环境安装成功，但是不懂为什么运行demo报错，求解决。

[SmallSmallQiu]

ssh://[email protected]:22/home/kailing/anaconda3/envs/kailing3.7/bin/python3 -u /home/kailing/qiu/ABSA/Senta-master/demo.py ModuleNotFoundError: No module named 'numpy.core._multiarray_umath' ModuleNotFoundError: No module named 'numpy.core._multiarray_umath' W0704 17:25:20.889032 8592 device_context.cc:236] Please NOTE: device: 0, CUDA Capability: 75, Driver API Version: 11.2, Runtime API Version: 10.0 W0704 17:25:20.892278 8592 device_context.cc:244] device: 0, cuDNN Version: 7.6. Traceback (most recent call last): File "/home/kailing/qiu/ABSA/Senta-master/demo.py", line 24, in result = my_senta.predict(texts, aspects) File "/home/kailing/qiu/ABSA/Senta-master/senta/train.py", line 271, in predict result = self.inference.run(inputs) paddle.fluid.core_avx.EnforceNotMet:

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C++ Call Stacks (More useful to developers):

0 std::string paddle::platform::GetTraceBackString<char const*>(char const*&&, char const*, int) 1 paddle::platform::EnforceNotMet::EnforceNotMet(std::__exception_ptr::exception_ptr, char const*, int) 2 void paddle::operators::math::Blaspaddle::platform::CUDADeviceContext::MatMul(paddle::framework::Tensor const&, paddle::operators::math::MatDescriptor const&, paddle::framework::Tensor const&, paddle::operators::math::MatDescriptor const&, float, paddle::framework::Tensor*, float) const 3 paddle::operators::MatMulKernel<paddle::platform::CUDADeviceContext, float>::Compute(paddle::framework::ExecutionContext const&) const 4 std::_Function_handler<void (paddle::framework::ExecutionContext const&), paddle::framework::OpKernelRegistrarFunctor<paddle::platform::CUDAPlace, false, 0ul, paddle::operators::MatMulKernel<paddle::platform::CUDADeviceContext, float>, paddle::operators::MatMulKernel<paddle::platform::CUDADeviceContext, double>, paddle::operators::MatMulKernel<paddle::platform::CUDADeviceContext, paddle::platform::float16> >::operator()(char const*, char const*, int) const::{lambda(paddle::framework::ExecutionContext const&)#1}>::_M_invoke(std::_Any_data const&, paddle::framework::ExecutionContext const&) 5 paddle::framework::OperatorWithKernel::RunImpl(paddle::framework::Scope const&, paddle::platform::Place const&, paddle::framework::RuntimeContext*) const 6 paddle::framework::OperatorWithKernel::RunImpl(paddle::framework::Scope const&, paddle::platform::Place const&) const 7 paddle::framework::OperatorBase::Run(paddle::framework::Scope const&, paddle::platform::Place const&) 8 paddle::framework::Executor::RunPreparedContext(paddle::framework::ExecutorPrepareContext*, paddle::framework::Scope*, bool, bool, bool) 9 paddle::NativePaddlePredictor::Run(std::vector<paddle::PaddleTensor, std::allocatorpaddle::PaddleTensor > const&, std::vector<paddle::PaddleTensor, std::allocatorpaddle::PaddleTensor >*, int)

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Python Call Stacks (More useful to users):

File "/root/gaocan01/0-bin/4-paddle_1.6.3_py3.7/miniconda3/lib/python3.7/site-packages/paddle/fluid/framework.py", line 2488, in append_op attrs=kwargs.get("attrs", None)) File "/root/gaocan01/0-bin/4-paddle_1.6.3_py3.7/miniconda3/lib/python3.7/site-packages/paddle/fluid/layer_helper.py", line 43, in append_op return self.main_program.current_block().append_op(*args, **kwargs) File "/root/gaocan01/0-bin/4-paddle_1.6.3_py3.7/miniconda3/lib/python3.7/site-packages/paddle/fluid/layers/nn.py", line 7072, in matmul 'alpha': float(alpha), File "/mnt/du/gaocan01/1-textone/senta/senta/modules/ernie.py", line 152, in _build_model x=input_mask, y=input_mask, transpose_y=True) File "/mnt/du/gaocan01/1-textone/senta/senta/modules/ernie.py", line 85, in init input_mask) File "/mnt/du/gaocan01/1-textone/senta/senta/models/ernie_two_sent_classification_ch.py", line 132, in make_embedding use_fp16=use_fp16 File "/mnt/du/gaocan01/1-textone/senta/senta/models/ernie_two_sent_classification_ch.py", line 51, in forward emb_dict = self.make_embedding(fields_dict, phase) File "/mnt/du/gaocan01/1-textone/senta/senta/training/base_trainer.py", line 192, in init_save_inference_net forward_output_dict = self.model_class.forward(fields_dict, phase=InstanceName.SAVE_INFERENCE) File "/mnt/du/gaocan01/1-textone/senta/senta/training/base_trainer.py", line 141, in init_net self.init_save_inference_net() File "/mnt/du/gaocan01/1-textone/senta/senta/training/base_trainer.py", line 48, in init self.init_net() File "/mnt/du/gaocan01/1-textone/senta/senta/training/custom_trainer.py", line 31, in init BaseTrainer.init(self, params, data_set_reader, model_class) File "./train.py", line 71, in build_trainer trainer = trainer_class(params=params_dict, data_set_reader=dataset_reader, model_class=model) File "./train.py", line 91, in trainer = build_trainer(trainer_params_dict, dataset_reader, model, num_train_examples)

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Error Message Summary:

Error: Paddle internal Check failed. (Please help us create a new issue, here we need to find the developer to add a user friendly error message) [CUBLAS: execution failed.] at (/paddle/paddle/fluid/operators/math/blas_impl.cu.h:51) [operator < matmul > error]

Process finished with exit code 1

[hhk123]

我解决了：把numpy改成1.22.3版本，sklearn也改成0.22.1