` file.
> the older ABI. If you compile your op library with `gcc>=5`, add
> `-D_GLIBCXX_USE_CXX11_ABI=0` to the command line to make the library
> compatible with the older abi.
-> Furthermore if you are using TensorFlow package created from source remember to add `-cxxopt="-D_GLIBCXX_USE_CXX11_ABI=0"`
+> Furthermore if you are using TensorFlow package created from source remember to add `--cxxopt="-D_GLIBCXX_USE_CXX11_ABI=0"`
> as bazel command to compile the Python package.
### Compile the op using bazel (TensorFlow source installation)
@@ -382,7 +382,7 @@ TensorFlow Python API provides the
load the dynamic library and register the op with the TensorFlow
framework. `load_op_library` returns a Python module that contains the Python
wrappers for the op and the kernel. Thus, once you have built the op, you can
-do the following to run it from Python :
+do the following to run it from Python:
```python
import tensorflow as tf