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modelbox-ai / modelbox

A high performance, high expansion, easy to use framework for AI application. 为AI应用的开发者提供一套统一的高性能、易用的编程框架，快速基于AI全栈服务、开发跨端边云的AI行业应用，支持GPU，NPU加速。
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Mnist_mind实例运行失败 #357

Open yubo105139 opened 1 year ago

yubo105139 commented 1 year ago

运行环境信息 | System information (请提供足够详细的信息 | Please provide as much relevant information as possible)

使用dockers modelbox/modelbox-develop-mindspore_1.9.0-cann_6.0.1-d310p-ubuntu-x86_64:latest

npu -info image

描述问题 | Describe the current behavior: 运行Mnist_mind实例，失败 错误信息：request invalid, job config is invalid, Not found, build graph failed, please check graph config. -> create flowunit 'mnist_infer' failed. -> current environment does not support the inference type: 'mindspore:cpu' 同时新建单元后面功能无法圈选 b60234120c29493007fa462a0ea39c9

期望的行为 | Describe the expected behavior:

重现步骤描述 | Standalone code to reproduce the issue: 使用acl_inference 的om模型也无法运行

提供具体重现问题的步骤，如果可能，提供相关的截图信息，日志信息。
Provide a reproducible test case that is the bare minimum necessary to replicate the problem.

日志信息 | Logs

收集ModelBox的运行日志，路径为/var/log/modelbox Please Provide modleobx logs, log path /var/log/modelbox

其他信息 | Other Info.

pymumu commented 1 year ago

你选了cpu的推理，要选ascend的

yubo105139 commented 1 year ago

create flowunit 'mnist_infer' failed. -> current environment does not support the inference type: 'mindspore:ascend'

yubo105139 commented 1 year ago

我这边没有任何作用

pymumu commented 1 year ago

modelbox-tool driver -info -details 看看输出，应该是没要找到mindspore的库

yubo105139 commented 1 year ago

Device Information : -------------------------------- : name: 0 type: ascend version:
description: This is a ascend device description.

name: 1 type: ascend version:
description: This is a ascend device description.

name: 2 type: ascend version:
description: This is a ascend device description.

name: 3 type: ascend version:
description: This is a ascend device description.

name: 4 type: ascend version:
description: This is a ascend device description.

name: 5 type: ascend version:
description: This is a ascend device description.

name: 6 type: ascend version:
description: This is a ascend device description.

name: 7 type: ascend version:
description: This is a ascend device description.

name: 0 type: CPU version:
description: Host cpu device.

Driver Information : -------------------------------- : driver name: device-ascend device type: ascend version:
class: DRIVER-DEVICE description: A ascend device driver

driver name: device-cpu device type: cpu version:
class: DRIVER-DEVICE description: A cpu device driver

driver name: graphconf-graphvize device type: graph version: 1.0.0 class: DRIVER-GRAPHCONF description: graph config parse graphviz

driver name: acl_inference device type: ascend version:
class: DRIVER-INFERENCE description: A ascend inference flowunit

driver name: crop device type: ascend version: 1.0.0 class: DRIVER-FLOWUNIT description: @Brief: A crop flowunit on ascend device. @Port parameter: The input port 'in_image' and the output port 'out_image' buffer type are image. The image type buffer contain the following meta fields: Field Name: width, Type: int32_t Field Name: height, Type: int32_t Field Name: width_stride, Type: int32_t Field Name: height_stride, Type: int32_t Field Name: channel, Type: int32_t Field Name: pix_fmt, Type: string Field Name: layout, Type: int32_t Field Name: shape, Type: vector Field Name: type, Type: ModelBoxDataType::MODELBOX_UINT8 The other input port 'in_region' buffer type is rectangle, the memory arrangement is [x,y,w,h]. it contain the following meta fields: Field Name: type, Type: ModelBoxDataType::MODELBOX_UINT8 @Constraint: The field value range of this flowunit support: 'pix_fmt': [nv12], 'layout': [hwc]. One image can only be cropped with one rectangle and output one crop image.

driver name: padding device type: ascend version: 1.0.0 class: DRIVER-FLOWUNIT description: @Brief: A padding flowunit on ascend device @Port paramter: the input port buffer type and the output port buffer type are image. The image type buffer contain the following meta fields: Field Name: width, Type: int32_t Field Name: height, Type: int32_t Field Name: width_stride, Type: int32_t Field Name: height_stride, Type: int32_t Field Name: pix_fmt, Type: string Field Name: layout, Type: int32_t Field Name: shape, Type: vector Field Name: type, Type: ModelBoxDataType::MODELBOX_UINT8 @Constraint: the field value range of this flowunit support：'pix_fmt': [nv12], 'layout': [hwc].

driver name: resize device type: ascend version: 1.0.0 class: DRIVER-FLOWUNIT description: @Brief: A resize flowunit on ascend device. @Port parameter: The input port buffer type and the output port buffer type are image. The image type buffer contain the following meta fields: Field Name: width, Type: int32_t Field Name: height, Type: int32_t Field Name: width_stride, Type: int32_t Field Name: height_stride, Type: int32_t Field Name: channel, Type: int32_t Field Name: pix_fmt, Type: string Field Name: layout, Type: int32_t Field Name: shape, Type: vector Field Name: type, Type: ModelBoxDataType::MODELBOX_UINT8 @Constraint: The field value range of this flowunit support: 'pix_fmt': [nv12], 'layout': [hwc].

driver name: video_decoder device type: ascend version: 1.0.0 class: DRIVER-FLOWUNIT description: @Brief: A resize flowunit on cpu. @Port parameter: the input port buffer type is video_packet, the output port buffer type is video_frame. The video_packet buffer contain the following meta fields: Field Name: pts, Type: int64_t Field Name: dts, Type: int64_t Field Name: rate_num, Type: int32_t Field Name: rate_den, Type: int32_t Field Name: duration, Type: int64_t Field Name: time_base, Type: double Field Name: width, Type: int32_t Field Name: height, Type: int32_t The video_frame buffer contain the following meta fields: Field Name: index, Type: int64_t Field Name: rate_num, Type: int32_t Field Name: rate_den, Type: int32_t Field Name: duration, Type: int64_t Field Name: url, Type: string Field Name: timestamp, Type: int64_t Field Name: eos, Type: bool Field Name: width, Type: int32_t Field Name: height, Type: int32_t Field Name: width_stride, Type: int32_t Field Name: height_stride, Type: int32_t Field Name: channel, Type: int32_t Field Name: pix_fmt, Type: string Field Name: layout, Type: int32_t Field Name: shape, Type: vector Field Name: type, Type: ModelBoxDataType::MODELBOX_UINT8 @Constraint: the flowuint 'video_decoder' must be used pair with 'video_demuxer. the output buffer meta fields 'pix_fmt' is 'nv12', 'layout' is 'hcw'.

