fix tools/train.py

tools/train.py

@@ -109,47 +109,21 @@ def main(args):
             program.run(train_dataloader, config, dp_net, optimizer,
                         lr_scheduler, epoch_id, 'train', vdl_writer)
 
-            if use_xpu:
-                if paddle.distributed.get_rank() == 0:
-                    # 2. validate with validate dataset
-                    if config.validate and epoch_id % config.valid_interval == 0:
-                        net.eval()
-                        top1_acc = program.run(valid_dataloader, config, net,
-                                               None, None, epoch_id, 'valid')
-                        if top1_acc > best_top1_acc:
-                            best_top1_acc = top1_acc
-                            best_top1_epoch = epoch_id
-                            if epoch_id % config.save_interval == 0:
-                                model_path = os.path.join(
-                                    config.model_save_dir,
-                                    config.ARCHITECTURE["name"])
-                                save_model(net, optimizer, model_path,
-                                           "best_model")
-                        message = "The best top1 acc {:.5f}, in epoch: {:d}".format(
-                            best_top1_acc, best_top1_epoch)
-                        logger.info("{:s}".format(
-                            logger.coloring(message, "RED")))
-
-            else:
-                # 2. validate with validate dataset
-                if paddle.distributed.get_rank() == 0:
-                    if config.validate and epoch_id % config.valid_interval == 0:
-                        net.eval()
-                        with paddle.no_grad():
-                            top1_acc = program.run(valid_dataloader, config,
-                                                   net, None, None, epoch_id,
-                                                   'valid', vdl_writer)
-                        if top1_acc > best_top1_acc:
-                            best_top1_acc = top1_acc
-                            best_top1_epoch = epoch_id
-                            model_path = os.path.join(
-                                config.model_save_dir,
-                                config.ARCHITECTURE["name"])
-                            save_model(net, optimizer, model_path,
-                                       "best_model")
-                        message = "The best top1 acc {:.5f}, in epoch: {:d}".format(
-                            best_top1_acc, best_top1_epoch)
-                        logger.info(message)
+            # 2. validate with validate dataset
+            if config.validate and epoch_id % config.valid_interval == 0:
+                net.eval()
+                with paddle.no_grad():
+                    top1_acc = program.run(valid_dataloader, config, net, None,
+                                           None, epoch_id, 'valid', vdl_writer)
+                if top1_acc > best_top1_acc:
+                    best_top1_acc = top1_acc
+                    best_top1_epoch = epoch_id
+                    model_path = os.path.join(config.model_save_dir,
+                                              config.ARCHITECTURE["name"])
+                    save_model(net, optimizer, model_path, "best_model")
+                message = "The best top1 acc {:.5f}, in epoch: {:d}".format(
+                    best_top1_acc, best_top1_epoch)
+                logger.info(message)
 
             # 3. save the persistable model
             if epoch_id % config.save_interval == 0: