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Ernie 1.0模型 inference cpu切换gpu 报错
已完成
#I3NRLQ
PaddlePaddle-Gardener
创建于
2021-04-23 11:09
[<b>源自github用户bluestinger</b>](https://github.com/PaddlePaddle/Paddle/issues/32189): 环境是paddle 提供的docker的环境 hub.baidubce.com/paddlepaddle/paddle:1.8.0-gpu-cuda10.0-cudnn7-trt6 官方的Paddle-Inference-Demo可以正常使用 我自己训练的模型 Ernie 1.0 的pretrain模型,cpu下能正确输出结果。切换gpu后,报错如下 grep: warning: GREP_OPTIONS is deprecated; please use an alias or script E0411 03:34:51.655264 84 analysis_config.cc:180] Please compile with MKLDNN first to use MKLDNN I0411 03:34:52.433706 84 analysis_predictor.cc:138] Profiler is deactivated, and no profiling report will be generated. I0411 03:34:52.446473 84 analysis_predictor.cc:872] MODEL VERSION: 1.8.3 I0411 03:34:52.446512 84 analysis_predictor.cc:874] PREDICTOR VERSION: 1.8.0 I0411 03:34:52.446916 84 analysis_predictor.cc:432] TensorRT subgraph engine is enabled --- Running analysis [ir_graph_build_pass] --- Running analysis [ir_graph_clean_pass] --- Running analysis [ir_analysis_pass] --- Running IR pass [conv_affine_channel_fuse_pass] --- Running IR pass [conv_eltwiseadd_affine_channel_fuse_pass] --- Running IR pass [shuffle_channel_detect_pass] --- Running IR pass [quant_conv2d_dequant_fuse_pass] --- Running IR pass [delete_quant_dequant_op_pass] --- Running IR pass [simplify_with_basic_ops_pass] --- Running IR pass [embedding_eltwise_layernorm_fuse_pass] I0411 03:34:52.755502 84 graph_pattern_detector.cc:101] --- detected 1 subgraphs I0411 03:34:52.756510 84 graph_pattern_detector.cc:101] --- detected 1 subgraphs I0411 03:34:52.761987 84 graph_pattern_detector.cc:101] --- detected 25 subgraphs --- Running IR pass [multihead_matmul_fuse_pass_v2] I0411 03:34:54.146399 84 graph_pattern_detector.cc:101] --- detected 12 subgraphs --- Running IR pass [skip_layernorm_fuse_pass] I0411 03:34:54.173033 84 graph_pattern_detector.cc:101] --- detected 24 subgraphs --- Running IR pass [conv_bn_fuse_pass] --- Running IR pass [fc_fuse_pass] I0411 03:34:54.181416 84 graph_pattern_detector.cc:101] --- detected 12 subgraphs I0411 03:34:54.185427 84 graph_pattern_detector.cc:101] --- detected 25 subgraphs --- Running IR pass [tensorrt_subgraph_pass] I0411 03:34:54.195298 84 tensorrt_subgraph_pass.cc:115] --- detect a sub-graph with 77 nodes W0411 03:34:54.197585 84 tensorrt_subgraph_pass.cc:285] The Paddle lib links the 6015 version TensorRT, make sure the runtime TensorRT you are using is no less than this version, otherwise, there might be Segfault! I0411 03:34:54.197618 84 tensorrt_subgraph_pass.cc:321] Prepare TRT engine (Optimize model structure, Select OP kernel etc). This process may cost a lot of time. Traceback (most recent call last): File "Demo_pre5.py", line 119, in <module> pred=create_predictor() File "Demo_pre5.py", line 68, in create_predictor predictor=create_paddle_predictor(config) paddle.fluid.core_avx.EnforceNotMet: -------------------------------------------- C++ Call Stacks (More useful to developers): -------------------------------------------- 0 std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > paddle::platform::GetTraceBackString<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > >(std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >&&, char const*, int) 1 paddle::platform::EnforceNotMet::EnforceNotMet(std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, char const*, int) 2 paddle::inference::tensorrt::OpConverter::ConvertBlockToTRTEngine(paddle::framework::BlockDesc*, paddle::framework::Scope const&, std::vector<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >, std::allocator<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > > > const&, std::unordered_set<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >, std::hash<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > >, std::equal_to<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > >, std::allocator<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > > > const&, std::vector<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >, std::allocator<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > > > const&, paddle::inference::tensorrt::TensorRTEngine*) 