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authorGravatar Martin Wicke <wicke@google.com>2016-09-21 13:16:48 -0800
committerGravatar TensorFlower Gardener <gardener@tensorflow.org>2016-09-21 14:31:57 -0700
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@@ -1000,6 +1000,11 @@ cuda_op_kernel.cu.o -I $TF_INC -fPIC -lcudart
`cuda_op_kernel.so` produced above can be loaded as usual in Python, using the
`tf.load_op_library` function.
+Note that if your CUDA libraries are not installed in `/usr/local/lib64`,
+you'll need to specify the path explicitly in the second (g++) command above.
+For example, add `-L /usr/local/cuda-8.0/lib64/` if your CUDA is installed in
+`/usr/local/cuda-8.0`.
+
## Implement the gradient in Python
Given a graph of ops, TensorFlow uses automatic differentiation