Type Members

1.  final class Annotation extends GeneratedMessageV3 with AnnotationOrBuilder

   Additional information about the schema or about a feature.
   

   Additional information about the schema or about a feature.
   

   Protobuf type tensorflow.metadata.v0.Annotation

2.  trait AnnotationOrBuilder extends MessageOrBuilder
3.  final class BoolDomain extends GeneratedMessageV3 with BoolDomainOrBuilder

   Encodes information about the domain of a boolean attribute that encodes its
   TRUE/FALSE values as strings, or 0=false, 1=true.
   Note that FeatureType could be either INT or BYTES.
   

   Encodes information about the domain of a boolean attribute that encodes its
   TRUE/FALSE values as strings, or 0=false, 1=true.
   Note that FeatureType could be either INT or BYTES.
   

   Protobuf type tensorflow.metadata.v0.BoolDomain

4.  trait BoolDomainOrBuilder extends MessageOrBuilder
5.  final class DatasetConstraints extends GeneratedMessageV3 with DatasetConstraintsOrBuilder

   Constraints on the entire dataset.
   

   Constraints on the entire dataset.
   

   Protobuf type tensorflow.metadata.v0.DatasetConstraints

6.  trait DatasetConstraintsOrBuilder extends MessageOrBuilder
7.  final class DistributionConstraints extends GeneratedMessageV3 with DistributionConstraintsOrBuilder

   Models constraints on the distribution of a feature's values.
   TODO(martinz): replace min_domain_mass with max_off_domain (but slowly).
   

   Models constraints on the distribution of a feature's values.
   TODO(martinz): replace min_domain_mass with max_off_domain (but slowly).
   

   Protobuf type tensorflow.metadata.v0.DistributionConstraints

8.  trait DistributionConstraintsOrBuilder extends MessageOrBuilder
9.  final class Feature extends GeneratedMessageV3 with FeatureOrBuilder

   Describes schema-level information about a specific feature.
   NextID: 33
   

   Describes schema-level information about a specific feature.
   NextID: 33
   

   Protobuf type tensorflow.metadata.v0.Feature

10.  final class FeatureComparator extends GeneratedMessageV3 with FeatureComparatorOrBuilder

    Protobuf type tensorflow.metadata.v0.FeatureComparator

11.  trait FeatureComparatorOrBuilder extends MessageOrBuilder
12.  final class FeatureCoverageConstraints extends GeneratedMessageV3 with FeatureCoverageConstraintsOrBuilder

    Encodes vocabulary coverage constraints.
    

    Encodes vocabulary coverage constraints.
    

    Protobuf type tensorflow.metadata.v0.FeatureCoverageConstraints

13.  trait FeatureCoverageConstraintsOrBuilder extends MessageOrBuilder
14.  trait FeatureOrBuilder extends MessageOrBuilder
15.  final class FeaturePresence extends GeneratedMessageV3 with FeaturePresenceOrBuilder

    Describes constraints on the presence of the feature in the data.
    

    Describes constraints on the presence of the feature in the data.
    

    Protobuf type tensorflow.metadata.v0.FeaturePresence

16.  trait FeaturePresenceOrBuilder extends MessageOrBuilder
17.  final class FeaturePresenceWithinGroup extends GeneratedMessageV3 with FeaturePresenceWithinGroupOrBuilder

    Records constraints on the presence of a feature inside a "group" context
    (e.g., .presence inside a group of features that define a sequence).
    

    Records constraints on the presence of a feature inside a "group" context
    (e.g., .presence inside a group of features that define a sequence).
    

    Protobuf type tensorflow.metadata.v0.FeaturePresenceWithinGroup

18.  trait FeaturePresenceWithinGroupOrBuilder extends MessageOrBuilder
19.  sealed abstract final class FeatureType extends Enum[FeatureType] with ProtocolMessageEnum

    Describes the physical representation of a feature.
    It may be different than the logical representation, which
    is represented as a Domain.
    

    Describes the physical representation of a feature.
    It may be different than the logical representation, which
    is represented as a Domain.
    

