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• 标题：用create_paddle_predictor多次创建predictor，在同一个data_generator下run报错

• 版本、环境信息：    1）PaddlePaddle版本：paddle fluid 1.5.1    2）GPU：预测若用GPU，请提供GPU型号、CUDA和CUDNN版本号    4）系统环境：cuda9，Python版本 python3.6 注：您可以通过执行summary_env.py获取以上信息。 简而言之，由于需要创建2个predictor用2个模型预测不同的任务，create_paddle_predictor了2次，两个predictor在同一个predict_data_generator下run了，以便一起获取结果。不知这样是否可以？(是需要创建2个fluid.Executor还是共用1个就好？还是不能2个模型一起预测？ 错误代码： predict_prog = fluid.Program() predict_startup = fluid.Program() with fluid.program_guard(predict_prog, predict_startup): with fluid.unique_name.guard(): ret = create_model( args, pyreader_name='predict_reader', ernie_config=ernie_config, is_classify=True, is_prediction=True, ) predict_pyreader = ret['pyreader'] left_score = ret['left_probs'] #right_score = ret['right_probs'] type_probs = ret['type_probs'] feed_targets_name = ret['feed_targets_name']

  predict_prog = predict_prog.clone(for_test=True)

  if args.use_cuda: dev_list = fluid.cuda_places() place = dev_list[0] print('----------place-----------') print(place) dev_count = len(dev_list) else: place = fluid.CPUPlace() dev_count = int(os.environ.get('CPU_NUM', multiprocessing.cpu_count()))

  place = fluid.CUDAPlace(0) if args.use_cuda == True else fluid.CPUPlace() exe = fluid.Executor(place) exe.run(predict_startup)

  if args.init_checkpoint: init_pretraining_params(exe, args.init_checkpoint, predict_prog) else: raise ValueError( "args 'init_checkpoint' should be set for prediction!", )

  assert args.save_inference_model_path,
  "args save_inference_model_path should be set for prediction" _, ckpt_dir = os.path.split(args.init_checkpoint.rstrip('/')) dir_name = ckpt_dir + '_inference_model' model_path = os.path.join(args.save_inference_model_path, dir_name) log.info("save inference model to %s" % model_path) log.info("feed_targets_name %s" % feed_targets_name) #feed_targets_name.remove('read_file_0.tmp_3') #feed_targets_name.remove('read_file_0.tmp_8') #feed_targets_name.remove('read_file_0.tmp_12')

  fluid.io.save_inference_model( model_path, feed_targets_name, [left_score, type_probs], #[left_score, right_score, type_probs], exe, main_program=predict_prog, )

  #save score reference model==================== predict_prog = fluid.Program() predict_startup = fluid.Program() with fluid.program_guard(predict_prog, predict_startup): with fluid.unique_name.guard(): ret = create_score_model( args, pyreader_name='predict_score_reader', ernie_config=ernie_config, is_classify=True, is_prediction=True, ) predict_pyreader = ret['pyreader'] left_score = ret['left_probs'] #right_score = ret['right_probs'] #type_probs = ret['type_probs'] feed_targets_name = ret['feed_targets_name']

  predict_prog = predict_prog.clone(for_test=True)

  if args.use_cuda: dev_list = fluid.cuda_places() place = dev_list[0] print('----------place-----------') print(place) dev_count = len(dev_list) else: place = fluid.CPUPlace() dev_count = int(os.environ.get('CPU_NUM', multiprocessing.cpu_count()))

  place = fluid.CUDAPlace(1) if args.use_cuda == True else fluid.CPUPlace() exe1 = fluid.Executor(place) exe1.run(predict_startup)

  if args.init_checkpoint: init_pretraining_params(exe, args.init_score_checkpoint, predict_prog) else: raise ValueError( "args 'init_checkpoint' should be set for prediction!", )

  assert args.save_score_inference_model_path,
  "args save_score_inference_model_path should be set for prediction" _, ckpt_dir = os.path.split(args.init_score_checkpoint.rstrip('/')) dir_name = ckpt_dir + '_inference_model' score_model_path = os.path.join(args.save_score_inference_model_path, dir_name) log.info("save score inference model to %s" % score_model_path) log.info("feed_targets_name %s" % feed_targets_name) #feed_targets_name.remove('read_file_0.tmp_3') #feed_targets_name.remove('read_file_0.tmp_8') #feed_targets_name.remove('read_file_0.tmp_12')

  fluid.io.save_inference_model( score_model_path, feed_targets_name, [left_score, type_probs], #[left_score, right_score, type_probs], exe, main_program=predict_prog, ) #================================================================

  config = AnalysisConfig(model_path) score_config = AnalysisConfig(score_model_path) if not args.use_cuda: log.info("disable gpu") config.disable_gpu() else: log.info("using gpu") config.enable_use_gpu(1024)

  if not args.use_cuda: log.info("disable gpu") score_config.disable_gpu() else: log.info("using gpu") score_config.enable_use_gpu(1024)

