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Warning as error for Windows (#13291)

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* parent 6e7016ccda
author Ilya Churaev <ilya.churaev@intel.com> 1664281499 +0400
committer Ilya Churaev <ilya.churaev@intel.com> 1664510018 +0400

Fixed warnings on local machine

* Added CMAKE_COMPILE_WARNING_AS_ERROR usage

* Fixed style

* Fixed merge conflicts

* Fixed typo

* Fixed myriad build for macOS

* Fixed warning

* Fixed tests

* Disabled incorrect test

* Try to fix linux tests

* Revert "Try to fix linux tests"

This reverts commit 29224c93ff.

* Fixed tests

* Revert logic with incorrect cast

* Fixed log softmax

* Disable warning as error for cuda

* Try to fix inference_engine_s

* Fixed cmake

* Revert "Fixed cmake"

This reverts commit 87e9e4e674.

* Revert "Try to fix inference_engine_s"

This reverts commit a1adca8b05.

* WA for static symbols in inference_engine_s test library

* Fixed code style

* Fixed static definition for master

* Revert "Fixed static definition for master"

This reverts commit 20d00d215a.

* Revert "Fixed code style"

This reverts commit 0eb2362543.

* Revert "WA for static symbols in inference_engine_s test library"

This reverts commit 75ef86a79d.

* Fixed linker issue for Windows

* Disable WaE by default

* Disable warning as error in the developer package

* Try to fix dev package

* Try to fix Windows Jenkins

* Revert old behavior for tread_warn_as_err variable
This commit is contained in:
Ilya Churaev
2022-10-06 13:44:21 +04:00
committed by GitHub
parent 25f85a3beb
commit 8a9c19e3eb
285 changed files with 1125 additions and 876 deletions
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14
src/plugins/auto_batch/auto_batch.cpp
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@@ -386,7 +386,7 @@ AutoBatchAsyncInferRequest::AutoBatchAsyncInferRequest(
t.second = std::move(task);
workerInferRequest._tasks.push(t);
// it is ok to call size() here as the queue only grows (and the bulk removal happens under the mutex)
const int sz = workerInferRequest._tasks.size();
const int sz = static_cast<int>(workerInferRequest._tasks.size());
if (sz == workerInferRequest._batchSize) {
workerInferRequest._cond.notify_one();
}
@@ -527,7 +527,7 @@ std::pair<AutoBatchExecutableNetwork::WorkerInferRequest&, int> AutoBatchExecuta
} else {
// as we pop the tasks from the queue only here
// it is ok to call size() (as the _tasks can only grow in parallel)
const int sz = workerRequestPtr->_tasks.size();
const int sz = static_cast<int>(workerRequestPtr->_tasks.size());
if (sz == workerRequestPtr->_batchSize) {
std::pair<AutoBatchAsyncInferRequest*, InferenceEngine::Task> t;
for (int n = 0; n < sz; n++) {
@@ -567,7 +567,7 @@ std::pair<AutoBatchExecutableNetwork::WorkerInferRequest&, int> AutoBatchExecuta
}
});
}
return {*_workerRequests.back(), batch_id};
return {*_workerRequests.back(), static_cast<int>(batch_id)};
}
InferenceEngine::IInferRequestInternal::Ptr AutoBatchExecutableNetwork::CreateInferRequest() {
@@ -632,7 +632,7 @@ InferenceEngine::Parameter AutoBatchExecutableNetwork::GetMetric(const std::stri
// (multiplied by the devices capabilities to run multiple <batched> requests for further perf)
reqs = _device.batchForDevice *
_networkWithoutBatch->GetMetric(METRIC_KEY(OPTIMAL_NUMBER_OF_INFER_REQUESTS)).as<unsigned int>();
} catch (const InferenceEngine::Exception& iie) {
} catch (const InferenceEngine::Exception&) {
}
reqs = std::max(reqs, _device.batchForDevice); // round up to the possible user's value
IE_SET_METRIC_RETURN(OPTIMAL_NUMBER_OF_INFER_REQUESTS, reqs);
@@ -757,7 +757,7 @@ void AutoBatchInferencePlugin::CheckConfig(const std::map<std::string, std::stri
auto t = std::stoi(val);
if (t < 0)
IE_THROW(ParameterMismatch);
} catch (const std::exception& e) {
} catch (const std::exception&) {
IE_THROW(ParameterMismatch)
<< " Expecting unsigned int value for " << CONFIG_KEY(AUTO_BATCH_TIMEOUT) << " got " << val;
}
@@ -934,8 +934,8 @@ InferenceEngine::IExecutableNetworkInternal::Ptr AutoBatchInferencePlugin::LoadN
if (batch1_footprint) {
const auto total_mem =
GetCore()->GetMetric(deviceName, GPU_METRIC_KEY(DEVICE_TOTAL_MEM_SIZE)).as<uint64_t>();
const int estimated_batch = (total_mem - batch1_footprint) / batch1_footprint;
int closest = pow(2, floor(log(estimated_batch) / log(2)));
const int estimated_batch = static_cast<int>((total_mem - batch1_footprint) / batch1_footprint);
int closest = static_cast<int>(pow(2, floor(log(estimated_batch) / log(2))));
closest = std::max(1, closest);
metaDevice.batchForDevice = std::min(metaDevice.batchForDevice, closest);
}