driver name: base64_decoder device type: cpu version: 1.0.0 class: DRIVER-FLOWUNIT description: @Brief: base64 decoder flowunit on cpu. @Port parameter: The input port buffer type is image file binary, the output port buffer type are image. The image type buffer contains the following meta fields: Field Name: width, Type: int32_t Field Name: height, Type: int32_t Field Name: width_stride, Type: int32_t Field Name: height_stride, Type: int32_t Field Name: channel, Type: int32_t Field Name: pix_fmt, Type: string Field Name: layout, Type: int32_t Field Name: shape, Type: vector Field Name: type, Type: ModelBoxDataType::MODELBOX_UINT8 @Constraint:

driver name: buff_meta_mapping device type: cpu version: 1.0.0 class: DRIVER-FLOWUNIT description: @Brief: Modify the input buffer meta field name and value according to custom rules. @Port parameter: The input port and the output buffer type are binary. @Constraint:

driver name: crop device type: cpu version: 1.0.0 class: DRIVER-FLOWUNIT description: @Brief: An OpenCV crop flowunit on cpu. @Port parameter: The input port 'in_image' and the output port 'out_image' buffer type are image. The image type buffer contain the following meta fields: Field Name: width, Type: int32_t Field Name: height, Type: int32_t Field Name: width_stride, Type: int32_t Field Name: height_stride, Type: int32_t Field Name: channel, Type: int32_t Field Name: pix_fmt, Type: string Field Name: layout, Type: int32_t Field Name: shape, Type: vector Field Name: type, Type: ModelBoxDataType::MODELBOX_UINT8 The other input port 'in_region' buffer type is rectangle, the memory arrangement is [x,y,w,h]. it contain the following meta fields: Field Name: type, Type: ModelBoxDataType::MODELBOX_UINT8 @Constraint: The field value range of this flowunit support: 'pix_fmt': [rgb_packed,bgr_packed], 'layout': [hwc]. One image can only be cropped with one rectangle and output one crop image.

driver name: data_source_generator device type: cpu version: 1.0.0 class: DRIVER-FLOWUNIT description: @Brief: The operator can generator test data source config for data_source_parser. @Port parameter: The output port buffer data indicate data source config. @Constraint: This flowunit is usually followed by 'data_source_parser'.

driver name: obs device type: cpu version:
class: DRIVER-SOURCE-PARSER description: An OBS data source parser plugin on CPU

driver name: restful device type: cpu version:
class: DRIVER-SOURCE-PARSER description: An restful data source parser plugin on CPU

driver name: url device type: cpu version:
class: DRIVER-SOURCE-PARSER description: A url data source parser plugin on CPU

driver name: vcn_restful device type: cpu version:
class: DRIVER-SOURCE-PARSER description: A VCN restful data source parser plugin on CPU

driver name: vis device type: cpu version:
class: DRIVER-SOURCE-PARSER description: An vis data source parser plugin on CPU

driver name: data_source_parser device type: cpu version: 1.0.0 class: DRIVER-FLOWUNIT description: @Brief: this flowunit can obtain the video stream address or download the video file to the local according to the input configuration data, and output the url. Currently supported types have obs, vcn, vis, resetful, url. @Port parameter: The input buffer data type is char , and contain the following meta fields: Field Name: source_type, Type: string the output buffer data type is char . @Constraint: the field value range of this flowunit support: 'source_type': [obs, vcn, vis, restful, url]. This flowunit is usually followed by 'video_demuxer'.

driver name: draw_bbox device type: cpu version: 1.0.0 class: DRIVER-FLOWUNIT description: @Brief: draw a rectangle area on the input image. @Port parameter: The input port 'in_image' and the output port 'out_image' buffer type are image. The image type buffer contain the following meta fields: Field Name: width, Type: int32_t Field Name: height, Type: int32_t Field Name: width_stride, Type: int32_t Field Name: height_stride, Type: int32_t Field Name: channel, Type: int32_t Field Name: pix_fmt, Type: string Field Name: layout, Type: int32_t Field Name: shape, Type: vector Field Name: type, Type: ModelBoxDataType::MODELBOX_UINT8 The other input port 'in_region' buffer type is yolo boundingbox, the memory arrangement is [float x,float y,float w,float h,int32_t condition,float score]. @Constraint: This flowunit can be only used follow the flowunit yolov3 postprocess'.

driver name: httpserver_async device type: cpu version: 1.0.0 class: DRIVER-FLOWUNIT description: @Brief: Start a http/https server, reply to the response immediately when a request is received, and output request info to next flowunit. @Port parameter: The output port buffer contain the following meta fields: Field Name: size, Type: size_t Field Name: method, Type: string Field Name: uri, Type: string Field Name: headers, Type: map<string,string> Field Name: endpoint, Type: string The the output port buffer data type is char * . @Constraint:

driver name: httpserver_sync device type: cpu version: 1.0.0 class: DRIVER-FLOWUNIT description: httpserver_sync contain flowunit 'httpserver_sync_receive' and 'httpserver_sync_reply'

driver name: image_decoder device type: cpu version: 1.0.0 class: DRIVER-FLOWUNIT description: @Brief: An OpenCV crop flowunit on cpu. @Port parameter: The input port buffer type is image file binary, the output port buffer type are image. The image type buffer contains the following meta fields: Field Name: width, Type: int32_t Field Name: height, Type: int32_t Field Name: width_stride, Type: int32_t Field Name: height_stride, Type: int32_t Field Name: channel, Type: int32_t Field Name: pix_fmt, Type: string Field Name: layout, Type: int32_t Field Name: shape, Type: vector Field Name: type, Type: ModelBoxDataType::MODELBOX_UINT8 @Constraint:

driver name: image_rotate device type: cpu version: 1.0.0 class: DRIVER-FLOWUNIT description: @Brief: An OpenCV rotate flowunit on cpu. @Port parameter: The input port buffer type is image file binary, the output port buffer type are image. The image type buffer contains the following meta fields: Field Name: width, Type: int32_t Field Name: height, Type: int32_t Field Name: width_stride, Type: int32_t Field Name: height_stride, Type: int32_t Field Name: rotate_angle, Type: int32_t Field Name: channel, Type: int32_t Field Name: pix_fmt, Type: string Field Name: layout, Type: int32_t Field Name: shape, Type: vector Field Name: type, Type: ModelBoxDataType::MODELBOX_UINT8 @Constraint:

driver name: mean device type: cpu version: 1.0.0 class: DRIVER-FLOWUNIT description: @Brief: The operator is used to subtract the mean for tensor data, for example the image(RGB/BGR), shape(W, H, C), subtract the corresponding value for different channels. @Port parameter: The input port and the output buffer type are tensor. The tensor type buffer contain the following meta fields: Field Name: shape, Type: vector Field Name: type, Type: ModelBoxDataType::MODELBOX_UINT8 @Constraint:

