format (pytorch#223)

quantize.py

@@ -9,8 +9,6 @@
 from math import gcd
 from typing import Dict, Optional, Tuple
 
-import quantized_ops
-
 import torch
 import torch.nn as nn
 import torch.nn.functional as F
@@ -1318,7 +1316,7 @@ def get_inputs(
         inputs = input_recorder.get_recorded_inputs()
         assert inputs is not None, (
             f"No inputs were collected, use a task other than {calibration_tasks}, "
-            + f"use option pad_calibration_inputs, or decrease calibration_sequence_length (currently "
+            + "use option pad_calibration_inputs, or decrease calibration_sequence_length (currently "
             + f"{calibration_seq_length})"
         )
         print(f"Obtained {len(inputs[0].values)} calibration samples")
@@ -1335,7 +1333,7 @@ def create_quantized_state_dict(
         calibration_limit,
         calibration_seq_length,
         pad_calibration_inputs,
-    ) -> "StateDict":
+    ) -> Dict:  # "StateDict":
         inputs = GPTQQuantHandler.get_inputs(
             self.mod,
             tokenizer,
@@ -1511,7 +1509,7 @@ def create_quantized_state_dict(self):
         from hqq.core.quantize import Quantizer  # TODO maybe torchao
 
         for m in self.mod.modules():
-            for name, child in m.named_children():
+            for _name, child in m.named_children():
                 if isinstance(child, torch.nn.Linear):
                     child.weight = torch.nn.Parameter(
                         Quantizer.dequantize(