# 模型构建与训练报错案例

-   **[报错RuntimeError:Exceed function call depth limit 1000](报错RuntimeError-Exceed-function-call-depth-limit-1000.md)**  

-   **[报错:AttributeError: Tensor has no attribute](报错-AttributeError-Tensor-has-no-attribute.md)**  

-   **[报错AttributeError:NoneType has no attribute...](报错AttributeError-NoneType-has-no-attribute.md)**  

-   **[报错:the dimension of logits must be equal to 2](报错-the-dimension-of-logits-must-be-equal-to-2.md)**  

-   **[报错ValueError:For 'Pad', all elements of paddings must be \>= 0.](报错ValueError-For-Pad-all-elements-of-paddings-must-be-0.md)**  

-   **[报错ValueError:For xx,the x shape:xx must be equal to xxx](报错ValueError-For-xx-the-x-shape-xx-must-be-equal-to-xxx.md)**  

-   **[报类型错误TypeError: For 'Tensor', the type of \`input\_data\` should be one of ...](报类型错误TypeError-For-Tensor-the-type-of-input_data-should-be-one-of.md)**  

-   **[报错 ScatterNdUpdate这个算子在Ascend硬件上不支持input0是int32的数据类型](报错-ScatterNdUpdate这个算子在Ascend硬件上不支持input0是int32的数据类型.md)**  

-   **[报错TypeError: ScalarAdd不支持bool类型，官网缺少说明](报错TypeError-ScalarAdd不支持bool类型-官网缺少说明.md)**  

-   **[报RuntimeError:ReduceSum算子不支持8维及以上的输入而报错](报RuntimeError-ReduceSum算子不支持8维及以上的输入而报错.md)**  

-   **[报类型错误:Unsupported parameter type for python primitive...](报类型错误-Unsupported-parameter-type-for-python-primitive.md)**  

-   **[报错RuntimeError: Primitive ScatterAdd's bprop not defined.](报错RuntimeError-Primitive-ScatterAdd-s-bprop-not-defined.md)**  

-   **[报运行时错误: For Conv2d,x shape的C\_in除以group应等于weight的C\_in](报运行时错误-For-Conv2d-x-shape的C_in除以group应等于weight的C_in.md)**  

-   **[报错：alueError: For 'Reshape', the shape of 'input\_x' is \[65209\], the value of 'input\_shape' value is \[16302, 4\].](报错-alueError-For-Reshape-the-shape-of-input_x-is-65209-the-value-of-input_shape-value-is-16302-4.md)**  

-   **[报错ValueError: For xxx,x和y的shape不支持 broadcast](报错ValueError-For-xxx-x和y的shape不支持-broadcast.md)**  

-   **[报错“ValueError: For MatMul, the input dimensions必须相等](报错-ValueError-For-MatMul-the-input-dimensions必须相等.md)**  

-   **[报错：Can not select a valid kernel info for \[Default/Pow-op0\] in AI CORE or AI CPU kernel info candidates list](报错-Can-not-select-a-valid-kernel-info-for-Default-Pow-op0-in-AI-CORE-or-AI-CPU-kernel-info-candidate.md)**  

-   **[报错：ValueError: \`x rank\` in \`NLLLoss\` should be int and must in \[1, 2\], but got \`4\` with type \`int](报错-ValueError-x-rank-in-NLLLoss-should-be-int-and-must-in-1-2-but-got-4-with-type-int.md)**  

-   **[报错：Select GPU kernel op\[BatchNorm\] fail! Incompatible data type!](报错-Select-GPU-kernel-op-BatchNorm-fail-Incompatible-data-type.md)**  

-   **[报错：ValueError: For 'MirrorPad', paddings must be a Tensor with type of int64, but got None.](报错-ValueError-For-MirrorPad-paddings-must-be-a-Tensor-with-type-of-int64-but-got-None.md)**  

-   **[报错：For primitive\[TensorSummary\], the v rank 必须大于等于0](报错-For-primitive-TensorSummary-the-v-rank-必须大于等于0.md)**  