driver name: modeldecrypt-plugin device type: cpu version: 1.0.0 class: DRIVER-MODEL-DECRYPT description: default model descrypt plugin with AES256

driver name: normalize device type: cpu version: 1.0.0 class: DRIVER-FLOWUNIT description: @Brief: The operator is used to normalize for tensor data, for example the image(RGB/BGR). @Port parameter: The input port and the output buffer type are tensor. The tensor type buffer contain the following meta fields: Field Name: shape, Type: vector Field Name: type, Type: ModelBoxDataType::MODELBOX_UINT8 @Constraint:

driver name: obs device type: cpu version:
class: DRIVER-OUTPUT-BROKER description: A obs output broker plugin on CPU

driver name: webhook device type: cpu version:
class: DRIVER-OUTPUT-BROKER description: A webhook output broker plugin on CPU

driver name: output_broker device type: cpu version: 1.0.0 class: DRIVER-FLOWUNIT description: @Brief: Output the input data to the specified service. Currently supported types have dis, obs, webhook. @Port parameter: the input port buffer contain the following meta fields: Field Name: out_broker_names, Type: string Field Name: out_file_names, Type: string @Constraint: the fields 'out_file_names' can be only required when output type is obs.

driver name: packed_planar_transpose device type: cpu version: 1.0.0 class: DRIVER-FLOWUNIT description: @Brief: Convert the image format from packed to planar. @Port parameter: The input port 'in_image' and the output port 'out_image' buffer type are image. The image type buffer contain the following meta fields: Field Name: width, Type: int32_t Field Name: height, Type: int32_t Field Name: width_stride, Type: int32_t Field Name: height_stride, Type: int32_t Field Name: channel, Type: int32_t Field Name: pix_fmt, Type: string Field Name: layout, Type: int32_t Field Name: shape, Type: vector Field Name: type, Type: ModelBoxDataType::MODELBOX_UINT8 @Constraint: The field value range of this flowunit support: 'pix_fmt': [rgb,bgr], 'layout': [hwc]

driver name: padding device type: cpu version: 1.0.0 class: DRIVER-FLOWUNIT description: @Brief: A padding flowunit on cpu. @Port parameter: The input port buffer type and the output port buffer type are image. The image type buffer contains the following meta fields: Field Name: width, Type: int32_t Field Name: height, Type: int32_t Field Name: width_stride, Type: int32_t Field Name: height_stride, Type: int32_t Field Name: channel, Type: int32_t Field Name: pix_fmt, Type: string Field Name: layout, Type: int32_t Field Name: shape, Type: vector Field Name: type, Type: ModelBoxDataType::MODELBOX_UINT8 @Constraint: The field value range of this flowunit supports: 'pix_fmt': [rgb,bgr], 'layout': [hwc].

driver name: python device type: cpu version:
class: DRIVER-FLOWUNIT description: A python flowunit

driver name: resize device type: cpu version: 1.0.0 class: DRIVER-FLOWUNIT description: @Brief: A resize flowunit on cpu. @Port parameter: The input port buffer type and the output port buffer type are image. The image type buffer contains the following meta fields: Field Name: width, Type: int32_t Field Name: height, Type: int32_t Field Name: width_stride, Type: int32_t Field Name: height_stride, Type: int32_t Field Name: channel, Type: int32_t Field Name: pix_fmt, Type: string Field Name: layout, Type: int32_t Field Name: shape, Type: vector Field Name: type, Type: ModelBoxDataType::MODELBOX_UINT8 @Constraint: The field value range of this flowunit supports: 'pix_fmt': [rgb_packed,bgr_packed], 'layout': [hwc].

driver name: video_decoder device type: cpu version: 1.0.0 class: DRIVER-FLOWUNIT description: @Brief: A video decoder on cpu. @Port parameter: The input port buffer type is video_packet, the output port buffer type is video_frame. The video_packet buffer contain the following meta fields: Field Name: pts, Type: int64_t Field Name: dts, Type: int64_t Field Name: rate_num, Type: int32_t Field Name: rate_den, Type: int32_t Field Name: duration, Type: int64_t Field Name: time_base, Type: double Field Name: width, Type: int32_t Field Name: height, Type: int32_t The video_frame buffer contain the following meta fields: Field Name: index, Type: int64_t Field Name: rate_num, Type: int32_t Field Name: rate_den, Type: int32_t Field Name: duration, Type: int64_t Field Name: url, Type: string Field Name: timestamp, Type: int64_t Field Name: eos, Type: bool Field Name: width, Type: int32_t Field Name: height, Type: int32_t Field Name: width_stride, Type: int32_t Field Name: height_stride, Type: int32_t Field Name: channel, Type: int32_t Field Name: pix_fmt, Type: string Field Name: layout, Type: int32_t Field Name: shape, Type: vector Field Name: type, Type: ModelBoxDataType::MODELBOX_UINT8 @Constraint: The flowuint 'video_decoder' must be used pair with 'video_demuxer. the output buffer meta fields 'pix_fmt' is 'brg_packed' or 'rgb_packed', 'layout' is 'hcw'.

driver name: video_demuxer device type: cpu version: 1.0.0 class: DRIVER-FLOWUNIT description: @Brief: A video demuxer flowunit on cpu. @Port parameter: The input port buffer data indicate video file path or stream path, the output port buffer type is video_packet. The video_packet buffer contain the following meta fields: Field Name: pts, Type: int64_t Field Name: dts, Type: int64_t Field Name: rate_num, Type: int32_t Field Name: rate_den, Type: int32_t Field Name: duration, Type: int64_t Field Name: time_base, Type: double Field Name: width, Type: int32_t Field Name: height, Type: int32_t @Constraint: The flowuint 'video_decoder' must be used pair with 'video_demuxer.

driver name: video_encoder device type: cpu version: 1.0.0 class: DRIVER-FLOWUNIT description: @Brief: A video encoder flowunit on cpu. @Port parameter: The input port buffer meta type is image The image type buffer contains the following meta fields: Field Name: width, Type: int32_t Field Name: height, Type: int32_t Field Name: width_stride, Type: int32_t Field Name: height_stride, Type: int32_t Field Name: channel, Type: int32_t Field Name: pix_fmt, Type: string Field Name: layout, Type: int32_t Field Name: shape, Type: vector Field Name: type, Type: ModelBoxDataType::MODELBOX_UINT8 @Constraint: The field value range of this flowunit supports: 'pix_fmt': [rgb, bgr, nv12], 'layout': [hwc].

