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Call the API for obtaining the preset AI frameworks supported by a training job to view the engines and their versions supported by a training job.
This parameter is mandatory. double vinc Vertical magnification for the AI core output channel [0.03125, 1) or (1, 4] If a resizing coefficient exceeds the value range, the VPC reports an error. If resizing is not required, set the value to 1.
This parameter is mandatory. double vinc Vertical magnification for the AI core output channel [0.03125, 1) or (1, 4] If a resizing coefficient exceeds the value range, the VPC reports an error. If resizing is not required, set the value to 1.
The default value is 0. ai_project String AI project to which a training job belongs. The default value is default-ai-project. items Array of JobResponse objects Details of the training jobs that meet the search criteria of the current user.
Options: 0: OBS bucket (default value) 1: GaussDB(DWS) 2: DLI 3: RDS 4: MRS 5: AI Gallery 6: Inference service schema_maps No Array of SchemaMap objects Schema mapping information corresponding to the table data. source_info No SourceInfo object Information required for importing
The malware is found and removed by analysis on program characteristics and behaviors, AI image fingerprint algorithms, and cloud scanning and killing. Supported OSs: Linux and Windows.
Artifact Center SWR Artifact Center provides container developers with basic container artifacts (also called images) that are from open source communities, including OS artifacts, language artifacts, AI/big data artifacts.
The malware is found and removed by analysis on program characteristics and behaviors, AI image fingerprint algorithms, and cloud scanning and killing. Viruses Check containers in real time and report alarms for viruses detected in the container runtime.
Options: 0: OBS bucket (default value) 1: GaussDB(DWS) 2: DLI 3: RDS 4: MRS 5: AI Gallery 6: Inference service schema_maps Array of SchemaMap objects Schema mapping information corresponding to the table data. source_info SourceInfo object Information required for importing a table
Volcano provides general-purpose, high-performance computing capabilities, such as job scheduling engine, heterogeneous chip management, and job running management, serving end users through computing frameworks for different industries, such as AI, big data, gene sequencing, and
The content includes migration evaluation and solution design of AI applications and matching models, reconstruction and commissioning of AI applications and model inference scripts, performance optimization of single-node and distributed systems, and fine-tuning, training script
CMS_CONF_NOT_SUPPORT_AI_RECORD 111077101 AI meeting minutes are not supported. CMS_CONF_RE_APPLY_AI_RECORD_RES 111077102 The system is requesting meeting minutes resources again. CMS_AI_RECORD_RESOURCE_NOT_ENOUGH 111077103 AI meeting minutes resources are insufficient.
Scenarios High-performance computing and computer simulation Big data applications AI training and inference Specifications Table 13 C6h ECS specifications Flavor vCPUs Memory (GiB) Max./Assured Bandwidth (Gbit/s) Max. PPS (10,000) Max. NIC Queues Max.
WAF uses an AI protection engine to analyze and automatically learn requests, and then handles the attack behavior based on the configured behavior detection score and protective action. You can set three score ranges for bot behavior detection. Score range: 0 to 100.
If this parameter is not left blank, it is an Atlas 500 AI edge station. ntp_configs Table 30 object NTP configuration. error_reason String Node fault cause. tags Array of Table 27 objects Edge node tags. npu_num Integer Number of NPUs. npu_info npu_info object NPU model and memory
Options: 0: OBS bucket (default value) 1: GaussDB(DWS) 2: DLI 3: RDS 4: MRS 5: AI Gallery 6: Inference service schema_maps Array of SchemaMap objects Schema mapping information corresponding to the table data. source_info SourceInfo object Information required for importing a table
Set AI Engine to Custom. Set Engine Package to the image created in 3. Figure 3 Creating a model Deploy the created model as a real-time service. Generally, the time for loading and starting a large model is longer than that for a common model. Set Timeout to a proper value.
It combines data lakes, data warehouses, business intelligence (BI), and artificial intelligence (AI) into a full-stack platform that can be further customized based on service requirements.
The default value is 0. ai_project String AI project to which a job belongs. The default value is default-ai-project. items Array of JobResponse objects Jobs that meet the search criteria of the current user.
This section provides custom script examples (including inference code examples) for common AI engines. For details about how to write model inference code, see Specifications for Writing a Model Inference Code File.
