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Fix indeterministic params order in RunGraph #15

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Merged
merged 1 commit into from
Mar 18, 2020
Merged

Fix indeterministic params order in RunGraph #15

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8 changes: 3 additions & 5 deletions tests/core/converters/test_linear.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -8,7 +8,7 @@
TEST(Converters, ATenLinearNoBiasConvertsCorrectly) {
const auto graph = R"IR(
graph(%0 : Tensor,
%1 : Float(2, 2)):
%1 : Float(3, 2)):
%2 : None = prim::Constant()
%3 : Tensor = aten::linear(%0, %1, %2)
return (%3))IR";
Expand All @@ -19,7 +19,7 @@ TEST(Converters, ATenLinearNoBiasConvertsCorrectly) {
//Input Tensor needs to be 4D for TensorRT linear
auto in = at::randint(1, 10, {1, 2}, {at::kCUDA});
auto w = at::randint(1, 10, {3, 2}, {at::kCUDA});

auto params = trtorch::core::conversion::get_named_params(g->inputs(), {w});
auto jit_results = trtorch::tests::util::RunGraph(g, params, {in});

Expand All @@ -32,8 +32,6 @@ TEST(Converters, ATenLinearNoBiasConvertsCorrectly) {
}


//TODO: Track down the cause of why the JIT linear function fails
//TODO: Sort out what the exepected output dim should be?
TEST(Converters, ATenLinearBiasConvertsCorrectly) {
const auto graph = R"IR(
graph(%0 : Tensor,
Expand All @@ -53,7 +51,7 @@ TEST(Converters, ATenLinearBiasConvertsCorrectly) {
auto jit_in = at::clone(in);
auto jit_w = at::clone(w);
auto jit_b = at::clone(b);

auto params = trtorch::core::conversion::get_named_params(g->inputs(), {jit_w, jit_b});
auto jit_results = trtorch::tests::util::RunGraph(g, params, {jit_in});

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5 changes: 1 addition & 4 deletions tests/models/BUILD
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Expand Up @@ -15,10 +15,7 @@ cc_test(
name = "test_multiple_registered_engines",
srcs = ["test_multiple_registered_engines.cpp"],
deps = [
"//cpp/api:trtorch",
"//tests/util",
"@libtorch//:libtorch",
"@googletest//:gtest_main",
":module_test",
],
data = [
":jit_models"
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12 changes: 6 additions & 6 deletions tests/models/test_multiple_registered_engines.cpp
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Original file line number Diff line number Diff line change
@@ -1,8 +1,8 @@
#include <string>
#include "gtest/gtest.h"
#include "torch/csrc/jit/irparser.h"
#include "torch/script.h"
#include "tests/util/util.h"
#include "cpp/trtorch.h"
#include "trtorch/trtorch.h"

TEST(ModuleTests, CanRunMultipleEngines) {
torch::jit::script::Module mod1;
Expand All @@ -16,7 +16,7 @@ TEST(ModuleTests, CanRunMultipleEngines) {
return;
}

const std::vector<int64_t> input_shape = {1,3,224,224};
const std::vector<std::vector<int64_t>> input_shapes = {{1,3,224,224}};

std::vector<torch::jit::IValue> jit1_inputs_ivalues;
std::vector<torch::jit::IValue> trt1_inputs_ivalues;
Expand All @@ -38,18 +38,18 @@ TEST(ModuleTests, CanRunMultipleEngines) {
std::vector<at::Tensor> jit1_results;
jit1_results.push_back(jit1_results_ivalues.toTensor());

torch::jit::IValue jit2_results_ivalues = trtorch::tests::util::RunModuleForward(mod2, jit2_inputs_ivalues);
torch::jit::IValue jit2_results_ivalues = trtorch::tests::util::RunModuleForward(mod2, jit2_inputs_ivalues);
std::vector<at::Tensor> jit2_results;
jit2_results.push_back(jit2_results_ivalues.toTensor());


auto trt_mod1 = trtorch::CompileGraph(mod1, input_shapes);
torch::jit::IValue trt1_results_ivalues = trtorch::tests::util::RunModuleForward(trt1_mod, trt1_inputs_ivalues);
torch::jit::IValue trt1_results_ivalues = trtorch::tests::util::RunModuleForward(trt_mod1, trt1_inputs_ivalues);
std::vector<at::Tensor> trt1_results;
trt1_results.push_back(trt1_results_ivalues.toTensor());

auto trt_mod2 = trtorch::CompileGraph(mod2, input_shapes);
torch::jit::IValue trt2_results_ivalues = trtorch::tests::util::RunModuleForward(trt2_mod, trt2_inputs_ivalues);
torch::jit::IValue trt2_results_ivalues = trtorch::tests::util::RunModuleForward(trt_mod2, trt2_inputs_ivalues);
std::vector<at::Tensor> trt2_results;
trt2_results.push_back(trt2_results_ivalues.toTensor());

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7 changes: 5 additions & 2 deletions tests/util/run_graph.cpp
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Expand Up @@ -21,8 +21,11 @@ std::vector<at::Tensor> RunGraph(std::shared_ptr<torch::jit::Graph>& g,
inputs_.push_back(in.clone());
}

for (auto p : params) {
inputs_.push_back(p.second.clone());
for (auto* in : g->inputs()) {
const auto iter = params.find(in);
if (iter != params.end()) {
inputs_.push_back(iter->second.clone());
}
}

torch::jit::GraphExecutor executor(g);
Expand Down