    Protobuf enum tensorflow.metadata.v0.FeatureType

20.  final class FixedShape extends GeneratedMessageV3 with FixedShapeOrBuilder

    Specifies a fixed shape for the feature's values. The immediate implication
    is that each feature has a fixed number of values. Moreover, these values
    can be parsed in a multi-dimensional tensor using the specified axis sizes.
    The FixedShape defines a lexicographical ordering of the data. For instance,
    if there is a FixedShape {
      dim {size:3} dim {size:2}
    }
    then tensor[0][0]=field[0]
    then tensor[0][1]=field[1]
    then tensor[1][0]=field[2]
    then tensor[1][1]=field[3]
    then tensor[2][0]=field[4]
    then tensor[2][1]=field[5]
    The FixedShape message is identical with the TensorFlow TensorShape proto
    message.
    

    Specifies a fixed shape for the feature's values. The immediate implication
    is that each feature has a fixed number of values. Moreover, these values
    can be parsed in a multi-dimensional tensor using the specified axis sizes.
    The FixedShape defines a lexicographical ordering of the data. For instance,
    if there is a FixedShape {
      dim {size:3} dim {size:2}
    }
    then tensor[0][0]=field[0]
    then tensor[0][1]=field[1]
    then tensor[1][0]=field[2]
    then tensor[1][1]=field[3]
    then tensor[2][0]=field[4]
    then tensor[2][1]=field[5]
    The FixedShape message is identical with the TensorFlow TensorShape proto
    message.
    

    Protobuf type tensorflow.metadata.v0.FixedShape

21.  trait FixedShapeOrBuilder extends MessageOrBuilder
22.  final class FloatDomain extends GeneratedMessageV3 with FloatDomainOrBuilder

    Encodes information for domains of float values.
    Note that FeatureType could be either INT or BYTES.
    

    Encodes information for domains of float values.
    Note that FeatureType could be either INT or BYTES.
    

    Protobuf type tensorflow.metadata.v0.FloatDomain

23.  trait FloatDomainOrBuilder extends MessageOrBuilder
24.  final class ImageDomain extends GeneratedMessageV3 with ImageDomainOrBuilder

    Image data.
    

    Image data.
    

    Protobuf type tensorflow.metadata.v0.ImageDomain

25.  trait ImageDomainOrBuilder extends MessageOrBuilder
26.  final class InfinityNorm extends GeneratedMessageV3 with InfinityNormOrBuilder

    Checks that the L-infinity norm is below a certain threshold between the
    two discrete distributions. Since this is applied to a FeatureNameStatistics,
    it only considers the top k.
    L_infty(p,q) = max_i |p_i-q_i|
    

    Checks that the L-infinity norm is below a certain threshold between the
    two discrete distributions. Since this is applied to a FeatureNameStatistics,
    it only considers the top k.
    L_infty(p,q) = max_i |p_i-q_i|
    

    Protobuf type tensorflow.metadata.v0.InfinityNorm

27.  trait InfinityNormOrBuilder extends MessageOrBuilder
28.  final class IntDomain extends GeneratedMessageV3 with IntDomainOrBuilder

    Encodes information for domains of integer values.
    Note that FeatureType could be either INT or BYTES.
    

    Encodes information for domains of integer values.
    Note that FeatureType could be either INT or BYTES.
    

    Protobuf type tensorflow.metadata.v0.IntDomain

29.  trait IntDomainOrBuilder extends MessageOrBuilder
30.  final class JensenShannonDivergence extends GeneratedMessageV3 with JensenShannonDivergenceOrBuilder

    Checks that the approximate Jensen-Shannon Divergence is below a certain
    threshold between the two distributions.
    

    Checks that the approximate Jensen-Shannon Divergence is below a certain
    threshold between the two distributions.
    

    Protobuf type tensorflow.metadata.v0.JensenShannonDivergence

31.  trait JensenShannonDivergenceOrBuilder extends MessageOrBuilder
32.  sealed abstract final class LifecycleStage extends Enum[LifecycleStage] with ProtocolMessageEnum

    LifecycleStage. Only UNKNOWN_STAGE, BETA, and PRODUCTION features are
    actually validated.
    PLANNED, ALPHA, DISABLED, and DEBUG are treated as DEPRECATED.
    

