"add book recommender_system testing" (#5143)

* "add sequence conv layer"

* "add book recommender_system testing"

* "add training loop"

* "add sequence layer"

* "add recommender system training data"

* "fix conv2d layer bug"

* add sequence_conv_pool

* "fix input is Null"

* add networks

* "fix based comment"

* "add sum op layer"

* "merge layers"

* Update layers.py

* "fix input is NULL bug"

* "debug embedding table"

* "modify layers.py"

* "fix pool interface"

* "add export type to layers"

* "fix based on comment"

* "need lod info support in all operator"

* "remove accuracy layer"

* "tuning learning rate"

* "add sparse test"

* "add gpu test"

* Update test_recommender_system.py

python/paddle/v2/framework/layers.py

@@ -197,11 +197,11 @@ def sums(input, program=None, init_program=None):
     return out
 
 
-def cos_sim(X, Y, program=None, init_program=None):
-    helper = LayerHelper('cos_sim', **locals())
-    out = helper.create_tmp_variable(dtype=helper.input_dtype("X"))
-    xnorm = helper.create_tmp_variable(dtype=helper.input_dtype("X"))
-    ynorm = helper.create_tmp_variable(dtype=helper.input_dtype("X"))
+def cos_sim(X, Y, **kwargs):
+    helper = LayerHelper('cos_sim', **kwargs)
+    out = helper.create_tmp_variable(dtype=X.data_type)
+    xnorm = helper.create_tmp_variable(dtype=X.data_type)
+    ynorm = helper.create_tmp_variable(dtype=X.data_type)
     helper.append_op(
         type='cos_sim',
         inputs={'X': [X],
@@ -209,7 +209,7 @@ def cos_sim(X, Y, program=None, init_program=None):
         outputs={'Out': [out],
                  'XNorm': [xnorm],
                  'YNorm': [ynorm]})
-    return out, xnorm, ynorm
+    return out
 
 
 def cross_entropy(input, label, **kwargs):
@@ -265,7 +265,7 @@ def accuracy(input, label, k=1, **kwargs):
 def sequence_conv(input,
                   num_filters,
                   filter_size=3,
-                  stride=1,
+                  filter_stride=1,
                   padding=None,
                   bias_attr=None,
                   param_attr=None,
@@ -291,9 +291,9 @@ def sequence_conv(input,
         },
         outputs={"Out": pre_bias},
         attrs={
-            'context_stride': stride,
-            'context_start': 0,
-            'context_length': filter_size
+            'contextStride': filter_stride,
+            'contextStart': 0,
+            'contextLength': filter_size
         })
     pre_act = helper.append_bias_op(pre_bias)
     return helper.append_activation(pre_act)

python/paddle/v2/framework/nets.py

@@ -101,6 +101,7 @@ def img_conv_group(input,
 def sequence_conv_pool(input,
                        num_filters,
                        filter_size,
+                       act="sigmoid",
                        pool_type="max",
                        program=None,
                        init_program=None):