1 Error description
1.1 System Environment
Hardware Environment(Ascend/GPU/CPU): CPU
– MindSpore version (source or binary): 1.2.0
– Python version (eg, Python 3.7.5): 3.7.5
– OS platform and distribution (eg, Linux Ubuntu 16.04): Ubuntu 4.15.0-74-generic
– GCC/Compiler version (if compiled from source):
1.2 Basic information
This case runs the linear function fitting example on the official website, and mindspore has been successfully installed before.
1.2.2 Error reporting
Error message: RuntimeError: Thread ID 140706176251712 Unexpected error. GeneratorDataset’s num_workers=8, this value is not within the required range of [1, cpu_thread_cnt=2].
Line of code : 639
File : /home/jenkins/agent-working-dir /workspace/Compile_CPU_X86_Ubuntu/mindspore/mindspore/ccsrc/minddata/dataset/engine/ir/datasetops/dataset_node.cc
2 Reason analysis
The number of CPU cores when the user is running is less than the number of cores used by default when the dataset module generates data. Mindspore does not perform adaptive configuration for the number of CPU cores in the hardware in 1.2.0. It is required when the configuration of the PC is not high. Manually configure the number of CPU cores.
1. Add code to manually configure the number of CPU cores:
2. Use a higher version of mindspore, the current mindspore-1.6.0 will be adaptively configured according to the number of CPU cores in the hardware to avoid the occurrence of CPU cores If the number is too low, an error will be reported.
1. You can locate the problem according to the prompt of the error message. In this case, it is a problem of the number of CPU cores. You can search for the method of setting the number of CPU cores in the official website tutorial and the open source MindSpore documentation.
2. At present, MindSpore provides an automatic data tuning tool – Dataset AutoTune, which is used to automatically adjust the parallelism of the data processing pipeline according to the environment resources during the training process. During this process, the CPU cores in the hardware will be automatically detected. The number of adaptive configuration.
3. The config module in MindSpore can set or obtain the global configuration parameters of data processing.
- How to Solve “Error db.num is null” when starting Nacos
- [Solved] MindSpore Error: Data type conversion of ‘Parameter’ is not supporte
- [Solved] MindSpore Error: task_fail_info or current_graph_ is nullptr
- Error occurred when finalizing generatordataset iterator [How to Solve]
- [Solved] MindSpore Error: “ValueError：invalid literal for int()with base10’the’
- [Solved] MindSpore Error: “TypeError: parse() missing 1 required positional.”
- [Solved] MindSpore Error: “RuntimeError: Invalid data, Page size.”
- [Solved] MindSpore Error: “RuntimeError: Unable to data from Generator..”
- [Solved] MindSpore Error: Should not use Python in runtime
- [Solved] MindSpore Error: ValueError: Minimum inputs size 0 does not match…
- [Solved] MindSpore Error: `half_pixel_centers`=True only support in Ascend
- [Solved] MindSpore Network custom reverse error: TypeError: The params of function ‘bprop’ of
- [Solved] MindSpore Error: ValueError: `padding_idx` in `Embedding` out of range
- [Solved] MindSpore Error: TypeError: For ‘TopK’, the type of ‘x’ should be…
- [Solved] MindSpore Error: “RuntimeError: Unexpected error. Inconsistent batch..
- [Solved] MindSpore Error: ValueError: For ‘AvgPool’ every dimension of the output shape must be greater than zero
- [Solved] MindSpore Error: Select GPU kernel op * fail! Incompatible data type
- [Solved] MindSpore Error: For ‘MirrorPad‘, paddings must be a Tensor with *
- [Solved] MindSpore Error: StridedSlice operator does not support input of uint8 data type on Ascend hardware