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+### `tf.register_tensor_conversion_function(base_type, conversion_func, priority=100)` {#register_tensor_conversion_function}
+
+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:
+
+
+*  <b>`base_type`</b>: The base type or tuple of base types for all objects that
+    `conversion_func` accepts.
+*  <b>`conversion_func`</b>: A function that converts instances of `base_type` to
+    `Tensor`.
+*  <b>`priority`</b>: 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:
+
+
+*  <b>`TypeError`</b>: If the arguments do not have the appropriate type.
+