adding application

app.py

@@ -12,10 +12,10 @@ import torch
 from tqdm import tqdm
 from abc import ABC, abstractmethod
 
-from .utils.enums import MultiTokenKind, RetrievalTechniques
+from enums import MultiTokenKind, RetrievalTechniques
 from .processor import RetrievalProcessor
-from .utils.logit_lens import ReverseLogitLens
-from .utils.model_utils import extract_token_i_hidden_states
+# from .utils.logit_lens import ReverseLogitLens
+from model_utils import extract_token_i_hidden_states
 
 
 class WordRetrieverBase(ABC):
@@ -118,15 +118,15 @@ class PatchscopesRetriever(WordRetrieverBase):
         return patchscopes_description_by_layers, last_token_hidden_states
 
 
-class ReverseLogitLensRetriever(WordRetrieverBase):
-    def __init__(self, model, tokenizer, device='cuda', dtype=torch.float16):
-        super().__init__(model, tokenizer)
-        self.reverse_logit_lens = ReverseLogitLens.from_model(model).to(device).to(dtype)
-
-    def retrieve_word(self, hidden_states, layer_idx=None, num_tokens_to_generate=3):
-        result = self.reverse_logit_lens(hidden_states, layer_idx)
-        token = self.tokenizer.decode(torch.argmax(result, dim=-1).item())
-        return token
+# class ReverseLogitLensRetriever(WordRetrieverBase):
+#     def __init__(self, model, tokenizer, device='cuda', dtype=torch.float16):
+#         super().__init__(model, tokenizer)
+#         self.reverse_logit_lens = ReverseLogitLens.from_model(model).to(device).to(dtype)
+#
+#     def retrieve_word(self, hidden_states, layer_idx=None, num_tokens_to_generate=3):
+#         result = self.reverse_logit_lens(hidden_states, layer_idx)
+#         token = self.tokenizer.decode(torch.argmax(result, dim=-1).item())
+#         return token
 
 
 class AnalysisWordRetriever: