fixed wrong file path

min_dalle/load_params.py

@@ -129,7 +129,7 @@ def convert_and_save_torch_params(is_mega: bool, model_path: str):
         encoder_params[i] = encoder_params[i].to(torch.float16)
 
     detoker_params = load_vqgan_torch_params('./pretrained/vqgan')
-    detoker_path = os.path.join('pretrained', 'vqgan', 'detokenizer.pt')
+    detoker_path = os.path.join('pretrained', 'vqgan', 'detoker.pt')
 
     torch.save(encoder_params, os.path.join(model_path, 'encoder.pt'))
     torch.save(decoder_params, os.path.join(model_path, 'decoder.pt'))

min_dalle/min_dalle_base.py

@@ -3,7 +3,6 @@ import json
 import numpy
 
 from .text_tokenizer import TextTokenizer
-from .models.vqgan_detokenizer import VQGanDetokenizer
 
 class MinDalleBase:
     def __init__(self, is_mega: bool):

min_dalle/min_dalle_torch.py

@@ -27,7 +27,7 @@ class MinDalleTorch(MinDalleBase):
     
         self.encoder_params_path = os.path.join(self.model_path, 'encoder.pt')
         self.decoder_params_path = os.path.join(self.model_path, 'decoder.pt')
-        self.detoker_params_path = os.path.join('pretrained', 'vqgan', 'detokenizer.pt')
+        self.detoker_params_path = os.path.join('pretrained', 'vqgan', 'detoker.pt')
 
         is_converted = os.path.exists(self.encoder_params_path)
         is_converted &= os.path.exists(self.decoder_params_path)