3 paddle::inference::analysis::TensorRtSubgraphPass::CreateTensorRTOp(paddle::framework::ir::Node*, paddle::framework::ir::Graph*, std::vector<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >, std::allocator<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > > > const&, std::vector<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >, std::allocator<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > > >*) const 4 paddle::inference::analysis::TensorRtSubgraphPass::ApplyImpl(paddle::framework::ir::Graph*) const 5 paddle::framework::ir::Pass::Apply(paddle::framework::ir::Graph*) const 6 paddle::inference::analysis::IRPassManager::Apply(std::unique_ptr<paddle::framework::ir::Graph, std::default_delete<paddle::framework::ir::Graph> >) 7 paddle::inference::analysis::IrAnalysisPass::RunImpl(paddle::inference::analysis::Argument*) 8 paddle::inference::analysis::Analyzer::RunAnalysis(paddle::inference::analysis::Argument*) 9 paddle::AnalysisPredictor::OptimizeInferenceProgram() 10 paddle::AnalysisPredictor::PrepareProgram(std::shared_ptr<paddle::framework::ProgramDesc> const&) 11 paddle::AnalysisPredictor::Init(std::shared_ptr<paddle::framework::Scope> const&, std::shared_ptr<paddle::framework::ProgramDesc> const&) 12 std::unique_ptr<paddle::PaddlePredictor, std::default_delete<paddle::PaddlePredictor> > paddle::CreatePaddlePredictor<paddle::AnalysisConfig, (paddle::PaddleEngineKind)2>(paddle::AnalysisConfig const&) 13 std::unique_ptr<paddle::PaddlePredictor, std::default_delete<paddle::PaddlePredictor> > paddle::CreatePaddlePredictor<paddle::AnalysisConfig>(paddle::AnalysisConfig const&) ---------------------- Error Message Summary: ---------------------- InvalidArgumentError: TensorRT's tensor input requires at least 2 dimensions, but input 1 has 1 dims. [Hint: Expected shape.size() > 1UL, but received shape.size():1 <= 1UL:1.] at (/paddle /trt_refine_int8/paddle/fluid/inference/tensorrt/engine.h:67)
[<b>源自github用户bluestinger</b>](https://github.com/PaddlePaddle/Paddle/issues/32189): 环境是paddle 提供的docker的环境 hub.baidubce.com/paddlepaddle/paddle:1.8.0-gpu-cuda10.0-cudnn7-trt6 官方的Paddle-Inference-Demo可以正常使用 我自己训练的模型 Ernie 1.0 的pretrain模型,cpu下能正确输出结果。切换gpu后,报错如下 grep: warning: GREP_OPTIONS is deprecated; please use an alias or script E0411 03:34:51.655264 84 analysis_config.cc:180] Please compile with MKLDNN first to use MKLDNN I0411 03:34:52.433706 84 analysis_predictor.cc:138] Profiler is deactivated, and no profiling report will be generated. I0411 03:34:52.446473 84 analysis_predictor.cc:872] MODEL VERSION: 1.8.3 I0411 03:34:52.446512 84 analysis_predictor.cc:874] PREDICTOR VERSION: 1.8.0 I0411 03:34:52.446916 84 analysis_predictor.cc:432] TensorRT subgraph engine is enabled --- Running analysis [ir_graph_build_pass] --- Running analysis [ir_graph_clean_pass] --- Running analysis [ir_analysis_pass] --- Running IR pass [conv_affine_channel_fuse_pass] --- Running IR pass [conv_eltwiseadd_affine_channel_fuse_pass] --- Running IR pass [shuffle_channel_detect_pass] --- Running IR pass [quant_conv2d_dequant_fuse_pass] --- Running IR pass [delete_quant_dequant_op_pass] --- Running IR pass [simplify_with_basic_ops_pass] --- Running IR pass [embedding_eltwise_layernorm_fuse_pass] I0411 03:34:52.755502 84 graph_pattern_detector.cc:101] --- detected 1 subgraphs I0411 03:34:52.756510 84 graph_pattern_detector.cc:101] --- detected 1 subgraphs I0411 03:34:52.761987 84 graph_pattern_detector.cc:101] --- detected 25 subgraphs --- Running IR pass [multihead_matmul_fuse_pass_v2] I0411 03:34:54.146399 84 graph_pattern_detector.cc:101] --- detected 12 subgraphs --- Running IR pass [skip_layernorm_fuse_pass] I0411 03:34:54.173033 84 graph_pattern_detector.cc:101] --- detected 24 subgraphs --- Running IR pass [conv_bn_fuse_pass] --- Running IR pass [fc_fuse_pass] I0411 03:34:54.181416 84 graph_pattern_detector.cc:101] --- detected 12 subgraphs I0411 03:34:54.185427 84 