refactor(imperative): remove infer_output_mem_desc

GitOrigin-RevId: bff62b33a0

imperative/python/megengine/core/__init__.py

@@ -12,13 +12,3 @@ from contextlib import contextmanager
 
 from ._imperative_rt.core2 import get_option, set_option
 from .tensor.megbrain_graph import Graph
-
-
-@contextmanager
-def option(key, value):
-    value = int(value)
-    old = get_option(key)
-    set_option(key, value)
-    yield
-    assert get_option(key) == value
-    set_option(key, old)

imperative/python/test/unit/core/test_interpreter.py

@@ -76,10 +76,11 @@ def test_drop_basic():
 def test_finalize():
     prog = """
 import megengine
-with megengine.core.option("enable_host_compute", 0):
-    x = megengine.tensor(0)
-    y = x + 1
-    y.numpy()
+megengine.core.set_option("enable_host_compute", 0)
+x = megengine.tensor(0)
+y = x + 1
+y.numpy()
+megengine.core.set_option("enable_host_compute", 1)
 """
     subprocess.check_call([sys.executable, "-c", prog])
 

imperative/python/test/unit/utils/test_profiler.py

@@ -15,7 +15,6 @@ import pytest
 from megengine import Parameter
 from megengine import distributed as dist
 from megengine import tensor
-from megengine.core import option
 from megengine.jit import trace
 from megengine.module import Module
 from megengine.utils.profiler import Profiler, scope

imperative/src/impl/interpreter/interpreter_impl.cpp

@@ -155,7 +155,6 @@ TensorInfo* ChannelImpl::put_impl(const HostTensorND& value, bool no_cache) {
         info->h_value = value;
         info->desc.value = value.proxy_to_default_cpu();
     }
-    info->mem_desc.id = StorageIdentifier::make(++m_storage_id);
     m_worker.add_task(
             {Profiler::next_id(), Put{info, value, no_cache},
              get_channel_state().stack_manager.dump()});
@@ -180,7 +179,6 @@ TensorInfo* ChannelImpl::put_impl(
     auto info = alloc();
     MGB_RECORD_EVENT(TensorCommandEvent, info->id, TensorCommandKind::Put);
     init(info, {data.layout(), data.comp_node()});
-    info->mem_desc.id = StorageIdentifier::make(++m_storage_id);
     info->ptr = Tensor::make(data, hvalue);
     MGB_RECORD_EVENT(
             TensorProduceEvent, info->id, info->desc.layout, info->desc.comp_node,
@@ -536,9 +534,6 @@ void ChannelImpl::init(TensorInfo* info, LogicalTensorDesc desc) {
     MGB_RECORD_EVENT(TensorDeclareEvent, info->id, info->name);
     info->status = TensorInfo::Allocated;
     info->desc = std::move(desc);
-    info->mem_desc.layout = info->desc.layout;
-    info->mem_desc.cn = info->desc.comp_node;
-    info->mem_desc.offset = 0;
 }
 
 void ChannelImpl::do_drop(TensorInfo* ptr, bool user = false) {
@@ -667,18 +662,14 @@ void ChannelImpl::do_apply_op(const ApplyOp& cmd, std::string reason) {
     bool profiling_device =
             Profiler::is_profiling() && Profiler::get_option("profile_device", 0);
     uint64_t apply_id = cmd.id;
-    struct TensorWithDesc {
-        TensorPtr tensor;
-        MemoryDesc desc;
-    };
-    SmallVector<TensorWithDesc> inputs;
+    SmallVector<TensorPtr> inputs;
     inputs.reserve(cmd.inputs.size());
     // refcnt == 1, owners: [TensorInfo::ptr]
     for (auto i : cmd.inputs) {
         mgb_assert(i->ptr, "Invalid input tensor ptr!");
         // refcnt ++, owners: [i->ptr, tensor_inputs]
         // tensor_inputs.push_back(i->ptr);
-        inputs.push_back({i->ptr, i->mem_desc});
+        inputs.push_back(i->ptr);
     }
     if (state.options.enable_dtr_auto_drop &&
         state.options.dtr_eviction_threshold > 0) {
@@ -686,56 +677,28 @@ void ChannelImpl::do_apply_op(const ApplyOp& cmd, std::string reason) {
     }
     auto apply_on_physical_tensor =
             [&](auto&& self, const OpDef& def,
-                SmallVector<TensorWithDesc> inputs) -> SmallVector<TensorWithDesc> {
+                SmallVector<TensorPtr> inputs) -> SmallVector<TensorPtr> {
         auto apply_functor = [&](std::shared_ptr<OpDef> op,
-                                 SmallVector<TensorWithDesc> inputs,
-                                 size_t nr_outputs) -> SmallVector<TensorWithDesc> {
+                                 SmallVector<TensorPtr> inputs,
+                                 size_t nr_outputs) -> SmallVector<TensorPtr> {
             auto opname = op->trait()->make_name(*op);
             imperative_log_profile_begin(opname.c_str());
             auto outputs = self(self, *op, inputs);
             imperative_log_profile_end(opname.c_str());
             return outputs;
         };
-        auto const_functor = [&](TensorPtr value) -> TensorWithDesc {
-            return {value, MemoryDesc{
-                                   value->layout(), 0, value->comp_node(),
-                                   StorageIdentifier::make()}};
-        };
+        auto const_functor = [&](TensorPtr value) -> TensorPtr { return value; };
         if (def.trait()->make_forward_graph) {
             // apply recursivily
             SmallVector<LogicalTensorDesc> input_descs;
             for (auto&& input : inputs) {
-                input_descs.push_back(
-                        {{{}, input.tensor->dtype()}, input.tensor->comp_node()});
+                input_descs.push_back({{{}, input->dtype()}, input->comp_node()});
             }
             auto forward_graph = OpDef::make_forward_graph(def, input_descs);
             auto outputs = forward_graph.apply(inputs, apply_functor, const_functor);
             return outputs;
         }
-        SmallVector<TensorPtr> input_tensors;
-        SmallVector<MemoryDesc> input_descs;
-        for (auto&& input : inputs) {
-            input_tensors.push_back(input.tensor);
-            input_descs.push_back(input.desc);
-        }
-        auto [output_descs, output_tensors, workspaces] =
-                init_output_and_workspace(def, input_tensors, input_descs);
-        if (!output_descs.empty()) {
-            OpDef::execute(def, input_tensors, output_tensors, workspaces);
-        } else {
-            output_tensors = OpDef::apply_on_physical_tensor(def, input_tensors);
-            for (auto&& output_tensor : output_tensors) {
-                output_descs.push_back(MemoryDesc{
-                        output_tensor->layout(), 0, output_tensor->comp_node(),
-                        StorageIdentifier::make()});
-            }
-        }
-        SmallVector<TensorWithDesc> outputs;
-        for (auto&& [output_tensor, output_desc] :
-             ranges::zip_view(output_tensors, output_descs)) {
-            outputs.push_back({output_tensor, output_desc});
-        }
-        return outputs;
+        return OpDef::apply_on_physical_tensor(def, inputs);
     };
     MGB_RECORD_EVENT(OpExecuteEvent, apply_id, {}, reason);
     // Begin profiling operator
@@ -787,8 +750,7 @@ void ChannelImpl::do_apply_op(const ApplyOp& cmd, std::string reason) {
             MGB_RECORD_EVENT(OpOutputFinishEvent, output->id);
         } else {
             MGB_RECORD_EVENT(OpOutputEvent, output->id);
-            produce_tensor(output, outputs[i].tensor);
-            output->mem_desc = outputs[i].desc;
+            produce_tensor(output, outputs[i]);
             MGB_RECORD_EVENT(OpOutputFinishEvent, output->id);
             sample_on_device(output->desc.comp_node, false);
         }
@@ -800,7 +762,7 @@ void ChannelImpl::do_apply_op(const ApplyOp& cmd, std::string reason) {
             estimate_compute_time += i->memory;
         }
         for (auto i : outputs) {
-            estimate_compute_time += i.tensor->blob()->size();
+            estimate_compute_time += i->blob()->size();
         }
         m_dtr.estimate_timestamp += estimate_compute_time / 1e8;
         for (auto i : cmd.outputs) {
@@ -1012,52 +974,6 @@ void ChannelImpl::alloc_tensor_with_evict(Blob* x) {
     set_log_level(pre_level);
 }
 
