Open yubo105139 opened 1 year ago
你选了cpu的推理,要选ascend的
create flowunit 'mnist_infer' failed. -> current environment does not support the inference type: 'mindspore:ascend'
我这边没有任何作用
modelbox-tool driver -info -details 看看输出,应该是没要找到mindspore的库
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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 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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
没有mindspore的东西。
modelbox是你自己编译,还是镜像里面带的?
用的镜像。然后python 中有
还有你是怎么进入镜像的?你ssh看看,有可能缺少环境变量。
/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
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?
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
好的,谢谢您
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:
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。
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.
EE8888: Inner Error! Unsupport flags, flags=4[FUNC:StreamCreate][FILE:api_error.cc][LINE:300] rtStreamCreateWithFlags execute failed, reason=[feature not support][FUNC:FuncErrorReason][FILE:error_message_manage.cc][LINE:49] Solution: Please contact support engineer.
Create stream failed, ret:207000
mindspore/ccsrc/plugin/device/ascend/hal/device/ascend_kernel_runtime.cc:425 Init mindspore/ccsrc/plugin/device/ascend/hal/device/ascend_stream_manager.cc:96 CreateStreamWithFlags
mindspore.set_context(device_target='Ascend') mindspore.run_check() MindSpore version: 1.9.0 MindSpore running check failed. Ascend kernel runtime initialization failed.
EE8888: Inner Error! Unsupport flags, flags=4[FUNC:StreamCreate][FILE:api_error.cc][LINE:300] rtStreamCreateWithFlags execute failed, reason=[feature not support][FUNC:FuncErrorReason][FILE:error_message_manage.cc][LINE:49] Solution: Please contact support engineer.
Create stream failed, ret:207000
mindspore/ccsrc/plugin/device/ascend/hal/device/ascend_kernel_runtime.cc:425 Init mindspore/ccsrc/plugin/device/ascend/hal/device/ascend_stream_manager.cc:96 CreateStreamWithFlags
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??
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。
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
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?
你改下推理单元的设备类型,改成ascend。
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](https://github.com/modelbox-ai/modelbox/assets/44567843/7fa3529f-6364-4110-a48d-b13b4a7ecb40)
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](https://github.com/modelbox-ai/modelbox/assets/44567843/028d5eca-5836-4a9c-9aa8-491aaed44792)
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.