# 训练推理问题案例

-   **[MindSpore报错：TypeError: Multiply values for specific argument: query\_embeds](MindSpore报错-TypeError-Multiply-values-for-specific-argument-query_embeds.md)**  

-   **[Tokenizer指向报错TypeError GPT2Tokenizer: \_\_init\_\_ \(\) missing 2 required positional arguments: 'vocab\_file' and "merges\_file'.](Tokenizer指向报错TypeError-GPT2Tokenizer-__init__-()-missing-2-required-positional-arguments-vocab_file.md)**  

-   **[Tokenizer文件缺失报错TypeError:\_\_init\_\(\) missing 2 required positional arguments: 'vocab\_file' and 'merge\_file'](Tokenizer文件缺失报错TypeError-__init_()-missing-2-required-positional-arguments-vocab_file-and-merge_file.md)**  

-   **[模型推理时验证model.generate\(\)功能报错RuntimeError A model class needs to define a \`prepare inputs fordgeneration\` method in order to use .generate\(\)\`](模型推理时验证model-generate()功能报错RuntimeError-A-model-class-needs-to-define-a-prepare-inputs-fordgeneratio.md)**  

-   **[MindSpore模型推理报错：memory isn't enough and alloc failed, kernel name: kernel\_graph\_@ HostDSActor, alloc size: 8192B](MindSpore模型推理报错-memory-isn-t-enough-and-alloc-failed-kernel-name-kernel_graph_-HostDSActor-alloc-siz.md)**  

-   **[MindSpore模型推理报错TypeError: cell\_reuse\(\) takes 0 positional arguments but 1 was given](MindSpore模型推理报错TypeError-cell_reuse()-takes-0-positional-arguments-but-1-was-given.md)**  

-   **[运行wizardcoder迁移代码报错broken pipe](运行wizardcoder迁移代码报错broken-pipe.md)**  

-   **[MindSpore Lite模型加载报错RuntimeError: build from file failed! Error is Common error code.](MindSpore-Lite模型加载报错RuntimeError-build-from-file-failed-Error-is-Common-error-code.md)**  

-   **[Mindspore在自回归推理时的精度对齐设置](Mindspore在自回归推理时的精度对齐设置.md)**  

-   **[MindSpore大模型打开pp并行或者梯度累积之后loss不溢出也不收敛](MindSpore大模型打开pp并行或者梯度累积之后loss不溢出也不收敛.md)**  

-   **[Ascend上用ADGEN数据集评估时报错not support in PyNative RunOp!](Ascend上用ADGEN数据集评估时报错not-support-in-PyNative-RunOp.md)**  

-   **[qwen1.5\_1.8B推理出现回答混乱问题及解决](qwen1-5_1-8B推理出现回答混乱问题及解决.md)**  

-   **[单机4卡分布式推理失报错RuntimeError: Ascend kernel runtime initialization failed. The details refer to 'Ascend Error Message'.](单机4卡分布式推理失报错RuntimeError-Ascend-kernel-runtime-initialization-failed-The-details-refer-to-Ascend-Err.md)**  

-   **[使用单卡Ascend910进行LLaMA2-7B推理,速度缓慢](使用单卡Ascend910进行LLaMA2-7B推理-速度缓慢.md)**  

-   **[MindSpore大模型微调时报溢出及解决](MindSpore大模型微调时报溢出及解决.md)**  

-   **[MindSpore大模型在线推理速度慢及解决方案](MindSpore大模型在线推理速度慢及解决方案.md)**  

-   **[Llama推理报参数校验错误TypeError: The input value must be int. but got 'NoneType.](Llama推理报参数校验错误TypeError-The-input-value-must-be-int-but-got-NoneType.md)**  

-   **[MindSpore模型报错Reason: Memory resources are exhausted.](MindSpore模型报错Reason-Memory-resources-are-exhausted.md)**  

-   **[MindSpore2.2.10 ge图模式报错: Current execute mode is KernelByKernel, the processes must be launched with OpenMPI or ...](MindSpore2-2-10-ge图模式报错-Current-execute-mode-is-KernelByKernel-the-processes-must-be-launched-with-O.md)**  

-   **[baichuan2-13b算子溢出 loss跑飞问题和定位](baichuan2-13b算子溢出-loss跑飞问题和定位.md)**  

-   **[MindSpore训练异常中止：Try to send request before Open\(\)、Try to get response before Open\(\)、Response is empty](MindSpore训练异常中止-Try-to-send-request-before-Open()-Try-to-get-response-before-Open()-Response-is-empt.md)**  

-   **[Ascend 910训练脚本刚运行就报错：RuntimeError: Initialize GE failed!](Ascend-910训练脚本刚运行就报错-RuntimeError-Initialize-GE-failed.md)**  

