Update fragment_embedder.py

fragment_embedder.py

@@ -14,11 +14,11 @@ CHUNKSIZE = 1024
 
 class FragmentEmbedder(object):
     def __init__(self):
-    
+
         url = 'https://huggingface.co/ligdis/fpred/resolve/main/morgan_descriptor.joblib' # The URL of the file you want to load
         with urllib.request.urlopen(url) as response:     # Download the file
             self.morgan_desc = joblib.load(BytesIO(response.read()))
-    
+
         url = 'https://huggingface.co/ligdis/fpred/resolve/main/physchem_descriptor.joblib' # The URL of the file you want to load
         with urllib.request.urlopen(url) as response:     # Download the file
             self.physchem_desc = joblib.load(BytesIO(response.read()))
@@ -28,12 +28,13 @@ class FragmentEmbedder(object):
             yield l[i : i + n]
 
     def encoder_inference(self, X):
-#        sess = rt.InferenceSession(os.path.join(self.models_dir, "encoder_model.onnx"))       
+#        sess = rt.InferenceSession(os.path.join(self.models_dir, "encoder_model.onnx"))
         url = 'https://huggingface.co/ligdis/fpred/resolve/main/encoder_model.onnx'
         response = requests.get(url)
         model_bytes = BytesIO(response.content) # Create a file-like object from the byte data
-        sess = rt.InferenceSession(model_bytes)  
-        
+        sess = rt.InferenceSession(model_bytes.read())
+
+
         input_name = sess.get_inputs()[0].name
         output_name = sess.get_outputs()[0].name
         output_data = sess.run(
@@ -54,3 +55,4 @@ class FragmentEmbedder(object):
             else:
                 X = np.vstack([X, X_o])
         return X
+