Call cuda empty_cache to prevent OOM when quantizing model (#2671)

* Call cuda empty_cache to prevent OOM when quantizing model

* empty cache during export and after forward

lmdeploy/lite/quantization/calibration.py

@@ -253,9 +253,11 @@ def export(self, out_dir):
 
         inp_stats = self.collect_inputs_stats()
         torch.save(inp_stats, out_dir / 'inputs_stats.pth')
+        torch.cuda.empty_cache()
 
         out_stats = self.collect_outputs_stats()
         torch.save(out_stats, out_dir / 'outputs_stats.pth')
+        torch.cuda.empty_cache()
 
     def calibrate(self, data):
         """Forward pass through the model in inference mode with given data."""
@@ -267,6 +269,7 @@ def calibrate(self, data):
             model = self.model.model
         with torch.inference_mode():
             _ = model(data.to(self.device))
+        torch.cuda.empty_cache()
 
     def __enter__(self):
         """Prepares the Calibration object for a 'with' statement by
@@ -440,6 +443,7 @@ def export(self, out_dir):
             inputs_stats['absmean'][name] = obs.absmean_val
             inputs_stats['ratios'][name] = obs.ratio
         torch.save(inputs_stats, out_dir / 'inputs_stats.pth')
+        torch.cuda.empty_cache()
 
     def _wrap_decoder_layers_for_search(self):
         """Method to wrap the decoder layers' forward functions for observing