com.google.cloud.aiplatform.v1beta1

Enum ExplanationMetadata.InputMetadata.Encoding

java.lang.Object

java.lang.Enum<ExplanationMetadata.InputMetadata.Encoding>

com.google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.Encoding

All Implemented Interfaces:

com.google.protobuf.Internal.EnumLite, com.google.protobuf.ProtocolMessageEnum, Serializable, Comparable<ExplanationMetadata.InputMetadata.Encoding>

Enclosing class:

ExplanationMetadata.InputMetadata

public static enum ExplanationMetadata.InputMetadata.Encoding
extends Enum<ExplanationMetadata.InputMetadata.Encoding>
implements com.google.protobuf.ProtocolMessageEnum

 Defines how a feature is encoded. Defaults to IDENTITY.
 

Protobuf enum google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.Encoding

Enum Constant Summary

Enum Constants

Enum Constant and Description
BAG_OF_FEATURES The tensor represents a bag of features where each index maps to a feature.
BAG_OF_FEATURES_SPARSE The tensor represents a bag of features where each index maps to a feature.
COMBINED_EMBEDDING The tensor is encoded into a 1-dimensional array represented by an encoded tensor.
CONCAT_EMBEDDING Select this encoding when the input tensor is encoded into a 2-dimensional array represented by an encoded tensor.
ENCODING_UNSPECIFIED Default value.
IDENTITY The tensor represents one feature.
INDICATOR The tensor is a list of binaries representing whether a feature exists or not (1 indicates existence).
UNRECOGNIZED

Field Summary

Fields

Modifier and Type	Field and Description
static int	BAG_OF_FEATURES_SPARSE_VALUE The tensor represents a bag of features where each index maps to a feature.
static int	BAG_OF_FEATURES_VALUE The tensor represents a bag of features where each index maps to a feature.
static int	COMBINED_EMBEDDING_VALUE The tensor is encoded into a 1-dimensional array represented by an encoded tensor.
static int	CONCAT_EMBEDDING_VALUE Select this encoding when the input tensor is encoded into a 2-dimensional array represented by an encoded tensor.
static int	ENCODING_UNSPECIFIED_VALUE Default value.
static int	IDENTITY_VALUE The tensor represents one feature.
static int	INDICATOR_VALUE The tensor is a list of binaries representing whether a feature exists or not (1 indicates existence).

Method Summary

Modifier and Type	Method and Description
static ExplanationMetadata.InputMetadata.Encoding	forNumber(int value)
static com.google.protobuf.Descriptors.EnumDescriptor	getDescriptor()
com.google.protobuf.Descriptors.EnumDescriptor	getDescriptorForType()
int	getNumber()
com.google.protobuf.Descriptors.EnumValueDescriptor	getValueDescriptor()
static com.google.protobuf.Internal.EnumLiteMap<ExplanationMetadata.InputMetadata.Encoding>	internalGetValueMap()
static ExplanationMetadata.InputMetadata.Encoding	valueOf(com.google.protobuf.Descriptors.EnumValueDescriptor desc)
static ExplanationMetadata.InputMetadata.Encoding	valueOf(int value) Deprecated. Use forNumber(int) instead.
static ExplanationMetadata.InputMetadata.Encoding	valueOf(String name) Returns the enum constant of this type with the specified name.
static ExplanationMetadata.InputMetadata.Encoding[]	values() Returns an array containing the constants of this enum type, in the order they are declared.

Methods inherited from class java.lang.Enum

clone, compareTo, equals, finalize, getDeclaringClass, hashCode, name, ordinal, toString, valueOf

Methods inherited from class java.lang.Object

getClass, notify, notifyAll, wait, wait, wait

Enum Constant Detail

ENCODING_UNSPECIFIED

public static final ExplanationMetadata.InputMetadata.Encoding ENCODING_UNSPECIFIED

 Default value. This is the same as IDENTITY.
 

ENCODING_UNSPECIFIED = 0;

IDENTITY

public static final ExplanationMetadata.InputMetadata.Encoding IDENTITY

 The tensor represents one feature.
 

