Import a GraphDef and convert it to a textual MLIR module.
tf.mlir.experimental.convert_graph_def(
graph_def,
pass_pipeline='tf-standard-pipeline',
show_debug_info=False
)
This API is only intended for inspecting the internals of TensorFlow and the
string returned is at the moment intended for debugging purposes.
Args |
|---|
graph_def
|
An object of type graph_pb2.GraphDef or a textual proto
representation of a valid GraphDef.
|
pass_pipeline
|
A textual description of an MLIR Pass Pipeline to run on the
module, see MLIR documentation for the textual pass pipeline
syntax.
|
show_debug_info
|
Whether to include locations in the emitted textual form.
|
Returns |
|---|
|
A textual representation of the MLIR module corresponding to the graphdef.
|
Raises |
|---|
InvalidArgumentError
|
if graph_def is invalid or cannot be converted to
MLIR.
|
View source on GitHub