-   **[报错：TypeError: For 'CellList', each cell should be subclass of Cell, but got NoneType.](报错-TypeError-For-CellList-each-cell-should-be-subclass-of-Cell-but-got-NoneType.md)**  

-   **[报错：task\_fail\_info or current\_graph\_ is nullptr](报错-task_fail_info-or-current_graph_-is-nullptr.md)**  

-   **[报错ValueError：\`padding\_idx\` in \`Embedding超出范围](报错ValueError-padding_idx-in-Embedding超出范围.md)**  

-   **[报错ValueError: \`seed2\` in \`StandardNormal\` should be int and must \>= 0](报错ValueError-seed2-in-StandardNormal-should-be-int-and-must-0.md)**  

-   **[报错 Ascend 环境下ReduceMean不支持8维及其以上的输入](报错-Ascend-环境下ReduceMean不支持8维及其以上的输入.md)**  

-   **[报错： Conv2D第三维输出数据类型必须是正整数或者SHP\_ANY](报错-Conv2D第三维输出数据类型必须是正整数或者SHP_ANY.md)**  

-   **[报错：For 'TopK', the type of 'x' should be one of Tensor\[Int32\]](报错-For-TopK-the-type-of-x-should-be-one-of-Tensor-Int32.md)**  

-   **[报错Minimum inputs size 0 does not match the requires signature size 2](报错Minimum-inputs-size-0-does-not-match-the-requires-signature-size-2.md)**  

-   **[报错ValueError: Currently \`half\_pixel\_centers\`=True only support in Ascend device\_target, but got CPU](报错ValueError-Currently-half_pixel_centers-True-only-support-in-Ascend-device_target-but-got-CPU.md)**  

-   **[报错ValueError: For AvgPool输出形状的每一维都要大于零](报错ValueError-For-AvgPool输出形状的每一维都要大于零.md)**  

-   **[报错TypeError: The function construct needs 0 positional argument and 0 default argument, but provided 1](报错TypeError-The-function-construct-needs-0-positional-argument-and-0-default-argument-but-provided-1.md)**  

-   **[报错Operator\[ \] input\( \) output\( \) is not support](报错Operator-input(-)-output(-)-is-not-support.md)**  

-   **[报错 sth should be initialized as a Parameter type in ...](报错-sth-should-be-initialized-as-a-Parameter-type-in.md)**  

-   **[报错：The 'add' operation does not support the type \[kMetaTypeNone, Int64\].](报错-The-add-operation-does-not-support-the-type-kMetaTypeNone-Int64.md)**  

-   **[报错：When eval 'Tensor\(self.data, mindspore.float32\)' by using Fallback feature, an error occurred: data.](报错-When-eval-Tensor(self-data-mindspore-float32)-by-using-Fallback-feature-an-error-occurred-data.md)**  

-   **[报错RuntimeError: Net parameters weight shape \(\(751, 512\)\) is different from parameter\_dict's \(\(31789, 512\)\)](报错RuntimeError-Net-parameters-weight-shape-((751-512))-is-different-from-parameter_dict-s-((31789-51.md)**  

-   **[GPU设备提示:The device with Cuda compute capability 5.2 is lower than the minimum required capability 5.3](GPU设备提示-The-device-with-Cuda-compute-capability-5-2-is-lower-than-the-minimum-required-capability-5.md)**  

-   **[GPU环境运行MindSpore报错：设卡失败 SetDevice failed](GPU环境运行MindSpore报错-设卡失败-SetDevice-failed.md)**  

-   **[Ascend环境使用MindSpore报出如下错误: Total stream number xxx exceeds the limit of 1024, secrch details information in mindspore's FAQ.](Ascend环境使用MindSpore报出如下错误-Total-stream-number-xxx-exceeds-the-limit-of-1024-secrch-details-informati.md)**  

-   **[LoadTask Distribute Task Failed 报错解决](LoadTask-Distribute-Task-Failed-报错解决.md)**  

-   **[GPU训练提示分配流失败\[cudaStreamCreate failed\]](GPU训练提示分配流失败-cudaStreamCreate-failed.md)**  

-   **[GPU训练过程中报错：The memory alloc size is 0](GPU训练过程中报错-The-memory-alloc-size-is-0.md)**  