    LifecycleStage. Only UNKNOWN_STAGE, BETA, and PRODUCTION features are
    actually validated.
    PLANNED, ALPHA, DISABLED, and DEBUG are treated as DEPRECATED.
    

    Protobuf enum tensorflow.metadata.v0.LifecycleStage

33.  final class MIDDomain extends GeneratedMessageV3 with MIDDomainOrBuilder

    Knowledge graph ID, see: https://www.wikidata.org/wiki/Property:P646
    

    Knowledge graph ID, see: https://www.wikidata.org/wiki/Property:P646
    

    Protobuf type tensorflow.metadata.v0.MIDDomain

34.  trait MIDDomainOrBuilder extends MessageOrBuilder
35.  final class NaturalLanguageDomain extends GeneratedMessageV3 with NaturalLanguageDomainOrBuilder

    Natural language text.
    Support for the fields in NaturalLanguageDomain is not ready so please do not
    use them.
    TODO(b/174175636): Remove warning once fields in NaturalLanguageDomain are
    supported.
    

    Natural language text.
    Support for the fields in NaturalLanguageDomain is not ready so please do not
    use them.
    TODO(b/174175636): Remove warning once fields in NaturalLanguageDomain are
    supported.
    

    Protobuf type tensorflow.metadata.v0.NaturalLanguageDomain

36.  trait NaturalLanguageDomainOrBuilder extends MessageOrBuilder
37.  final class NumericValueComparator extends GeneratedMessageV3 with NumericValueComparatorOrBuilder

    Checks that the ratio of the current value to the previous value is not below
    the min_fraction_threshold or above the max_fraction_threshold. That is,
    previous value * min_fraction_threshold <= current value <=
    previous value * max_fraction_threshold.
    To specify that the value cannot change, set both min_fraction_threshold and
    max_fraction_threshold to 1.0.
    

    Checks that the ratio of the current value to the previous value is not below
    the min_fraction_threshold or above the max_fraction_threshold. That is,
    previous value * min_fraction_threshold <= current value <=
    previous value * max_fraction_threshold.
    To specify that the value cannot change, set both min_fraction_threshold and
    max_fraction_threshold to 1.0.
    

    Protobuf type tensorflow.metadata.v0.NumericValueComparator

38.  trait NumericValueComparatorOrBuilder extends MessageOrBuilder
39.  final class Path extends GeneratedMessageV3 with PathOrBuilder

    A path is a more general substitute for the name of a field or feature that
    can be used for flat examples as well as structured data. For example, if
    we had data in a protocol buffer:
    message Person {
      int age = 1;
      optional string gender = 2;
      repeated Person parent = 3;
    }
    Thus, here the path {step:["parent", "age"]} in statistics would refer to the
    age of a parent, and {step:["parent", "parent", "age"]} would refer to the
    age of a grandparent. This allows us to distinguish between the statistics
    of parents' ages and grandparents' ages. In general, repeated messages are
    to be preferred to linked lists of arbitrary length.
    For SequenceExample, if we have a feature list "foo", this is represented
    by {step:["##SEQUENCE##", "foo"]}.
    

    A path is a more general substitute for the name of a field or feature that
    can be used for flat examples as well as structured data. For example, if
    we had data in a protocol buffer:
    message Person {
      int age = 1;
      optional string gender = 2;
      repeated Person parent = 3;
    }
    Thus, here the path {step:["parent", "age"]} in statistics would refer to the
    age of a parent, and {step:["parent", "parent", "age"]} would refer to the
    age of a grandparent. This allows us to distinguish between the statistics
    of parents' ages and grandparents' ages. In general, repeated messages are
    to be preferred to linked lists of arbitrary length.
    For SequenceExample, if we have a feature list "foo", this is represented
    by {step:["##SEQUENCE##", "foo"]}.
    

