# tf.mlir.experimental.convert_graph_def

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| [![](https://www.tensorflow.org/images/GitHub-Mark-32px.png) View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v2.14.0/tensorflow/python/compiler/mlir/mlir.py#L21-L45) |

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

#### View aliases


**Compat aliases for migration**

See
[Migration guide](https://www.tensorflow.org/guide/migrate) for
more details.

[`tf.compat.v1.mlir.experimental.convert_graph_def`](https://www.tensorflow.org/api_docs/python/tf/mlir/experimental/convert_graph_def)

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    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.

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| ## 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](https://mlir.llvm.org/docs/PassManagement/#textual-pass-pipeline-specification). |
| `show_debug_info` | Whether to include locations in the emitted textual form. |

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| ## Returns ||
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| A textual representation of the MLIR module corresponding to the graphdef. ||

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| ## Raises ||
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| `InvalidArgumentError` | if graph_def is invalid or cannot be converted to MLIR. |

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