提交 c7ded2fe 编写于 作者: M Megvii Engine Team

refactor(imperative): remove unnecessary reverve in small vector

GitOrigin-RevId: 85c30bc828a65bc6e626ced97095ee3c68a50c31
上级 8c2b916e
......@@ -238,7 +238,6 @@ void ChannelImpl::dispatch_default_cpu(
MGB_RECORD_EVENT(ShapeInferEvent, validated);
SmallVector<DeviceTensorND> input_tensornds;
input_tensornds.reserve(input_descs.size());
CompNode output_cn;
{
MGB_LOCK_GUARD(m_mutex);
......@@ -261,9 +260,7 @@ void ChannelImpl::dispatch_default_cpu(
}
}
outputs->reserve(output_descs.size());
SmallVector<DeviceTensorND> output_tensornds;
output_tensornds.reserve(output_descs.size());
for (auto&& desc : output_descs) {
// TODO: may conflict with condtake, which need alloc inside
mgb_assert(!desc.layout.is_empty());
......@@ -290,7 +287,6 @@ void ChannelImpl::dispatch_default_cpu(
}
SmallVector<TensorInfo*> output_infos;
output_infos.reserve(output_descs.size());
for (auto&& tensornd : output_tensornds) {
HostTensorND host_tensornd =
HostTensorND::make_proxy(tensornd).proxy_to_comp_node(output_cn);
......@@ -329,9 +325,6 @@ void ChannelImpl::dispatch_kernel(
ApplyOp cmd{Profiler::next_id(), std::move(op)};
cmd.inputs = std::move(input_infos);
cmd.outputs.reserve(output_descs.size());
outputs->reserve(output_descs.size());
for (int i = 0; i < output_descs.size(); ++i) {
auto&& desc = output_descs[i];
auto info = alloc();
......@@ -399,9 +392,7 @@ SmallVector<Handle> ChannelImpl::apply_op_impl(
i);
}
SmallVector<TensorInfo*> input_infos;
input_infos.reserve(inputs.size());
SmallVector<LogicalTensorDesc> input_descs;
input_descs.reserve(inputs.size());
{
MGB_LOCK_GUARD(m_mutex);
for (auto i : inputs) {
......
......@@ -87,7 +87,6 @@ void apply_on_device_tensornd(
HostTensorND get_var_shape_host_tensor(
const OpDef& def, const SmallVector<TensorPtr>& inputs) {
SmallVector<DeviceTensorND> input_tensornds;
input_tensornds.reserve(inputs.size());
for (auto&& inp : inputs) {
input_tensornds.push_back(inp->dev_tensor());
}
......
......@@ -232,7 +232,6 @@ public:
// fill args for infer_func
cg::static_infer::InpVal args{1};
args.val.reserve(desc->deps.size());
auto push_shape = [&args](const TensorShape* shape) {
args.val.emplace_back();
args.val.back().m_shape = shape;
......@@ -607,8 +606,6 @@ EncodedSubgraph ProxyGraph::make_backward_graph(
}
// set backward graph inputs
igraph.inputs.reserve(nr_backward_graph_inputs);
result.input_mask.reserve(nr_backward_graph_inputs);
auto write_inputs = [&igraph, &var2idx, &result](const VarNodeArray& vars) {
for (auto&& i : vars) {
auto&& iter = var2idx.find(i);
......
......@@ -132,7 +132,6 @@ protected:
mgb_assert(!infer_func);
infer_func = func;
inp_val.val.resize(dep_val.size());
deps.reserve(dep_val.size());
for (auto&& dep : dep_val) {
auto [found, i] = find_index(opr->input(), dep.dest);
......@@ -253,7 +252,6 @@ public:
// fix permuted input: the order of m_opr->input() and vinputs may be
// different, input_remap keeps the index map of m_opr->input() and vinputs
input_remap.reserve(m_opr->input().size());
for (auto* v : m_opr->input()) {
auto [found, i] = find_index(vinputs, v);
mgb_assert(found);
......@@ -272,7 +270,6 @@ public:
}
// fix permuted output
output_remap.reserve(ovars.size());
for (auto* v : ovars) {
auto [found, i] = find_index(m_opr->output(), v);
mgb_assert(found);
......@@ -784,7 +781,6 @@ public:
auto sess = minigraph.infer_session(inputs);
std::tuple<SmallVector<LogicalTensorDesc>, bool> ret;
auto& [descs, noerr] = ret;
descs.reserve(minigraph.output_size());
for (size_t i = 0; i < minigraph.output_size(); ++i) {
descs.emplace_back();
auto& desc = descs.back();
......@@ -819,7 +815,6 @@ public:
mgb_assert(shape);
minigraph.opr()->output()[i]->shape(*shape);
}
descs.reserve(minigraph.output_size());
for (size_t i = 0; i < minigraph.output_size(); ++i) {
auto* ovar = minigraph.output_var(i);
mgb_assert(ovar->dtype().valid() && ovar->comp_node().valid());
......
Markdown is supported
0% .
You are about to add 0 people to the discussion. Proceed with caution.
先完成此消息的编辑!
想要评论请 注册