driver name: video_input device type: cpu version: 1.0.0 class: DRIVER-FLOWUNIT description: @Brief: The operator can convert the url configured by the user to buffer data, and be used for video demux. @Port parameter: The output port buffer data indicate video path. @Constraint: This flowunit is usually followed by 'video_demuxer'.

driver name: yolov3_postprocess device type: cpu version: 1.0.0 class: DRIVER-FLOWUNIT description: A cpu yolobox flowunit

driver name: inference device type: virtual version: 1.0.0 class: DRIVER-VIRTUAL description:

driver name: python device type: virtual version: 1.0.0 class: DRIVER-VIRTUAL description:

driver name: yolo_postprocess device type: virtual version: 1.0.0 class: DRIVER-VIRTUAL description:

FlowUnit Information :

flowunit name : crop type : ascend driver name : crop version : 1.0.0 description : @Brief: A crop flowunit on ascend device. @Port parameter: The input port 'in_image' and the output port 'out_image' buffer type are image. The image type buffer contain the following meta fields: Field Name: width, Type: int32_t Field Name: height, Type: int32_t Field Name: width_stride, Type: int32_t Field Name: height_stride, Type: int32_t Field Name: channel, Type: int32_t Field Name: pix_fmt, Type: string Field Name: layout, Type: int32_t Field Name: shape, Type: vector Field Name: type, Type: ModelBoxDataType::MODELBOX_UINT8 The other input port 'in_region' buffer type is rectangle, the memory arrangement is [x,y,w,h]. it contain the following meta fields: Field Name: type, Type: ModelBoxDataType::MODELBOX_UINT8 @Constraint: The field value range of this flowunit support: 'pix_fmt': [nv12], 'layout': [hwc]. One image can only be cropped with one rectangle and output one crop image. group : Image inputs : input index : 1 name : in_image type : device : input index : 2 name : in_region type : device : cpu outputs : output index : 1 name : out_image device :

flowunit name : padding type : ascend driver name : padding version : 1.0.0 description : @Brief: A padding flowunit on ascend device @Port paramter: the input port buffer type and the output port buffer type are image. The image type buffer contain the following meta fields: Field Name: width, Type: int32_t Field Name: height, Type: int32_t Field Name: width_stride, Type: int32_t Field Name: height_stride, Type: int32_t Field Name: pix_fmt, Type: string Field Name: layout, Type: int32_t Field Name: shape, Type: vector Field Name: type, Type: ModelBoxDataType::MODELBOX_UINT8 @Constraint: the field value range of this flowunit support：'pix_fmt': [nv12], 'layout': [hwc]. group : Image inputs : input index : 1 name : in_image type : device : outputs : output index : 1 name : out_image device : options : option : 1 name : image_width default : 0 desc : the padding width required : true type : int option : 2 name : image_height default : 0 desc : the padding height required : true type : int option : 3 name : vertical_align default : top desc : vertical align type required : false type : string option : 4 name : horizontal_align default : left desc : horizontal align type required : false type : string option : 5 name : padding_data default : 0,0,0 desc : the padding data required : false type : string

flowunit name : resize type : ascend driver name : resize version : 1.0.0 description : @Brief: A resize flowunit on ascend device. @Port parameter: The input port buffer type and the output port buffer type are image. The image type buffer contain the following meta fields: Field Name: width, Type: int32_t Field Name: height, Type: int32_t Field Name: width_stride, Type: int32_t Field Name: height_stride, Type: int32_t Field Name: channel, Type: int32_t Field Name: pix_fmt, Type: string Field Name: layout, Type: int32_t Field Name: shape, Type: vector Field Name: type, Type: ModelBoxDataType::MODELBOX_UINT8 @Constraint: The field value range of this flowunit support: 'pix_fmt': [nv12], 'layout': [hwc]. group : Image inputs : input index : 1 name : in_image type : device : outputs : output index : 1 name : out_image device : options : option : 1 name : image_width default : 0 desc : the resize width required : true type : int option : 2 name : image_height default : 0 desc : the resize height required : true type : int

flowunit name : video_decoder type : ascend driver name : video_decoder version : 1.0.0 description : @Brief: A resize flowunit on cpu. @Port parameter: the input port buffer type is video_packet, the output port buffer type is video_frame. The video_packet buffer contain the following meta fields: Field Name: pts, Type: int64_t Field Name: dts, Type: int64_t Field Name: rate_num, Type: int32_t Field Name: rate_den, Type: int32_t Field Name: duration, Type: int64_t Field Name: time_base, Type: double Field Name: width, Type: int32_t Field Name: height, Type: int32_t The video_frame buffer contain the following meta fields: Field Name: index, Type: int64_t Field Name: rate_num, Type: int32_t Field Name: rate_den, Type: int32_t Field Name: duration, Type: int64_t Field Name: url, Type: string Field Name: timestamp, Type: int64_t Field Name: eos, Type: bool Field Name: width, Type: int32_t Field Name: height, Type: int32_t Field Name: width_stride, Type: int32_t Field Name: height_stride, Type: int32_t Field Name: channel, Type: int32_t Field Name: pix_fmt, Type: string Field Name: layout, Type: int32_t Field Name: shape, Type: vector Field Name: type, Type: ModelBoxDataType::MODELBOX_UINT8 @Constraint: the flowuint 'video_decoder' must be used pair with 'video_demuxer. the output buffer meta fields 'pix_fmt' is 'nv12', 'layout' is 'hcw'. group : Video inputs : input index : 1 name : in_video_packet type : device : cpu outputs : output index : 1 name : out_video_frame device : options : option : 1 name : pix_fmt default : nv12 desc : the pix format required : true type : string

flowunit name : base64_decoder type : cpu driver name : base64_decoder version : 1.0.0 description : @Brief: base64 decoder flowunit on cpu. @Port parameter: The input port buffer type is image file binary, the output port buffer type are image. The image type buffer contains the following meta fields: Field Name: width, Type: int32_t Field Name: height, Type: int32_t Field Name: width_stride, Type: int32_t Field Name: height_stride, Type: int32_t Field Name: channel, Type: int32_t Field Name: pix_fmt, Type: string Field Name: layout, Type: int32_t Field Name: shape, Type: vector Field Name: type, Type: ModelBoxDataType::MODELBOX_UINT8 @Constraint: group : Image inputs : input index : 1 name : in_data type : device : cpu outputs : output index : 1 name : out_data device :

flowunit name : buff_meta_mapping type : cpu driver name : buff_meta_mapping version : 1.0.0 description : @Brief: Modify the input buffer meta field name and value according to custom rules. @Port parameter: The input port and the output buffer type are binary. @Constraint: group : Image inputs : input index : 1 name : in_data type : device : outputs : output index : 1 name : out_data device : options : option : 1 name : src_meta default : desc : the source meta required : true type : string option : 2 name : dest_meta default : desc : the dest meta required : true type : string option : 3 name : rules default : desc : the meta mapping rules required : false type : string

