updata reader api test=develop (#3534)

slim/eval.py

@@ -132,7 +132,7 @@ def main():
     place = fluid.CUDAPlace(0) if cfg.use_gpu else fluid.CPUPlace()
     exe = fluid.Executor(place)
 
-    eval_pyreader, test_feed_vars = create_feed(eval_feed, use_pyreader=False)
+    _, test_feed_vars = create_feed(eval_feed, iterable=True)
 
     eval_reader = create_reader(eval_feed, args_path=FLAGS.dataset_dir)
     #eval_pyreader.decorate_sample_list_generator(eval_reader, place)

slim/quantization/compress.py

@@ -47,7 +47,7 @@ from ppdet.data.data_feed import create_reader
 from ppdet.utils.eval_utils import parse_fetches, eval_results
 from ppdet.utils.stats import TrainingStats
 from ppdet.utils.cli import ArgsParser
-from ppdet.utils.check import check_gpu
+from ppdet.utils.check import check_gpu, check_version
 import ppdet.utils.checkpoint as checkpoint
 from ppdet.modeling.model_input import create_feed
 
@@ -118,6 +118,7 @@ def main():
 
     # check if set use_gpu=True in paddlepaddle cpu version
     check_gpu(cfg.use_gpu)
+    #check_version()
 
     if cfg.use_gpu:
         devices_num = fluid.core.get_cuda_device_count()
@@ -147,7 +148,7 @@ def main():
     with fluid.program_guard(train_prog, startup_prog):
         with fluid.unique_name.guard():
             model = create(main_arch)
-            train_pyreader, feed_vars = create_feed(train_feed)
+            train_loader, feed_vars = create_feed(train_feed, iterable=True)
             train_fetches = model.train(feed_vars)
             loss = train_fetches['loss']
             lr = lr_builder()
@@ -157,7 +158,7 @@ def main():
 
     train_reader = create_reader(train_feed, cfg.max_iters * devices_num,
                                  FLAGS.dataset_dir)
-    train_pyreader.decorate_sample_list_generator(train_reader, place)
+    train_loader.set_sample_list_generator(train_reader, place)
 
     # parse train fetches
     train_keys, train_values, _ = parse_fetches(train_fetches)
@@ -172,7 +173,7 @@ def main():
     with fluid.program_guard(eval_prog, startup_prog):
         with fluid.unique_name.guard():
             model = create(main_arch)
-            eval_pyreader, test_feed_vars = create_feed(eval_feed, use_pyreader=False)
+            _, test_feed_vars = create_feed(eval_feed, iterable=True)
             fetches = model.eval(test_feed_vars)
     eval_prog = eval_prog.clone(True)
 
@@ -231,8 +232,8 @@ def main():
         place,
         fluid.global_scope(),
         train_prog,
-        train_reader=train_pyreader,
-        train_feed_list=None,
+        train_reader=train_reader,
+        train_feed_list=[(key, value.name) for key, value in feed_vars.items()],
         train_fetch_list=train_fetch_list,
         eval_program=eval_prog,
         eval_reader=eval_reader,

slim/quantization/freeze.py

@@ -132,7 +132,7 @@ def main():
     place = fluid.CUDAPlace(0) if cfg.use_gpu else fluid.CPUPlace()
     exe = fluid.Executor(place)
 
-    eval_pyreader, test_feed_vars = create_feed(eval_feed, use_pyreader=False)
+    _, test_feed_vars = create_feed(eval_feed, iterable=True)
 
     eval_reader = create_reader(eval_feed, args_path=FLAGS.dataset_dir)
     #eval_pyreader.decorate_sample_list_generator(eval_reader, place)