# For libraries building on TensorFlow

### tf.register_tensor_conversion_function(base_type, conversion_func, priority=100)

Registers a function for converting objects of base_type to Tensor.

The conversion function must have the following signature:

def conversion_func(value, dtype=None, name=None, as_ref=False):
# ...


It must return a Tensor with the given dtype if specified. If the conversion function creates a new Tensor, it should use the given name if specified. All exceptions will be propagated to the caller.

The conversion function may return NotImplemented for some inputs. In this case, the conversion process will continue to try subsequent conversion functions.

If as_ref is true, the function must return a Tensor reference, such as a Variable.

NOTE: The conversion functions will execute in order of priority, followed by order of registration. To ensure that a conversion function F runs before another conversion function G, ensure that F is registered with a smaller priority than G.

##### Args:
• base_type: The base type or tuple of base types for all objects that conversion_func accepts.
• conversion_func: A function that converts instances of base_type to Tensor.
• priority: Optional integer that indicates the priority for applying this conversion function. Conversion functions with smaller priority values run earlier than conversion functions with larger priority values. Defaults to 100.
##### Raises:
• TypeError: If the arguments do not have the appropriate type.