Call self.post_init() in __init__

transformers 5.x sets all_tied_weights_keys inside PreTrainedModel.post_init(), and its loading path then reads that attribute directly, so a model whose __init__ skips post_init() fails with AttributeError on load.

Under 4.x the call is a no-op here: the module tree is empty at __init__ time and the real weights are loaded later by load_variant, so nothing is re-initialised.

Verified: outputs are bit-identical with and without the call under transformers 4.57.6 (max|diff| = 0.0), and the model loads under 5.3.0 only with it.

modeling_vjepa2_fmri_encoder.py

@@ -214,6 +214,7 @@ class VJEPA2FMRIEncoderModel(PreTrainedModel):
         self.decoders = nn.ModuleList()
         self.extractor = None
         self.vjepa = None
+        self.post_init()
 
     @classmethod
     def from_pretrained(cls, pretrained_model_name_or_path, *args, config=None, variant=None, load_vjepa=None, **kwargs):