Complete unittest for trainer_config_helpers. (#108)

* Fix lots of trainer_config_helpers bug, and complete unittest for `layers.py`

Author: reyoung

python/paddle/trainer/config_parser.py

@@ -1279,7 +1279,7 @@ def create_input_parameter(
             size,
             dims=None,
             sparse = None,
-            format = "csr"):
+            format = None):
         if dims is None:
             # TODO(yuyang18): print warning and callstack here!
             dims = list()
@@ -2074,7 +2074,7 @@ def __init__(
             active_type='linear',
             device=None,
             bias=False,
-            output_max_index=False):
+            output_max_index=None):
         super(MaxLayer, self).__init__(name, 'max', 0, inputs=inputs, device=device)
         config_assert(len(self.inputs) == 1, 'MaxLayer must have 1 input')
         self.config.trans_type =  trans_type
@@ -2083,7 +2083,8 @@ def __init__(
             input_layer = self.get_input_layer(input_index)
             self.set_layer_size(input_layer.size)
         self.create_bias_parameter(bias, self.config.size)
-        self.config.output_max_index=output_max_index
+        if output_max_index is not None:
+            self.config.output_max_index = output_max_index
 
 
 @config_layer('maxid')
@@ -2440,7 +2441,7 @@ def __init__(
             inputs,
             size=0,
             bias=True,
-            error_clipping_threshold=0.0,
+            error_clipping_threshold=None,
             **xargs):
         config_assert(inputs, 'inputs cannot be empty')
         super(MixedLayer, self).__init__(
@@ -2510,7 +2511,8 @@ def __init__(
 
         self.create_bias_parameter(bias, self.config.size)
 
-        self.config.error_clipping_threshold = error_clipping_threshold
+        if error_clipping_threshold is not None:
+            self.config.error_clipping_threshold = error_clipping_threshold
 
 # like MixedLayer, but no bias parameter
 @config_func

python/paddle/trainer_config_helpers/activations.py

@@ -15,8 +15,10 @@
 __all__ = ["TanhActivation", "SigmoidActivation",
            "SoftmaxActivation", "IdentityActivation", "LinearActivation",
            'SequenceSoftmaxActivation', 'ExpActivation',
-           "ReluActivation", "BReluActivation", "SoftReluActivation", "STanhActivation",
-           "AbsActivation", "SquareActivation", "BaseActivation"]
+           "ReluActivation", "BReluActivation", "SoftReluActivation",
+           "STanhActivation",
+           "AbsActivation", "SquareActivation",
+           "BaseActivation"]
 
 
 class BaseActivation(object):
@@ -36,6 +38,9 @@ def __init__(self, name, support_hppl):
         self.name = name
         self.support_hppl = support_hppl
 
+    def __repr__(self):
+        return self.name
+
 
 class TanhActivation(BaseActivation):
     """