-std::tuple<SmallVector<MemoryDesc>, SmallVector<TensorPtr>, SmallVector<TensorPtr>>
-ChannelImpl::init_output_and_workspace(
-        const OpDef& def, SmallVector<TensorPtr> inputs,
-        SmallVector<MemoryDesc> inputs_mem_desc) {
-    auto [outputs_desc, workspaces_desc] =
-            OpDef::infer_output_mem_desc(def, inputs, inputs_mem_desc);
-    if (!outputs_desc.size()) {
-        // failed to infer memplan
-        return {{}, {}, {}};
-    }
-    // refine storage id to make it unique
-    for (auto&& desc : outputs_desc) {
-        if (desc.id->is_sys_alloc()) {
-            // TODO: there may be some outputs sharing the same storage id
-            desc.id->id = ++m_storage_id;
-        }
-    }
-    auto& state = get_worker_state();
-    auto alloc_storage = [&](SmallVector<MemoryDesc>& desc) {
-        SmallVector<TensorPtr> tensors;
-        for (size_t i = 0; i < desc.size(); i++) {
-            if (desc[i].id->is_sys_alloc()) {
-                tensors.push_back(Tensor::make(desc[i].layout, desc[i].cn));
-                if (state.options.enable_dtr_auto_drop && !desc[i].layout.is_empty()) {
-                    alloc_tensor_with_evict(tensors.back()->blob().get());
-                }
-            } else if (desc[i].id->is_from_other()) {
-                for (size_t j = 0; j < inputs_mem_desc.size(); j++) {
-                    if (inputs_mem_desc[j].id->desc == desc[i].id->desc) {
-                        tensors.push_back(
-                                inputs[j]->sub(desc[i].offset, desc[i].layout));
-                        break;
-                    }
-                }
-            } else if (desc[i].id->is_device_ptr()) {
-                tensors.push_back(desc[i].id->ptr);
-            } else {
-                mgb_assert(0, "not implemented");
-            }
-        }
-        return tensors;
-    };
-
-    return {outputs_desc, alloc_storage(outputs_desc), alloc_storage(workspaces_desc)};
-}
-
 void ChannelImpl::process_one_task(Command& icmd) {
     using namespace ranges;
     using namespace ranges::views;

imperative/src/impl/interpreter/interpreter_impl.h

@@ -105,11 +105,6 @@ private:
     void flush_apply_stack();
     void do_apply_op(const ApplyOp& cmd, std::string reason);
 
-    std::tuple<SmallVector<MemoryDesc>, SmallVector<TensorPtr>, SmallVector<TensorPtr>>
-    init_output_and_workspace(
-            const OpDef& def, SmallVector<TensorPtr> inputs,
-            SmallVector<MemoryDesc> inputs_mem_desc);
-
     void dispatch_default_cpu(
             std::shared_ptr<OpDef> op, const SmallVector<TensorInfo*>& input_infos,
             const SmallVector<LogicalTensorDesc>& input_descs,
@@ -296,6 +291,8 @@ private:
                    op_blacklist.end();
         }
 
+        // operators that cannot be re-computed, including :
+        // distributed operators, inplace operator, random generator operators
         std::vector<std::string> op_blacklist = {
                 "CollectiveComm", "InplaceAdd", "ParamPackSplit", "ParamPackConcat",
                 "GaussianRNG",    "UniformRNG", "GammaRNG",       "PermutationRNG",

imperative/src/impl/interpreter/tensor_info.h

@@ -59,7 +59,6 @@ struct TensorInfo {
     // Lock interpreter when visiting `ptr`.
     TensorPtr ptr;
     LogicalTensorDesc desc;
-    MemoryDesc mem_desc;
 
     double compute_time;
     size_t memory;

imperative/src/impl/op_def.cpp

@@ -41,20 +41,6 @@ SmallVector<TensorPtr> OpDef::apply_on_physical_tensor(
         const OpDef& def, SmallVector<TensorPtr> inputs) {
     return def.trait()->apply_on_physical_tensor(def, std::move(inputs));
 }
-
-std::tuple<SmallVector<MemoryDesc>, SmallVector<MemoryDesc>> OpDef::
-        infer_output_mem_desc(
-                const OpDef& def, const SmallVector<TensorPtr>& inputs_tensors,
-                const SmallVector<MemoryDesc>& inputs_mems) {
-    return def.trait()->infer_output_mem_desc(def, inputs_tensors, inputs_mems);
-}
-
-void OpDef::execute(
-        const OpDef& def, SmallVector<TensorPtr> inputs, SmallVector<TensorPtr> outputs,
-        SmallVector<TensorPtr> workspace) {
-    def.trait()->execute(def, std::move(inputs), outputs, std::move(workspace));
-}
-
 void OpDef::apply_on_device_tensornd(
         const OpDef& def, const SmallVector<DeviceTensorND>& inputs,
         SmallVector<DeviceTensorND>* outputs) {

