fix(imperative): do not use output_desc in rng ops

GitOrigin-RevId: e6a399be17

imperative/src/impl/ops/rng.cpp

@@ -419,7 +419,8 @@ _INST_RNG_MAKER(2)
 template <typename Op>
 void exec(
         const OpDef& op, const SmallVector<TensorPtr>& inputs,
-        const SmallVector<TensorPtr>& outputs) {
+        const SmallVector<TensorPtr>& outputs,
+        const SmallVector<TensorPtr>& workspace) {
     auto&& rng = op.cast_final_safe<Op>();
 
     auto dest = outputs[0];
@@ -450,56 +451,71 @@ void exec(
 }
 
 template <typename Op>
-SmallVector<CompNode> infer_output_cns(
+SmallVector<LogicalTensorDesc> infer_output_attrs(
         const OpDef& op, const SmallVector<TensorPtr>& inputs) {
-    CompNode cn;
+    LogicalTensorDesc dest;
     auto&& rng = op.cast_final_safe<Op>();
     auto handle = rng.handle;
     if (handle) {
-        cn = RNGDnnOpManager::get_comp_node(handle);
+        dest.comp_node = RNGDnnOpManager::get_comp_node(handle);
     } else {
-        cn = inputs[0]->comp_node();
+        dest.comp_node = inputs[0]->comp_node();
     }
     constexpr bool rng_with_shape = OpMeth<Op>::DnnOp::NR_INPUTS == 0;
     if (!rng_with_shape) {
         for (int i = 0; i < inputs.size(); ++i) {
             mgb_assert(
-                    inputs[i]->comp_node() == cn,
+                    inputs[i]->comp_node() == dest.comp_node,
                     "%s expects the device of inputs[%d] to be same as the device of "
                     "handle; "
                     "got %s and %s actually",
                     rng.dyn_typeinfo()->name, i,
-                    inputs[i]->comp_node().to_string().c_str(), cn.to_string().c_str());
+                    inputs[i]->comp_node().to_string().c_str(),
+                    dest.comp_node.to_string().c_str());
         }
     }
-    return {cn};
+    dest.layout = _InferLayout<rng_with_shape>::do_infer(inputs[0], rng);
+    return {dest};
 }
 
 template <>
-SmallVector<CompNode> infer_output_cns<ShuffleRNG>(
+SmallVector<LogicalTensorDesc> infer_output_attrs<ShuffleRNG>(
         const OpDef& op, const SmallVector<TensorPtr>& inputs) {
-    SmallVector<CompNode> cns(2);
+    SmallVector<LogicalTensorDesc> dests(2);
     auto&& rng = op.cast_final_safe<ShuffleRNG>();
     auto handle = rng.handle;
     if (handle) {
-        cns[0] = RNGDnnOpManager::get_comp_node(handle);
-        cns[1] = RNGDnnOpManager::get_comp_node(handle);
+        dests[0].comp_node = RNGDnnOpManager::get_comp_node(handle);
+        dests[1].comp_node = RNGDnnOpManager::get_comp_node(handle);
     } else {
-        cns[0] = inputs[0]->comp_node();
-        cns[1] = inputs[0]->comp_node();
+        dests[0].comp_node = inputs[0]->comp_node();
+        dests[1].comp_node = inputs[0]->comp_node();
     }
-    return cns;
+    dests[0].layout = TensorLayout(inputs[0]->layout());
+    dests[0].layout.dtype = inputs[0]->layout().dtype;
+    dests[1].layout =
+            TensorLayout(TensorShape({inputs[0]->layout()[0]}), dtype::Int32());
+    return dests;
 }
 
 template <>
-SmallVector<CompNode> infer_output_cns<Dropout>(
+SmallVector<LogicalTensorDesc> infer_output_attrs<Dropout>(
         const OpDef& op, const SmallVector<TensorPtr>& inputs) {
-    SmallVector<CompNode> cns(2);
+    SmallVector<LogicalTensorDesc> dests(2);
     auto&& cn = inputs[0]->comp_node();
 
-    cns[0] = cn;
-    cns[1] = cn;
-    return cns;
+    dests[0].comp_node = cn;
+    dests[0].layout = TensorLayout(inputs[0]->layout());
+    dests[0].layout.dtype = inputs[0]->layout().dtype;
+
+    auto get_mask_size = [&]() -> size_t {
+        auto dnn_handle = MegDNNHandle::get(CompNodeEnv::from_comp_node(cn)).handle();
+        return dnn_handle->create_operator<megdnn::Dropout>()->get_mask_size_in_bytes(
+                inputs[0]->layout());
+    };
+    dests[1].comp_node = cn;
+    dests[1].layout = TensorLayout(TensorShape({get_mask_size()}), dtype::Byte());
+    return dests;
 }
 
 template <typename Op>
@@ -507,11 +523,11 @@ SmallVector<TensorPtr> apply_on_physical_tensor(
         const OpDef& def, const SmallVector<TensorPtr>& inputs,
         SmallVector<LogicalTensorDesc>& output_descs, const bool& validated) {
     SmallVector<TensorPtr> outputs;
-    SmallVector<CompNode> cns = infer_output_cns<Op>(def, inputs);
-    for (size_t i = 0; i < cns.size(); i++) {
-        outputs.push_back(Tensor::make(output_descs[i].layout, cns[i]));
+    SmallVector<LogicalTensorDesc> desc = infer_output_attrs<Op>(def, inputs);
+    for (auto&& i : desc) {
+        outputs.push_back(Tensor::make(i.layout, i.comp_node));
     }
-    exec<Op>(def, inputs, outputs);
+    exec<Op>(def, inputs, outputs, {});
     return outputs;
 }