-   **[报错：ValueError: For 'load\_checkpoint', the checkpoint](报错-ValueError-For-load_checkpoint-the-checkpoint.md)**  

-   **[加载checkpoint的时候报warning日志xxx parameters in the 'net' are not loaded, because they are not in the 'parameter\_dict'](加载checkpoint的时候报warning日志xxx-parameters-in-the-net-are-not-loaded-because-they-are-not-in-the-parame.md)**  

-   **[报错：ValueError: For 'context.set\_context', package type xxx support 'device\_target' type xxx, but got xxx.](报错-ValueError-For-context-set_context-package-type-xxx-support-device_target-type-xxx-but-got-xxx.md)**  

-   **[PyNative模式下The pointer\[top\_cell\_\] is null错误](PyNative模式下The-pointer-top_cell_-is-null错误.md)**  

-   **[报错RuntimeError:alloc device memory failed, free memory size is less than half of total memory size.](报错RuntimeError-alloc-device-memory-failed-free-memory-size-is-less-than-half-of-total-memory-size.md)**  

-   **[报错ValueError: Please input the correct checkpoint](报错ValueError-Please-input-the-correct-checkpoint.md)**  

-   **[求导传入sens值时infer报错ValueError: For 'MatMul', the input dimensions must be equal](求导传入sens值时infer报错ValueError-For-MatMul-the-input-dimensions-must-be-equal.md)**  

-   **[没有ckpt文件导致模型加载执行报错：please check whether the 'ckpt\_file\_name' is correct](没有ckpt文件导致模型加载执行报错-please-check-whether-the-ckpt_file_name-is-correct.md)**  

-   **[Tensor张量shape不匹配导致执行报错：ValueError: For 'Sub', x.shape and y.shape are supposed to broadcast](Tensor张量shape不匹配导致执行报错-ValueError-For-Sub-x-shape-and-y-shape-are-supposed-to-broadcast.md)**  

-   **[自定义loss没有继承nn.Cell导致执行报错：ParseStatement\] Unsupported statement 'Try'.](自定义loss没有继承nn-Cell导致执行报错-ParseStatement-Unsupported-statement-Try.md)**  

-   **[参数类型错误导致优化器执行报错：TypeError: For 'Optimizer', the argument parameters must be Iterable type](参数类型错误导致优化器执行报错-TypeError-For-Optimizer-the-argument-parameters-must-be-Iterable-type.md)**  

-   **[形参与实参的不对应导致ops.GradOperation执行报错：The parameters number of the function is 2, but the number of provided arguments is 1.](形参与实参的不对应导致ops-GradOperation执行报错-The-parameters-number-of-the-function-is-2-but-the-number-of-provid.md)**  

-   **[return回来的参数承接问题导致执行报错：AttributeError: 'tuple' object has no attribute 'asnumpy'](return回来的参数承接问题导致执行报错-AttributeError-tuple-object-has-no-attribute-asnumpy.md)**  

-   **[维度数错误引起模型输入错误：For primitive\[Conv2D\], the x shape size must be equal to 4, but got 3.](维度数错误引起模型输入错误-For-primitive-Conv2D-the-x-shape-size-must-be-equal-to-4-but-got-3.md)**  

-   **[报错：The value parameter,it's name 'xxxx' already exsts. please set a unique name for the parameter .](报错-The-value-parameter-it-s-name-xxxx-already-exsts-please-set-a-unique-name-for-the-parameter.md)**  

-   **[construct方法名称错误引起损失函数执行报错:The 'sub' operation does not support the type \[Tensor\[Float32\], None\].](construct方法名称错误引起损失函数执行报错-The-sub-operation-does-not-support-the-type-Tensor-Float32-None.md)**  

-   **[RuntimeError:The 'sub' operation does not support the type \[Tensor\[Float32\], None\].](RuntimeError-The-sub-operation-does-not-support-the-type-Tensor-Float32-None.md)**  

-   **[注释不当报错：There are incorrect indentations in definition or comment of function: 'Net.construct'.](注释不当报错-There-are-incorrect-indentations-in-definition-or-comment-of-function-Net-construct.md)**  