  Create PaddlePredictor

  predictor = create_paddle_predictor(config) score_predictor = create_paddle_predictor(score_config)

  predict_data_generator = reader.data_generator( input_file=args.predict_set, batch_size=args.batch_size, epoch=1, shuffle=False, )

  log.info("-------------- prediction results --------------") np.set_printoptions(precision=4, suppress=True) index = 0 total_time = 0 qid_total = None left_score_total = None #right_score_total = None type_prob_total = None ent_id_total = None for sample in predict_data_generator(): src_ids_1 = sample[0] sent_ids_1 = sample[1] pos_ids_1 = sample[2] task_ids_1 = sample[3] input_mask_1 = sample[4] src_ids_2 = sample[5] sent_ids_2 = sample[6] pos_ids_2 = sample[7] task_ids_2 = sample[8] input_mask_2 = sample[9] #src_ids_3 = sample[10] #sent_ids_3 = sample[11] #pos_ids_3 = sample[12] #task_ids_3 = sample[13] #input_mask_3 = sample[14] #qids = sample[15] #ent_ids = sample[16] qids = sample[10] ent_ids = sample[11] inputs = [array2tensor(ndarray) for ndarray in [ src_ids_1, sent_ids_1, pos_ids_1, task_ids_1, input_mask_1, src_ids_2, sent_ids_2, pos_ids_2, task_ids_2, input_mask_2, #src_ids_3, sent_ids_3, pos_ids_3, task_ids_3, input_mask_3, qids, ]] #print('inputs',inputs) begin_time = time.time() outputs = predictor.run(inputs) score_outputs = score_predictor.run(inputs)

