I create a model based on efficientNet_b0, when I tried to save it in the default keras format it gave the following error:
KeyError: “Failed to add concrete function ‘b’__inference_EfficientNet_layer_call_fn_1379410’’ to object-based SavedModel as it captures tensor <tf.Tensor: shape=(), dtype=resource, value=> which is unsupported or not reachable One reason could be that a stateful object or a variable that the function depends on is not assigned to an attribute of the serialized trackable object (see SaveTest.test_captures_unreachable_variable).”
So, I saved it to .h5, but the result was not the same as the one obtained before (this on the same dataset).
Previously obtained result:
- Confusion Matrix
231 0
0 97
Result obtained with the load in .h5 format:
- Confusion Matrix
231 62
0 35
So, I try this problem, I just saved the weights, and I recreated the architecture, and the result is back to normal.
Any tips where I might be going wrong? And how to fix the error of saving by keras default mode?