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Fix compilation warning and spurious print (#87297)

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Fixes compilation warning, make this warning an error and remove a random print.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/87297
Approved by: https://github.com/malfet
This commit is contained in:
albanD
2022-10-19 20:56:37 +00:00
committed by PyTorch MergeBot
parent 4a533f1215
commit c141f28b64
6 changed files with 7 additions and 7 deletions
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1
CMakeLists.txt
View File

@ -826,6 +826,7 @@ if(NOT MSVC)
append_cxx_flag_if_supported("-Werror=return-type" CMAKE_CXX_FLAGS)
append_cxx_flag_if_supported("-Werror=non-virtual-dtor" CMAKE_CXX_FLAGS)
append_cxx_flag_if_supported("-Werror=braced-scalar-init" CMAKE_CXX_FLAGS)
append_cxx_flag_if_supported("-Werror=range-loop-construct" CMAKE_CXX_FLAGS)
append_cxx_flag_if_supported("-Wno-missing-field-initializers" CMAKE_CXX_FLAGS)
append_cxx_flag_if_supported("-Wno-type-limits" CMAKE_CXX_FLAGS)
append_cxx_flag_if_supported("-Wno-array-bounds" CMAKE_CXX_FLAGS)

6
torch/csrc/jit/runtime/graph_executor.cpp
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@ -133,7 +133,7 @@ struct CaptureList {
auto tensors = val.toTensorList();
sizes_.push_back(tensors.size());
for (const at::Tensor tensor : tensors) {
for (const auto& tensor : tensors) {
captureTensor(tensor, is_output);
}
} else {
@ -326,7 +326,7 @@ struct DifferentiableGraphBackward : public autograd::Node {
void addOutputForIValue(const IValue& value) {
if (value.isTensorList()) {
input_tensor_lists_.insert({index_, value.toTensorList().size()});
for (const at::Tensor tensor : value.toTensorList()) {
for (const at::Tensor& tensor : value.toTensorList()) {
addOutputForTensor(tensor);
index_++;
}
@ -357,7 +357,7 @@ struct DifferentiableGraphBackward : public autograd::Node {
if (v.isTensorList()) {
auto tensors = v.toTensorList();
input_instructions_.pushTensorList(tensors.size());
for (const at::Tensor tensor : tensors) {
for (const at::Tensor& tensor : tensors) {
addInputVariable(tensor);
}
} else if (v.isTensor()) {

2
torch/csrc/jit/serialization/unpickler.cpp
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@ -129,7 +129,7 @@ void restoreAccurateTypeTags(const IValue& root, const TypePtr& type_tag) {
auto elem_type = w.type->containedType(0);
auto lst = w.value.toList();
lst.unsafeSetElementType(elem_type);
for (const IValue item : lst) {
for (const IValue& item : lst) {
Work elem = {elem_type, item};
to_process.emplace_back(std::move(elem));
}

2
torch/csrc/profiler/standalone/nvtx_observer.cpp
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@ -71,7 +71,7 @@ std::list<std::pair<at::RecordFunctionHandle, int>> flattenOpIdList(
std::list<std::pair<at::RecordFunctionHandle, int>> input_op_id_list;
auto state_ptr = NVTXThreadLocalState::getTLS();
TORCH_INTERNAL_ASSERT(state_ptr, "Expected profiler state set");
for (const c10::IValue input : list) {
for (const c10::IValue& input : list) {
if (input.isTensor()) {
const at::Tensor& tensor = input.toTensor();
auto producer_op_pair = state_ptr->getOpIdFromInput(tensor);

2
torch/csrc/profiler/util.cpp
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@ -198,7 +198,7 @@ std::vector<std::vector<int64_t>> flattenList(
c10::List<c10::IValue> list,
std::string fn_name) {
std::vector<std::vector<int64_t>> tensor_dims;
for (const c10::IValue input : list) {
for (const c10::IValue& input : list) {
if (input.isTensor()) {
const at::Tensor& tensor = input.toTensor();
if (tensor.defined()) {

1
torch/utils/data/datapipes/gen_pyi.py
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@ -231,5 +231,4 @@ def main() -> None:
if __name__ == '__main__':
print("Generating Python interface file 'datapipe.pyi'...")
main()