forked from mindspore-Ecosystem/mindspore
waiting tasks in the queue exceeds the limit
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4d088ae2c7
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a7e625245e
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@ -80,6 +80,7 @@ enum StatusCode : uint32_t {
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kLiteThreadPoolError = kLite | (0x0FFFFFFF & -8), /**< Error occur in thread pool. */
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kLiteUninitializedObj = kLite | (0x0FFFFFFF & -9), /**< Object is not initialized. */
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kLiteFileError = kLite | (0x0FFFFFFF & -10), /**< Invalid file. */
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kLiteServiceDeny = kLite | (0x0FFFFFFF & -11), /**< Denial of service. */
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// Executor error code, range: [-100,-200)
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kLiteOutOfTensorRange = kLite | (0x0FFFFFFF & -100), /**< Failed to check range. */
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@ -57,7 +57,7 @@ Status ModelParallelRunner::Predict(const std::vector<MSTensor> &inputs, std::ve
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auto status = model_pool_->Predict(inputs, outputs, before, after);
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if (status != kSuccess) {
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MS_LOG(ERROR) << "model runner predict failed.";
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return kLiteError;
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return status;
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}
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return kSuccess;
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}
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@ -29,6 +29,7 @@ namespace mindspore {
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namespace {
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constexpr int32_t kNumThreads = 8;
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constexpr int kNumDeviceInfo = 2;
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constexpr int kNumMaxTaskQueueSize = 1000;
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int GetCoreNum() {
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int core_num = 1;
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#if defined(_MSC_VER) || defined(_WIN32)
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@ -639,6 +640,11 @@ Status ModelPool::Predict(const std::vector<MSTensor> &inputs, std::vector<MSTen
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return kSuccess;
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} else {
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// do predict
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if (predict_task_queue_->GetTaskNum(max_wait_worker_node_id) > kNumMaxTaskQueueSize) {
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MS_LOG(ERROR) << "The number of waiting tasks in the queue exceeds the limit, ret=" << kLiteServiceDeny;
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predict_task_mutex_.unlock();
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return kLiteServiceDeny;
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}
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predict_task_queue_->DecreaseWaitModelNum(1, max_wait_worker_node_id);
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auto predict_task = std::make_shared<PredictTask>(&inputs, outputs, before, after);
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if (predict_task == nullptr) {
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