-   **[静态图执行卡死问题：For MakeTuple, the inputs should not be empty..node:xxxxxxxxxxxx](静态图执行卡死问题-For-MakeTuple-the-inputs-should-not-be-empty-node-xxxxxxxxxxxx.md)**  

-   **[报错: module\(\) takes at most 2 arguments \(3 given\)](报错-module()-takes-at-most-2-arguments-(3-given).md)**  

-   **[报错ERROR：For 'ScatterNdAdd', the 3-th value of 'indices'\[7\] is out of range\[4\]scatterNdAdd.](报错ERROR-For-ScatterNdAdd-the-3-th-value-of-indices-7-is-out-of-range-4-scatterNdAdd.md)**  

-   **[使用ops.nonzero算子报错TypeError: Type Join Failed: dtype1 = Float32, dtype2 = Int64.](使用ops-nonzero算子报错TypeError-Type-Join-Failed-dtype1-Float32-dtype2-Int64.md)**  

-   **[调用MindSpore内部函数时的语法错误TypeError: 'module' object is not callable](调用MindSpore内部函数时的语法错误TypeError-module-object-is-not-callable.md)**  

-   **[MindSpore在静态图模式下使用try语法报错RuntimeError: Unsupported statement 'Try'.](MindSpore在静态图模式下使用try语法报错RuntimeError-Unsupported-statement-Try.md)**  

-   **[MindSpore报错: ValueError: For 'MatMul', the input dimensions must be equal, but got 'x1\_col': 817920 and 'x2\_row': 272640.](MindSpore报错-ValueError-For-MatMul-the-input-dimensions-must-be-equal-but-got-x1_col-817920-and-x2_ro.md)**  

-   **[MindSpore 报错提示 DropoutGrad 的bprop反向未定义："Illegal primitive: Primitive DropoutGrad’s bprop not defined."](MindSpore-报错提示-DropoutGrad-的bprop反向未定义-Illegal-primitive-Primitive-DropoutGrad-s-bprop-not-defined.md)**  

-   **[MindSpore报错The graph generated form MindIR is not support to execute in the PynativeMode,please convert to the GraphMode](MindSpore报错The-graph-generated-form-MindIR-is-not-support-to-execute-in-the-PynativeMode-please-conv.md)**  

-   **[MindSpore报错RuntimeError: For ’Optimizer’, the argument group params must not be empty.](MindSpore报错RuntimeError-For-Optimizer-the-argument-group-params-must-not-be-empty.md)**  

-   **[使用mindspore.ops.MaxPool3D算子设置为ceil\_mode=True时，在MindSpore1.8.1和1.9.0版本中计算结果不一致](使用mindspore-ops-MaxPool3D算子设置为ceil_mode-True时-在MindSpore1-8-1和1-9-0版本中计算结果不一致.md)**  

-   **[Construct内报错和定位解决](Construct内报错和定位解决.md)**  

-   **[gather算子报错：TypeError以及定位解决](gather算子报错-TypeError以及定位解决.md)**  

-   **[报错：module\(\) takes at most 2 arguments \(3 given\)](报错-module()-takes-at-most-2-arguments-(3-given)-1.md)**  

-   **[注释不当报错：There are incorrect indentations in definition or comment of function: 'Net.construct'.](注释不当报错-There-are-incorrect-indentations-in-definition-or-comment-of-function-Net-construct-2.md)**  

-   **[MindSpore报错untimeError: Exceed function call depth limit 1000.](MindSpore报错untimeError-Exceed-function-call-depth-limit-1000.md)**  

-   **[MindSpore图编译报错TypeError: ‘int’ object is not iterable.](MindSpore图编译报错TypeError-int-object-is-not-iterable.md)**  

-   **[MindSpore报错RuntimeError: The 'getitem' operation does not support the type \[Func, Int64\].](MindSpore报错RuntimeError-The-getitem-operation-does-not-support-the-type-Func-Int64.md)**  

-   **[MindSpore cpu版本源码编译失败](MindSpore-cpu版本源码编译失败.md)**  

-   **[MindSpore图编译报错TypeError: ‘int’ object is not iterable.](MindSpore图编译报错TypeError-int-object-is-not-iterable-3.md)**  

