fix windows training (#1038)

* fix windows training

* fix typo

ppcls/engine/trainer.py

@@ -21,6 +21,7 @@ __dir__ = os.path.dirname(os.path.abspath(__file__))
 sys.path.append(os.path.abspath(os.path.join(__dir__, '../../')))
 
 import time
+import platform
 import datetime
 import argparse
 import paddle
@@ -152,10 +153,14 @@ class Trainer(object):
                 best_metric.update(metric_info)
 
         tic = time.time()
+        max_iter = len(self.train_dataloader) - 1 if platform.system(
+        ) == "Windows" else len(self.train_dataloader)
         for epoch_id in range(best_metric["epoch"] + 1,
                               self.config["Global"]["epochs"] + 1):
             acc = 0.0
             for iter_id, batch in enumerate(self.train_dataloader()):
+                if iter_id >= max_iter:
+                    break
                 if iter_id == 5:
                     for key in time_info:
                         time_info[key].reset()
@@ -349,7 +354,11 @@ class Trainer(object):
 
         metric_key = None
         tic = time.time()
+        max_iter = len(self.eval_dataloader) - 1 if platform.system(
+        ) == "Windows" else len(self.eval_dataloader)
         for iter_id, batch in enumerate(self.eval_dataloader()):
+            if iter_id >= max_iter:
+                break
             if iter_id == 5:
                 for key in time_info:
                     time_info[key].reset()
@@ -498,8 +507,12 @@ class Trainer(object):
             raise RuntimeError("Only support gallery or query dataset")
 
         has_unique_id = False
+        max_iter = len(dataloader) - 1 if platform.system(
+        ) == "Windows" else len(dataloader)
         for idx, batch in enumerate(dataloader(
         )):  # load is very time-consuming
+            if idx >= max_iter:
+                break
             if idx % self.config["Global"]["print_batch_step"] == 0:
                 logger.info(
                     f"{name} feature calculation process: [{idx}/{len(dataloader)}]"