[Fix] CPU memory type need device_id=0 to get allocator#14050
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PeixuanZuo merged 1 commit intomainfrom Dec 26, 2022
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[Fix] CPU memory type need device_id=0 to get allocator#14050PeixuanZuo merged 1 commit intomainfrom
PeixuanZuo merged 1 commit intomainfrom
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pengwa
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Dec 22, 2022
simon-moo
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) ### Description <!-- Describe your changes. --> Fix an error: `onnxruntime.capi.onnxruntime_pybind11_state.RuntimeException: [ONNXRuntimeError] : 6 : RUNTIME_EXCEPTION : Exception during initialization: /onnxruntime_src/onnxruntime/core/framework/allocation_planner.cc:819 onnxruntime::common::Status onnxruntime::PlannerImpl::ComputeValueLocation() allocator was false.` This error happens when we run huggingface models with DDP on multi-GPUs. In a thread with rank>0, it will attempt to obtain a CPU memory allocator with device_id>0, which causes the error. There is a workaround judges whether node’s output is on the CPU or not. If the output is on CPU, we set device_id = 0. Co-authored-by: peixuanzuo <peixuanzuo@linmif39a000004.zvflicr54joexhdgnhvmxrxygg.phxx.internal.cloudapp.net>
pengwa
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### Add CPU allocation test for non-CPU devices distributed run When CUDA EP is enabled in distributed training, CPU memory is still used for some node output. Early we have distributed run test coverage, but don't cover the case when some of the node are using CPU devices for storing tensor output. As a result, I recalled we hit regression twice in the passing months: - #14050 - #15823 So adding this test to avoid future regressions. The test graph looks like this:  ### Motivation and Context <!-- - Why is this change required? What problem does it solve? - If it fixes an open issue, please link to the issue here. -->
prathikr
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May 16, 2023
### Add CPU allocation test for non-CPU devices distributed run When CUDA EP is enabled in distributed training, CPU memory is still used for some node output. Early we have distributed run test coverage, but don't cover the case when some of the node are using CPU devices for storing tensor output. As a result, I recalled we hit regression twice in the passing months: - #14050 - #15823 So adding this test to avoid future regressions. The test graph looks like this:  ### Motivation and Context <!-- - Why is this change required? What problem does it solve? - If it fixes an open issue, please link to the issue here. -->
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Description
Fix an error:
onnxruntime.capi.onnxruntime_pybind11_state.RuntimeException: [ONNXRuntimeError] : 6 : RUNTIME_EXCEPTION : Exception during initialization: /onnxruntime_src/onnxruntime/core/framework/allocation_planner.cc:819 onnxruntime::common::Status onnxruntime::PlannerImpl::ComputeValueLocation() allocator was false.This error happens when we run huggingface models with DDP on multi-GPUs. In a thread with rank>0, it will attempt to obtain a CPU memory allocator with device_id>0, which causes the error. There is a workaround judges whether node’s output is on the CPU or not. If the output is on CPU, we set device_id = 0.