flowunit name : crop type : cpu driver name : crop version : 1.0.0 description : @Brief: An OpenCV crop flowunit on cpu. @Port parameter: The input port 'in_image' and the output port 'out_image' buffer type are image. The image type buffer contain the following meta fields: Field Name: width, Type: int32_t Field Name: height, Type: int32_t Field Name: width_stride, Type: int32_t Field Name: height_stride, Type: int32_t Field Name: channel, Type: int32_t Field Name: pix_fmt, Type: string Field Name: layout, Type: int32_t Field Name: shape, Type: vector Field Name: type, Type: ModelBoxDataType::MODELBOX_UINT8 The other input port 'in_region' buffer type is rectangle, the memory arrangement is [x,y,w,h]. it contain the following meta fields: Field Name: type, Type: ModelBoxDataType::MODELBOX_UINT8 @Constraint: The field value range of this flowunit support: 'pix_fmt': [rgb_packed,bgr_packed], 'layout': [hwc]. One image can only be cropped with one rectangle and output one crop image. group : Image inputs : input index : 1 name : in_image type : device : input index : 2 name : in_region type : device : outputs : output index : 1 name : out_image device :

flowunit name : data_source_generator type : cpu driver name : data_source_generator version : 1.0.0 description : @Brief: The operator can generator test data source config for data_source_parser. @Port parameter: The output port buffer data indicate data source config. @Constraint: This flowunit is usually followed by 'data_source_parser'. group : Input outputs : output index : 1 name : out_data device :

flowunit name : data_source_parser type : cpu driver name : data_source_parser version : 1.0.0 description : @Brief: this flowunit can obtain the video stream address or download the video file to the local according to the input configuration data, and output the url. Currently supported types have obs, vcn, vis, resetful, url. @Port parameter: The input buffer data type is char , and contain the following meta fields: Field Name: source_type, Type: string the output buffer data type is char . @Constraint: the field value range of this flowunit support: 'source_type': [obs, vcn, vis, restful, url]. This flowunit is usually followed by 'video_demuxer'. group : Input inputs : input index : 1 name : in_data type : device : outputs : output index : 1 name : out_video_url device : options : option : 1 name : retry_enable default : false desc : enable source parser retry required : false type : bool option : 2 name : retry_interval_ms default : 1000 desc : the source parser retry interval in ms required : false type : int option : 3 name : retry_count_limit default : -1 desc : the source parser retry count limit required : false type : int

flowunit name : draw_bbox type : cpu driver name : draw_bbox version : 1.0.0 description : @Brief: draw a rectangle area on the input image. @Port parameter: The input port 'in_image' and the output port 'out_image' buffer type are image. The image type buffer contain the following meta fields: Field Name: width, Type: int32_t Field Name: height, Type: int32_t Field Name: width_stride, Type: int32_t Field Name: height_stride, Type: int32_t Field Name: channel, Type: int32_t Field Name: pix_fmt, Type: string Field Name: layout, Type: int32_t Field Name: shape, Type: vector Field Name: type, Type: ModelBoxDataType::MODELBOX_UINT8 The other input port 'in_region' buffer type is yolo boundingbox, the memory arrangement is [float x,float y,float w,float h,int32_t condition,float score]. @Constraint: This flowunit can be only used follow the flowunit yolov3 postprocess'. group : Image inputs : input index : 1 name : in_image type : device : input index : 2 name : in_region type : device : outputs : output index : 1 name : out_image device :

flowunit name : httpserver_async type : cpu driver name : httpserver_async version : 1.0.0 description : @Brief: Start a http/https server, reply to the response immediately when a request is received, and output request info to next flowunit. @Port parameter: The output port buffer contain the following meta fields: Field Name: size, Type: size_t Field Name: method, Type: string Field Name: uri, Type: string Field Name: headers, Type: map<string,string> Field Name: endpoint, Type: string The the output port buffer data type is char * . @Constraint: group : Input outputs : output index : 1 name : out_request_info device : options : option : 1 name : endpoint default : https://127.0.0.1:8080 desc : http server listen URL. required : true type : string option : 2 name : max_requests default : 1000 desc : max http request. required : true type : integer option : 3 name : keepalive_timeout_sec default : 200 desc : keep-alive timeout time(sec) required : false type : integer option : 4 name : cert default : desc : cert file path required : false type : string option : 5 name : key default : desc : key file path required : false type : string option : 6 name : passwd default : desc : encrypted key file password. required : false type : string option : 7 name : key_pass default : desc : key for encrypted password. required : false type : string

flowunit name : httpserver_sync_receive type : cpu driver name : httpserver_sync version : 1.0.0 description : @Brief: Start a http/https server, output request info to next flowunit. @Port parameter: The output port buffer contain the following meta fields: Field Name: size, Type: size_t Field Name: method, Type: string Field Name: uri, Type: string Field Name: headers, Type: map<string,string> Field Name: endpoint, Type: string The the output port buffer data type is char * . @Constraint: The flowuint 'httpserver_sync_receive' must be used pair with 'httpserver_sync_reply'. group : Input outputs : output index : 1 name : out_request_info device : options : option : 1 name : endpoint default : https://127.0.0.1:8080 desc : http server listen URL. required : true type : string option : 2 name : max_requests default : 1000 desc : max http request. required : false type : integer option : 3 name : keepalive_timeout_sec default : 200 desc : keep-alive timeout time(sec) required : false type : integer option : 4 name : time_out_ms default : 5000 desc : max http request timeout. required : false type : integer option : 5 name : cert default : desc : cert file path required : false type : string option : 6 name : key default : desc : key file path required : false type : string option : 7 name : passwd default : desc : encrypted key file password. required : false type : string option : 8 name : key_pass default : desc : key for encrypted password. required : false type : string

flowunit name : httpserver_sync_reply type : cpu driver name : httpserver_sync version : 1.0.0 description : @Brief: Send reply when receive a response info.flowunit. @Port parameter: The input port buffer contain the following meta fields: Field Name: status, Type: int32_t Field Name: headers, Type: map<string,string> The the input port buffer data type is char * . @Constraint: The flowuint 'httpserver_sync_reply' must be used pair with 'httpserver_sync_receive'. group : Output inputs : input index : 1 name : in_reply_info type : device :