-   **[MindSpore的Cell.insert\_child\_to\_cell 添加层会出现参数名重复](MindSpore的Cell-insert_child_to_cell-添加层会出现参数名重复.md)**  

-   **[mindspore.numpy.unique\(\) 不支持 0 shape tensor](mindspore-numpy-unique()-不支持-0-shape-tensor.md)**  

-   **[MindSpore直接将Tensor从布尔值转换为浮点数导致错误Error: IndexError: index 1 is out of bounds for dimension with size 1](MindSpore直接将Tensor从布尔值转换为浮点数导致错误Error-IndexError-index-1-is-out-of-bounds-for-dimension-with-size-1.md)**  

-   **[MindSpore中的mindspore.numpy.bincount 大数值情况下报ValueError定位与解决](MindSpore中的mindspore-numpy-bincount-大数值情况下报ValueError定位与解决.md)**  

-   **[使用mindspore.numpy.broadcast\_to 算子报错及解决](使用mindspore-numpy-broadcast_to-算子报错及解决.md)**  

-   **[使用MindSpore中的SoftMax\(\)算子计算单一数据出错Run op inputs type is invalid!](使用MindSpore中的SoftMax()算子计算单一数据出错Run-op-inputs-type-is-invalid.md)**  

-   **[CSRTensor 矩阵乘法计算出错RuntimeError:CUDA Error: cudaMemcpy failed.|Error Number: 700 an illegal memory access was encountered](CSRTensor-矩阵乘法计算出错RuntimeError-CUDA-Error-cudaMemcpy-failed-Error-Number-700-an-illegal-memory-acces.md)**  

-   **[Cell对象序列化失败-使用pickle.dumps保存到本地后重新加载失败](Cell对象序列化失败-使用pickle-dumps保存到本地后重新加载失败.md)**  

-   **[TopK算子返回的全零的Tensor的解决](TopK算子返回的全零的Tensor的解决.md)**  

-   **[在NPU上的切片操作x=x\[:,::-1,:,:\]不生效的分析解决](在NPU上的切片操作x-x--1-不生效的分析解决.md)**  

-   **[张量运算失败报错RuntimeError:Malloc for kernel output failed, Memory isn’t enough](张量运算失败报错RuntimeError-Malloc-for-kernel-output-failed-Memory-isn-t-enough.md)**  

-   **[MindSpore Dump功能使用经验](MindSpore-Dump功能使用经验.md)**  

-   **[使用SymbolTree.get\_network处理conv2d算子时报错NameError:name "Cell" is not defined](使用SymbolTree-get_network处理conv2d算子时报错NameError-name-Cell-is-not-defined.md)**  

-   **[使用mindspore中Conv2dTranspose的outputpadding时，设置has\_bias=True时失效](使用mindspore中Conv2dTranspose的outputpadding时-设置has_bias-True时失效.md)**  

-   **[使用mindspore.ops.pad算子报错位置有误](使用mindspore-ops-pad算子报错位置有误.md)**  

-   **[使用mindspore.numpy.sqrt 计算结果不正确](使用mindspore-numpy-sqrt-计算结果不正确.md)**  

-   **[函数变换获得梯度计算函数时报错AttributeError: module 'mindspore' has no attribute 'value\_and\_grad'](函数变换获得梯度计算函数时报错AttributeError-module-mindspore-has-no-attribute-value_and_grad.md)**  

-   **[自定义ops.Custom报错TypeError: function output\_tensor expects two inputs, but get 1](自定义ops-Custom报错TypeError-function-output_tensor-expects-two-inputs-but-get-1.md)**  

-   **[报错ValueError: Input buffer\_size is not within the required interval of \[2, 2147483647\].](报错ValueError-Input-buffer_size-is-not-within-the-required-interval-of-2-2147483647.md)**  

-   **[使用MindSpore的LayerNorm报错ValueError: For 'LayerNorm', gamma or beta shape must match input shape.](使用MindSpore的LayerNorm报错ValueError-For-LayerNorm-gamma-or-beta-shape-must-match-input-shape.md)**  

