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在win10系统下使用PaddleInference2.5编译ppyoloe_crn_l,出现如下问题, 请问如何解决? #519
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你好,感谢您的反馈,从上面的报错暂时看不出原因。你可以设置如下flag: 另外,也可以参考 https://www.paddlepaddle.org.cn/inference/master/guides/performance_tuning/precision_tracing.html 确认是否为某个pass的问题。 最后,可以尝试更换到2.6版本,确认问题是否存在。 如果你尝试了以上办法,请务必将运行结果贴在这里,这对我们后续的分析定位会很有帮助。 |
win10系统下, 在cmd设置 set FLAGS_call_stack_level = 2 Code: #include #include <gflags/gflags.h> #include "paddle_inference_api.h" using paddle_infer::Config; DEFINE_string(model_dir, "", "Directory of the inference model."); using Time = decltype(std::chrono::high_resolution_clock::now()); std::shared_ptr InitPredictor()
} void run(Predictor* predictor,const std::vector& input,const std::vector& input_shape,std::vector* out_data)
} int main(int argc, char* argv[])
} Problem: C++ Traceback (most recent call last):Not support stack backtrace yet. Error Message Summary:InvalidArgumentError: The axis is expected to be in range of [1, -1), but got 1 |
你好,现在看来应该是内部问题,有一个输入没有被初始化,我们会尽快提PR修复,合入后会及时在PR里同步。 |
已经修复了 |
你好, 我昨天也调试了一下. 挨个观察, 发现是run_mode的设置问题. 默认是paddle_gpu, 改成trt_xxx就可以了. |
另外请教一个问题. 使用TensorRT的情况下, 加载模型需要时间太长. 有没有办法在几秒或者几十秒内完成? |
原生gpu改了应该也要正确,确实是个bug
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主题: Re: [PaddlePaddle/Paddle-Inference-Demo] 在win10系统下使用PaddleInference2.5编译ppyoloe_crn_l,出现如下问题, 请问如何解决? (Issue #519)
你好, 我昨天也调试了一下. 挨个观察, 发现是run_mode的设置问题. 默认是paddle_gpu, 改成trt_xxx就可以了.
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理论上所有run_mode应该都能跑通,现在我们已经修复了原生GPU下的问题,可以尝试下原生GPU。使用 TRT加载时间太长可能跟TRT的图优化过程有关,可以分享下你现在具体加载的用时。 |
W0508 15:06:45.928721 8180 op_compat_sensible_pass.cc:232] Check the Attr(axis) of Op(elementwise_add) in pass(conv_elementwise_add_fuse_pass) failed! 中间2行: 15:06:48 到 15:09:45 时间用了将近3分钟. 另外请问 原生GPU , 是指你们已经更新了SDK包吗? 在哪里下载? 可以给出链接吗? |
原生GPU指你一开始的配置,即不使用TRT。更新的话主要更新的是本仓库,你拉下这个仓库的最新commit就行,或者手动仿照 #520 更新下 关于TRT的时间问题,我会反馈给相关同事,短期内可能没法修复。 |
ppyoloe_crn_l.exe --model_file ppyoloe_crn_l_300e_coco/model.pdmodel --params_file ppyoloe_crn_l_300e_coco/model.pdiparams
D:\000-AI\paddle\Deploy\2.5\Paddle-Inference-Demo-master\c++\gpu\ppyoloe_crn_l\build\Release>ppyoloe_crn_l.exe --model_file ppyoloe_crn_l_300e_coco/model.pdmodel --params_file ppyoloe_crn_l_300e_coco/model.pdiparams
e[1me[35m--- Running analysis [ir_graph_build_pass]e[0m
WARNING: Logging before InitGoogleLogging() is written to STDERR
I0505 13:45:31.034536 5320 executor.cc:187] Old Executor is Running.
e[1me[35m--- Running analysis [ir_analysis_pass]e[0m
e[32m--- Running IR pass [map_op_to_another_pass]e[0m
e[32m--- Running IR pass [identity_scale_op_clean_pass]e[0m
e[32m--- Running IR pass [is_test_pass]e[0m
e[32m--- Running IR pass [simplify_with_basic_ops_pass]e[0m
e[32m--- Running IR pass [delete_quant_dequant_linear_op_pass]e[0m
e[32m--- Running IR pass [delete_weight_dequant_linear_op_pass]e[0m
e[32m--- Running IR pass [constant_folding_pass]e[0m
e[32m--- Running IR pass [silu_fuse_pass]e[0m
e[32m--- Running IR pass [conv_bn_fuse_pass]e[0m
I0505 13:45:31.640825 5320 fuse_pass_base.cc:59] --- detected 78 subgraphs
e[32m--- Running IR pass [conv_eltwiseadd_bn_fuse_pass]e[0m
e[32m--- Running IR pass [embedding_eltwise_layernorm_fuse_pass]e[0m
e[32m--- Running IR pass [multihead_matmul_fuse_pass_v2]e[0m
e[32m--- Running IR pass [vit_attention_fuse_pass]e[0m
e[32m--- Running IR pass [fused_multi_transformer_encoder_pass]e[0m
e[32m--- Running IR pass [fused_multi_transformer_decoder_pass]e[0m
e[32m--- Running IR pass [fused_multi_transformer_encoder_fuse_qkv_pass]e[0m
e[32m--- Running IR pass [fused_multi_transformer_decoder_fuse_qkv_pass]e[0m
e[32m--- Running IR pass [multi_devices_fused_multi_transformer_encoder_pass]e[0m
e[32m--- Running IR pass [multi_devices_fused_multi_transformer_encoder_fuse_qkv_pass]e[0m
e[32m--- Running IR pass [multi_devices_fused_multi_transformer_decoder_fuse_qkv_pass]e[0m
e[32m--- Running IR pass [fuse_multi_transformer_layer_pass]e[0m
e[32m--- Running IR pass [gpu_cpu_squeeze2_matmul_fuse_pass]e[0m