imperative/src/impl/op_trait.cpp

@@ -43,13 +43,6 @@ void OpMethFallbackByProxyGraph::impl(
         ApplyOnPhysicalTensor& func, op_meth_tag::ApplyOnPhysicalTensor) {
     func.Base::operator=(proxy_graph_detail::apply_on_physical_tensor);
 }
-void OpMethFallbackByProxyGraph::impl(Execute& func, op_meth_tag::Execute) {
-    func.Base::operator=(proxy_graph_detail::execute);
-}
-void OpMethFallbackByProxyGraph::impl(
-        InferOutputMemDesc& func, op_meth_tag::InferOutputMemDesc) {
-    func.Base::operator=(proxy_graph_detail::infer_output_mem_desc);
-}
 void OpMethFallbackByProxyGraph::impl(
         InferOutputAttrsFallible& func, op_meth_tag::InferOutputAttrsFallible) {
     func.Base::operator=(proxy_graph_detail::infer_output_attrs_fallible);
@@ -62,10 +55,6 @@ void OpMethFallbackFromSubgraph::impl(
         ApplyOnPhysicalTensor& func, op_meth_tag::ApplyOnPhysicalTensor) {
     func.Base::operator=(subgraph_detail::apply_on_physical_tensor);
 }
-void OpMethFallbackFromSubgraph::impl(
-        InferOutputMemDesc& func, op_meth_tag::InferOutputMemDesc) {
-    func.Base::operator=(subgraph_detail::infer_output_mem_desc);
-}
 void OpMethFallbackFromSubgraph::impl(
         ApplyOnVarNode& func, op_meth_tag::ApplyOnVarNode) {
     func.Base::operator=(subgraph_detail::apply_on_var_node);

imperative/src/impl/op_trait.h

@@ -64,12 +64,6 @@ OpMethType(DecideDispatchMode,
 OpMethType(ApplyOnPhysicalTensor,
            decltype(OpDef::apply_on_physical_tensor));
 
-OpMethType(InferOutputMemDesc,
-           decltype(OpDef::infer_output_mem_desc));
-
-OpMethType(Execute,
-           decltype(OpDef::execute));
-
 OpMethType(ApplyOnDeviceTensorND,
            decltype(OpDef::apply_on_device_tensornd));
 
@@ -123,8 +117,6 @@ struct OpMethFallback : OpMethImplBase {
 struct OpMethFallbackByProxyGraph : OpMethImplBase {
     using OpMethImplBase::impl;
     static void impl(ApplyOnPhysicalTensor& func, op_meth_tag::ApplyOnPhysicalTensor);
-    static void impl(Execute& func, op_meth_tag::Execute);
-    static void impl(InferOutputMemDesc& func, op_meth_tag::InferOutputMemDesc);
     static void impl(
             InferOutputAttrsFallible& func, op_meth_tag::InferOutputAttrsFallible);
     static void impl(GradMaker& func, op_meth_tag::GradMaker);
@@ -133,7 +125,6 @@ struct OpMethFallbackByProxyGraph : OpMethImplBase {
 struct OpMethFallbackFromSubgraph : OpMethImplBase {
     using OpMethImplBase::impl;
     static void impl(ApplyOnPhysicalTensor& func, op_meth_tag::ApplyOnPhysicalTensor);
-    static void impl(InferOutputMemDesc& func, op_meth_tag::InferOutputMemDesc);
     static void impl(ApplyOnVarNode& func, op_meth_tag::ApplyOnVarNode);
     static void impl(
             InferOutputAttrsFallible& func, op_meth_tag::InferOutputAttrsFallible);
@@ -185,8 +176,6 @@ struct OpTrait {
     OpDefMaker make_from_op_node;
     DecideDispatchMode decide_dispatch_mode;
     ApplyOnPhysicalTensor apply_on_physical_tensor;
-    InferOutputMemDesc infer_output_mem_desc;
-    Execute execute;
     ApplyOnDeviceTensorND apply_on_device_tensornd;
     ApplyOnVarNode apply_on_var_node;
     InferOutputAttrsFallible infer_output_attrs_fallible;
@@ -207,8 +196,6 @@ struct OpTrait {
     cb(make_from_op_node)           \
     cb(decide_dispatch_mode)        \
     cb(apply_on_physical_tensor)    \
-    cb(infer_output_mem_desc)       \
-    cb(execute)                     \
     cb(apply_on_device_tensornd)    \
     cb(apply_on_var_node)           \
     cb(infer_output_attrs_fallible) \

imperative/src/impl/ops/broadcast.cpp

@@ -81,50 +81,10 @@ std::tuple<SmallVector<LogicalTensorDesc>, bool> infer_output_attrs_fallible(
     return {{{TensorLayout(out_shape, src.layout.dtype), src.comp_node}}, true};
 }
 
-std::tuple<SmallVector<MemoryDesc>, SmallVector<MemoryDesc>> infer_output_mem_desc(
-        const OpDef& def, const SmallVector<TensorPtr>& inputs_tensors,
-        const SmallVector<MemoryDesc>& inputs_mems) {
-    auto& input = inputs_tensors[0];
-    TensorShape target_shape;
-    cg::copy_tensor_value_to_shape(
-            target_shape, inputs_tensors[1]->get_value().proxy_to_default_cpu());
-    // TODO: memory forward
-    // if (input->shape().eq_shape(target_shape)) {
-    //     return {{{input->layout(), 0, input->comp_node(),
-    //     StorageIdentifier::make(&inputs_mems[0])}}, {}};
-    // }
-    return {{{{target_shape, input->dtype()},
-              0,
-              input->comp_node(),
-              StorageIdentifier::make(0)}},
-            {}};
-}
-
-void execute(
-        const OpDef& def, SmallVector<TensorPtr> inputs, SmallVector<TensorPtr> outputs,
-        SmallVector<TensorPtr> workspace) {
-    if (outputs[0]->layout().is_empty()) {
-        return;
-    }
-    if (inputs[0]->shape().eq_shape(outputs[0]->shape())) {
-        mgb_assert(inputs[0]->layout().eq_layout(outputs[0]->layout()));
-        // TODO: memory forward
-        // mgb_assert(inputs[0]->offset() == outputs[0]->offset());
-        // mgb_assert(inputs[0]->blob() == outputs[0]->blob());
-        outputs[0]->dev_tensor().copy_from_fixlayout(inputs[0]->dev_tensor());
-    } else {
-        TensorLayout input_layout = inputs[0]->layout().broadcast(outputs[0]->shape());
-        outputs[0]->dev_tensor().copy_from_fixlayout(inputs[0]->dev_tensor().sub(
-                SubTensorSpec::make_from_layout(input_layout)));
-    }
-}
-
 OP_TRAIT_REG(Broadcast, Broadcast, opr::Broadcast)
         .make_from_op_node(make_from_op_node)
         .apply_on_var_node(apply_on_var_node)
         .infer_output_attrs_fallible(infer_output_attrs_fallible)
-        .infer_output_mem_desc(infer_output_mem_desc)
-        .execute(execute)
         .fallback();
 }  // namespace broadcast
 
@@ -187,41 +147,9 @@ std::tuple<SmallVector<LogicalTensorDesc>, bool> infer_output_attrs_fallible(
     return {{{TensorLayout(out_shape, src.layout.dtype), src.comp_node}}, true};
 }
 