graph_pattern_detector.cc:101] --- detected 25 subgraphs --- Running IR pass [tensorrt_subgraph_pass] I0411 03:34:54.195298 84 tensorrt_subgraph_pass.cc:115] --- detect a sub-graph with 77 nodes W0411 03:34:54.197585 84 tensorrt_subgraph_pass.cc:285] The Paddle lib links the 6015 version TensorRT, make sure the runtime TensorRT you are using is no less than this version, otherwise, there might be Segfault! I0411 03:34:54.197618 84 tensorrt_subgraph_pass.cc:321] Prepare TRT engine (Optimize model structure, Select OP kernel etc). This process may cost a lot of time. Traceback (most recent call last): File "Demo_pre5.py", line 119, in <module> pred=create_predictor() File "Demo_pre5.py", line 68, in create_predictor predictor=create_paddle_predictor(config) paddle.fluid.core_avx.EnforceNotMet: -------------------------------------------- C++ Call Stacks (More useful to developers): -------------------------------------------- 0 std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > paddle::platform::GetTraceBackString<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > >(std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >&&, char const*, int) 1 paddle::platform::EnforceNotMet::EnforceNotMet(std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, char const*, int) 2 paddle::inference::tensorrt::OpConverter::ConvertBlockToTRTEngine(paddle::framework::BlockDesc*, paddle::framework::Scope const&, std::vector<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >, std::allocator<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > > > const&, std::unordered_set<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >, std::hash<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > >, std::equal_to<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > >, std::allocator<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > > > const&, std::vector<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >, std::allocator<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > > > const&, paddle::inference::tensorrt::TensorRTEngine*) 3 paddle::inference::analysis::TensorRtSubgraphPass::CreateTensorRTOp(paddle::framework::ir::Node*, paddle::framework::ir::Graph*, std::vector<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >, std::allocator<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > > > const&, std::vector<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >, std::allocator<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > > >*) const 4 paddle::inference::analysis::TensorRtSubgraphPass::ApplyImpl(paddle::framework::ir::Graph*) const 5 paddle::framework::ir::Pass::Apply(paddle::framework::ir::Graph*) const 6 paddle::inference::analysis::IRPassManager::Apply(std::unique_ptr<paddle::framework::ir::Graph, std::default_delete<paddle::framework::ir::Graph> >) 7 paddle::inference::analysis::IrAnalysisPass::RunImpl(paddle::inference::analysis::Argument*) 8 paddle::inference::analysis::Analyzer::RunAnalysis(paddle::inference::analysis::Argument*) 9 paddle::AnalysisPredictor::OptimizeInferenceProgram() 10 paddle::AnalysisPredictor::PrepareProgram(std::shared_ptr<paddle::framework::ProgramDesc> const&) 11 paddle::AnalysisPredictor::Init(std::shared_ptr<paddle::framework::Scope> const&, std::shared_ptr<paddle::framework::ProgramDesc> const&) 12 std::unique_ptr<paddle::PaddlePredictor, std::default_delete<paddle::PaddlePredictor> > paddle::CreatePaddlePredictor<paddle::AnalysisConfig, (paddle::PaddleEngineKind)2>(paddle::AnalysisConfig const&) 13 std::unique_ptr<paddle::PaddlePredictor, std::default_delete<paddle::PaddlePredictor> > paddle::CreatePaddlePredictor<paddle::AnalysisConfig>(paddle::AnalysisConfig const&) ---------------------- Error Message Summary: ---------------------- InvalidArgumentError: TensorRT's tensor input requires at least 2 dimensions, but input 1 has 1 dims. [Hint: Expected shape.size() > 1UL, but received shape.size():1 <= 1UL:1.] at (/paddle /trt_refine_int8/paddle/fluid/inference/tensorrt/engine.h:67)
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