Obtaining the Available Flavors¶

Function¶

Obtain the available flavors.

Constraints¶

None

Debugging¶

You can debug this API through automatic authentication in or use the SDK sample code generated by API Explorer.

URI¶

GET /v1/{project_id}/notebooks/flavors

**Table 1** Path Parameters¶
Parameter	Mandatory	Type	Description
project_id	Yes	String	Project ID. For details, see Obtaining a Project ID and Name.

**Table 2** Query Parameters¶
Parameter	Mandatory	Type	Description
category	No	String	Processor type. Options: CPU GPU
limit	No	Integer	Number of records on each page. (No limit by default)
offset	No	Integer	Start offset of the records on each page. The default value is 0.
type	No	String	Cluster type. MANAGED: public cluster DEDICATED: dedicated cluster
sort_dir	No	String	Sorting mode. The options are ASC (ascending order) and DESC (descending order). The default value is DESC.
sort_key	No	String	Sorting fields. Separate multiple fields with commas (,).

Request Parameters¶

None

Response Parameters¶

Status code: 200

**Table 3** Response body parameters¶
Parameter	Type	Description
current	Integer	Current page
data	Array of NotebookFlavor objects	Pagination data
flavors	Array of NotebookFlavor objects	Data
pages	Integer	Total number of pages
size	Integer	Number of records on each page
total	Long	Total number of records

**Table 4** NotebookFlavor¶
Parameter	Type	Description
arch	String	Architecture type. Options: X86_64 AARCH64
ascend	AscendInfo object	NPU information
billing	BillingInfo object	CDR information
category	String	Processor type. Options: CPU GPU
description	String	Specification description
feature	String	Flavor type. Options: DEFAULT: CodeLab NOTEBOOK: notebook
free	Boolean	Free flavor or not
gpu	GPUInfo object	GPU information
id	String	Flavor ID
memory	Long	Memory size
name	String	Flavor name
sold_out	Boolean	Whether resources are sufficient. true: Resources are insufficient. false: Resources are sufficient.
storages	Array of strings	Storage type. Options: EVS EFS
vcpus	Integer	Number of vCPUs

**Table 5** AscendInfo¶
Parameter	Type	Description
npu	Integer	Number of NPUs
npu_memory	String	NPU memory
type	String	NPU type

**Table 6** BillingInfo¶
Parameter	Type	Description
code	String	Billing code
unit_num	Integer	Billing unit

**Table 7** GPUInfo¶
Parameter	Type	Description
gpu	Integer	Number of GPUs
gpu_memory	String	GPU memory
type	String	GPU type

Example Requests¶

None

Example Responses¶

Status code: 200

{
  "current" : 2,
  "data" : [ {
    "arch" : "x86_64",
    "billing" : {
      "code" : "modelarts.bm.gpu.v100NV32",
      "unit_num" : 4
    },
    "category" : "GPU",
    "description" : "Four NVIDIA V100 GPUs, each with 32GB of memory, ideal for deep learning algorithm training and debugging.",
    "feature" : "NOTEBOOK",
    "free" : false,
    "gpu" : {
      "gpu" : 4,
      "gpu_memory" : "128",
      "type" : "nvidia-v100-pcie32"
    },
    "id" : "modelarts.bm.gpu.4v100NV32.nosdi",
    "memory" : 134217728,
    "name" : "GPU: 4*V100(128GB)|CPU: 32vCPUs 256GB",
    "sold_out" : true,
    "storages" : [ "EFS", "OBSFS", "OBS", "EVS" ],
    "vcpus" : 32
  }, {
    "arch" : "x86_64",
    "billing" : {
      "code" : "modelarts.bm.gpu.v100NV32.eco",
      "unit_num" : 2
    },
    "category" : "GPU",
    "description" : "Two Shared NVIDIA V100 GPU with 64GB of memory, ideal for ML development",
    "feature" : "NOTEBOOK",
    "free" : false,
    "gpu" : {
      "gpu" : 0.5,
      "gpu_memory" : "64",
      "type" : "nvidia-v100-nv32"
    },
    "id" : "modelarts.bm.gpu.2v100NV32.share",
    "memory" : 67108864,
    "name" : "vGPU: 2*V100(32GB)|CPU: 8vCPUs 64GB",
    "sold_out" : false,
    "storages" : [ "EFS", "OBSFS", "OBS", "EVS" ],
    "vcpus" : 8
  } ],
  "pages" : 26,
  "size" : 2,
  "total" : 52
}

Status Codes¶

Status Code	Description
200	OK
401	Unauthorized
403	Forbidden
404	Not Found

Error Codes¶

See Error Codes.

last updated: 2024-11-28 19:02 UTC - commit: 7e602c6c50500da4fb13dea67589040fd3f7deb8