fix unitest of test_RecurrentGradientMachine, and some tiny doc update

Change-Id: I028e402c964ca4f4431cbf8153bea4379dd4df70

doc/demo/imagenet_model/resnet_model.md

@@ -165,7 +165,7 @@ We provide both C++ and Python interfaces to extract features. The following exa
 
 ### C++ Interface
 
-First, specify image data list in `define_py_data_sources` in the config, see example `demo/model_zoo/resnet/resnet.py`.
+First, specify image data list in `define_py_data_sources2` in the config, see example `demo/model_zoo/resnet/resnet.py`.
 
 ```
     train_list = 'train.list' if not is_test else None

doc/demo/rec/ml_regression.rst

@@ -257,7 +257,7 @@ In these network, we use several api in `trainer_config_helpers
 *  Text Convolution Pooling Layer, `text_conv_pool
    <../../ui/api/trainer_config_helpers/networks.html
    #trainer_config_helpers.networks.text_conv_pool>`_
-*  Declare Python Data Sources, `define_py_data_sources
+*  Declare Python Data Sources, `define_py_data_sources2
    <../../ui/api/trainer_config_helpers/data_sources.html>`_
 
 Data Provider

paddle/gserver/tests/sequenceGen.py

@@ -18,27 +18,33 @@
 import os
 import sys
 
-from paddle.trainer.PyDataProviderWrapper import *
+from paddle.trainer.PyDataProvider2 import *
 
-@init_hook_wrapper
-def hook(obj, dict_file, **kwargs):
-    obj.word_dict = dict_file
-    obj.slots = [IndexSlot(len(obj.word_dict)), IndexSlot(3)]
-    obj.logger.info('dict len : %d' % (len(obj.word_dict)))
+def hook(settings, dict_file, **kwargs):
+    settings.word_dict = dict_file
+    settings.input_types = [integer_value_sequence(len(settings.word_dict)), 
+                            integer_value_sequence(3)]
+    settings.logger.info('dict len : %d' % (len(settings.word_dict)))
 
-@provider(use_seq=True, init_hook=hook)
-def process(obj, file_name):
+@provider(init_hook=hook)
+def process(settings, file_name):
     with open(file_name, 'r') as fdata:
         for line in fdata:
             label, comment = line.strip().split('\t')
             label = int(''.join(label.split()))
             words = comment.split()
-            word_slot = [obj.word_dict[w] for w in words if w in obj.word_dict]
+            word_slot = [settings.word_dict[w] for w in words if w in settings.word_dict]
             yield word_slot, [label]
 
 ## for hierarchical sequence network
-@provider(use_seq=True, init_hook=hook)
-def process2(obj, file_name):
+def hook2(settings, dict_file, **kwargs):
+    settings.word_dict = dict_file
+    settings.input_types = [integer_value_sub_sequence(len(settings.word_dict)),
+                            integer_value_sub_sequence(3)]
+    settings.logger.info('dict len : %d' % (len(settings.word_dict)))
+
+@provider(init_hook=hook2)
+def process2(settings, file_name):
     with open(file_name) as fdata:
         label_list = []
         word_slot_list = []
@@ -47,7 +53,7 @@ def process2(obj, file_name):
                 label,comment = line.strip().split('\t')
                 label = int(''.join(label.split()))
                 words = comment.split()
-                word_slot = [obj.word_dict[w] for w in words if w in obj.word_dict]
+                word_slot = [settings.word_dict[w] for w in words if w in settings.word_dict]
                 label_list.append([label])
                 word_slot_list.append(word_slot)
             else:

paddle/gserver/tests/sequence_layer_group.conf

@@ -21,7 +21,7 @@ dict_file = dict()
 for line_count, line in enumerate(open(dict_path, "r")):
     dict_file[line.strip()] = line_count
 
-define_py_data_sources(train_list='gserver/tests/Sequence/train.list',
+define_py_data_sources2(train_list='gserver/tests/Sequence/train.list',
                         test_list=None,
                         module='sequenceGen',
                         obj='process',

paddle/gserver/tests/sequence_nest_layer_group.conf

@@ -21,7 +21,7 @@ dict_file = dict()
 for line_count, line in enumerate(open(dict_path, "r")):
     dict_file[line.strip()] = line_count
 
-define_py_data_sources(train_list='gserver/tests/Sequence/train.list.nest',
+define_py_data_sources2(train_list='gserver/tests/Sequence/train.list.nest',
                         test_list=None,
                         module='sequenceGen',
                         obj='process2',