fix(dnn): fix bool cvt

GitOrigin-RevId: 2f883dcbe005a8a8cd43e9051d1d0a59b8e61c0e

dnn/src/cuda/cond_take/opr_impl.cpp

@@ -59,6 +59,7 @@ CondTakeImpl::Output CondTakeImpl::exec(
             break; \
         }
         MEGDNN_FOREACH_COMPUTING_DTYPE(cb)
+        cb(::megdnn::dtype::Bool)
 #undef cb
         default:
             megdnn_throw("bad mask dtype");

dnn/src/cuda/type_cvt/kern.cu

@@ -111,8 +111,7 @@ struct TypeCvtOpFromQuantized<
         ctype_dest, ctype_src,
         typename std::enable_if<
                 std::is_same<ctype_src, dt_qint8>::value ||
-                std::is_same<ctype_src, dt_quint8>::value ||
-				std::is_same<ctype_src, dt_bool>::value>::type> {
+                std::is_same<ctype_src, dt_quint8>::value>::type> {
     ctype_dest* dest;
     CudaDTypeParam<ctype_src> param;
     using src_vect_type = typename VectTypeTrait<ctype_src>::vect_type;
@@ -140,8 +139,7 @@ struct TypeCvtOpBetweenQuantized<
         ctype_dest, ctype_src,
         typename std::enable_if<
                 std::is_same<ctype_src, dt_qint8>::value ||
-                std::is_same<ctype_src, dt_quint8>::value ||
-				std::is_same<ctype_src, dt_bool>::value>::type> {
+                std::is_same<ctype_src, dt_quint8>::value>::type> {
     ctype_dest* dest;
     CudaDTypeParam<ctype_src> src_param;
     CudaDTypeParam<ctype_dest> dst_param;

dnn/src/cuda/type_cvt/opr_impl.cpp

@@ -109,6 +109,7 @@ void TypeCvtImpl::exec(_megdnn_tensor_in src, _megdnn_tensor_out dst) {
         return;                                 \
     }
             MEGDNN_FOREACH_COMPUTING_DTYPE(cb)
+            cb(::megdnn::dtype::Bool)
 #undef cb
             default:
                 megdnn_assert_internal(0);

src/opr/test/basic_arith/others.cpp

@@ -568,6 +568,27 @@ TEST(TestOprBasicArith, TypeCvtBool) {
     ASSERT_EQ(TensorShape({3}), host_y.shape());
 }
 
+TEST(TestOprBasicArith, TypeCvtFromBool) {
+    auto graph = ComputingGraph::make();
+    HostTensorGenerator<dtype::Bool> gen;
+    auto host_x = gen({2});
+    auto px = host_x->ptr<bool>();
+    px[0] = true;
+    px[1] = false;
+
+    auto x = opr::Host2DeviceCopy::make(*graph, host_x),
+         y = opr::TypeCvt::make(x, dtype::Int32{});
+    HostTensorND host_y;
+    auto func = graph->compile({make_callback_copy(y, host_y)});
+    func->execute();
+
+    auto py = host_y.ptr<int>();
+    for (size_t i = 0;i < 2;i ++) {
+        ASSERT_EQ(static_cast<int>(px[i]), py[i]);
+    }
+    ASSERT_EQ(TensorShape({2}), host_y.shape());
+}
+
 TEST(TestOprBasicArith, ElemwiseMemFwd) {
     auto graph = ComputingGraph::make();
     graph->options().graph_opt_level = 0;