flowunit name : image_decoder type : cpu driver name : image_decoder version : 1.0.0 description : @Brief: An OpenCV crop flowunit on cpu. @Port parameter: The input port buffer type is image file binary, the output port buffer type are image. The image type buffer contains the following meta fields: Field Name: width, Type: int32_t Field Name: height, Type: int32_t Field Name: width_stride, Type: int32_t Field Name: height_stride, Type: int32_t Field Name: channel, Type: int32_t Field Name: pix_fmt, Type: string Field Name: layout, Type: int32_t Field Name: shape, Type: vector Field Name: type, Type: ModelBoxDataType::MODELBOX_UINT8 @Constraint: group : Image inputs : input index : 1 name : in_encoded_image type : device : outputs : output index : 1 name : out_image device : options : option : 1 name : pix_fmt default : bgr desc : the output pixel format required : true type : string

flowunit name : image_rotate type : cpu driver name : image_rotate version : 1.0.0 description : @Brief: An OpenCV rotate flowunit on cpu. @Port parameter: The input port buffer type is image file binary, the output port buffer type are image. The image type buffer contains the following meta fields: Field Name: width, Type: int32_t Field Name: height, Type: int32_t Field Name: width_stride, Type: int32_t Field Name: height_stride, Type: int32_t Field Name: rotate_angle, Type: int32_t Field Name: channel, Type: int32_t Field Name: pix_fmt, Type: string Field Name: layout, Type: int32_t Field Name: shape, Type: vector Field Name: type, Type: ModelBoxDataType::MODELBOX_UINT8 @Constraint: group : Image inputs : input index : 1 name : in_image type : device : outputs : output index : 1 name : out_image device : options : option : 1 name : rotate_angle default : 0 desc : the image rotate image required : false type : int

flowunit name : mean type : cpu driver name : mean version : 1.0.0 description : @Brief: The operator is used to subtract the mean for tensor data, for example the image(RGB/BGR), shape(W, H, C), subtract the corresponding value for different channels. @Port parameter: The input port and the output buffer type are tensor. The tensor type buffer contain the following meta fields: Field Name: shape, Type: vector Field Name: type, Type: ModelBoxDataType::MODELBOX_UINT8 @Constraint: group : Image inputs : input index : 1 name : in_data type : device : outputs : output index : 1 name : out_data device : options : option : 1 name : mean default : desc : the mean param required : true type : string

flowunit name : normalize type : cpu driver name : normalize version : 1.0.0 description : @Brief: The operator is used to normalize for tensor data, for example the image(RGB/BGR). @Port parameter: The input port and the output buffer type are tensor. The tensor type buffer contain the following meta fields: Field Name: shape, Type: vector Field Name: type, Type: ModelBoxDataType::MODELBOX_UINT8 @Constraint: group : Image inputs : input index : 1 name : in_data type : device : outputs : output index : 1 name : out_data device : options : option : 1 name : standard_deviation_inverse default : desc : the normalize param required : true type : string

flowunit name : output_broker type : cpu driver name : output_broker version : 1.0.0 description : @Brief: Output the input data to the specified service. Currently supported types have dis, obs, webhook. @Port parameter: the input port buffer contain the following meta fields: Field Name: out_broker_names, Type: string Field Name: out_file_names, Type: string @Constraint: the fields 'out_file_names' can be only required when output type is obs. group : Output inputs : input index : 1 name : in_output_info type : device :

flowunit name : packed_planar_transpose type : cpu driver name : packed_planar_transpose version : 1.0.0 description : @Brief: Convert the image format from packed to planar. @Port parameter: The input port 'in_image' and the output port 'out_image' buffer type are image. The image type buffer contain the following meta fields: Field Name: width, Type: int32_t Field Name: height, Type: int32_t Field Name: width_stride, Type: int32_t Field Name: height_stride, Type: int32_t Field Name: channel, Type: int32_t Field Name: pix_fmt, Type: string Field Name: layout, Type: int32_t Field Name: shape, Type: vector Field Name: type, Type: ModelBoxDataType::MODELBOX_UINT8 @Constraint: The field value range of this flowunit support: 'pix_fmt': [rgb,bgr], 'layout': [hwc] group : Image inputs : input index : 1 name : in_image type : device : outputs : output index : 1 name : out_image device :

flowunit name : padding type : cpu driver name : padding version : 1.0.0 description : @Brief: A padding flowunit on cpu. @Port parameter: The input port buffer type and the output port buffer type are image. The image type buffer contains the following meta fields: Field Name: width, Type: int32_t Field Name: height, Type: int32_t Field Name: width_stride, Type: int32_t Field Name: height_stride, Type: int32_t Field Name: channel, Type: int32_t Field Name: pix_fmt, Type: string Field Name: layout, Type: int32_t Field Name: shape, Type: vector Field Name: type, Type: ModelBoxDataType::MODELBOX_UINT8 @Constraint: The field value range of this flowunit supports: 'pix_fmt': [rgb,bgr], 'layout': [hwc]. group : Image inputs : input index : 1 name : in_image type : device : outputs : output index : 1 name : out_image device : options : option : 1 name : image_width default : 0 desc : Output img width required : true type : int option : 2 name : image_height default : 0 desc : Output img height required : true type : int option : 3 name : vertical_align default : top desc : Output roi vertical align type required : false type : list bottom : bottom center : center top : top option : 4 name : horizontal_align default : left desc : Output roi horizontal align type required : false type : list center : center left : left right : right option : 5 name : padding_data default : 0,0,0 desc : Data for padding required : false type : string option : 6 name : need_scale default : true desc : Will scale roi to fit output image required : false type : bool option : 7 name : interpolation default : inter_linear desc : Interpolation method to scale roi required : false type : list inter_cubic : inter_cubic inter_lanczos : inter_lanczos inter_linear : inter_linear inter_nn : inter_nn inter_super : inter_super

flowunit name : resize type : cpu driver name : resize version : 1.0.0 description : @Brief: A resize flowunit on cpu. @Port parameter: The input port buffer type and the output port buffer type are image. The image type buffer contains the following meta fields: Field Name: width, Type: int32_t Field Name: height, Type: int32_t Field Name: width_stride, Type: int32_t Field Name: height_stride, Type: int32_t Field Name: channel, Type: int32_t Field Name: pix_fmt, Type: string Field Name: layout, Type: int32_t Field Name: shape, Type: vector Field Name: type, Type: ModelBoxDataType::MODELBOX_UINT8 @Constraint: The field value range of this flowunit supports: 'pix_fmt': [rgb_packed,bgr_packed], 'layout': [hwc]. group : Image inputs : input index : 1 name : in_image type : device : outputs : output index : 1 name : out_image device : options : option : 1 name : image_width default : 640 desc : the resize width required : true type : int option : 2 name : image_height default : 480 desc : the resize height required : true type : int option : 3 name : interpolation default : inter_linear desc : the resize interpolation method required : true type : list inter_area : inter_area inter_cubic : inter_cubic inter_lanczos4 : inter_lanczos4 inter_linear : inter_linear inter_max : inter_max inter_nearest : inter_nearest warp_fill_outliers : warp_fill_outliers warp_inverse_map : warp_inverse_map

