description: Import a ConcreteFunction and convert it to a textual MLIR module.

tf.mlir.experimental.convert_function

Import a ConcreteFunction and convert it to a textual MLIR module.

tf.mlir.experimental.convert_function(
    concrete_function, pass_pipeline='tf-standard-pipeline'
)

This API is only intended for inspecting the internals of TensorFlow and the string returned is at the moment intended for debugging purposes.

A tf.function can be imported and converted from TensorFlow to TensorFlow MLIR with this API by extracting its ConcreteFunction (eagerly-executing wrapper around a tf.Graph).

For example:

>>> @tf.function
... def add(a, b):
...   return a + b

>>> concrete_function = add.get_concrete_function(
...     tf.TensorSpec(None, tf.dtypes.float32),
...     tf.TensorSpec(None, tf.dtypes.float32))
>>> tf.mlir.experimental.convert_function(concrete_function)
'...module attributes {...} {...}'

Args

concrete_function An object of type ConcreteFunction.
pass_pipeline A textual description of an MLIR Pass Pipeline to run on the module, see MLIR documentation for the textual pass pipeline syntax.

Returns

A textual representation of the MLIR module corresponding to the ConcreteFunction.

Raises

InvalidArgumentError if concrete_function is invalid or cannot be converted to MLIR.