|
enable_bulk_inferrer=True, |
The BulkInferrer component fails in the unit tests provided by the penguin examples.
The error is:
Could not find variable dense_6/bias. This could mean that the variable has been deleted. In TF1, it can also mean the variable is uninitialized. Debug info: container=localhost, status error message=Resource localhost/dense_6/bias/N10tensorflow3VarE does not exist.
[[{{node functional_2_1/dense_6_1/Add/ReadVariableOp}}]] [while running 'RunInference[train]/RunInference/RunInferenceImpl/BulkInference/BeamML_RunInference']
Steps to reproduce:
git clone https://github.com/tensorflow/tfx.git
git checkout v1.16.0
(set up a virtual environment for python 3.10, and install dependencies in test_constraints.txt)
cd tfx/examples/penguin
python -m unittest penguin_pipeline_local_e2e_test.py
The test for which enable_bulk_inferror=True, fails
This was run on a system with Ubuntu 24.04, python 3.10.
Note that I separately checked that the saved_model could be loaded, the "serving_default" signature extracted, and that the extracted method successfully gave predictions given examples.
tfx/tfx/examples/penguin/penguin_pipeline_local_e2e_test.py
Line 256 in c423075
The BulkInferrer component fails in the unit tests provided by the penguin examples.
The error is:
Could not find variable dense_6/bias. This could mean that the variable has been deleted. In TF1, it can also mean the variable is uninitialized. Debug info: container=localhost, status error message=Resource localhost/dense_6/bias/N10tensorflow3VarE does not exist.
[[{{node functional_2_1/dense_6_1/Add/ReadVariableOp}}]] [while running 'RunInference[train]/RunInference/RunInferenceImpl/BulkInference/BeamML_RunInference']
Steps to reproduce:
git clone https://github.com/tensorflow/tfx.git
git checkout v1.16.0
(set up a virtual environment for python 3.10, and install dependencies in test_constraints.txt)
cd tfx/examples/penguin
python -m unittest penguin_pipeline_local_e2e_test.py
The test for which enable_bulk_inferror=True, fails
This was run on a system with Ubuntu 24.04, python 3.10.
Note that I separately checked that the saved_model could be loaded, the "serving_default" signature extracted, and that the extracted method successfully gave predictions given examples.