    Protobuf type tensorflow.metadata.v0.Path

40.  trait PathOrBuilder extends MessageOrBuilder
41.  final class PathOuterClass extends AnyRef
42.  final class Schema extends GeneratedMessageV3 with SchemaOrBuilder

    Message to represent schema information.
    NextID: 14
    

    Message to represent schema information.
    NextID: 14
    

    Protobuf type tensorflow.metadata.v0.Schema

43.  trait SchemaOrBuilder extends MessageOrBuilder
44.  final class SchemaOuterClass extends AnyRef
45.  final class SequenceValueConstraints extends GeneratedMessageV3 with SequenceValueConstraintsOrBuilder

    Encodes constraints on specific values in sequences.
    

    Encodes constraints on specific values in sequences.
    

    Protobuf type tensorflow.metadata.v0.SequenceValueConstraints

46.  trait SequenceValueConstraintsOrBuilder extends MessageOrBuilder
47.  final class SparseFeature extends GeneratedMessageV3 with SparseFeatureOrBuilder

    A sparse feature represents a sparse tensor that is encoded with a
    combination of raw features, namely index features and a value feature. Each
    index feature defines a list of indices in a different dimension.
    

    A sparse feature represents a sparse tensor that is encoded with a
    combination of raw features, namely index features and a value feature. Each
    index feature defines a list of indices in a different dimension.
    

    Protobuf type tensorflow.metadata.v0.SparseFeature

48.  trait SparseFeatureOrBuilder extends MessageOrBuilder
49.  final class StringDomain extends GeneratedMessageV3 with StringDomainOrBuilder

    Encodes information for domains of string values.
    

    Encodes information for domains of string values.
    

    Protobuf type tensorflow.metadata.v0.StringDomain

50.  trait StringDomainOrBuilder extends MessageOrBuilder
51.  final class StructDomain extends GeneratedMessageV3 with StructDomainOrBuilder

    Domain for a recursive struct.
    NOTE: If a feature with a StructDomain is deprecated, then all the
    child features (features and sparse_features of the StructDomain) are also
    considered to be deprecated.  Similarly child features can only be in
    environments of the parent feature.
    

    Domain for a recursive struct.
    NOTE: If a feature with a StructDomain is deprecated, then all the
    child features (features and sparse_features of the StructDomain) are also
    considered to be deprecated.  Similarly child features can only be in
    environments of the parent feature.
    

    Protobuf type tensorflow.metadata.v0.StructDomain

52.  trait StructDomainOrBuilder extends MessageOrBuilder
53.  final class TensorRepresentation extends GeneratedMessageV3 with TensorRepresentationOrBuilder

    A TensorRepresentation captures the intent for converting columns in a
    dataset to TensorFlow Tensors (or more generally, tf.CompositeTensors).
    Note that one tf.CompositeTensor may consist of data from multiple columns,
    for example, a N-dimensional tf.SparseTensor may need N + 1 columns to
    provide the sparse indices and values.
    Note that the "column name" that a TensorRepresentation needs is a
    string, not a Path -- it means that the column name identifies a top-level
    Feature in the schema (i.e. you cannot specify a Feature nested in a STRUCT
    Feature).
    

    A TensorRepresentation captures the intent for converting columns in a
    dataset to TensorFlow Tensors (or more generally, tf.CompositeTensors).
    Note that one tf.CompositeTensor may consist of data from multiple columns,
    for example, a N-dimensional tf.SparseTensor may need N + 1 columns to
    provide the sparse indices and values.
    Note that the "column name" that a TensorRepresentation needs is a
    string, not a Path -- it means that the column name identifies a top-level
    Feature in the schema (i.e. you cannot specify a Feature nested in a STRUCT
    Feature).
    

