I converted the VCTK multiband melgan model which was made from converted weights from kan-bayashi's repo into a SavedModel as detailed in the multiband melgan inference notebook and it works fine in Python but when loading it into the C API (the same way I loaded a FastSpeech2 model and ran inference) and trying to run inference I get this:

You must feed a value for placeholder tensor 'saver_filename' with dtype string
         [[{{node saver_filename}}]]

When I feed it that value with anything, it first saves the weights then throws an error saying that it can't find the weights, or if they're already there, throws another error saying that it can't find a certain variable.
For reference, these are the last operations in the loaded model: (StatefulPartitionedCall_xxs are the outputs)

NoOp
Const
serving_default_mels
StatefulPartitionedCall
saver_filename
StatefulPartitionedCall_1
StatefulPartitionedCall_2

The FastSpeech2 model did not have this layer and it ran well, so I doubt it's an issue with my implementation.