-std::tuple<SmallVector<MemoryDesc>, SmallVector<MemoryDesc>> infer_output_mem_desc(
-        const OpDef& def, const SmallVector<TensorPtr>& inputs,
-        const SmallVector<MemoryDesc>& inputs_mems) {
-    auto&& op_def = def.cast_final_safe<Reshape>();
-    size_t nr_inp = inputs.size();
-    mgb_assert(nr_inp == 2, "Reshape expects 2 inputs; got %lu actually", nr_inp);
-    auto&& src = inputs[0];
-    auto&& tshp_nd = inputs[1];
-    auto slayout = src->layout();
-
-    TensorShape tshp;
-    cg::copy_tensor_value_to_shape(tshp, tshp_nd->get_value().proxy_to_default_cpu());
-    if (op_def.axis != opr::Reshape::Param::INVALID_AXIS) {
-        mgb_assert(tshp[op_def.axis] == -1);
-        tshp[op_def.axis] = 1;
-        tshp[op_def.axis] = src->layout().total_nr_elems() / tshp.total_nr_elems();
-    }
-    TensorLayout tlayout = slayout.reshape(tshp);
-    // memory forward
-    return {{{tlayout, 0, src->comp_node(), StorageIdentifier::make(&inputs_mems[0])}},
-            {}};
-}
-
-void execute(
-        const OpDef& def, SmallVector<TensorPtr> inputs, SmallVector<TensorPtr> outputs,
-        SmallVector<TensorPtr> workspace) {
-    mgb_assert(inputs[0]->offset() == outputs[0]->offset());
-    mgb_assert(inputs[0]->blob() == outputs[0]->blob());
-}
-
 OP_TRAIT_REG(Reshape, Reshape)
         .apply_on_var_node(apply_on_var_node)
         .infer_output_attrs_fallible(infer_output_attrs_fallible)
-        .infer_output_mem_desc(infer_output_mem_desc)
-        .execute(execute)
         .fallback();
 }  // namespace reshape
 

imperative/src/impl/ops/cond_take.cpp

@@ -78,25 +78,10 @@ std::tuple<SmallVector<LogicalTensorDesc>, bool> infer_output_attrs_fallible(
             false};
 }
 
-std::tuple<SmallVector<MemoryDesc>, SmallVector<MemoryDesc>> infer_output_mem_desc(
-        const OpDef& def, const SmallVector<TensorPtr>& inputs,
-        const SmallVector<MemoryDesc>& inputs_mems) {
-    return {{}, {}};
-}
-
-void execute(
-        const OpDef& def, const SmallVector<TensorPtr>& inputs,
-        const SmallVector<TensorPtr>& outputs,
-        const SmallVector<TensorPtr>& workspace) {
-    mgb_assert(0);
-}
-
 OP_TRAIT_REG(CondTake, CondTake, opr::CondTake)
         .apply_on_var_node(apply_on_var_node)
         .apply_on_physical_tensor(apply_on_physical_tensor)
         .infer_output_attrs_fallible(infer_output_attrs_fallible)
-        .infer_output_mem_desc(infer_output_mem_desc)
-        .execute(execute)
         .fallback();
 
 }  // namespace

imperative/src/impl/ops/custom_opdef.cpp

@@ -234,12 +234,6 @@ std::tuple<SmallVector<LogicalTensorDesc>, bool> infer_output_attrs_fallible(
     return op.infer_output_attrs(inputs);
 }
 
-std::tuple<SmallVector<MemoryDesc>, SmallVector<MemoryDesc>> infer_output_mem_desc(
-        const OpDef& def, const SmallVector<TensorPtr>& inputs_tensors,
-        const SmallVector<MemoryDesc>& inputs_mems) {
-    return {{}, {}};
-}
-
 size_t hash(const OpDef& def) {
     auto&& op = static_cast<const CustomOpDef&>(def);
     const custom::Param& param = op.param();
@@ -279,7 +273,6 @@ OP_TRAIT_REG(CustomOpDef, CustomOpDef)
         .apply_on_var_node(apply_on_var_node)
         .apply_on_device_tensornd(apply_on_device_tensornd)
         .infer_output_attrs_fallible(infer_output_attrs_fallible)
-        .infer_output_mem_desc(infer_output_mem_desc)
         .hash(hash)
         .is_same_st(is_same_st)
         .props(props)

imperative/src/impl/ops/elemwise.cpp

@@ -110,35 +110,6 @@ void apply_on_device_tensornd(
     opr::Elemwise::perform(op_def.mode, (*outputs)[0], inputs, dnn_opr);
 }
 
-void execute(
-        const OpDef& def, SmallVector<TensorPtr> inputs, SmallVector<TensorPtr> outputs,
-        SmallVector<TensorPtr> workspace) {
-    mgb_assert(outputs.size() == 1);
-    SmallVector<DeviceTensorND> inp_tensornds(inputs.size());
-    for (size_t i = 0; i < inputs.size(); ++i) {
-        inp_tensornds[i] = inputs[i]->dev_tensor();
-    }
-    SmallVector<DeviceTensorND> out_tensornds = {outputs[0]->dev_tensor()};
-    apply_on_device_tensornd(def, inp_tensornds, &out_tensornds);
-}
-
-std::tuple<SmallVector<MemoryDesc>, SmallVector<MemoryDesc>> infer_output_mem_desc(
-        const OpDef& def, const SmallVector<TensorPtr>& inputs_tensors,
-        const SmallVector<MemoryDesc>& inputs_mems) {
-    auto&& op_def = def.cast_final_safe<Elemwise>();
-    TensorShapeArray inp_shapes(inputs_tensors.size());
-    for (size_t i = 0; i < inputs_tensors.size(); ++i) {
-        inp_shapes[i] = inputs_tensors[i]->layout();
-    }
-    TensorShape shape = opr::Elemwise::get_output_var_shape(op_def.mode, inp_shapes);
-    SmallVector<MemoryDesc> outputs = {
-            {{shape, inputs_tensors[0]->dtype()},
-             0,
-             inputs_tensors[0]->comp_node(),
-             StorageIdentifier::make(1)}};
-    return {outputs, {}};
-}
-
 SmallVector<TensorPtr> apply_on_physical_tensor(
         const OpDef& def, const SmallVector<TensorPtr>& inputs) {
     auto&& op_def = def.cast_final_safe<Elemwise>();
@@ -251,7 +222,7 @@ cg::OperatorNodeBase* apply_inplace_add_on_var_node(
 SmallVector<TensorPtr> apply_inplace_add_on_physical_tensor(
         const OpDef& def, const SmallVector<TensorPtr>& inputs) {
     mgb_assert(
-            inputs[0]->blob().use_count() == 2 && inputs[0]->blob()->storage().unique(),
+            inputs[0]->blob().use_count() == 1 && inputs[0]->blob()->storage().unique(),
             "This inplace modification may change the elements of other tensors. "
             "Please set MEGENGINE_INPLACE_UPDATE to 0 to ensure the program runs "
             "correctly.");
@@ -265,23 +236,6 @@ SmallVector<TensorPtr> apply_inplace_add_on_physical_tensor(
     return {std::make_shared<Tensor>(dest->blob(), dest->offset(), dest->layout())};
 }
 