flowunit name : video_decoder type : cpu driver name : video_decoder version : 1.0.0 description : @Brief: A video decoder on cpu. @Port parameter: The input port buffer type is video_packet, the output port buffer type is video_frame. The video_packet buffer contain the following meta fields: Field Name: pts, Type: int64_t Field Name: dts, Type: int64_t Field Name: rate_num, Type: int32_t Field Name: rate_den, Type: int32_t Field Name: duration, Type: int64_t Field Name: time_base, Type: double Field Name: width, Type: int32_t Field Name: height, Type: int32_t The video_frame buffer contain the following meta fields: Field Name: index, Type: int64_t Field Name: rate_num, Type: int32_t Field Name: rate_den, Type: int32_t Field Name: duration, Type: int64_t Field Name: url, Type: string Field Name: timestamp, Type: int64_t Field Name: eos, Type: bool Field Name: width, Type: int32_t Field Name: height, Type: int32_t Field Name: width_stride, Type: int32_t Field Name: height_stride, Type: int32_t Field Name: channel, Type: int32_t Field Name: pix_fmt, Type: string Field Name: layout, Type: int32_t Field Name: shape, Type: vector Field Name: type, Type: ModelBoxDataType::MODELBOX_UINT8 @Constraint: The flowuint 'video_decoder' must be used pair with 'video_demuxer. the output buffer meta fields 'pix_fmt' is 'brg_packed' or 'rgb_packed', 'layout' is 'hcw'. group : Video inputs : input index : 1 name : in_video_packet type : device : outputs : output index : 1 name : out_video_frame device : options : option : 1 name : pix_fmt default : 0 desc : the decoder pixel format required : true type : list bgr : bgr nv12 : nv12 rgb : rgb

flowunit name : video_demuxer type : cpu driver name : video_demuxer version : 1.0.0 description : @Brief: A video demuxer flowunit on cpu. @Port parameter: The input port buffer data indicate video file path or stream path, the output port buffer type is video_packet. The video_packet buffer contain the following meta fields: Field Name: pts, Type: int64_t Field Name: dts, Type: int64_t Field Name: rate_num, Type: int32_t Field Name: rate_den, Type: int32_t Field Name: duration, Type: int64_t Field Name: time_base, Type: double Field Name: width, Type: int32_t Field Name: height, Type: int32_t @Constraint: The flowuint 'video_decoder' must be used pair with 'video_demuxer. group : Video inputs : input index : 1 name : in_video_url type : device : outputs : output index : 1 name : out_video_packet device :

flowunit name : video_encoder type : cpu driver name : video_encoder version : 1.0.0 description : @Brief: A video encoder flowunit on cpu. @Port parameter: The input port buffer meta type is image The image type buffer contains the following meta fields: Field Name: width, Type: int32_t Field Name: height, Type: int32_t Field Name: width_stride, Type: int32_t Field Name: height_stride, Type: int32_t Field Name: channel, Type: int32_t Field Name: pix_fmt, Type: string Field Name: layout, Type: int32_t Field Name: shape, Type: vector Field Name: type, Type: ModelBoxDataType::MODELBOX_UINT8 @Constraint: The field value range of this flowunit supports: 'pix_fmt': [rgb, bgr, nv12], 'layout': [hwc]. group : Video inputs : input index : 1 name : in_video_frame type : device : options : option : 1 name : default_dest_url default : desc : the encoder dest url required : true type : string option : 2 name : format default : rtsp desc : the encoder format required : true type : list flv : flv mp4 : mp4 rtsp : rtsp option : 3 name : encoder default : mpeg4 desc : the encoder method required : true type : string

flowunit name : video_input type : cpu driver name : video_input version : 1.0.0 description : @Brief: The operator can convert the url configured by the user to buffer data, and be used for video demux. @Port parameter: The output port buffer data indicate video path. @Constraint: This flowunit is usually followed by 'video_demuxer'. group : Video outputs : output index : 1 name : out_video_url device : options : option : 1 name : source_url default : desc : the video source url required : true type : string

pymumu commented 1 year ago

没有mindspore的东西。

modelbox是你自己编译，还是镜像里面带的？

yubo105139 commented 1 year ago

用的镜像。然后python 中有

pymumu commented 1 year ago

还有你是怎么进入镜像的？你ssh看看，有可能缺少环境变量。

yubo105139 commented 1 year ago

/usr/local/lib/python3.8/dist-packages/mindspore /usr/local/Ascend/ascend-toolkit/6.0.RC1/tools/msopgen/template/custom_operator_sample/DSL/Mindspore/mindspore /usr/local/Ascend/ascend-toolkit/6.0.RC1/tools/msopgen/template/custom_operator_sample/TIK/Mindspore/mindspore /usr/local/Ascend/ascend-toolkit/6.0.RC1/tools/msopgen/template/operator_demo_projects/mindspore_operator_sample/mindspore /usr/local/Ascend/ascend-toolkit/6.0.RC1/tools/ascend_automl/examples/mindspore /usr/local/Ascend/ascend-toolkit/6.0.RC1/tools/ascend_automl/algorithms/quant/mindspore /usr/local/Ascend/ascend-toolkit/6.0.RC1/tools/ascend_automl/algorithms/prune/mindspore /usr/local/Ascend/ascend-toolkit/6.0.RC1/tools/ascend_automl/core/networks/mindspore /usr/local/Ascend/ascend-toolkit/6.0.RC1/tools/ascend_automl/core/utils/mindspore /usr/local/Ascend/ascend-toolkit/6.0.RC1/tools/ascend_automl/core/metrics/mindspore /usr/local/Ascend/ascend-toolkit/6.0.RC1/tools/ascend_automl/core/evaluator/mindspore /usr/local/Ascend/ascend-toolkit/6.0.RC1/tools/ascend_automl/core/lr_scheduler/mindspore /usr/local/Ascend/ascend-toolkit/6.0.RC1/tools/ascend_automl/core/datasets/mindspore /usr/local/Ascend/ascend-toolkit/6.0.RC1/tools/ascend_tlt/vega/common/metrics/mindspore /usr/local/Ascend/ascend-toolkit/6.0.RC1/tools/ascend_tlt/vega/abstract/metrics/mindspore /usr/local/Ascend/ascend-toolkit/6.0.RC1/tools/ascend_tlt/vega/abstract/callbacks/mindspore /usr/local/Ascend/ascend-toolkit/6.0.RC1/tools/ascend_tlt/vega/abstract/datasets/mindspore /usr/local/Ascend/ascend-toolkit/6.0.RC1/tools/x2mindspore/x2ms/mindspore /usr/local/Ascend/ascend-toolkit/6.0.RC1/tools/ascend_utils/mindspore /usr/local/Ascend/ascend-toolkit/6.0.RC1/tools/ascend_model_compression/mindspore

