Merge pull request #440 from reyoung/feature/fix_pydataprovider_multiple_obj_bugs

Feature/fix pydataprovider multiple obj bugs

python/paddle/trainer_config_helpers/data_sources.py

@@ -139,7 +139,7 @@ def define_py_data_sources(train_list, test_list, module, obj, args=None,
     test_obj = obj
     train_obj = obj
     if __is_splitable__(obj):
-        train_module, test_module = module
+        train_obj, test_obj = obj
 
     if args is None:
         args = ""

python/paddle/trainer_config_helpers/tests/configs/generate_protostr.sh

@@ -13,9 +13,16 @@ img_layers img_trans_layers util_layers simple_rnn_layers unused_layers test_cos
 test_rnn_group shared_fc shared_lstm test_cost_layers_with_weight
 test_spp_layer test_bilinear_interp test_maxout test_bi_grumemory math_ops)
 
+whole_configs=(test_split_datasource)
 
 for conf in ${configs[*]}
 do
     echo "Generating " $conf
     python -m paddle.utils.dump_config $conf.py > $protostr/$conf.protostr.unitest
 done
+
+for conf in ${whole_configs[*]}
+do
+    echo "Generating " $conf
+    python -m paddle.utils.dump_config $conf.py "" --whole > $protostr/$conf.protostr.unitest
+done

python/paddle/trainer_config_helpers/tests/configs/protostr/test_split_datasource.protostr

@@ -0,0 +1,72 @@
+model_config {
+  type: "nn"
+  layers {
+    name: "a"
+    type: "data"
+    size: 10
+    active_type: ""
+  }
+  input_layer_names: "a"
+  output_layer_names: "a"
+  sub_models {
+    name: "root"
+    layer_names: "a"
+    input_layer_names: "a"
+    output_layer_names: "a"
+    is_recurrent_layer_group: false
+  }
+}
+data_config {
+  type: "py2"
+  files: "train.list"
+  async_load_data: true
+  for_test: false
+  load_data_module: "a"
+  load_data_object: "c"
+  load_data_args: ""
+  data_ratio: 1
+  is_main_data: true
+  usage_ratio: 1.0
+}
+opt_config {
+  batch_size: 1000
+  algorithm: "sgd"
+  learning_rate: 0.001
+  learning_rate_decay_a: 0.0
+  learning_rate_decay_b: 0.0
+  l1weight: 0.1
+  l2weight: 0.0
+  c1: 0.0001
+  backoff: 0.5
+  owlqn_steps: 10
+  max_backoff: 5
+  l2weight_zero_iter: 0
+  average_window: 0
+  learning_method: "momentum"
+  ada_epsilon: 1e-06
+  do_average_in_cpu: false
+  ada_rou: 0.95
+  learning_rate_schedule: "poly"
+  delta_add_rate: 1.0
+  shrink_parameter_value: 0
+  adam_beta1: 0.9
+  adam_beta2: 0.999
+  adam_epsilon: 1e-08
+  learning_rate_args: ""
+  async_lagged_grad_discard_ratio: 1.5
+}
+test_data_config {
+  type: "py2"
+  files: "test.list"
+  async_load_data: true
+  for_test: true
+  load_data_module: "b"
+  load_data_object: "d"
+  load_data_args: ""
+  data_ratio: 1
+  is_main_data: true
+  usage_ratio: 1.0
+}
+save_dir: "./output/model"
+start_pass: 0
+

python/paddle/trainer_config_helpers/tests/configs/test_split_datasource.py

@@ -0,0 +1,12 @@
+from paddle.trainer_config_helpers import *
+
+define_py_data_sources2(train_list="train.list",
+                        test_list="test.list",
+                        module=["a", "b"],
+                        obj=("c", "d"))
+settings(
+    learning_rate=1e-3,
+    batch_size=1000
+)
+
+outputs(data_layer(name="a", size=10))

python/paddle/utils/dump_config.py

@@ -19,13 +19,21 @@ import sys
 __all__ = []
 
 if __name__ == '__main__':
+    whole_conf = False
     if len(sys.argv) == 2:
         conf = parse_config(sys.argv[1], '')
     elif len(sys.argv) == 3:
         conf = parse_config(sys.argv[1], sys.argv[2])
+    elif len(sys.argv) == 4:
+        conf = parse_config(sys.argv[1], sys.argv[2])
+        if sys.argv[3] == '--whole':
+            whole_conf = True
     else:
         raise RuntimeError()
 
     assert isinstance(conf, TrainerConfig_pb2.TrainerConfig)
 
-    print conf.model_config
+    if whole_conf:
+        print conf
+    else:
+        print conf.model_config