-void execute_inplace(
-        const OpDef& def, SmallVector<TensorPtr> inputs, SmallVector<TensorPtr> outputs,
-        SmallVector<TensorPtr> workspace) {
-    apply_inplace_add_on_physical_tensor(def, inputs);
-}
-
-std::tuple<SmallVector<MemoryDesc>, SmallVector<MemoryDesc>>
-infer_inplace_output_mem_desc(
-        const OpDef& def, const SmallVector<TensorPtr>& inputs_tensors,
-        const SmallVector<MemoryDesc>& inputs_mems) {
-    auto dest = inputs_tensors[0];
-    SmallVector<MemoryDesc> outputs = {
-            {dest->layout(), 0, dest->comp_node(),
-             StorageIdentifier::make(&inputs_mems[0])}};
-    return {outputs, {}};
-}
-
 std::tuple<SmallVector<LogicalTensorDesc>, bool> infer_inplace_add_output_attrs_fallible(
         const OpDef& def, const SmallVector<LogicalTensorDesc>& inputs) {
     mgb_assert(inputs.size() == 4, "invalid input number for inplace_add");
@@ -319,16 +273,12 @@ OP_TRAIT_REG(Elemwise, Elemwise, opr::Elemwise)
         .infer_output_attrs_fallible(infer_output_attrs_fallible)
         .apply_on_device_tensornd(apply_on_device_tensornd)
         .apply_on_physical_tensor(apply_on_physical_tensor)
-        .infer_output_mem_desc(infer_output_mem_desc)
-        .execute(execute)
         .fallback();
 
 OP_TRAIT_REG(InplaceAdd, InplaceAdd, opr::AddUpdate)
         .apply_on_var_node(apply_inplace_add_on_var_node)
         .apply_on_physical_tensor(apply_inplace_add_on_physical_tensor)
         .infer_output_attrs_fallible(infer_inplace_add_output_attrs_fallible)
-        .infer_output_mem_desc(infer_inplace_output_mem_desc)
-        .execute(execute_inplace)
         .fallback();
 }  // anonymous namespace
 

imperative/src/impl/ops/misc.cpp

@@ -75,16 +75,11 @@ SmallVector<LogicalTensorDesc> infer_output_attrs(
     dests[size].layout = TensorLayout(TensorShape({1}), dtype::Int32());
     return dests;
 }
-std::tuple<SmallVector<MemoryDesc>, SmallVector<MemoryDesc>> infer_output_mem_desc(
-        const OpDef& def, const SmallVector<TensorPtr>& inputs_tensors,
-        const SmallVector<MemoryDesc>& inputs_mems) {
-    return {{}, {}};
-}
+
 OP_TRAIT_REG(CheckNonFinite, CheckNonFinite)
         .apply_on_var_node(apply_on_var_node)
         .apply_on_physical_tensor(apply_on_physical_tensor)
         .infer_output_attrs_fallible(infer_output_attrs_fallible)
-        .infer_output_mem_desc(infer_output_mem_desc)
         .fallback();
 }  // namespace check_non_finite
 

imperative/src/impl/ops/reduce.cpp

@@ -36,6 +36,7 @@ std::shared_ptr<OpDef> make_from_op_node(cg::OperatorNodeBase* node_) {
     return Reduce::make(node->param());
 }
 
+// TODO: using this for apply_on_physical_tensor
 bool memory_forward_success(const OpDef& def, SmallVector<TensorPtr> inputs) {
     auto&& reduce = static_cast<const Reduce&>(def);
     if (reduce.mode != Reduce::Mode::SUM_SQR && inputs.size() == 2) {
@@ -49,31 +50,9 @@ bool memory_forward_success(const OpDef& def, SmallVector<TensorPtr> inputs) {
     return false;
 }
 
-std::tuple<SmallVector<MemoryDesc>, SmallVector<MemoryDesc>> infer_output_mem_desc(
-        const OpDef& def, const SmallVector<TensorPtr>& inputs_tensors,
-        const SmallVector<MemoryDesc>& inputs_mems) {
-    if (memory_forward_success(def, inputs_tensors)) {
-        auto& src_desc = inputs_mems[0];
-        return {{{src_desc.layout, 0, src_desc.cn, StorageIdentifier::make(&src_desc)}},
-                {}};
-    }
-    return proxy_graph_detail::infer_output_mem_desc(def, inputs_tensors, inputs_mems);
-}
-
-void execute(
-        const OpDef& def, SmallVector<TensorPtr> inputs, SmallVector<TensorPtr> outputs,
-        SmallVector<TensorPtr> workspace) {
-    if (memory_forward_success(def, inputs)) {
-        return;
-    }
-    return proxy_graph_detail::execute(def, inputs, outputs, workspace);
-}
-
 OP_TRAIT_REG(Reduce, Reduce, opr::Reduce)
         .make_from_op_node(make_from_op_node)
         .apply_on_var_node(apply_on_var_node)
-        .infer_output_mem_desc(infer_output_mem_desc)
-        .execute(execute)
         .fallback();
 }  // namespace reduce
 }  // namespace

imperative/src/impl/ops/rng.cpp

@@ -517,20 +517,6 @@ SmallVector<LogicalTensorDesc> infer_output_attrs<Dropout>(
     return dests;
 }
 
-template <typename Op>
-std::tuple<SmallVector<MemoryDesc>, SmallVector<MemoryDesc>> infer_output_mem_desc(
-        const OpDef& def, const SmallVector<TensorPtr>& inputs_tensors,
-        const SmallVector<MemoryDesc>& inputs_mems) {
-    auto&& dests = infer_output_attrs<Op>(def, inputs_tensors);
-    SmallVector<MemoryDesc> outputs;
-    for (size_t i = 0; i < dests.size(); ++i) {
-        outputs.push_back(
-                {dests[i].layout, 0, dests[i].comp_node,
-                 StorageIdentifier::make(i + 1)});
-    }
-    return {outputs, {}};
-}
-
 template <typename Op>
 SmallVector<TensorPtr> apply_on_physical_tensor(
         const OpDef& def, const SmallVector<TensorPtr>& inputs) {
@@ -543,13 +529,6 @@ SmallVector<TensorPtr> apply_on_physical_tensor(
     return outputs;
 }
 
