fix: [collection] remove aten::__getitem__ and prim::ListConstruct

Signed-off-by: inocsin <[email protected]>
pytorch · Apr 8, 2022 · 47455d1 · 47455d1
1 parent a206336
commit 47455d1
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diff --git a/core/conversion/evaluators/aten.cpp b/core/conversion/evaluators/aten.cpp
@@ -264,21 +264,6 @@ auto aten_registrations TORCHTRT_UNUSED =
              },
              EvalOptions().validSchemas(
                  {"aten::size(Tensor self) -> (int[])", "aten::size.int(Tensor self, int dim) -> (int)"})})
-        .evaluator({c10::Symbol::fromQualString("aten::__getitem__"),
-                    [](const torch::jit::Node* n, kwargs& args) -> c10::optional<torch::jit::IValue> {
-                      auto list = args.at(n->input(0)).IValue()->to<c10::List<c10::IValue>>();
-                      auto idx = args.at(n->input(1)).unwrapToInt();
-
-                      const int64_t list_size = list.size();
-                      const int64_t normalized_idx = normalizeIndex(idx, list_size);
-                      TORCHTRT_CHECK(
-                          normalized_idx >= 0 || normalized_idx < list_size,
-                          "List index out of range (aten::__getitem__)");
-                      return list.get(normalized_idx);
-                    },
-                    EvalOptions().validSchemas({
-                        "aten::__getitem__.t(t[](a) list, int idx) -> (t(*))",
-                    })})
         .evaluator({c10::Symbol::fromQualString("aten::append"),
                     [](const torch::jit::Node* n, kwargs& args) -> c10::optional<torch::jit::IValue> {
                       auto list = args.at(n->input(0)).IValue()->to<c10::List<c10::IValue>>();

diff --git a/core/conversion/evaluators/prim.cpp b/core/conversion/evaluators/prim.cpp
@@ -40,68 +40,6 @@ auto prim_registrations =
                       auto outputVec = outputs->toList().vec();
                       return std::move(c10::ivalue::Tuple::create(outputVec));
                     }})
-        .evaluator({torch::jit::prim::ListConstruct,
-                    [](const torch::jit::Node* n, kwargs& args) -> c10::optional<torch::jit::IValue> {
-                      const auto num_inputs = n->inputs().size();
-                      if (constTypesOnly(args)) {
-                        c10::ListTypePtr lt = n->output()->type()->expect<c10::ListType>();
-                        if (torch::jit::IntType::get() == lt->getElementType()) {
-                          c10::List<int64_t> list;
-                          list.reserve(num_inputs);
-                          for (auto in : n->inputs()) {
-                            list.emplace_back(std::move(args.at(in).unwrapToInt()));
-                          }
-                          return c10::optional<torch::jit::IValue>(std::move(torch::jit::IValue(list)));
-                        } else if (torch::jit::FloatType::get() == lt->getElementType()) {
-                          c10::List<double> list;
-                          list.reserve(num_inputs);
-                          for (auto in : n->inputs()) {
-                            list.emplace_back(std::move(args.at(in).unwrapToDouble()));
-                          }
-                          return c10::optional<torch::jit::IValue>(std::move(torch::jit::IValue(list)));
-                        } else if (lt->getElementType() == torch::jit::BoolType::get()) {
-                          c10::List<bool> list;
-                          list.reserve(num_inputs);
-                          for (auto in : n->inputs()) {
-                            list.emplace_back(std::move(args.at(in).unwrapToBool()));
-                          }
-                          return c10::optional<torch::jit::IValue>(std::move(torch::jit::IValue(list)));
-                        } else if (lt->getElementType()->isSubtypeOf(torch::jit::TensorType::get())) {
-                          c10::List<at::Tensor> list;
-                          list.reserve(num_inputs);
-                          for (auto in : n->inputs()) {
-                            if (args.at(in).isIValue()) {
-                              list.emplace_back(std::move(args.at(in).unwrapToTensor()));
-                            }
-                          }
-                          return c10::optional<torch::jit::IValue>(std::move(torch::jit::IValue(list)));
-                        } else {
-                          c10::TypePtr elementType = lt->getElementType();
-                          auto list = c10::impl::GenericList(elementType);
-                          list.reserve(num_inputs);
-                          for (auto in : n->inputs()) {
-                            list.emplace_back(std::move(*(args.at(in).IValue())));
-                          }
-                          return c10::optional<torch::jit::IValue>(std::move(torch::jit::IValue(list)));
-                        }
-                      } else {
-                        c10::ListTypePtr lt = n->output()->type()->expect<c10::ListType>();
-                        c10::TypePtr elementType = lt->getElementType();
-                        auto list = c10::impl::GenericList(elementType);
-                        list.reserve(num_inputs);
-                        for (auto in : n->inputs()) {
-                          if (args.at(in).isITensor()) {
-                            auto tensor_holder = TensorContainer();
-                            tensor_holder.hold_tensor(args.at(in).ITensor());
-                            auto ival = c10::IValue(std::move(c10::make_intrusive<TensorContainer>(tensor_holder)));
-                            list.emplace_back(std::move(ival));
-                          } else {
-                            list.emplace_back(std::move(args.at(in).unwrapToTensor()));
-                          }
-                        }
-                        return c10::optional<torch::jit::IValue>(std::move(torch::jit::IValue(list)));
-                      }
-                    }})
         .evaluator({c10::Symbol::fromQualString("prim::dtype"),
                     [](const torch::jit::Node* n, kwargs& args) -> c10::optional<torch::jit::IValue> {
                       auto input = args.at(n->input(0));