add cos

paddle/fluid/operators/activation_op.cc

@@ -260,6 +260,21 @@ $out = floor(x)$
   }
 };
 
+class CosOpMaker : public framework::OpProtoAndCheckerMaker {
+ public:
+  CosOpMaker(OpProto *proto, OpAttrChecker *op_checker)
+      : framework::OpProtoAndCheckerMaker(proto, op_checker) {
+    AddInput("X", "Input of Floor operator");
+    AddOutput("Out", "Output of Floor operator");
+    AddComment(R"DOC(
+Floor Activation Operator.
+
+$out = cos(x)$
+
+)DOC");
+  }
+};
+
 class RoundOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
   RoundOpMaker(OpProto *proto, OpAttrChecker *op_checker)
@@ -561,6 +576,9 @@ REGISTER_OP(ceil, ops::ActivationOp, ops::CeilOpMaker, ceil_grad,
 REGISTER_OP(floor, ops::ActivationOp, ops::FloorOpMaker, floor_grad,
             ops::ActivationOpGrad);
 
+REGISTER_OP(cos, ops::ActivationOp, ops::CosOpMaker, cos_grad,
+            ops::ActivationOpGrad);
+
 REGISTER_OP(round, ops::ActivationOp, ops::RoundOpMaker, round_grad,
             ops::ActivationOpGrad);
 

paddle/fluid/operators/activation_op.h

@@ -331,6 +331,54 @@ struct FloorFunctor : public BaseActivationFunctor<T> {
   }
 };
 
+template <typename T>
+struct Sine {
+  HOSTDEVICE T operator()(const T& val) const { return sin(val); }
+};
+
+template <typename T>
+struct Cosine {
+  HOSTDEVICE T operator()(const T& val) const { return cos(val); }
+};
+
+// cosine'(x) = -sin(x)
+template <typename T>
+struct CosGradFunctor : public BaseActivationFunctor<T> {
+  template <typename Device, typename X, typename Out, typename dOut,
+            typename dX>
+  void operator()(Device d, X x, Out out, dOut dout, dX dx) const {
+    dx.device(d) = -dout * x.unaryExpr(Sine<T>());
+  }
+};
+
+// cosine(x) = cos(x)
+template <typename T>
+struct CosFunctor : public BaseActivationFunctor<T> {
+  template <typename Device, typename X, typename Out>
+  void operator()(Device d, X x, Out out) const {
+    out.device(d) = x.unaryExpr(Cosine<T>());
+  }
+};
+
+// sine'(x) = cos(x)
+template <typename T>
+struct SinGradFunctor : public BaseActivationFunctor<T> {
+  template <typename Device, typename X, typename Out, typename dOut,
+            typename dX>
+  void operator()(Device d, X x, Out out, dOut dout, dX dx) const {
+    dx.device(d) = dout * x.unaryExpr(Cosine<T>());
+  }
+};
+
+// sine(x) = sin(x)
+template <typename T>
+struct SinFunctor : public BaseActivationFunctor<T> {
+  template <typename Device, typename X, typename Out>
+  void operator()(Device d, X x, Out out) const {
+    out.device(d) = x.unaryExpr(Sine<T>());
+  }
+};
+
 // round(x) = [x]
 template <typename T>
 struct RoundFunctor : public BaseActivationFunctor<T> {
@@ -782,6 +830,7 @@ struct SwishGradFunctor : public BaseActivationFunctor<T> {
   __macro(abs, AbsFunctor, AbsGradFunctor);                          \
   __macro(ceil, CeilFunctor, ZeroGradFunctor);                       \
   __macro(floor, FloorFunctor, ZeroGradFunctor);                     \
+  __macro(cos, CosFunctor, CosGradFunctor);                          \
   __macro(round, RoundFunctor, ZeroGradFunctor);                     \
   __macro(reciprocal, ReciprocalFunctor, ReciprocalGradFunctor);     \
   __macro(log, LogFunctor, LogGradFunctor);                          \

paddle/function/EigenGemm.cpp

@@ -63,6 +63,7 @@ struct EigenBlasGemm {
     const EigenMatrix a(const_cast<T*>(A), sizeA);
     const EigenMatrix b(const_cast<T*>(B), sizeB);
     EigenMatrix c(C, sizeC);
+    Eigen::Tensor<T, 2, Eigen::RowMajor, int> ss;
 
     typedef typename Eigen::Tensor<T, 2>::DimensionPair DimPair;
     Eigen::array<DimPair, 1> dims;

python/paddle/fluid/layers/ops.py

@@ -25,6 +25,7 @@ __activations__ = [
     'abs',
     'ceil',
     'floor',
+    'cos',
     'round',
     'reciprocal',
     'log',

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

@@ -14,6 +14,7 @@
 
 import unittest
 import numpy as np
+import math
 import paddle.fluid.core as core
 from op_test import OpTest
 from scipy.special import expit
@@ -196,6 +197,20 @@ class TestFloor(OpTest):
         self.check_grad(['X'], 'Out', max_relative_error=0.007)
 
 
+class TestCos(OpTest):
+    def setUp(self):
+        self.op_type = "cos"
+        x = np.random.uniform(-1, 1, [4, 4]).astype("float32")
+        self.inputs = {'X': x}
+        self.outputs = {'Out': math.cos(self.inputs['X'])}
+
+    def test_check_output(self):
+        self.check_output()
+
+    def test_check_grad(self):
+        self.check_grad(['X'], 'Out', max_relative_error=0.007)
+
+
 class TestRound(OpTest):
     def setUp(self):
         self.op_type = "round"