-template <typename Op>
-void execute(
-        const OpDef& def, SmallVector<TensorPtr> inputs, SmallVector<TensorPtr> outputs,
-        SmallVector<TensorPtr> workspace) {
-    exec<Op>(def, inputs, outputs, {});
-}
-
 template <typename Op, typename Output>
 Output apply_on_var_node(const OpDef& def, const VarNodeArray& inputs) {
     size_t nr_inp = inputs.size();
@@ -641,8 +620,6 @@ CompNode get_rng_handle_compnode(Handle handle) {
             .apply_on_var_node(apply_on_var_node<NAME, Output>)             \
             .apply_on_physical_tensor(apply_on_physical_tensor<NAME>)       \
             .infer_output_attrs_fallible(infer_output_attrs_fallible<NAME>) \
-            .infer_output_mem_desc(infer_output_mem_desc<NAME>)             \
-            .execute(execute<NAME>)                                         \
             .fallback();                                                    \
     }
 

imperative/src/impl/ops/tensor_manip.cpp

@@ -141,39 +141,6 @@ std::tuple<SmallVector<LogicalTensorDesc>, bool> infer_output_attrs_fallible(
     return {{{value.layout(), desc.comp_node, std::move(value)}}, true};
 }
 
-std::tuple<SmallVector<MemoryDesc>, SmallVector<MemoryDesc>> infer_output_mem_desc(
-        const OpDef& def, const SmallVector<TensorPtr>& inputs,
-        const SmallVector<MemoryDesc>& inputs_mems) {
-    HostTensorND tensor = get_var_shape_host_tensor(def, inputs);
-    SmallVector<MemoryDesc> ret;
-    auto&& blob = MultiCNConstTensorCache::inst().lookup(tensor);
-    if (blob) {
-        ret.push_back(
-                {tensor.layout(), 0, inputs[0]->comp_node(),
-                 StorageIdentifier::make(Tensor::make(
-                         std::forward<decltype(blob)>(blob), tensor.layout(),
-                         tensor))});
-    } else {
-        ret.push_back(
-                {tensor.layout(), 0, inputs[0]->comp_node(),
-                 StorageIdentifier::make(1)});
-    }
-    return {ret, {}};
-}
-
-void execute(
-        const OpDef& def, const SmallVector<TensorPtr>& inputs,
-        const SmallVector<TensorPtr>& outputs,
-        const SmallVector<TensorPtr>& workspace) {
-    HostTensorND tensor = get_var_shape_host_tensor(def, inputs);
-    SmallVector<MemoryDesc> ret;
-    auto&& blob = MultiCNConstTensorCache::inst().lookup(tensor);
-    if (!blob || blob->storage() != outputs[0]->blob()->storage()) {
-        outputs[0]->dev_tensor().copy_from_fixlayout(tensor);
-        AsyncReleaser::inst()->add(tensor);
-    }
-}
-
 std::shared_ptr<OpDef> make_from_op_node(cg::OperatorNodeBase* node_) {
     auto* node = &node_->cast_final_safe<opr::GetVarShape>();
     return GetVarShape::make(node->param());
@@ -186,8 +153,6 @@ OP_TRAIT_REG(GetVarShape, GetVarShape, opr::GetVarShape)
         .apply_on_var_node(apply_on_var_node)
         .apply_on_device_tensornd(apply_on_device_tensornd)
         .apply_on_physical_tensor(apply_on_physical_tensor)
-        .infer_output_mem_desc(infer_output_mem_desc)
-        .execute(execute)
         .fallback();
 }  // namespace get_var_shape
 
@@ -215,38 +180,6 @@ cg::OperatorNodeBase* param_pack_split_apply_on_var_node(
     return opr;
 }
 
-std::tuple<SmallVector<MemoryDesc>, SmallVector<MemoryDesc>>
-param_pack_split_infer_output_mem_desc(
-        const OpDef& def, const SmallVector<TensorPtr>& inputs,
-        const SmallVector<MemoryDesc>& inputs_mems) {
-    auto&& param = def.cast_final_safe<ParamPackSplit>();
-    mgb_assert(
-            inputs.size() == 1, "ParamPackSplit take 1 input, got %lu", inputs.size());
-    auto&& inp = inputs[0];
-    auto&& shp = inp->layout();
-    mgb_assert(shp.ndim == 1, "ParamPackSplit input shape invalid, ndim should be 1");
-    mgb_assert(param.shapes.size() * 2 == param.offsets.size());
-    SmallVector<MemoryDesc> ret;
-    auto&& shapes = get_shapes(param.shapes);
-    size_t dtype_size = inputs[0]->layout().dtype.size();
-    for (size_t i = 0; i < shapes.size(); ++i) {
-        // memory forward
-        ret.push_back(
-                {{shapes[i], inputs[0]->dtype()},
-                 param.offsets[i * 2] * dtype_size,
-                 inp->comp_node(),
-                 StorageIdentifier::make(&inputs_mems[0])});
-    }
-    return {ret, {}};
-}
-
-void param_pack_split_execute(
-        const OpDef& def, const SmallVector<TensorPtr>& inputs,
-        const SmallVector<TensorPtr>& outputs,
-        const SmallVector<TensorPtr>& workspace) {
-    // do nothing
-}
-
 SmallVector<TensorPtr> param_pack_split_apply_on_physical_tensor(
         const OpDef& def, const SmallVector<TensorPtr>& inputs) {
     auto&& param = def.cast_final_safe<ParamPackSplit>();
@@ -268,8 +201,6 @@ SmallVector<TensorPtr> param_pack_split_apply_on_physical_tensor(
 
 OP_TRAIT_REG(ParamPackSplit, ParamPackSplit, mgb::opr::ParamPackSplit)
         .apply_on_var_node(param_pack_split_apply_on_var_node)
-        .infer_output_mem_desc(param_pack_split_infer_output_mem_desc)
-        .execute(param_pack_split_execute)
         .apply_on_physical_tensor(param_pack_split_apply_on_physical_tensor)
         .fallback();
 
@@ -286,75 +217,6 @@ cg::OperatorNodeBase* param_pack_concat_apply_on_var_node(
     return opr;
 }
 
