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chore: Fix centralized partititoning #1367

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Merged
merged 4 commits into from
Sep 30, 2022
Merged

chore: Fix centralized partititoning #1367

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2b57efd
chore: Fix centralized partititoning
peri044 Sep 22, 2022
93ec6b0
chore: Add new parititoning headers to py packaging
peri044 Sep 23, 2022
789be61
chore: Add partitioning headers to C++ tar package
peri044 Sep 23, 2022
3017a39
chore: Increase threshold for topk
peri044 Sep 29, 2022
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3 changes: 3 additions & 0 deletions BUILD
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Expand Up @@ -22,6 +22,9 @@ pkg_tar(
"//core/lowering:include",
"//core/lowering/passes:include",
"//core/partitioning:include",
"//core/partitioning/segmentedblock:include",
"//core/partitioning/partitioninginfo:include",
"//core/partitioning/partitioningctx:include",
"//core/plugins:impl_include",
"//core/plugins:include",
"//core/runtime:include",
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3 changes: 2 additions & 1 deletion core/partitioning/CMakeLists.txt
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Expand Up @@ -4,6 +4,7 @@ add_library(${lib_name} OBJECT)
set(CXX_SRCS
"${CMAKE_CURRENT_SOURCE_DIR}/partitioning.cpp"
"${CMAKE_CURRENT_SOURCE_DIR}/shape_analysis.cpp"
"${CMAKE_CURRENT_SOURCE_DIR}/stitching.cpp"
)

set(HEADER_FILES
Expand Down Expand Up @@ -36,4 +37,4 @@ add_subdirectory(partitioningctx)
add_subdirectory(partitioninginfo)
add_subdirectory(segmentedblock)

install(FILES ${HEADER_FILES} DESTINATION "${CMAKE_INSTALL_INCLUDEDIR}/torch_tensorrt/core/partitioning")
install(FILES ${HEADER_FILES} DESTINATION "${CMAKE_INSTALL_INCLUDEDIR}/torch_tensorrt/core/partitioning")
2 changes: 0 additions & 2 deletions core/partitioning/shape_analysis.cpp
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Expand Up @@ -33,8 +33,6 @@ std::unordered_map<const torch::jit::Value*, torch::jit::IValue> generateRandomI

for (auto& input : inputs) {
if (input.first->type()->kind() == torch::jit::TypeKind::ListType) {
// create list
std::vector<torch::jit::IValue> list;
c10::TypePtr elementType = c10::TensorType::get();
auto generic_list = c10::impl::GenericList(elementType);
for (size_t i = 0; i < input.second.size(); i++) {
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3 changes: 3 additions & 0 deletions py/setup.py
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Expand Up @@ -422,6 +422,9 @@ def run(self):
"include/torch_tensorrt/core/lowering/*.h",
"include/torch_tensorrt/core/lowering/passes/*.h",
"include/torch_tensorrt/core/partitioning/*.h",
"include/torch_tensorrt/core/partitioning/segmentedblock/*.h",
"include/torch_tensorrt/core/partitioning/partitioninginfo/*.h",
"include/torch_tensorrt/core/partitioning/partitioningctx/*.h",
"include/torch_tensorrt/core/plugins/*.h",
"include/torch_tensorrt/core/plugins/impl/*.h",
"include/torch_tensorrt/core/runtime/*.h",
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4 changes: 2 additions & 2 deletions tests/core/conversion/converters/test_topk.cpp
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Expand Up @@ -26,7 +26,7 @@ TEST(Converters, ATenTopKConvertsCorrectly) {
auto trt_results = torch_tensorrt::tests::util::RunGraphEngine(g, params, {in});

ASSERT_TRUE(
torch_tensorrt::tests::util::almostEqual(jit_results[0], trt_results[0].reshape_as(jit_results[0]), 2e-6));
torch_tensorrt::tests::util::almostEqual(jit_results[0], trt_results[0].reshape_as(jit_results[0]), 8e-5));
ASSERT_TRUE(
torch_tensorrt::tests::util::almostEqual(jit_results[1], trt_results[1].reshape_as(jit_results[1]), 2e-6));
torch_tensorrt::tests::util::almostEqual(jit_results[1], trt_results[1].reshape_as(jit_results[1]), 8e-5));
}
12 changes: 6 additions & 6 deletions tests/util/util.cpp
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Expand Up @@ -11,9 +11,9 @@ bool cosineSimEqual(const at::Tensor& computed_tensor, const at::Tensor& gt_tens
computed_tensor.flatten(), gt_tensor.flatten(), torch::nn::functional::CosineSimilarityFuncOptions().dim(0));
std::ostringstream ss;
ss << computed_tensor << std::endl << gt_tensor << std::endl;
LOG_GRAPH(ss.str());
LOG_GRAPH(std::string("Cosine Similarity score: ") + std::to_string(cosine_sim.item<float>()));
LOG_GRAPH(std::string("Acceptable Threshold: ") + std::to_string(threshold));
LOG_DEBUG(ss.str());
LOG_DEBUG(std::string("Cosine Similarity score: ") + std::to_string(cosine_sim.item<float>()));
LOG_DEBUG(std::string("Acceptable Threshold: ") + std::to_string(threshold));

return cosine_sim.item<float>() >= threshold;
}
Expand All @@ -31,14 +31,14 @@ bool almostEqual(const at::Tensor& computed_tensor, const at::Tensor& gt_tensor,
auto result = diff.abs().max().item<float>();
auto threshold = atol + (rtol * gt_tensor.abs().max().item<float>());

LOG_GRAPH(std::string("Max Difference: ") + std::to_string(result));
LOG_GRAPH(std::string("Acceptable Threshold: ") + std::to_string(threshold));
LOG_DEBUG(std::string("Max Difference: ") + std::to_string(result));
LOG_DEBUG(std::string("Acceptable Threshold: ") + std::to_string(threshold));

return result <= threshold;
}

bool exactlyEqual(const at::Tensor& computed_tensor, const at::Tensor& gt_tensor) {
LOG_GRAPH(computed_tensor << std::endl << gt_tensor << std::endl);
LOG_DEBUG(computed_tensor << std::endl << gt_tensor << std::endl);
std::cout << "Max Difference: " << (computed_tensor - gt_tensor).abs().max().item<float>() << std::endl;

return (computed_tensor - gt_tensor).abs().max().item<float>() == 0.f;
Expand Down