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public enum ExplanationMetadata.InputMetadata.Encoding extends Enum<ExplanationMetadata.InputMetadata.Encoding> implements ProtocolMessageEnum
Defines how a feature is encoded. Defaults to IDENTITY.
Protobuf enum google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.Encoding
Implements
ProtocolMessageEnumStatic Fields
Name | Description |
BAG_OF_FEATURES | The tensor represents a bag of features where each index maps to
a feature.
InputMetadata.index_feature_mapping
must be provided for this encoding. For example:
|
BAG_OF_FEATURES_SPARSE | The tensor represents a bag of features where each index maps to a
feature. Zero values in the tensor indicates feature being
non-existent.
InputMetadata.index_feature_mapping
must be provided for this encoding. For example:
|
BAG_OF_FEATURES_SPARSE_VALUE | The tensor represents a bag of features where each index maps to a
feature. Zero values in the tensor indicates feature being
non-existent.
InputMetadata.index_feature_mapping
must be provided for this encoding. For example:
|
BAG_OF_FEATURES_VALUE | The tensor represents a bag of features where each index maps to
a feature.
InputMetadata.index_feature_mapping
must be provided for this encoding. For example:
|
COMBINED_EMBEDDING | The tensor is encoded into a 1-dimensional array represented by an
encoded tensor.
InputMetadata.encoded_tensor_name
must be provided for this encoding. For example:
|
COMBINED_EMBEDDING_VALUE | The tensor is encoded into a 1-dimensional array represented by an
encoded tensor.
InputMetadata.encoded_tensor_name
must be provided for this encoding. For example:
|
CONCAT_EMBEDDING | Select this encoding when the input tensor is encoded into a
2-dimensional array represented by an encoded tensor.
InputMetadata.encoded_tensor_name
must be provided for this encoding. The first dimension of the encoded
tensor's shape is the same as the input tensor's shape. For example:
|
CONCAT_EMBEDDING_VALUE | Select this encoding when the input tensor is encoded into a
2-dimensional array represented by an encoded tensor.
InputMetadata.encoded_tensor_name
must be provided for this encoding. The first dimension of the encoded
tensor's shape is the same as the input tensor's shape. For example:
|
ENCODING_UNSPECIFIED | Default value. This is the same as IDENTITY. |
ENCODING_UNSPECIFIED_VALUE | Default value. This is the same as IDENTITY. |
IDENTITY | The tensor represents one feature. |
IDENTITY_VALUE | The tensor represents one feature. |
INDICATOR | The tensor is a list of binaries representing whether a feature exists
or not (1 indicates existence).
InputMetadata.index_feature_mapping
must be provided for this encoding. For example:
|
INDICATOR_VALUE | The tensor is a list of binaries representing whether a feature exists
or not (1 indicates existence).
InputMetadata.index_feature_mapping
must be provided for this encoding. For example:
|
UNRECOGNIZED |
Static Methods
Name | Description |
forNumber(int value) | |
getDescriptor() | |
internalGetValueMap() | |
valueOf(Descriptors.EnumValueDescriptor desc) | |
valueOf(int value) | Deprecated. Use #forNumber(int) instead. |
valueOf(String name) | |
values() |
Methods
Name | Description |
getDescriptorForType() | |
getNumber() | |
getValueDescriptor() |