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[TensorRT EP] Fix bug for handling outer scope values in GetCapability (#18342)

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The issues found in yolov3, tiny-yolov3 etc where it has control flow
ops.

Two modifications:

1. In GetCapability/GetSupporedtList, only if the newly built graph has
control flow op as well as it has parent node, it needs to handle outer
scope values before calling graph.Resolve().
2. Two graph/subgraphs has the chance to have the same graph->Name().
Add a function to get the unique graph name.
This commit is contained in:
Chi Lo 2023-11-14 08:26:06 +00:00 committed by GitHub
parent a09099f2dd
commit 3e1cf71067
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GPG key ID: 4AEE18F83AFDEB23
3 changed files with 50 additions and 43 deletions
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4
onnxruntime/core/providers/tensorrt/tensorrt_execution_provider.cc
View file

@ -1562,7 +1562,9 @@ SubGraphCollection_t TensorrtExecutionProvider::GetSupportedList(SubGraphCollect
}
}
if (has_control_flow_op) {
// Only if the newly built graph has control flow op as well as it has parent node,
// it needs to handle outer scope values before calling graph.Resolve().
if (has_control_flow_op && graph.ParentNode()) {
LOGS_DEFAULT(VERBOSE) << "[TensorRT EP] Handle outer scope values for the subgraph " << graph_build.Name();
BuildSubGraphContext(graph_build);
SetGraphOuterScopeValuesAndInputs(graph_build, graph.GetGraph());

51
onnxruntime/core/providers/tensorrt/tensorrt_execution_provider_helper.cc
View file

@ -3,10 +3,36 @@
#include "core/providers/shared_library/provider_api.h"
#include "tensorrt_execution_provider.h"
#include "core/framework/murmurhash3.h"
#include <iostream>
namespace onnxruntime {
namespace {
// Get unique graph name based on graph's name and all nodes' name
std::string GetUniqueGraphName(const Graph& graph) {
HashValue model_hash = 0;
uint32_t hash[4] = {0, 0, 0, 0};
auto hash_str = [&hash](const std::string& str) {
MurmurHash3::x86_128(str.data(), gsl::narrow_cast<int32_t>(str.size()), hash[0], &hash);
};
// Hash all nodes' name
for (int i = 0; i < graph.MaxNodeIndex(); ++i) {
auto node = graph.GetNode(i);
if (node == nullptr) {
continue;
}
hash_str(node->Name());
}
model_hash = hash[0] | (uint64_t(hash[1]) << 32);
return graph.Name() + "_" + std::to_string(model_hash);
}
} // namespace
// The newly-built graph has not yet being resolved by Graph::Resolve(), so we can't leverage
// Graph::ResolveContext::IsInputInitializerOrOutput(). We have to implement this fuction again.
bool TensorrtExecutionProvider::IsInputInitializerOrOutput(const Graph& graph,
@ -31,10 +57,11 @@ bool TensorrtExecutionProvider::IsOuterScopeValue(const Graph& graph,
// Graph::ResolveContext::IsLocalValue(). We have to implement this function again.
bool TensorrtExecutionProvider::IsLocalValue(const Graph& graph,
const std::string& name) const {
if (subgraph_context_map_.find(graph.Name()) == subgraph_context_map_.end()) {
std::string unique_graph_name = GetUniqueGraphName(graph);
if (subgraph_context_map_.find(unique_graph_name) == subgraph_context_map_.end()) {
return false;
}
SubGraphContext* context = subgraph_context_map_.at(graph.Name()).get();
SubGraphContext* context = subgraph_context_map_.at(unique_graph_name).get();
return context->output_args.find(name) != context->output_args.cend() ||
context->inputs_and_initializers.find(name) != context->inputs_and_initializers.cend();
}
@ -59,13 +86,15 @@ void TensorrtExecutionProvider::BuildSubGraphContext(const Graph& graph) const {
}
}
std::string unique_graph_name = GetUniqueGraphName(graph);
// Subgraph context has been built before, no need to do it again
if (subgraph_context_map_.find(graph.Name()) != subgraph_context_map_.end()) {
if (subgraph_context_map_.find(unique_graph_name) != subgraph_context_map_.end()) {
return;
}
subgraph_context_map_.emplace(graph.Name(), std::make_unique<SubGraphContext>());
SubGraphContext* context = subgraph_context_map_.at(graph.Name()).get();
subgraph_context_map_.emplace(unique_graph_name, std::make_unique<SubGraphContext>());
SubGraphContext* context = subgraph_context_map_.at(unique_graph_name).get();
// Collect all nodes' outputs and nodes' name
for (int i = 0; i < graph.MaxNodeIndex(); ++i) {
@ -138,13 +167,14 @@ void TensorrtExecutionProvider::SetGraphOuterScopeValuesAndInputs(Graph& graph_b
while (top_level_graph->MutableParentGraph()) {
top_level_graph = top_level_graph->MutableParentGraph();
}
if (subgraph_context_map_.find(top_level_graph->Name()) == subgraph_context_map_.end()) {
std::string unique_graph_name = GetUniqueGraphName(*top_level_graph);
if (subgraph_context_map_.find(unique_graph_name) == subgraph_context_map_.end()) {
LOGS_DEFAULT(ERROR) << "[TensorRT EP] Can't find top-level graph context. \
Please check BuildSubGraphContext() has built the graph context correctly.";
return;
}
SubGraphContext* context = subgraph_context_map_.at(top_level_graph->Name()).get();
SubGraphContext* context = subgraph_context_map_.at(unique_graph_name).get();
LOGS_DEFAULT(VERBOSE) << "[TensorRT EP] Subgraph name is " << graph_build.Name();
LOGS_DEFAULT(VERBOSE) << "[TensorRT EP] Its parent node is " << graph.ParentNode()->Name();
@ -197,12 +227,13 @@ void TensorrtExecutionProvider::SetGraphOuterScopeValuesAndInputs(Graph& graph_b
void TensorrtExecutionProvider::SetAllGraphInputs(Graph& graph) const {
// If ORT TRT doesn't manully set graph input in TensorrtExecutionProvider::SetGraphOuterScopeValuesAndInputs(),
// Graph::Resolve() will help set graph inputs in Graph::SetGraphInputsOutputs(), so no need to set graph inputs here.
if (subgraph_context_map_.find(graph.Name()) == subgraph_context_map_.end() ||
subgraph_context_map_[graph.Name()].get()->manually_added_graph_inputs.size() == 0) {
std::string unique_graph_name = GetUniqueGraphName(graph);
if (subgraph_context_map_.find(unique_graph_name) == subgraph_context_map_.end() ||
subgraph_context_map_[unique_graph_name].get()->manually_added_graph_inputs.size() == 0) {
return;
}
SubGraphContext* context = subgraph_context_map_[graph.Name()].get();
SubGraphContext* context = subgraph_context_map_[unique_graph_name].get();
std::vector<const NodeArg*> graph_inputs_including_initializers;
std::unordered_set<std::string> graph_inputs_including_initializers_set;