-   **[使用nn.pad报错RuntimeError:For 'Pad', output buffer memset failed](使用nn-pad报错RuntimeError-For-Pad-output-buffer-memset-failed.md)**  

-   **[使用shard接口遇到空指针的报错RuntineError: The pointer \[comm\_lib\_instance\_\] is null.](使用shard接口遇到空指针的报错RuntineError-The-pointer-comm_lib_instance_-is-null.md)**  

-   **[AttributeError: Tensor\[Int64\] object has no attribute: asnumpy](AttributeError-Tensor-Int64-object-has-no-attribute-asnumpy.md)**  

-   **[使用计算得到的Tensor进行slicing赋值时报错RuntimeError: The int64\_t value\(-1\) is less than 0.](使用计算得到的Tensor进行slicing赋值时报错RuntimeError-The-int64_t-value(-1)-is-less-than-0.md)**  

-   **[总loss由多个loss组成时的组合](总loss由多个loss组成时的组合.md)**  

-   **[使用classmindspore\_rl.policy.EpsilonGreedyPolicy发现维度不匹配及解决](使用classmindspore_rl-policy-EpsilonGreedyPolicy发现维度不匹配及解决.md)**  

-   **[自定义Callback重载函数调用顺序错误及解决](自定义Callback重载函数调用顺序错误及解决.md)**  

-   **[MindSpore报错：all types should be same, but got \[mindspore.tensor\[float64\], mindspore.tensor\[float32\]](MindSpore报错-all-types-should-be-same-but-got-mindspore-tensor-float64-mindspore-tensor-float32.md)**  

-   **[MindSpore在GRAPH\_MODE下初始化，报错提示当前的执行模式是禁用了任务下沉（TASK\_SINK）](MindSpore在GRAPH_MODE下初始化-报错提示当前的执行模式是禁用了任务下沉（TASK_SINK）.md)**  

-   **[使用vision.ToPIL在一定情况下无效](使用vision-ToPIL在一定情况下无效.md)**  

-   **[MindSpore不能像torch的param.grad直接获取梯度问题](MindSpore不能像torch的param-grad直接获取梯度问题.md)**  

-   **[MindSpore跑resnet50报错For 'MatMul' the input dimensions must be equal, but got 'x1\_col': 32768 and 'x2\_row': 2048.方法一](MindSpore跑resnet50报错For-MatMul-the-input-dimensions-must-be-equal-but-got-x1_col-32768-and-x2_row-20.md)**  

-   **[新节点24使用piecewise\_constant\_lr造成梯度异常](新节点24使用piecewise_constant_lr造成梯度异常.md)**  

-   **[MindSpore报错AttributeError: module 'mindspore.ops' has no attribute 'mm'](MindSpore报错AttributeError-module-mindspore-ops-has-no-attribute-mm.md)**  

-   **[MindSpore报错'Resize' from mindspore.dataset.vision.c\_transforms is deprecated](MindSpore报错-Resize-from-mindspore-dataset-vision-c_transforms-is-deprecated.md)**  

-   **[MindSpore中的text\_format.Merge和text\_format.Parse的区别](MindSpore中的text_format-Merge和text_format-Parse的区别.md)**  

-   **[MindSpore如何将add\_node函数添加节点信息到self.node中](MindSpore如何将add_node函数添加节点信息到self-node中.md)**  

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-   **[MindSpore报错：The supported input and output data types for the current operator are: node is Default/BitwiseAnd](MindSpore报错-The-supported-input-and-output-data-types-for-the-current-operator-are-node-is-Default-B.md)**  

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-   **[MindSpore报错Kernel launch failed, msg: Acl compile and execute failed, op\_type\_:AvgPool3D](MindSpore报错Kernel-launch-failed-msg-Acl-compile-and-execute-failed-op_type_-AvgPool3D.md)**  

-   **[MindSpore报错“ValueError: For 'MatMul', the input dimensions必须相等](MindSpore报错-ValueError-For-MatMul-the-input-dimensions必须相等.md)**  

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-   **[Asttokens版本稳定性性的问题](Asttokens版本稳定性性的问题.md)**  

