Tensorflow: None of the MLIR optimization passes are enabled (registered 1)
Question:
I am using a very small model for testing purposes using tensorflow 2.3 and keras.
Looking at my terminal, I get the following warning:
I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:118] None of the MLIR optimization passes are enabled (registered 1)
However, the code works as expected. But what does this message mean?
Thanks.
Answers:
MLIR is being used as another solution to implementing and optimizing Tensorflow logic. This informative message is benign and is saying MLIR was not being used. This is expected as in TF 2.3, the MLIR based implementation is still being developed and proven, so end users are generally not expected to use the MLIR implementation and are instead expected to use the non-MLIR feature complete implementation.
Update: still experimental on version 2.9.1. On the docs it is written:
DO NOT USE, DEV AND TESTING ONLY AT THE MOMENT.
I faced exactly the same problem and Here is a one reason.
This is because of a problem with your .record file (train.record and test.record)
You need to assign verbose=1 in your code
I am using a very small model for testing purposes using tensorflow 2.3 and keras.
Looking at my terminal, I get the following warning:
I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:118] None of the MLIR optimization passes are enabled (registered 1)
However, the code works as expected. But what does this message mean?
Thanks.
MLIR is being used as another solution to implementing and optimizing Tensorflow logic. This informative message is benign and is saying MLIR was not being used. This is expected as in TF 2.3, the MLIR based implementation is still being developed and proven, so end users are generally not expected to use the MLIR implementation and are instead expected to use the non-MLIR feature complete implementation.
Update: still experimental on version 2.9.1. On the docs it is written:
DO NOT USE, DEV AND TESTING ONLY AT THE MOMENT.
I faced exactly the same problem and Here is a one reason.
This is because of a problem with your .record file (train.record and test.record)
You need to assign verbose=1 in your code