Best way to modify a built-in TensorFlow kernel - tensorflow

Question

I would like to learn the best way to modify TensorFlow built-in operator kernels.
For example, I want to modify the value of static const double A in tensorflow/core/kernels/resize_bicubic_op.cc. I have come up with two possible ways:
Modify it directly and recompile the whole TensorFlow library. The problems of this solution are: A. This influences all the functions which use bicubic interpolation. B. This requires me to recompile the entire library and does not work when installing from a binary.
Define it as a custom op. The problem is that in the source code, there is no REGISTER_OP() inside. I don't know how to write the REGISTER_OP() for this bicubic function and whether other modification needs to be made.
Are there other better ways?
Thanks.

Answer 1

The best way to approach this problem is to build a custom op. See this tutorial for more details about how to add custom ops in general. The REGISTER_OP call for the tf.image.resize_bicubic() op is in tensorflow/core/ops/image_ops.cc.
Another alternative is to re-use the same op registration, and register a new kernel with the alternative implementation. This would enable you to use the (experimental) Graph.kernel_label_map() API to select an alternative implementation for the "ResizeBicubic" op. For example, you could do the following in your Python program:
_ = tf.load_op_library(...) # Load the .so containing your implementation.
with tf.get_default_graph().kernel_label_map({"ResizeBicubic": "my_impl"}):
images = tf.image.resize_bicubic(...) # Will use your implementation.
...and add a kernel registration that specifies the label "my_impl" with your C++ code:
template <typename Device, typename T>
class MyResizeBicubicOp<Device, T> : public OpKernel {
// Custom implementation goes here...
}
#define REGISTER_KERNEL(T) \
REGISTER_KERNEL_BUILDER(Name("ResizeBicubic") \
.Device(DEVICE_CPU) \
.Label("my_impl") \
.TypeConstraint<T>("T") \
.HostMemory("size"), \
MyResizeBicubicOp<CPUDevice, T>);
TF_CALL_REAL_NUMBER_TYPES(REGISTER_KERNEL);