e[32m--- Running IR pass [gpu_cpu_reshape2_matmul_fuse_pass]e[0m
e[32m--- Running IR pass [gpu_cpu_flatten2_matmul_fuse_pass]e[0m
e[32m--- Running IR pass [gpu_cpu_map_matmul_v2_to_mul_pass]e[0m
e[32m--- Running IR pass [gpu_cpu_map_matmul_v2_to_matmul_pass]e[0m
e[32m--- Running IR pass [matmul_scale_fuse_pass]e[0m
e[32m--- Running IR pass [multihead_matmul_fuse_pass_v3]e[0m
e[32m--- Running IR pass [gpu_cpu_map_matmul_to_mul_pass]e[0m
e[32m--- Running IR pass [fc_fuse_pass]e[0m
e[32m--- Running IR pass [fc_elementwise_layernorm_fuse_pass]e[0m
e[32m--- Running IR pass [conv_elementwise_add_act_fuse_pass]e[0m
I0505 13:45:34.308128 5320 fuse_pass_base.cc:59] --- detected 9 subgraphs
e[32m--- Running IR pass [conv_elementwise_add2_act_fuse_pass]e[0m
e[32m--- Running IR pass [conv_elementwise_add_fuse_pass]e[0m
I0505 13:45:34.541483 5320 fuse_pass_base.cc:59] --- detected 118 subgraphs
e[32m--- Running IR pass [transpose_flatten_concat_fuse_pass]e[0m
e[32m--- Running IR pass [conv2d_fusion_layout_transfer_pass]e[0m
e[32m--- Running IR pass [transfer_layout_elim_pass]e[0m
e[32m--- Running IR pass [auto_mixed_precision_pass]e[0m
e[32m--- Running IR pass [inplace_op_var_pass]e[0m
e[1me[35m--- Running analysis [save_optimized_model_pass]e[0m
W0505 13:45:34.565424 5320 save_optimized_model_pass.cc:28] save_optim_cache_model is turned off, skip save_optimized_model_pass
e[1me[35m--- Running analysis [ir_params_sync_among_devices_pass]e[0m
I0505 13:45:34.566417 5320 ir_params_sync_among_devices_pass.cc:51] Sync params from CPU to GPU
e[1me[35m--- Running analysis [adjust_cudnn_workspace_size_pass]e[0m
e[1me[35m--- Running analysis [inference_op_replace_pass]e[0m
e[1me[35m--- Running analysis [memory_optimize_pass]e[0m
I0505 13:45:34.726987 5320 memory_optimize_pass.cc:222] Cluster name : tmp_2 size: 26214400
I0505 13:45:34.726987 5320 memory_optimize_pass.cc:222] Cluster name : batch_norm_2.tmp_2 size: 26214400
I0505 13:45:34.726987 5320 memory_optimize_pass.cc:222] Cluster name : image size: 4915200
I0505 13:45:34.727985 5320 memory_optimize_pass.cc:222] Cluster name : sigmoid_2.tmp_0 size: 26214400
I0505 13:45:34.727985 5320 memory_optimize_pass.cc:222] Cluster name : batch_norm_48.tmp_2 size: 1228800
I0505 13:45:34.727985 5320 memory_optimize_pass.cc:222] Cluster name : tmp_0 size: 13107200
I0505 13:45:34.728982 5320 memory_optimize_pass.cc:222] Cluster name : elementwise_add_0 size: 4915200
I0505 13:45:34.728982 5320 memory_optimize_pass.cc:222] Cluster name : tmp_7 size: 4915200
I0505 13:45:34.728982 5320 memory_optimize_pass.cc:222] Cluster name : elementwise_add_16 size: 614400
I0505 13:45:34.728982 5320 memory_optimize_pass.cc:222] Cluster name : pool2d_5.tmp_0 size: 768
I0505 13:45:34.729979 5320 memory_optimize_pass.cc:222] Cluster name : scale_factor size: 8
I0505 13:45:34.729979 5320 memory_optimize_pass.cc:222] Cluster name : shape_2.tmp_0_slice_0 size: 4
e[1me[35m--- Running analysis [ir_graph_to_program_pass]e[0m
I0505 13:45:34.970336 5320 analysis_predictor.cc:1660] ======= optimize end =======
I0505 13:45:34.971334 5320 naive_executor.cc:164] --- skip [feed], feed -> scale_factor
I0505 13:45:34.973328 5320 naive_executor.cc:164] --- skip [feed], feed -> image
I0505 13:45:34.984299 5320 naive_executor.cc:164] --- skip [gather_nd_0.tmp_0], fetch -> fetch
I0505 13:45:34.984299 5320 naive_executor.cc:164] --- skip [multiclass_nms3_0.tmp_2], fetch -> fetch
W0505 13:45:34.987293 5320 gpu_resources.cc:119] Please NOTE: device: 0, GPU Compute Capability: 7.5, Driver API Version: 12.2, Runtime API Version: 11.8
W0505 13:45:34.991281 5320 gpu_resources.cc:149] device: 0, cuDNN Version: 8.6.
C++ Traceback (most recent call last):
Not support stack backtrace yet.
Error Message Summary:
InvalidArgumentError: The axis is expected to be in range of [-1, 1), but got 1
[Hint: Expected axis_value >= -rank && axis_value < rank == true, but received axis_value >= -rank && axis_value < rank:0 != true:1.] (at ..\paddle\phi\infermeta\unary.cc:3567)
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