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-   **[MindSpore PyNative模式下The pointer\[top\_cell\_\] is null错误](MindSpore-PyNative模式下The-pointer-top_cell_-is-null错误.md)**  

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-   **[MindSpore 图算融合 GPU调试](MindSpore-图算融合-GPU调试.md)**  

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-   **[MindSpore模型权重功能无法保存更新后的权重](MindSpore模型权重功能无法保存更新后的权重.md)**  

-   **[模型微调报错RuntimeError: Preprocess failed before run graph 1.](模型微调报错RuntimeError-Preprocess-failed-before-run-graph-1.md)**  

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-   **[使用dataset.create\_dict\_iterator\(\)后，计算前向网络报错：untimeError: Illegal AnfNode for evaluating, node: @Batch](使用dataset-create_dict_iterator()后-计算前向网络报错-untimeError-Illegal-AnfNode-for-evaluating-node-Batch.md)**  

-   **[使用MindSpore静态图速度慢的问题](使用MindSpore静态图速度慢的问题.md)**  

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-   **[运行MindCV案例报错Malloc for kernel input failed, Memory isn't enough, node:Default/ReduceMean-op0](运行MindCV案例报错Malloc-for-kernel-input-failed-Memory-isn-t-enough-node-Default-ReduceMean-op0.md)**  

-   **[使用mindspore.ops.Bernoulli在昇腾设备上训练报错RuntimeError: Sync stream failed:Ascend\_0](使用mindspore-ops-Bernoulli在昇腾设备上训练报错RuntimeError-Sync-stream-failed-Ascend_0.md)**  

-   **[使用mint.arctan2在图模式下报错RuntimeError: Compile graph kernel\_graph0 failed.](使用mint-arctan2在图模式下报错RuntimeError-Compile-graph-kernel_graph0-failed-6.md)**  

-   **[MindCV训练报错ValueError: For 'context.set\_context', the keyword argument jit\_config is notrecognized!](MindCV训练报错ValueError-For-context-set_context-the-keyword-argument-jit_config-is-notrecognized.md)**  

-   **[GRAPH\_MODE下运行ms\_tensor = mint.ones\_like\(input\_tensor, dtype=dtype\)报错The pointer\[device\_address\] is null.](GRAPH_MODE下运行ms_tensor-mint-ones_like(input_tensor-dtype-dtype)报错The-pointer-device_address-is-null.md)**  

-   **[使用mint.index\_select 在图模式下求梯度报错AssertionError](使用mint-index_select-在图模式下求梯度报错AssertionError.md)**  

-   **[使用mindspore.mint.where\(\)报错The supported input and output data types for the current operator are: node is Default/Bitwis](使用mindspore-mint-where()报错The-supported-input-and-output-data-types-for-the-current-operator-are-nod.md)**  

-   **[使用mindspore.mint.gather函数计算出的结果错误](使用mindspore-mint-gather函数计算出的结果错误.md)**  

-   **[使用Modelarts训练yolov5出现报错TypeError: modelarts\_pre\_process\(\) missing 1 required positional argument:’args’](使用Modelarts训练yolov5出现报错TypeError-modelarts_pre_process()-missing-1-required-positional-argument-args.md)**  

-   **[使用mint.masked\_select在图模式下报错Parse Lambda Function Fail. Node type must be Lambda, but got Call.](使用mint-masked_select在图模式下报错Parse-Lambda-Function-Fail-Node-type-must-be-Lambda-but-got-Call.md)**  

-   **[导入TextClassifier接口报错ModuleNotFoundError: No module named ‘mindnlp.models’](导入TextClassifier接口报错ModuleNotFoundError-No-module-named-mindnlp-models.md)**  

-   **[模型调用Pad接口填充报错For ‘Pad’, output buffer memset failed.](模型调用Pad接口填充报错For-Pad-output-buffer-memset-failed.md)**  

-   **[模型初始化和加载时间过长解决](模型初始化和加载时间过长解决.md)**  

-   **[静态式下报错TypeError: pynative模式不支持重新计算](静态式下报错TypeError-pynative模式不支持重新计算.md)**  

