Reference documentation and code samples for the Google Cloud Ai Platform V1 Client class IndexDatapoint.
A datapoint of Index.
Generated from protobuf message google.cloud.aiplatform.v1.IndexDatapoint
Namespace
Google \ Cloud \ AIPlatform \ V1Methods
__construct
Constructor.
Parameters | |
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Name | Description |
data |
array
Optional. Data for populating the Message object. |
↳ datapoint_id |
string
Required. Unique identifier of the datapoint. |
↳ feature_vector |
array
Required. Feature embedding vector for dense index. An array of numbers with the length of [NearestNeighborSearchConfig.dimensions]. |
↳ sparse_embedding |
IndexDatapoint\SparseEmbedding
Optional. Feature embedding vector for sparse index. |
↳ restricts |
array<IndexDatapoint\Restriction>
Optional. List of Restrict of the datapoint, used to perform "restricted searches" where boolean rule are used to filter the subset of the database eligible for matching. This uses categorical tokens. See: https://cloud.google.com/vertex-ai/docs/matching-engine/filtering |
↳ numeric_restricts |
array<IndexDatapoint\NumericRestriction>
Optional. List of Restrict of the datapoint, used to perform "restricted searches" where boolean rule are used to filter the subset of the database eligible for matching. This uses numeric comparisons. |
↳ crowding_tag |
IndexDatapoint\CrowdingTag
Optional. CrowdingTag of the datapoint, the number of neighbors to return in each crowding can be configured during query. |
getDatapointId
Required. Unique identifier of the datapoint.
Returns | |
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Type | Description |
string |
setDatapointId
Required. Unique identifier of the datapoint.
Parameter | |
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Name | Description |
var |
string
|
Returns | |
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Type | Description |
$this |
getFeatureVector
Required. Feature embedding vector for dense index. An array of numbers with the length of [NearestNeighborSearchConfig.dimensions].
Returns | |
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Type | Description |
Google\Protobuf\Internal\RepeatedField |
setFeatureVector
Required. Feature embedding vector for dense index. An array of numbers with the length of [NearestNeighborSearchConfig.dimensions].
Parameter | |
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Name | Description |
var |
float[]
|
Returns | |
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Type | Description |
$this |
getSparseEmbedding
Optional. Feature embedding vector for sparse index.
Returns | |
---|---|
Type | Description |
IndexDatapoint\SparseEmbedding|null |
hasSparseEmbedding
clearSparseEmbedding
setSparseEmbedding
Optional. Feature embedding vector for sparse index.
Parameter | |
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Name | Description |
var |
IndexDatapoint\SparseEmbedding
|
Returns | |
---|---|
Type | Description |
$this |
getRestricts
Optional. List of Restrict of the datapoint, used to perform "restricted searches" where boolean rule are used to filter the subset of the database eligible for matching. This uses categorical tokens. See: https://cloud.google.com/vertex-ai/docs/matching-engine/filtering
Returns | |
---|---|
Type | Description |
Google\Protobuf\Internal\RepeatedField |
setRestricts
Optional. List of Restrict of the datapoint, used to perform "restricted searches" where boolean rule are used to filter the subset of the database eligible for matching. This uses categorical tokens. See: https://cloud.google.com/vertex-ai/docs/matching-engine/filtering
Parameter | |
---|---|
Name | Description |
var |
array<IndexDatapoint\Restriction>
|
Returns | |
---|---|
Type | Description |
$this |
getNumericRestricts
Optional. List of Restrict of the datapoint, used to perform "restricted searches" where boolean rule are used to filter the subset of the database eligible for matching. This uses numeric comparisons.
Returns | |
---|---|
Type | Description |
Google\Protobuf\Internal\RepeatedField |
setNumericRestricts
Optional. List of Restrict of the datapoint, used to perform "restricted searches" where boolean rule are used to filter the subset of the database eligible for matching. This uses numeric comparisons.
Parameter | |
---|---|
Name | Description |
var |
array<IndexDatapoint\NumericRestriction>
|
Returns | |
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Type | Description |
$this |
getCrowdingTag
Optional. CrowdingTag of the datapoint, the number of neighbors to return in each crowding can be configured during query.
Returns | |
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Type | Description |
IndexDatapoint\CrowdingTag|null |
hasCrowdingTag
clearCrowdingTag
setCrowdingTag
Optional. CrowdingTag of the datapoint, the number of neighbors to return in each crowding can be configured during query.
Parameter | |
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Name | Description |
var |
IndexDatapoint\CrowdingTag
|
Returns | |
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Type | Description |
$this |