Update modeling_mplug_owl2.py

modeling_mplug_owl2.py

@@ -360,11 +360,9 @@ class MPLUGOwl2LlamaForCausalLM(LlamaForCausalLM, MPLUGOwl2MetaForCausalLM):
             with torch.inference_mode():
                 output_logits = self(input_ids, images=image_tensor)["logits"][:, -1, self.preferential_ids_]
                 output_logits = output_logits.cpu().detach().numpy() / 100
-                print(output_logits)
                 probabilities.append(np.dot(softmax(output_logits),  self.weight_tensor))
         updated_matrix = update_matrix(self.anchor_matrix, np.squeeze(np.array(probabilities)), self.anchor_indices)
         score = optimize_score_map_pytorch_cuda(updated_matrix, seed=0, original_seed=20020, num_iterations=100)
-        print(score)
         return score
 
     def forward(