IDENTITY = 1;

BAG_OF_FEATURES

public static final ExplanationMetadata.InputMetadata.Encoding BAG_OF_FEATURES

 The tensor represents a bag of features where each index maps to
 a feature.
 [InputMetadata.index_feature_mapping][google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.index_feature_mapping]
 must be provided for this encoding. For example:
 ```
 input = [27, 6.0, 150]
 index_feature_mapping = ["age", "height", "weight"]
 ```
 

BAG_OF_FEATURES = 2;

BAG_OF_FEATURES_SPARSE

public static final ExplanationMetadata.InputMetadata.Encoding 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][google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.index_feature_mapping]
 must be provided for this encoding. For example:
 ```
 input = [2, 0, 5, 0, 1]
 index_feature_mapping = ["a", "b", "c", "d", "e"]
 ```
 

BAG_OF_FEATURES_SPARSE = 3;

INDICATOR

public static final ExplanationMetadata.InputMetadata.Encoding INDICATOR

 The tensor is a list of binaries representing whether a feature exists
 or not (1 indicates existence).
 [InputMetadata.index_feature_mapping][google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.index_feature_mapping]
 must be provided for this encoding. For example:
 ```
 input = [1, 0, 1, 0, 1]
 index_feature_mapping = ["a", "b", "c", "d", "e"]
 ```
 

INDICATOR = 4;

COMBINED_EMBEDDING

public static final ExplanationMetadata.InputMetadata.Encoding COMBINED_EMBEDDING

 The tensor is encoded into a 1-dimensional array represented by an
 encoded tensor.
 [InputMetadata.encoded_tensor_name][google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.encoded_tensor_name]
 must be provided for this encoding. For example:
 ```
 input = ["This", "is", "a", "test", "."]
 encoded = [0.1, 0.2, 0.3, 0.4, 0.5]
 ```
 

COMBINED_EMBEDDING = 5;

CONCAT_EMBEDDING

public static final ExplanationMetadata.InputMetadata.Encoding 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][google.cloud.aiplatform.v1beta1.ExplanationMetadata.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:
 ```
 input = ["This", "is", "a", "test", "."]
 encoded = [[0.1, 0.2, 0.3, 0.4, 0.5],
            [0.2, 0.1, 0.4, 0.3, 0.5],
            [0.5, 0.1, 0.3, 0.5, 0.4],
            [0.5, 0.3, 0.1, 0.2, 0.4],
            [0.4, 0.3, 0.2, 0.5, 0.1]]
 ```
 

CONCAT_EMBEDDING = 6;

UNRECOGNIZED

public static final ExplanationMetadata.InputMetadata.Encoding UNRECOGNIZED

Field Detail

ENCODING_UNSPECIFIED_VALUE

public static final int ENCODING_UNSPECIFIED_VALUE

 Default value. This is the same as IDENTITY.
 

ENCODING_UNSPECIFIED = 0;

See Also:

Constant Field Values

IDENTITY_VALUE

public static final int IDENTITY_VALUE

 The tensor represents one feature.
 

IDENTITY = 1;

See Also:

Constant Field Values

BAG_OF_FEATURES_VALUE

public static final int BAG_OF_FEATURES_VALUE

 The tensor represents a bag of features where each index maps to
 a feature.
 [InputMetadata.index_feature_mapping][google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.index_feature_mapping]
 must be provided for this encoding. For example:
 ```
 input = [27, 6.0, 150]
 index_feature_mapping = ["age", "height", "weight"]
 ```
 

BAG_OF_FEATURES = 2;

See Also:

Constant Field Values

BAG_OF_FEATURES_SPARSE_VALUE

public static final int 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][google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.index_feature_mapping]
 must be provided for this encoding. For example:
 ```
 input = [2, 0, 5, 0, 1]
 index_feature_mapping = ["a", "b", "c", "d", "e"]
 ```
 

BAG_OF_FEATURES_SPARSE = 3;

See Also:

Constant Field Values

INDICATOR_VALUE

public static final int INDICATOR_VALUE

 The tensor is a list of binaries representing whether a feature exists
 or not (1 indicates existence).
 [InputMetadata.index_feature_mapping][google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.index_feature_mapping]
 must be provided for this encoding. For example:
 ```
 input = [1, 0, 1, 0, 1]
 index_feature_mapping = ["a", "b", "c", "d", "e"]
 ```
 

INDICATOR = 4;

See Also:

Constant Field Values

COMBINED_EMBEDDING_VALUE

public static final int COMBINED_EMBEDDING_VALUE

 The tensor is encoded into a 1-dimensional array represented by an
 encoded tensor.
 [InputMetadata.encoded_tensor_name][google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.encoded_tensor_name]
 must be provided for this encoding. For example:
 ```
 input = ["This", "is", "a", "test", "."]
 encoded = [0.1, 0.2, 0.3, 0.4, 0.5]
 ```
 

COMBINED_EMBEDDING = 5;

See Also:

Constant Field Values

CONCAT_EMBEDDING_VALUE

public static final int 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][google.cloud.aiplatform.v1beta1.ExplanationMetadata.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:
 ```
 input = ["This", "is", "a", "test", "."]
 encoded = [[0.1, 0.2, 0.3, 0.4, 0.5],
            [0.2, 0.1, 0.4, 0.3, 0.5],
            [0.5, 0.1, 0.3, 0.5, 0.4],
            [0.5, 0.3, 0.1, 0.2, 0.4],
            [0.4, 0.3, 0.2, 0.5, 0.1]]
 ```
 

CONCAT_EMBEDDING = 6;

See Also:

Constant Field Values

Method Detail

values

public static ExplanationMetadata.InputMetadata.Encoding[] values()

Returns an array containing the constants of this enum type, in the order they are declared. This method may be used to iterate over the constants as follows:

for (ExplanationMetadata.InputMetadata.Encoding c : ExplanationMetadata.InputMetadata.Encoding.values())
    System.out.println(c);

Returns:

an array containing the constants of this enum type, in the order they are declared

valueOf

public static ExplanationMetadata.InputMetadata.Encoding valueOf(String name)

Returns the enum constant of this type with the specified name. The string must match exactly an identifier used to declare an enum constant in this type. (Extraneous whitespace characters are not permitted.)

Parameters:

name - the name of the enum constant to be returned.

Returns:

the enum constant with the specified name

Throws:

IllegalArgumentException - if this enum type has no constant with the specified name

NullPointerException - if the argument is null

getNumber

public final int getNumber()

Specified by:

getNumber in interface com.google.protobuf.Internal.EnumLite

Specified by:

getNumber in interface com.google.protobuf.ProtocolMessageEnum

valueOf

@Deprecated
public static ExplanationMetadata.InputMetadata.Encoding valueOf(int value)

Deprecated. Use forNumber(int) instead.

Parameters:

value - The numeric wire value of the corresponding enum entry.

Returns:

The enum associated with the given numeric wire value.

forNumber

public static ExplanationMetadata.InputMetadata.Encoding forNumber(int value)

Parameters:

value - The numeric wire value of the corresponding enum entry.

Returns:

The enum associated with the given numeric wire value.

internalGetValueMap

public static com.google.protobuf.Internal.EnumLiteMap<ExplanationMetadata.InputMetadata.Encoding> internalGetValueMap()

getValueDescriptor

public final com.google.protobuf.Descriptors.EnumValueDescriptor getValueDescriptor()

Specified by:

getValueDescriptor in interface com.google.protobuf.ProtocolMessageEnum

getDescriptorForType

public final com.google.protobuf.Descriptors.EnumDescriptor getDescriptorForType()

Specified by:

getDescriptorForType in interface com.google.protobuf.ProtocolMessageEnum

getDescriptor

public static final com.google.protobuf.Descriptors.EnumDescriptor getDescriptor()

valueOf

public static ExplanationMetadata.InputMetadata.Encoding valueOf(com.google.protobuf.Descriptors.EnumValueDescriptor desc)