add api demo

demo/demo2/paddlepalm

+../../paddlepalm/
\ No newline at end of file

demo/demo2/run.py

@@ -2,7 +2,12 @@ import paddlepalm as palm
 
 if __name__ == '__main__':
 
-    match_reader = palm.reader.match(train_file, file_format='csv', tokenizer='wordpiece', lang='en')
+    max_seqlen = 512
+    batch_size = 32
+
+    match_reader = palm.reader.match(train_file, vocab, \
+        max_seqlen, file_format='csv', tokenizer='wordpiece', \
+        lang='en', shuffle_train=True)
     mrc_reader = palm.reader.mrc(train_file, phase='train')
     mlm_reader = palm.reader.mlm(train_file, phase='train')
     palm.reader.

demo/demo3/run.py

 import paddlepalm as palm
 
 if __name__ == '__main__':
-    controller = palm.Controller('config.yaml', task_dir='tasks')
+
+    max_seqlen = 512
+    batch_size = 32
+
+    match_reader = palm.reader.match(train_file, vocab, \
+        max_seqlen, file_format='csv', tokenizer='wordpiece', \
+        lang='en', shuffle_train=True)
+    mrc_reader = palm.reader.mrc(train_file, phase='train')
+    mlm_reader = palm.reader.mlm(train_file, phase='train')
+    palm.reader.
+
+    match = palm.tasktype.cls(num_classes=4)
+    mrc = palm.tasktype.match(learning_strategy='pairwise')
+    mlm = palm.tasktype.mlm()
+    mlm.print()
+
+    
+    bb_flags = palm.load_json('./pretrain/ernie/ernie_config.json')
+    bb = palm.backbone.ernie(bb_flags['xx'], xxx)
+    bb.print()
+
+    match4mrqa = palm.Task('match4mrqa', match_reader, match_tt)
+    mrc4mrqa = palm.Task('match4mrqa', match_reader, match_tt)
+
+    # match4mrqa.reuse_with(mrc4mrqa)
+
+
+    controller = palm.Controller([mrqa, match4mrqa, mlm4mrqa])
+
+    loss = controller.build_forward(bb, mask_task=[])
+
+    n_steps = controller.estimate_train_steps(basetask=mrqa, num_epochs=2, batch_size=8, dev_count=4)
+    adam = palm.optimizer.Adam(loss)
+    sched = palm.schedualer.LinearWarmup(learning_rate, max_train_steps=n_steps, warmup_steps=0.1*n_steps)
+    
+    controller.build_backward(optimizer=adam, schedualer=sched, weight_decay=0.001, use_ema=True, ema_decay=0.999)
+
+    controller.random_init_params()
     controller.load_pretrain('../../pretrain_model/ernie/params')
     controller.train()
 
+
+
+
+
+    # controller = palm.Controller(config='config.yaml', task_dir='tasks', for_train=False)
+    # controller.pred('mrqa', inference_model_dir='output_model/secondrun/mrqa/infer_model')
+
+