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[MXNET-703] Minor refactor of TensorRT code #13311

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Jan 26, 2019
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[MXNET-703] Minor refactor of TensorRT code #13311

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4 changes: 2 additions & 2 deletions src/executor/onnx_to_tensorrt.cc
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Expand Up @@ -100,8 +100,8 @@ nvinfer1::ICudaEngine* onnxToTrtCtx(
}

if ( !trt_parser->parse(onnx_model.c_str(), onnx_model.size()) ) {
int nerror = trt_parser->getNbErrors();
for ( int i=0; i < nerror; ++i ) {
size_t nerror = trt_parser->getNbErrors();
for ( size_t i=0; i < nerror; ++i ) {
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nvonnxparser::IParserError const* error = trt_parser->getError(i);
if ( error->node() != -1 ) {
::ONNX_NAMESPACE::NodeProto const& node =
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7 changes: 3 additions & 4 deletions src/executor/trt_graph_executor.cc
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Expand Up @@ -133,7 +133,7 @@ void TrtGraphExecutor::Init(nnvm::Symbol symbol,
}

auto trt_groups = GetTrtCompatibleSubsets(g, shared_buffer);
for (auto trt_group : trt_groups) {
for (const auto &trt_group : trt_groups) {
if (trt_group.size() > 1) {
g = ReplaceSubgraph(std::move(g), trt_group, shared_buffer);
g = ReinitGraph(std::move(g), default_ctx, ctx_map, in_arg_ctxes, arg_grad_ctxes,
Expand All @@ -142,7 +142,6 @@ void TrtGraphExecutor::Init(nnvm::Symbol symbol,
}
}


InitArguments(g.indexed_graph(), g.GetAttr<nnvm::ShapeVector>("shape"),
g.GetAttr<nnvm::DTypeVector>("dtype"),
g.GetAttr<StorageTypeVector>("storage_type"),
Expand Down Expand Up @@ -188,7 +187,7 @@ void TrtGraphExecutor::InitArguments(const nnvm::IndexedGraph& idx,
const uint32_t eid = idx.entry_id(nid, 0);
const TShape& inferred_shape = inferred_shapes[eid];
const int inferred_dtype = inferred_dtypes[eid];
const NDArrayStorageType inferred_stype = (NDArrayStorageType) inferred_stypes[eid];
const auto inferred_stype = (NDArrayStorageType) inferred_stypes[eid];
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const std::string& arg_name = idx[nid].source->attrs.name;
// aux_states
if (mutable_nodes.count(nid)) {
Expand Down Expand Up @@ -427,7 +426,7 @@ Executor *TrtGraphExecutor::TensorRTBind(nnvm::Symbol symbol,
std::unordered_map<std::string, NDArray> *shared_buffer,
Executor *shared_exec) {
auto exec = new exec::TrtGraphExecutor();
exec->Init(symbol, default_ctx, group2ctx,
exec->Init(std::move(symbol), default_ctx, group2ctx,
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Is Init accepting an rvalue reference?

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It's a good question I wanted to dive into a little. My understanding is that the Init function can bind its variable to either an lvalue or an rvalue when passing by value. You don't have to create an overload or anything to determine which one it expects. Here's an example:

https://gist.github.com/KellenSunderland/d431119580a116410c672b9535d85170
Which is using code borrowed from:
https://www.chromium.org/rvalue-references?tmpl=%2Fsystem%2Fapp%2Ftemplates%2Fprint%2F&showPrintDialog=1

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Well the question if the move is doing anything, because I don't know if there's an Init signature accepting an rvalue reference to a symbol, that was the original question.

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Yeah I was also curious about this. The example shows a similar pattern and it does save a copy.

in_arg_ctxes, arg_grad_ctxes, aux_state_ctxes,
arg_shape_map, arg_dtype_map, arg_stype_map,
grad_req_types, param_names,
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14 changes: 7 additions & 7 deletions src/operator/contrib/nnvm_to_onnx-inl.h
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Expand Up @@ -70,7 +70,7 @@ struct ONNXParam : public dmlc::Parameter<ONNXParam> {
nnvm_to_onnx::InferenceMap_t output_map;
::onnx::ModelProto onnx_pb_graph;

ONNXParam() {}
ONNXParam() = default;

ONNXParam(const ::onnx::ModelProto& onnx_graph,
const nnvm_to_onnx::InferenceMap_t& input_map,
Expand Down Expand Up @@ -104,14 +104,14 @@ std::unordered_map<std::string, uint32_t> GetOutputLookup(const nnvm::IndexedGra
void ConvertPlaceholder(
const std::string& node_name,
const std::unordered_map<std::string, TShape>& placeholder_shapes,
GraphProto* const graph_proto);
GraphProto* graph_proto);

void ConvertConstant(GraphProto* const graph_proto,
void ConvertConstant(GraphProto* graph_proto,
const std::string& node_name,
std::unordered_map<std::string, NDArray>* const shared_buffer);
std::unordered_map<std::string, NDArray>* shared_buffer);

void ConvertOutput(op::nnvm_to_onnx::InferenceMap_t* const trt_output_map,
GraphProto* const graph_proto,
void ConvertOutput(op::nnvm_to_onnx::InferenceMap_t* trt_output_map,
GraphProto* graph_proto,
const std::unordered_map<std::string, uint32_t>::iterator& out_iter,
const std::string& node_name,
const nnvm::Graph& g,
Expand Down Expand Up @@ -169,7 +169,7 @@ void ConvertElementwiseAdd(NodeProto *node_proto,

ONNXParam ConvertNnvmGraphToOnnx(
const nnvm::Graph &g,
std::unordered_map<std::string, NDArray> *const shared_buffer);
std::unordered_map<std::string, NDArray>* shared_buffer);

static const std::unordered_map<std::string, ConverterFunction> converter_map = {
{"Convolution", ConvertConvolution},
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4 changes: 2 additions & 2 deletions src/operator/contrib/nnvm_to_onnx.cc
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Expand Up @@ -263,7 +263,7 @@ void ConvertPooling(NodeProto* node_proto, const NodeAttrs& attrs,
AttributeProto* const kernel_shape = node_proto->add_attribute();
kernel_shape->set_name("kernel_shape");
kernel_shape->set_type(AttributeProto::INTS);
for (int kval : kernel) {
for (dim_t kval : kernel) {
kernel_shape->add_ints(static_cast<int64>(kval));
}

Expand All @@ -283,7 +283,7 @@ void ConvertPooling(NodeProto* node_proto, const NodeAttrs& attrs,
AttributeProto* const strides = node_proto->add_attribute();
strides->set_name("strides");
strides->set_type(AttributeProto::INTS);
for (int kval : stride) {
for (dim_t kval : stride) {
strides->add_ints(static_cast<int64>(kval));
}

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