gcpdiag.queries.vertex
Queries related to GCP Vertex AI
FEATURESTORES_KEY =
'featurestores'
NAME_KEY =
'name'
STATE_KEY =
'state'
REGIONS =
{1: 'asia-east1', 2: 'asia-east2', 3: 'asia-northeast1', 4: 'asia-northeast2', 5: 'asia-northeast3', 6: 'asia-south1', 7: 'asia-south2', 8: 'asia-southeast1', 9: 'asia-southeast2', 10: 'australia-southeast1', 11: 'australia-southeast2', 12: 'europe-central2', 13: 'europe-north1', 14: 'europe-southwest1', 15: 'europe-west1', 16: 'europe-west2', 17: 'europe-west3', 18: 'europe-west4', 19: 'europe-west6', 20: 'europe-west8', 21: 'europe-west9', 22: 'europe-west12', 23: 'me-central1', 24: 'me-west1', 25: 'northamerica-northeast1', 26: 'northamerica-northeast2', 27: 'southamerica-east1', 28: 'southamerica-west1', 29: 'us-central1', 30: 'us-east1', 31: 'us-east4', 32: 'us-east5', 33: 'us-south1', 34: 'us-west1', 35: 'us-west2', 36: 'us-west3', 37: 'us-west4'}
FEATURE_REGIONS =
{'featurestores': [1, 2, 3, 5, 6, 8, 9, 10, 12, 15, 16, 17, 18, 19, 21, 25, 26, 27, 29, 30, 31, 34, 35, 36, 37]}
class
FeaturestoreStateEnum(enum.Enum):
105class FeaturestoreStateEnum(enum.Enum): 106 """The possible states a Vertex AI featurestore can have. 107 108 https://cloud.google.com/vertex-ai/docs/reference/rest/v1/projects.locations.featurestores#state 109 """ 110 111 STATE_UNSPECIFIED = 'STATE_UNSPECIFIED' 112 STABLE = 'STABLE' 113 UPDATING = 'UPDATING' 114 115 def __str__(self): 116 return str(self.value)
The possible states a Vertex AI featurestore can have.
https://cloud.google.com/vertex-ai/docs/reference/rest/v1/projects.locations.featurestores#state
STATE_UNSPECIFIED =
<FeaturestoreStateEnum.STATE_UNSPECIFIED: 'STATE_UNSPECIFIED'>
STABLE =
<FeaturestoreStateEnum.STABLE: 'STABLE'>
UPDATING =
<FeaturestoreStateEnum.UPDATING: 'UPDATING'>
class
Featurestore(gcpdiag.models.Resource):
119class Featurestore(models.Resource): 120 """Represent a Vertex AI featurestore 121 122 https://cloud.google.com/vertex-ai/docs/reference/rest/v1/projects.locations.featurestores#resource:-featurestore 123 """ 124 125 _resource_data: dict 126 127 def __init__(self, project_id, resource_data): 128 super().__init__(project_id=project_id) 129 self._resource_data = resource_data 130 131 @property 132 def full_path(self) -> str: 133 """ 134 The 'name' of the featurestore is already in the full path form 135 projects/{project}/locations/{location}/featurestores/{featurestore}. 136 """ 137 return self._resource_data[NAME_KEY] 138 139 @property 140 def short_path(self) -> str: 141 path = self.full_path 142 path = re.sub(r'^projects/', '', path) 143 path = re.sub(r'/locations/', '/', path) 144 path = re.sub(r'/featurestores/', '/', path) 145 return path 146 147 @property 148 def name(self) -> str: 149 logging.debug(self._resource_data) 150 return self._resource_data[NAME_KEY] 151 152 @property 153 def state(self) -> str: 154 logging.debug(self._resource_data) 155 return self._resource_data[STATE_KEY]
Represent a Vertex AI featurestore
full_path: str
131 @property 132 def full_path(self) -> str: 133 """ 134 The 'name' of the featurestore is already in the full path form 135 projects/{project}/locations/{location}/featurestores/{featurestore}. 136 """ 137 return self._resource_data[NAME_KEY]
The 'name' of the featurestore is already in the full path form projects/{project}/locations/{location}/featurestores/{featurestore}.
short_path: str
139 @property 140 def short_path(self) -> str: 141 path = self.full_path 142 path = re.sub(r'^projects/', '', path) 143 path = re.sub(r'/locations/', '/', path) 144 path = re.sub(r'/featurestores/', '/', path) 145 return path
Returns the short name for this resource.
Note that it isn't clear from this name what kind of resource it is.
Example: 'gke1'
@caching.cached_api_call
def
get_featurestores( context: gcpdiag.models.Context) -> Dict[str, Featurestore]:
158@caching.cached_api_call 159def get_featurestores(context: models.Context) -> Dict[str, Featurestore]: 160 featurestores: Dict[str, Featurestore] = {} 161 if not apis.is_enabled(context.project_id, 'aiplatform'): 162 return featurestores 163 for region in FEATURE_REGIONS[FEATURESTORES_KEY]: 164 featurestores_res: Dict[str, Featurestore] = {} 165 region_name = REGIONS[region] 166 logging.debug( 167 'fetching list of Vertex AI featurestores in project %s for region %s', 168 context.project_id, 169 region_name, 170 ) 171 vertex_api = apis.get_api('aiplatform', 'v1', context.project_id, region_name) 172 query = ( 173 vertex_api.projects() 174 .locations() 175 .featurestores() 176 .list(parent=f'projects/{context.project_id}/locations/{region_name}') 177 ) 178 try: 179 resp = query.execute(num_retries=config.API_RETRIES) 180 if FEATURESTORES_KEY not in resp: 181 continue 182 for resp_i in resp[FEATURESTORES_KEY]: 183 # verify that we have some minimal data that we expect 184 if NAME_KEY not in resp_i: 185 raise RuntimeError( 186 'missing featurestore name in projects.locations.featurestores.list response' 187 ) 188 i = Featurestore(project_id=context.project_id, resource_data=resp_i) 189 featurestores_res[i.full_path] = i 190 if featurestores: 191 featurestores.update(featurestores_res) 192 else: 193 featurestores = featurestores_res 194 except googleapiclient.errors.HttpError as err: 195 raise utils.GcpApiError(err) from err 196 return featurestores