38
onnxruntime/test/providers/cpu/model_tests.cc
View file

@ -1,6 +1,7 @@
// Copyright (c) Microsoft Corporation. All rights reserved.
// Licensed under the MIT License.
#include <iostream>
#include <iterator>
#include <gtest/gtest.h>
@ -410,7 +411,7 @@ static ORT_STRING_VIEW provider_name_dml = ORT_TSTR("dml");
// If an EP doesn't have any CI build pipeline, then there is no need to specify any opset.
#ifdef USE_TENSORRT
// tensorrt: only enable opset 14 to 17 of onnx tests
provider_names[provider_name_tensorrt] = {opset14, opset15, opset16, opset17};
provider_names[provider_name_tensorrt] = {opset12, opset14, opset15, opset16, opset17};
#endif
#ifdef USE_MIGRAPHX
provider_names[provider_name_migraphx] = {opset7, opset8, opset9, opset10, opset11, opset12, opset13, opset14, opset15, opset16, opset17, opset18};
@ -592,37 +593,10 @@ static ORT_STRING_VIEW provider_name_dml = ORT_TSTR("dml");
ORT_TSTR("mul_uint8"),
ORT_TSTR("div_uint8")};
static const ORTCHAR_T* tensorrt_disabled_tests[] = {
ORT_TSTR("udnie"),
ORT_TSTR("rain_princess"),
ORT_TSTR("pointilism"),
ORT_TSTR("mosaic"),
ORT_TSTR("LSTM_Seq_lens_unpacked"),
ORT_TSTR("cgan"),
ORT_TSTR("candy"),
ORT_TSTR("tinyyolov3"),
ORT_TSTR("yolov3"),
ORT_TSTR("mlperf_ssd_resnet34_1200"),
ORT_TSTR("mlperf_ssd_mobilenet_300"),
ORT_TSTR("mask_rcnn"),
ORT_TSTR("faster_rcnn"),
ORT_TSTR("fp16_shufflenet"),
ORT_TSTR("fp16_inception_v1"),
ORT_TSTR("fp16_tiny_yolov2"),
ORT_TSTR("tf_inception_v3"),
ORT_TSTR("tf_mobilenet_v1_1.0_224"),
ORT_TSTR("tf_mobilenet_v2_1.0_224"),
ORT_TSTR("tf_mobilenet_v2_1.4_224"),
ORT_TSTR("tf_resnet_v1_101"),
ORT_TSTR("tf_resnet_v1_152"),
ORT_TSTR("tf_resnet_v1_50"),
ORT_TSTR("tf_resnet_v2_101"),
ORT_TSTR("tf_resnet_v2_152"),
ORT_TSTR("tf_resnet_v2_50"),
ORT_TSTR("convtranspose_1d"),
ORT_TSTR("convtranspose_3d"),
ORT_TSTR("conv_with_strides_and_asymmetric_padding"),
ORT_TSTR("conv_with_strides_padding"),
ORT_TSTR("size") // INVALID_ARGUMENT: Cannot find binding of given name: x
ORT_TSTR("YOLOv3-12"), // needs to run symbolic shape inference shape first
ORT_TSTR("SSD-MobilenetV1-12"), // symbolic shape inference shape error
ORT_TSTR("SSD"), // needs to run symbolic shape inference shape first
ORT_TSTR("size") // INVALID_ARGUMENT: Cannot find binding of given name: x
};
std::vector<std::basic_string<ORTCHAR_T>> paths;