-   **[昇腾910上算子溢出问题分析](昇腾910上算子溢出问题分析.md)**  

-   **[使用ops.nonzero算子报错TypeError](使用ops-nonzero算子报错TypeError.md)**  

-   **[训练过程中评测超时导致训练过程发生中断](训练过程中评测超时导致训练过程发生中断.md)**  

-   **[昇腾910上CodeLlama推理报错get fail deviceLogicId\[0\]](昇腾910上CodeLlama推理报错get-fail-deviceLogicId-0.md)**  

-   **[昇腾910上CodeLlama导出mindir模型报错rankTablePath is invalid](昇腾910上CodeLlama导出mindir模型报错rankTablePath-is-invalid.md)**  

-   **[权重文件被异常修改导致加载权重提示Failed to read the checkpoint file](权重文件被异常修改导致加载权重提示Failed-to-read-the-checkpoint-file.md)**  

-   **[Mindformers模型启动时因为host侧OOM导致任务被kill](Mindformers模型启动时因为host侧OOM导致任务被kill.md)**  

-   **[昇腾910FlashAttention适配alibi问题](昇腾910FlashAttention适配alibi问题.md)**  

-   **[llama3.1-8b的lora微调，不开启权重转换会导致维度不匹配，开启了之后会报错找不到rank1的ckpt，但是strategy目录里面是全的](llama3-1-8b的lora微调-不开启权重转换会导致维度不匹配-开启了之后会报错找不到rank1的ckpt-但是strategy目录里面是全的.md)**  

-   **[Mindspore+MIndformer训练plog报错halMemAlloc failed，drvRetCode=6](Mindspore+MIndformer训练plog报错halMemAlloc-failed-drvRetCode-6.md)**  

-   **[MindSpore的离线权重转换接口说明及转换过程](MindSpore的离线权重转换接口说明及转换过程.md)**  

-   **[MindSpore的ckpt格式完整权重和分布式权重互转](MindSpore的ckpt格式完整权重和分布式权重互转.md)**  

-   **[MindSpore+MindFormer-r.1.2.0微调qwen1.5 报错](MindSpore+MindFormer-r-1-2-0微调qwen1-5-报错.md)**  

-   **[Mindformer训练plog中算子GatherV2\_xxx\_high\_precision\_xx报错](Mindformer训练plog中算子GatherV2_xxx_high_precision_xx报错.md)**  

-   **[mindformers进行Lora微调后的权重合并](mindformers进行Lora微调后的权重合并.md)**  

-   **[pangu-100b 2k集群线性度问题定位](pangu-100b-2k集群线性度问题定位.md)**  

-   **[Mixtral 8\*7B 大模型精度问题总结](Mixtral-8-7B-大模型精度问题总结.md)**  

-   **[大模型内存占用调优](大模型内存占用调优.md)**  

-   **[大模型网络算法参数和输出对比](大模型网络算法参数和输出对比.md)**  

-   **[使用jit编译加速时编译流程中的常见if控制流问题](使用jit编译加速时编译流程中的常见if控制流问题.md)**  

-   **[jit编译加速功能开启时，如何避免多次重新编译](jit编译加速功能开启时-如何避免多次重新编译.md)**  

-   **[编译时报错ValueError: Please set a unique name for the parameter.](编译时报错ValueError-Please-set-a-unique-name-for-the-parameter.md)**  

-   **[大模型动态图训练内存优化](大模型动态图训练内存优化.md)**  

-   **[大模型精度收敛分析和调优](大模型精度收敛分析和调优.md)**  

-   **[Dump工具应用—算子执行报错，输入数据值越界](Dump工具应用-算子执行报错-输入数据值越界.md)**  

-   **[Dump工具应用—网络训练溢出](Dump工具应用-网络训练溢出.md)**  

-   **[模型训练长稳性能抖动或劣化问题经验总结](模型训练长稳性能抖动或劣化问题经验总结.md)**  

-   **[msprobe工具应用–网络训练溢出](msprobe工具应用-网络训练溢出.md)**  

-   **[msprobe精度定位工具常见问题整理](msprobe精度定位工具常见问题整理.md)**  

-   **[模型编译的性能优化总结](模型编译的性能优化总结.md)**  

-   **[大模型动态图训练性能调优指南](大模型动态图训练性能调优指南.md)**  

-   **[大模型迭代拖尾和其他性能优化](大模型迭代拖尾和其他性能优化.md)**  

-   **[大模型前反向计算的性能优化](大模型前反向计算的性能优化.md)**  

-   **[大模型迭代间隙的性能优化](大模型迭代间隙的性能优化.md)**  