c++ 报错 2020-09-01 16:29:05 Traceback (most recent call last): 2020-09-01 16:29:05 File "/media/cfs/liuhongru3/Research-master/KG/DuEL_Baseline/ernie/infer_type_ranker.py", line 448, in 2020-09-01 16:29:05 main(args) 2020-09-01 16:29:05 File "/media/cfs/liuhongru3/Research-master/KG/DuEL_Baseline/ernie/infer_type_ranker.py", line 308, in main 2020-09-01 16:29:05 score_outputs = score_predictor.run(inputs) 2020-09-01 16:29:05 paddle.fluid.core_avx.EnforceNotMet: Invoke operator scale error. 2020-09-01 16:29:05 Python Callstacks: 2020-09-01 16:29:05 File "/usr/local/anaconda3/lib/python3.6/site-packages/paddle/fluid/framework.py", line 1771, in append_op 2020-09-01 16:29:05 attrs=kwargs.get("attrs", None)) 2020-09-01 16:29:05 File "/usr/local/anaconda3/lib/python3.6/site-packages/paddle/fluid/layer_helper.py", line 43, in append_op 2020-09-01 16:29:05 return self.main_program.current_block().append_op(args, kwargs) 2020-09-01 16:29:05 File "/usr/local/anaconda3/lib/python3.6/site-packages/paddle/fluid/layers/nn.py", line 9947, in scale 2020-09-01 16:29:05 'bias_after_scale': bias_after_scale 2020-09-01 16:29:05 File "/usr/local/anaconda3/lib/python3.6/site-packages/paddle/fluid/io.py", line 1026, in save_inference_model 2020-09-01 16:29:05 var, 1., name="save_infer_model/scale_{}".format(i)) 2020-09-01 16:29:05 File "/media/cfs/liuhongru3/Research-master/KG/DuEL_Baseline/ernie/infer_type_ranker.py", line 240, in main 2020-09-01 16:29:05 main_program=predict_prog, 2020-09-01 16:29:05 File "/media/cfs/liuhongru3/Research-master/KG/DuEL_Baseline/ernie/infer_type_ranker.py", line 448, in 2020-09-01 16:29:05 main(args) 2020-09-01 16:29:05 C++ Callstacks: 2020-09-01 16:29:05 Input X(0) is not initialized at [/paddle/paddle/fluid/framework/operator.cc:1146] 2020-09-01 16:29:05 PaddlePaddle Call Stacks: 2020-09-01 16:29:05 0 0x7f3d5d697760p void paddle::platform::EnforceNotMet::Init<char const>(char const, char const, int) + 352 2020-09-01 16:29:05 1 0x7f3d5d697ad9p paddle::platform::EnforceNotMet::EnforceNotMet(std::exception_ptr::exception_ptr, char const*, int) + 137 2020-09-01 16:29:05 2 0x7f3d5f5fa34fp paddle::framework::OperatorWithKernel::IndicateDataType(paddle::framework::ExecutionContext const&) const + 1343 2020-09-01 16:29:05 3 0x7f3d5f5fa53fp paddle::framework::OperatorWithKernel::GetExpectedKernelType(paddle::framework::ExecutionContext const&) const + 47 2020-09-01 16:29:05 4 0x7f3d5f5fbdfbp paddle::framework::OperatorWithKernel::ChooseKernel(paddle::framework::RuntimeContext const&, paddle::framework::Scope const&, boost::variant<paddle::platform::CUDAPlace, paddle::platform::CPUPlace, paddle::platform::CUDAPinnedPlace, boost::detail::variant::void, boost::detail::variant::void, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_> const&) const + 235 2020-09-01 16:29:05 5 0x7f3d5f5fdf68p paddle::framework::OperatorWithKernel::RunImpl(paddle::framework::Scope const&, boost::variant<paddle::platform::CUDAPlace, paddle::platform::CPUPlace, paddle::platform::CUDAPinnedPlace, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_> const&, paddle::framework::RuntimeContext*) const + 728 2020-09-01 16:29:05 6 0x7f3d5f5fe0f3p paddle::framework::OperatorWithKernel::RunImpl(paddle::framework::Scope const&, boost::variant<paddle::platform::CUDAPlace, paddle::platform::CPUPlace, paddle::platform::CUDAPinnedPlace, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_> const&) const + 291 2020-09-01 16:29:05 7 0x7f3d5f5fb7dcp paddle::framework::OperatorBase::Run(paddle::framework::Scope const&, boost::variant<paddle::platform::CUDAPlace, paddle::platform::CPUPlace, paddle::platform::CUDAPinnedPlace, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_> const&) + 332 2020-09-01 16:29:05 8 0x7f3d5f5b1290p paddle::framework::NaiveExecutor::Run() + 560 2020-09-01 16:29:05 9 0x7f3d5d8a3ce8p paddle::AnalysisPredictor::Run(std::vector<paddle::PaddleTensor, std::allocatorpaddle::PaddleTensor > const&, std::vector<paddle::PaddleTensor, std::allocatorpaddle::PaddleTensor >*, int) + 184 2020-09-01 16:29:05 10 0x7f3d5d7b4426p 2020-09-01 16:29:05 11 0x7f3d5d6ca076p 2020-09-01 16:29:05 12 0x557d715c4fd4p _PyCFunction_FastCallDict + 340 2020-09-01 16:29:05 13 0x557d71652d3ep 2020-09-01 16:29:05 14 0x557d7167719ap _PyEval_EvalFrameDefault + 778 2020-09-01 16:29:05 15 0x557d7164c7dbp 2020-09-01 16:29:05 16 0x557d71652cc5p 2020-09-01 16:29:05 17 0x557d7167719ap _PyEval_EvalFrameDefault + 778 2020-09-01 16:29:05 18 0x557d7164d529p PyEval_EvalCodeEx + 809 2020-09-01 16:29:05 19 0x557d7164e2ccp PyEval_EvalCode + 28 2020-09-01 16:29:05 20 0x557d716caaf4p 2020-09-01 16:29:05 21 0x557d716caef1p PyRun_FileExFlags + 161 2020-09-01 16:29:05 22 0x557d716cb0f4p PyRun_SimpleFileExFlags + 452 2020-09-01 16:29:05 23 0x557d716cec28p Py_Main + 1608 2020-09-01 16:29:05 24 0x557d7159671ep main + 238 2020-09-01 16:29:05 25 0x7f3e57a0a3d5p __libc_start_main + 245 2020-09-01 16:29:05 26 0x557d7167dc98p 2020-09-01 16:29:05