gru add origin mode

test=develop

paddle/fluid/operators/gru_unit_op.cc

@@ -111,6 +111,10 @@ class GRUUnitOpMaker : public framework::OpProtoAndCheckerMaker {
                  "The activation type used in update gate and reset gate.")
         .SetDefault(sigmoid)
         .InEnum({identity, sigmoid, tanh, relu});
+    AddAttr<bool>("origin_mode",
+                  "bool"
+                  "use origin mode in article https://arxiv.org/abs/1412.3555")
+        .SetDefault(false);
     AddComment(R"DOC(
 GRUUnit Operator implements partial calculations of the GRU unit as following:
 

paddle/fluid/operators/gru_unit_op.h

@@ -113,7 +113,12 @@ class GRUUnitKernel : public framework::OpKernel<T> {
     auto c = g.slice(c_offsets, extents);  // output candidate
 
     // calculate final output
-    h.device(place) = u * (c - h_p) + h_p;
+    bool origin_mode = context.Attr<bool>("origin_mode");
+    if (origin_mode) {
+      h.device(place) = c + u * (h_p - c);  // (1 - u) * c + u * h_p
+    } else {
+      h.device(place) = u * (c - h_p) + h_p;  // u * c + (1 - u) * h_p
+    }
   }
 };
 

python/paddle/fluid/layers/nn.py

@@ -991,7 +991,8 @@ def gru_unit(input,
              param_attr=None,
              bias_attr=None,
              activation='tanh',
-             gate_activation='sigmoid'):
+             gate_activation='sigmoid',
+             origin_mode=False):
     """
     GRU unit layer. The equation of a gru step is:
 

python/paddle/fluid/tests/unittests/test_gru_op.py

@@ -31,7 +31,8 @@ def gru(
         is_reverse,
         act_state,
         act_gate,
-        dtype='float32'):
+        dtype='float32',
+        origin_mode=False):
     def _seq_to_batch(lod, is_reverse):
         idx_in_seq_list = []
         seq_lens = lod[0]
@@ -66,7 +67,10 @@ def gru(
         w_c = w.flatten()[D * D * 2:].reshape((D, D))
         c = act_state(np.dot(r_h_p, w_c) + g[:, D * 2:])
         g = np.hstack((u_r, c))
-        h = u * c + (1 - u) * h_p
+        if origin_mode:
+            h = (1 - u) * c + u * h_p
+        else:
+            h = u * c + (1 - u) * h_p
         return g, r_h_p, h
 
     T = sum(lod[0])
@@ -110,6 +114,7 @@ class TestGRUOp(OpTest):
         self.act_state = 'tanh'
         self.act_gate = 'sigmoid'
         self.dtype = 'float64'
+        self.origin_mode = False
         self.set_confs()
 
         T = sum(self.lod[0])
@@ -126,7 +131,8 @@ class TestGRUOp(OpTest):
 
         batch_gate, batch_reset_hidden_prev, batch_hidden, hidden = gru(
             input, self.lod, h0, weight, bias, self.is_reverse,
-            ACTIVATION[self.act_state], ACTIVATION[self.act_gate], self.dtype)
+            ACTIVATION[self.act_state], ACTIVATION[self.act_gate], self.dtype,
+            self.origin_mode)
         self.inputs = {'Input': (input, self.lod), 'Weight': weight}
 
         if self.with_bias:
@@ -145,7 +151,8 @@ class TestGRUOp(OpTest):
         self.attrs = {
             'activation': self.act_state,
             'gate_activation': self.act_gate,
-            'is_reverse': self.is_reverse
+            'is_reverse': self.is_reverse,
+            'origin_mode': self.origin_mode
         }
 
     def test_check_output(self):
@@ -155,12 +162,24 @@ class TestGRUOp(OpTest):
         self.check_grad(['Input', 'H0', 'Weight', 'Bias'], ['Hidden'])
 
 
+class TestGRUOriginMode(TestGRUOp):
+    def set_confs(self):
+        self.origin_mode = True
+
+
 class TestGRUOp2(TestGRUOp):
     def set_confs(self):
         self.D = 19
         self.dtype = 'float32'
 
 
+class TestGRUOp2OriginMode(TestGRUOp):
+    def set_confs(self):
+        self.D = 19
+        self.dtype = 'float32'
+        self.origin_mode = True
+
+
 class TestGRUOpNoInitial(TestGRUOp):
     def set_confs(self):
         self.with_h0 = False
@@ -182,5 +201,11 @@ class TestGRUOpReverse(TestGRUOp):
         self.is_reverse = True
 
 
+class TestGRUOpReverseOriginMode(TestGRUOp):
+    def set_confs(self):
+        self.is_reverse = True
+        self.origin_mode = True
+
+
 if __name__ == "__main__":
     unittest.main()