Obtaining the Available Flavors

Function

Obtain the available flavors.

Constraints

None

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 ASCEND
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	List of specifications that can be switched.
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 ASCEND
description	String	Specification description
feature	String	Specification type. The options are as follows: DEFAULT: CodeLab specification. NOTEBOOK: Notebook specifications.
free	Boolean	Specifies whether the flavor is free of charge.
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: EFS EVS
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

GET https://{endpoint}/v1/{project_id}/notebooks/flavors

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
}