-std::tuple<SmallVector<MemoryDesc>, SmallVector<MemoryDesc>>
-param_pack_concat_infer_output_mem_desc(
-        const OpDef& def, const SmallVector<TensorPtr>& inputs,
-        const SmallVector<MemoryDesc>& inputs_mems) {
-    def.cast_final_safe<ParamPackConcat>();
-    mgb_assert(inputs.size() > 1, "param_pack should have at least one input");
-    auto comp_node = inputs.front()->comp_node();
-    auto dtype = inputs.front()->dtype();
-    size_t nr_inputs = inputs.size() - 1;
-    size_t nr_elems = 0;
-    for (size_t i = 0; i < nr_inputs; ++i) {
-        auto& input = inputs[i];
-        mgb_assert(
-                comp_node == input->comp_node(),
-                "inputs for param_pack_concat must in same comp_node");
-        mgb_assert(
-                dtype == input->dtype(),
-                "inputs for param_pack_concat must have same dtype");
-        nr_elems += input->layout().total_nr_elems();
-    }
-    auto dest_layout = TensorLayout({nr_elems}, dtype);
-    auto caller = DnnOprCaller<megdnn::ParamPackConcat>(comp_node);
-    size_t ws_size;
-    {
-        TensorShapeArray src_shapes;
-        for (size_t i = 0; i < nr_inputs; ++i) {
-            src_shapes.push_back(inputs[i]->shape());
-        }
-        ws_size = caller.op->get_workspace_in_bytes(
-                src_shapes, inputs.back()->shape(), TensorShape{});
-    }
-
-    SmallVector<MemoryDesc> outputs = {
-            {dest_layout, 0, comp_node, StorageIdentifier::make(1)}};
-    MemoryDesc workspace = {
-            {{ws_size}, dtype::Byte()}, 0, comp_node, StorageIdentifier::make(2)};
-
-    return {outputs, {workspace}};
-}
-
-void param_pack_concat_execute(
-        const OpDef& def, const SmallVector<TensorPtr>& inputs,
-        const SmallVector<TensorPtr>& outputs,
-        const SmallVector<TensorPtr>& workspace) {
-    def.cast_final_safe<ParamPackConcat>();
-    mgb_assert(inputs.size() > 1, "param_pack should have at least one input");
-    auto comp_node = inputs.front()->comp_node();
-    size_t nr_inputs = inputs.size() - 1;
-    auto caller = DnnOprCaller<megdnn::ParamPackConcat>(comp_node);
-    size_t srcs_size = sizeof(void*) * nr_inputs;
-    void** srcs_raw_ptr = (void**)comp_node.alloc_host(srcs_size);
-    std::shared_ptr<dt_byte> srcs_ptr = {
-            (dt_byte*)srcs_raw_ptr,
-            [comp_node](dt_byte* ptr) { comp_node.free_host(ptr); }};
-    TensorLayout srcs_layout = TensorLayout{{nr_inputs}, dtype::Int32()};
-    for (size_t i = 0; i < nr_inputs; ++i) {
-        srcs_raw_ptr[i] = inputs[i]->dev_tensor().as_megdnn().raw_ptr();
-    }
-    HostTensorStorage srcs_storage;
-    srcs_storage.reset(comp_node, srcs_size, srcs_ptr);
-    megdnn::Workspace dnn_wk(
-            workspace[0]->blob()->storage().get(), workspace[0]->blob()->size());
-    caller.op->exec(
-            {srcs_raw_ptr, srcs_layout}, inputs.back()->dev_tensor().as_megdnn(),
-            outputs[0]->dev_tensor().as_megdnn(), dnn_wk);
-    AsyncReleaser::inst()->add(
-            HostTensorND{comp_node, srcs_layout}.storage(srcs_storage));
-}
-
 SmallVector<TensorPtr> param_pack_concat_apply_on_physical_tensor(
         const OpDef& def, const SmallVector<TensorPtr>& inputs) {
     def.cast_final_safe<ParamPackConcat>();
@@ -407,8 +269,6 @@ SmallVector<TensorPtr> param_pack_concat_apply_on_physical_tensor(
 
 OP_TRAIT_REG(ParamPackConcat, ParamPackConcat, mgb::opr::ParamPackConcat)
         .apply_on_var_node(param_pack_concat_apply_on_var_node)
-        .infer_output_mem_desc(param_pack_concat_infer_output_mem_desc)
-        .execute(param_pack_concat_execute)
         .apply_on_physical_tensor(param_pack_concat_apply_on_physical_tensor)
         .fallback();
 }  // namespace param_pack

imperative/src/impl/ops/utility.cpp

@@ -445,12 +445,6 @@ auto make_name(const OpDef& def) {
     return ssprintf("CompiledOp[%s]", op.op->make_name().c_str());
 }
 
-std::tuple<SmallVector<MemoryDesc>, SmallVector<MemoryDesc>> infer_output_mem_desc(
-        const OpDef& def, const SmallVector<TensorPtr>& inputs_tensors,
-        const SmallVector<MemoryDesc>& inputs_mems) {
-    return {};
-}
-
 EncodedSubgraph make_backward_graph(
         const OpDef& def, const SmallVector<LogicalTensorDesc>& inputs,
         const SmallVector<bool>& input_requires_grad,
@@ -498,7 +492,6 @@ OP_TRAIT_REG(CompiledOp, CompiledOp)
         .infer_output_attrs_fallible(infer_output_attrs_fallible)
         .make_backward_graph(make_backward_graph)
         .make_name(make_name)
-        .infer_output_mem_desc(infer_output_mem_desc)
         .props(props)
         .hash(hash)
         .is_same_st(is_same_st)

imperative/src/impl/proxy_graph.cpp

@@ -634,36 +634,6 @@ std::tuple<SmallVector<LogicalTensorDesc>, bool> ProxyGraph::
     mgb_assert(0);
 }
 
-std::tuple<SmallVector<MemoryDesc>, SmallVector<MemoryDesc>> ProxyGraph::
-        infer_output_mem_desc(
-                const OpDef& def, const SmallVector<Tensor*>& inputs_tensors,
-                const SmallVector<MemoryDesc>& inputs_mems) {
-    auto opr = get_proxy_opr(def, inputs_tensors);
-    CUR_OPR_GUARD(opr);
-    ::mgb::opr::intl::WorkspaceLimitHook::set_impl(
-            m_graph.get(), ProxyGraph::get_workspace_limit);
-    do_shape_infer(true);
-    SmallVector<MemoryDesc> outputs;
-    SmallVector<MemoryDesc> workspaces;
-    size_t cur_id = 0;
-    for (auto&& i : opr->output()) {
-        if (i->contain_flag(VarNode::Flag::VOLATILE_CONTENT)) {
-            workspaces.push_back(
-                    {{i->shape(), i->dtype(), i->format()},
-                     0,
-                     i->comp_node(),
-                     StorageIdentifier::make(++cur_id)});
-        } else {
-            outputs.push_back(
-                    {{i->shape(), i->dtype()},
-                     0,
-                     i->comp_node(),
-                     StorageIdentifier::make(++cur_id)});
-        }
-    }
-    return {outputs, workspaces};
-}
-
 struct ProxyGraph::GradGraph {
     cg::VarNodeArray inputs;
     cg::VarNodeArray outputs;
@@ -812,7 +782,6 @@ EncodedSubgraph ProxyGraph::make_backward_graph(
     return result;
 }
 
-
 VarNodeArray ProxyGraph::make_input_place_holders(
         const SmallVector<LogicalTensorDesc>& inputs) {
     VarNodeArray vinputs(inputs.size());

imperative/src/impl/proxy_graph.h

@@ -47,10 +47,6 @@ public:
             const SmallVector<bool>& input_requires_grad,
             const SmallVector<bool>& output_has_grad);
 
