update config and demo

demo/text-classification/simple_demo.py

 import paddle.fluid as fluid
 import paddlehub as hub
 
-# Step1: Select pre-trained model
 module = hub.Module(name="ernie")
-inputs, outputs, program = module.context(trainable=True, max_seq_len=128)
-
-# Step2: Prepare Dataset and DataReader
-dataset = hub.dataset.ChnSentiCorp()
-reader = hub.reader.ClassifyReader(
-    dataset=dataset, vocab_path=module.get_vocab_path(), max_seq_len=128)
-
-# Step3: Construct transfer learning task
-with fluid.program_guard(program):
-    label = fluid.layers.data(name="label", shape=[1], dtype='int64')
-    pooled_output = outputs["pooled_output"]
-    cls_task = hub.create_text_cls_task(
-        feature=pooled_output, label=label, num_classes=dataset.num_labels)
-
-# Step4: Setup config then start finetune
-strategy = hub.AdamWeightDecayStrategy(learning_rate=5e-5, weight_decay=0.01)
-
-config = hub.RunConfig(
-    use_cuda=True,
-    checkpoint_dir="./ckpt",
-    num_epoch=3,
-    batch_size=32,
-    strategy=strategy)
-
+inputs, outputs, program = module.context(trainable=True)
+reader = hub.reader.ClassifyReader(hub.dataset.ChnSentiCorp(),
+                                   module.get_vocab_path())
+task = hub.create_text_cls_task(feature=outputs["pooled_output"], num_classes=2)
+strategy = hub.AdamWeightDecayStrategy(learning_rate=5e-5)
+config = hub.RunConfig(use_cuda=True, num_epoch=3, strategy=strategy)
 feed_list = [
     inputs["input_ids"].name, inputs["position_ids"].name,
-    inputs["segment_ids"].name, inputs["input_mask"].name, label.name
+    inputs["segment_ids"].name, inputs["input_mask"].name,
+    task.variable("label").name
 ]
-
-hub.finetune_and_eval(
-    task=cls_task, data_reader=reader, feed_list=feed_list, config=config)
+hub.finetune_and_eval(task, reader, feed_list, config)

paddlehub/finetune/config.py

@@ -30,10 +30,10 @@ class RunConfig(object):
                  log_interval=10,
                  eval_interval=100,
                  save_ckpt_interval=None,
-                 use_cuda=False,
+                 use_cuda=True,
                  checkpoint_dir=None,
-                 num_epoch=10,
-                 batch_size=None,
+                 num_epoch=1,
+                 batch_size=32,
                  enable_memory_optim=True,
                  strategy=None):
         """ Construct finetune Config """

paddlehub/module/module.py

@@ -469,7 +469,7 @@ class Module(object):
     def context(self,
                 sign_name=None,
                 for_test=False,
-                trainable=False,
+                trainable=True,
                 regularizer=None,
                 max_seq_len=128,
                 learning_rate=1e-3):