yubo105139 commented 1 year ago

我根据https://modelbox-ai.com/modelbox-book/environment/container-usage.html创建的，然后我这边是6版本就找的6的镜像，不知道需要添加什么环境变量？

pymumu commented 1 year ago

ldd看一下mindspore-flowunit.so文件的依赖是否满足。 这些镜像每日构建都在运行，可能你容器mount的目录屏蔽了什么，导致找不到mindspore的库

yubo105139 commented 1 year ago

好的，谢谢您

mengmaren commented 1 year ago

我也遇到了这个问题，请问这个问题是如何解决的？ 也是直接拉取的上面的镜像，通过editor 主要有几个问题：

  1. 在editor的界面中，功能单元->新建单元 中，C++、推理、Yolo这三个选项都无法点击。
  2. mnist和mnist_mindpore都无法运行，报错为： request invalid, job config is invalid, Not found, build graph failed, please check graph config. -> create flowunit 'mnist_infer' failed. -> current environment does not support the inference type: 'mindspore:cpu'
  3. 提供的镜像容器，需要什么额外配置来运行示例程序吗？
pymumu commented 1 year ago

从提示看，是缺少cpu版本的mindspore推理引擎。镜像自带的一般是NPU版本的mindspore，如果要用CPU推理，则需要安装CPU版本的mindspore。

mengmaren commented 1 year ago

使用CPU和Ascend都报错：current environment does not support the inference type: 'mindspore:cpu'。 在python中看CPU的环境提示正确： [root@e45619086c67 home]$ python3 Python 3.8.10 (default, Mar 13 2023, 10:26:41) [GCC 9.4.0] on linux Type "help", "copyright", "credits" or "license" for more information.

import mindspore mindspore.run_check() MindSpore version: 1.9.0 MindSpore running check failed. Ascend kernel runtime initialization failed.

mindspore.set_context(device_target='Ascend') mindspore.run_check() MindSpore version: 1.9.0 MindSpore running check failed. Ascend kernel runtime initialization failed.

mindspore.set_context(device_target='CPU') mindspore.run_check() MindSpore version: 1.9.0 The result of multiplication calculation is correct, MindSpore has been installed successfully!

具体还有什么办法定位问题吗？ 拉取的镜像后还需要哪些配置？？

pymumu commented 1 year ago

如果想用ascend推理： 先要在hostOS中安装ascend的驱动。 然后用用下面的命令启动容器：https://modelbox-ai.com/modelbox-book/environment/container-usage.html

# ascend npu card id [modify]
ASCEND_NPU_ID=0

docker run -itd --device=/dev/davinci$ASCEND_NPU_ID --device=/dev/davinci_manager \
        --device=/dev/hisi_hdc --device=/dev/devmm_svm \
        --tmpfs /tmp --tmpfs /run -v /sys/fs/cgroup:/sys/fs/cgroup:ro \  
        --name $CONTAINER_NAME -v /home:/home -p $SSH_MAP_PORT:22 \
        -p $EDITOR_MAP_PORT:1104 $HTTP_DOCKER_PORT_COMMAND \
        $IMAGE_NAME

如果只是想用CPU测试mnist的话，可以参考这个： https://modelbox-ai.com/modelbox-book/cases/mnist-on-sbc.html

也可以执行懒人脚本： http://download.modelbox-ai.com/tools/build/get-start.sh

-m 参数表示使用国内镜像 -j N表示并发编译。

mengmaren commented 1 year ago

hostOS中驱动已经安装了： [root@192 Ascend]# ls -al total 32 drwxr-xr-x. 8 root root 259 Jul 28 10:53 . drwxr-xr-x. 16 root root 193 Jul 28 10:44 .. drwxr-xr-x. 4 root root 62 Jul 4 15:20 ascend-toolkit dr-xr-x---. 3 HwHiAiUser HwHiAiUser 19 Jul 28 10:44 develop drwxr-xr-x. 9 root root 156 Jul 28 10:44 driver dr-xr-x---. 5 root root 84 Jul 28 10:53 firmware -r-xr-x---. 1 root root 3778 Jul 28 10:44 host_servers_remove.sh -r-xr-x---. 1 root root 5707 Jul 28 10:44 host_servers_setup.sh -r-xr-x---. 1 root root 89 Jul 28 10:44 host_services_exit.sh -r-xr-x---. 1 root root 89 Jul 28 10:44 host_services_setup.sh -r-xr-x---. 1 root root 7485 Jul 28 10:44 host_sys_init.sh drwxr-xr-x. 4 root root 62 Jul 4 15:24 nnae drwxr-xr-x. 4 root root 62 Jul 4 15:22 nnrt -r--r--r--. 1 root root 22 Jul 28 10:44 version.info [root@192 Ascend]# cat version.info version=22.0.3.2.b030 [root@192 Ascend]# cat driver/version.info Version=22.0.3.2.b030 ascendhal_version=6.14.24 aicpu_version=1.0 tdt_version=1.0 log_version=1.0 prof_version=2.0 dvppkernels_version=1.1 tsfw_version=1.0 Innerversion=V100R001C83SPC003B220 package_version=6.0.rc1.2 [root@192 Ascend]# cat ascend-toolkit/ 6.0/ 6.0.2/ latest/ set_env.sh
[root@192 Ascend]# cat ascend-toolkit/latest/version.cfg

version: 1.0

runtime_running_version=[1.84.15.2.220:6.0.2] compiler_running_version=[1.84.15.2.220:6.0.2] opp_running_version=[1.84.15.2.220:6.0.2] toolkit_running_version=[1.84.15.2.220:6.0.2] aoe_running_version=[1.84.15.2.220:6.0.2] ncs_running_version=[1.84.15.2.220:6.0.2] runtime_upgrade_version=[1.84.15.2.220:6.0.2] compiler_upgrade_version=[1.84.15.2.220:6.0.2] opp_upgrade_version=[1.84.15.2.220:6.0.2] toolkit_upgrade_version=[1.84.15.2.220:6.0.2] aoe_upgrade_version=[1.84.15.2.220:6.0.2] ncs_upgrade_version=[1.84.15.2.220:6.0.2] runtime_installed_version=[1.84.15.2.220:6.0.2] compiler_installed_version=[1.84.15.2.220:6.0.2] opp_installed_version=[1.84.15.2.220:6.0.2] toolkit_installed_version=[1.84.15.2.220:6.0.2] aoe_installed_version=[1.84.15.2.220:6.0.2] ncs_installed_version=[1.84.15.2.220:6.0.2]

除了推理单元，其他示例都能跑通，现在就想用npu来推理，上面的驱动安装或者版本对吗？

pymumu commented 1 year ago

你改下推理单元的设备类型，改成ascend。