-    std::tuple<SmallVector<MemoryDesc>, SmallVector<MemoryDesc>> infer_output_mem_desc(
-            const OpDef& def, const SmallVector<Tensor*>& inputs_tensors,
-            const SmallVector<MemoryDesc>& inputs_mems);
-
     /********************** Logical Tensor API **********************/
 
     size_t get_opr_output_size(

imperative/src/impl/proxy_graph_detail.cpp

@@ -83,25 +83,6 @@ SmallVector<TensorPtr> apply_on_physical_tensor(
     return outputs;
 }
 
-std::tuple<SmallVector<MemoryDesc>, SmallVector<MemoryDesc>> infer_output_mem_desc(
-        const OpDef& def, const SmallVector<TensorPtr>& inputs_tensors,
-        const SmallVector<MemoryDesc>& inputs_mems) {
-    auto&& graph = ProxyGraph::get_default_graph();
-    return graph->infer_output_mem_desc(
-            def, to_raw_ptr_array(inputs_tensors), inputs_mems);
-}
-
-void execute(
-        const OpDef& def, SmallVector<TensorPtr> inputs, SmallVector<TensorPtr> outputs,
-        SmallVector<TensorPtr> workspace) {
-    exec(def, inputs, outputs, workspace);
-    auto async_error = ProxyGraph::get_async_error();
-    if (async_error) {
-        throw *async_error;
-    }
-    return;
-}
-
 // std::tuple<SmallVector<LogicalTensorDesc>, bool> infer_output_attrs_fallible(const
 // OpDef& def,
 //         const SmallVector<LogicalTensorDesc>& inputs) {

imperative/src/impl/subgraph_detail.cpp

@@ -162,12 +162,6 @@ EncodedSubgraph make_backward_graph(
             inputs, input_requires_grad, output_has_grad, forward_graph);
 }
 
-std::tuple<SmallVector<MemoryDesc>, SmallVector<MemoryDesc>> infer_output_mem_desc(
-        const OpDef& def, const SmallVector<TensorPtr>& inputs_tensors,
-        const SmallVector<MemoryDesc>& inputs_mems) {
-    return {{}, {}};
-}
-
 }  // namespace subgraph_detail
 }  // namespace imperative
 }  // namespace mgb

imperative/src/include/megbrain/imperative/op_def.h

@@ -53,10 +53,6 @@ public:
     static SmallVector<TensorPtr> apply_on_physical_tensor(
             const OpDef& def, SmallVector<TensorPtr> inputs);
 
-    static void execute(
-            const OpDef& def, SmallVector<TensorPtr> inputs,
-            SmallVector<TensorPtr> outputs, SmallVector<TensorPtr> workspace);
-
     /*!
      * \brief Call the corresponding dnn op to calculate results. Output
      * tensors' device memory should be allocated outside.
@@ -71,11 +67,6 @@ public:
     static std::tuple<SmallVector<LogicalTensorDesc>, bool> infer_output_attrs_fallible(
             const OpDef& def, const SmallVector<LogicalTensorDesc>& inputs);
 
-    static std::tuple<SmallVector<MemoryDesc>, SmallVector<MemoryDesc>>
-    infer_output_mem_desc(
-            const OpDef& def, const SmallVector<TensorPtr>& inputs_tensors,
-            const SmallVector<MemoryDesc>& inputs_mems);
-
     static EncodedSubgraph make_backward_graph(
             const OpDef& def, const SmallVector<LogicalTensorDesc>& inputs,
             const SmallVector<bool>& input_requires_grad,

imperative/src/include/megbrain/imperative/physical_tensor.h

@@ -288,36 +288,6 @@ struct LogicalTensorDesc {
     CompNode comp_node;
     DeviceTensorND value;  // cpu:default
 };
-
-struct StorageIdentifier;
-struct MemoryDesc {
-    TensorLayout layout;
-    size_t offset;
-    CompNode cn;
-    std::shared_ptr<StorageIdentifier> id;
-};
-
-struct StorageIdentifier {
-    enum { INVALID, SYS_ALLOC, FROM_OTHER, DEVICE_PTR } tag;
-    union {
-        size_t id;
-        MemoryDesc* desc;
-    };
-    TensorPtr ptr;
-    StorageIdentifier() = default;
-    StorageIdentifier(size_t id) : tag(SYS_ALLOC), id(id) {}
-    StorageIdentifier(const MemoryDesc* desc) : tag(FROM_OTHER), desc(desc->id->desc) {}
-    StorageIdentifier(TensorPtr dev_ptr) : tag(DEVICE_PTR), ptr(dev_ptr) {}
-
-    template <typename... Args>
-    static std::shared_ptr<StorageIdentifier> make(Args&&... args) {
-        return std::make_shared<StorageIdentifier>(std::forward<Args>(args)...);
-    }
-    bool is_sys_alloc() { return tag == SYS_ALLOC; }
-    bool is_from_other() { return tag == FROM_OTHER; }
-    bool is_device_ptr() { return tag == DEVICE_PTR; }
-    bool is_invalid() { return tag == INVALID; }
-};
 }  // namespace imperative
 }  // namespace mgb
 

imperative/src/include/megbrain/imperative/proxy_graph_detail.h

@@ -20,17 +20,9 @@ namespace proxy_graph_detail {
 SmallVector<TensorPtr> apply_on_physical_tensor(
         const OpDef& def, SmallVector<TensorPtr> inputs);
 
-void execute(
-        const OpDef& def, SmallVector<TensorPtr> inputs, SmallVector<TensorPtr> outputs,
-        SmallVector<TensorPtr> workspace);
-
 std::tuple<SmallVector<LogicalTensorDesc>, bool> infer_output_attrs_fallible(
         const OpDef& def, const SmallVector<LogicalTensorDesc>& inputs);
 
-std::tuple<SmallVector<MemoryDesc>, SmallVector<MemoryDesc>> infer_output_mem_desc(
-        const OpDef& def, const SmallVector<TensorPtr>& inputs_tensors,
-        const SmallVector<MemoryDesc>& inputs_mems);
-
 void exec(
         const OpDef& def, const SmallVector<TensorPtr>& inputs,
         const SmallVector<TensorPtr>& outputs);

imperative/src/include/megbrain/imperative/subgraph_detail.h

@@ -35,10 +35,6 @@ EncodedSubgraph make_backward_graph(
         const SmallVector<bool>& input_requires_grad,
         const SmallVector<bool>& output_has_grad);
 
-std::tuple<SmallVector<MemoryDesc>, SmallVector<MemoryDesc>> infer_output_mem_desc(
-        const OpDef& def, const SmallVector<TensorPtr>& inputs_tensors,
-        const SmallVector<MemoryDesc>& inputs_mems);
-
 }  // namespace subgraph_detail
 }  // namespace imperative
 }  // namespace mgb