feat(megdnn/softmax): add softmax operator in OpenCL

GitOrigin-RevId: e207d6ceb4

dnn/src/naive/softmax/opr_impl.h

@@ -4,7 +4,7 @@
 namespace megdnn {
 namespace naive {
 
-class SoftmaxForwardImpl final : public SoftmaxForward {
+class SoftmaxForwardImpl : public SoftmaxForward {
 public:
     using SoftmaxForward::SoftmaxForward;
     void exec(
@@ -16,7 +16,7 @@ public:
     }
 };
 
-class SoftmaxBackwardImpl final : public SoftmaxBackward {
+class SoftmaxBackwardImpl : public SoftmaxBackward {
 public:
     using SoftmaxBackward::SoftmaxBackward;
     void exec(
@@ -32,4 +32,4 @@ public:
 }  // namespace naive
 }  // namespace megdnn
 
-// vim: syntax=cpp.doxygen
+// vim: syntax=cpp.doxygen

dnn/test/naive/softmax.cpp

@@ -42,4 +42,61 @@ TEST_F(NAIVE, SOFTMAX_BACKWARD) {
             {0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.});
 
     checker.set_param(param).exect(Testcase{input, diff, {}}, Testcase{{}, {}, output});
-}
+}
+
+TEST_F(NAIVE, SOFTMAX_FORWARD_NHWCD4) {
+    Checker<Softmax> checker(handle(), false);
+    Softmax::Param param{0};
+
+    TensorND input1 = TensorValue(
+            {1, 2, 1, 2, 4}, dtype::Float32(),
+            {0, 4, 8, 12, 1, 5, 9, 13, 2, 6, 10, 14, 3, 7, 11, 15});
+    TensorND output1 = TensorValue(
+            {1, 2, 1, 2, 4}, dtype::Float32(),
+            {1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1});
+    checker.set_param(param).exect(Testcase{input1, {}}, Testcase{{}, output1});
+
+    TensorND input2 = TensorValue(
+            {2, 2, 1, 2, 4}, dtype::Float32(),
+            {0,  4,  8,  12, 1,  5,  9,  13, 2,  6,  10, 14, 3,  7,  11, 15,
+             16, 20, 24, 28, 17, 21, 25, 29, 18, 22, 26, 30, 19, 23, 27, 31});
+    TensorND output2 = TensorValue(
+            {2, 2, 1, 2, 4}, dtype::Float32(),
+            {1.12535162e-07, 1.12535162e-07, 1.12535162e-07, 1.12535162e-07,
+             1.12535162e-07, 1.12535162e-07, 1.12535162e-07, 1.12535162e-07,
+             1.12535162e-07, 1.12535162e-07, 1.12535162e-07, 1.12535162e-07,
+             1.12535162e-07, 1.12535162e-07, 1.12535162e-07, 1.12535162e-07,
+             9.99999887e-01, 9.99999887e-01, 9.99999887e-01, 9.99999887e-01,
+             9.99999887e-01, 9.99999887e-01, 9.99999887e-01, 9.99999887e-01,
+             9.99999887e-01, 9.99999887e-01, 9.99999887e-01, 9.99999887e-01,
+             9.99999887e-01, 9.99999887e-01, 9.99999887e-01, 9.99999887e-01});
+    checker.set_param(param).exect(Testcase{input2, {}}, Testcase{{}, output2});
+}
+
+TEST_F(NAIVE, SOFTMAX_BACKWARD_NHWCD4) {
+    Checker<SoftmaxBackward> checker(handle(), false);
+    Softmax::Param param{0};
+
+    TensorND input = TensorValue(
+            {2, 2, 1, 2, 4}, dtype::Float32(),
+            {1.12535162e-07, 1.12535162e-07, 1.12535162e-07, 1.12535162e-07,
+             1.12535162e-07, 1.12535162e-07, 1.12535162e-07, 1.12535162e-07,
+             1.12535162e-07, 1.12535162e-07, 1.12535162e-07, 1.12535162e-07,
+             1.12535162e-07, 1.12535162e-07, 1.12535162e-07, 1.12535162e-07,
+             9.99999887e-01, 9.99999887e-01, 9.99999887e-01, 9.99999887e-01,
+             9.99999887e-01, 9.99999887e-01, 9.99999887e-01, 9.99999887e-01,
+             9.99999887e-01, 9.99999887e-01, 9.99999887e-01, 9.99999887e-01,
+             9.99999887e-01, 9.99999887e-01, 9.99999887e-01, 9.99999887e-01});
+
+    TensorND diff = TensorValue(
+            {2, 2, 1, 2, 4}, dtype::Float32(),
+            {1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,
+             1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.});
+
+    TensorND output = TensorValue(
+            {2, 2, 1, 2, 4}, dtype::Float32(),
+            {0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
+             0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.});
+
+    checker.set_param(param).exect(Testcase{input, diff, {}}, Testcase{{}, {}, output});
+}