    Protobuf type tensorflow.metadata.v0.TensorRepresentation

54.  final class TensorRepresentationGroup extends GeneratedMessageV3 with TensorRepresentationGroupOrBuilder

    A TensorRepresentationGroup is a collection of TensorRepresentations with
    names. These names may serve as identifiers when converting the dataset
    to a collection of Tensors or tf.CompositeTensors.
    For example, given the following group:
    {
      key: "dense_tensor"
      tensor_representation {
        dense_tensor {
          column_name: "univalent_feature"
          shape {
            dim {
              size: 1
            }
          }
          default_value {
            float_value: 0
          }
        }
      }
    }
    {
      key: "varlen_sparse_tensor"
      tensor_representation {
        varlen_sparse_tensor {
          column_name: "multivalent_feature"
        }
      }
    }
    Then the schema is expected to have feature "univalent_feature" and
    "multivalent_feature", and when a batch of data is converted to Tensors using
    this TensorRepresentationGroup, the result may be the following dict:
    {
      "dense_tensor": tf.Tensor(...),
      "varlen_sparse_tensor": tf.SparseTensor(...),
    }
    

    A TensorRepresentationGroup is a collection of TensorRepresentations with
    names. These names may serve as identifiers when converting the dataset
    to a collection of Tensors or tf.CompositeTensors.
    For example, given the following group:
    {
      key: "dense_tensor"
      tensor_representation {
        dense_tensor {
          column_name: "univalent_feature"
          shape {
            dim {
              size: 1
            }
          }
          default_value {
            float_value: 0
          }
        }
      }
    }
    {
      key: "varlen_sparse_tensor"
      tensor_representation {
        varlen_sparse_tensor {
          column_name: "multivalent_feature"
        }
      }
    }
    Then the schema is expected to have feature "univalent_feature" and
    "multivalent_feature", and when a batch of data is converted to Tensors using
    this TensorRepresentationGroup, the result may be the following dict:
    {
      "dense_tensor": tf.Tensor(...),
      "varlen_sparse_tensor": tf.SparseTensor(...),
    }
    

    Protobuf type tensorflow.metadata.v0.TensorRepresentationGroup

55.  trait TensorRepresentationGroupOrBuilder extends MessageOrBuilder
56.  trait TensorRepresentationOrBuilder extends MessageOrBuilder
57.  final class TimeDomain extends GeneratedMessageV3 with TimeDomainOrBuilder

    Time or date representation.
    

    Time or date representation.
    

    Protobuf type tensorflow.metadata.v0.TimeDomain

58.  trait TimeDomainOrBuilder extends MessageOrBuilder
59.  final class TimeOfDayDomain extends GeneratedMessageV3 with TimeOfDayDomainOrBuilder

    Time of day, without a particular date.
    

    Time of day, without a particular date.
    

    Protobuf type tensorflow.metadata.v0.TimeOfDayDomain

60.  trait TimeOfDayDomainOrBuilder extends MessageOrBuilder
61.  final class URLDomain extends GeneratedMessageV3 with URLDomainOrBuilder

    A URL, see: https://en.wikipedia.org/wiki/URL
    

    A URL, see: https://en.wikipedia.org/wiki/URL
    

    Protobuf type tensorflow.metadata.v0.URLDomain

62.  trait URLDomainOrBuilder extends MessageOrBuilder
63.  final class UniqueConstraints extends GeneratedMessageV3 with UniqueConstraintsOrBuilder

    Checks that the number of unique values is greater than or equal to the min,
    and less than or equal to the max.
    

    Checks that the number of unique values is greater than or equal to the min,
    and less than or equal to the max.
    

    Protobuf type tensorflow.metadata.v0.UniqueConstraints

64.  trait UniqueConstraintsOrBuilder extends MessageOrBuilder
65.  final class ValueCount extends GeneratedMessageV3 with ValueCountOrBuilder

    Limits on maximum and minimum number of values in a
    single example (when the feature is present). Use this when the minimum
    value count can be different than the maximum value count. Otherwise prefer
    FixedShape.
    

    Limits on maximum and minimum number of values in a
    single example (when the feature is present). Use this when the minimum
    value count can be different than the maximum value count. Otherwise prefer
    FixedShape.
    

    Protobuf type tensorflow.metadata.v0.ValueCount

66.  final class ValueCountList extends GeneratedMessageV3 with ValueCountListOrBuilder

    Protobuf type tensorflow.metadata.v0.ValueCountList

67.  trait ValueCountListOrBuilder extends MessageOrBuilder
68.  trait ValueCountOrBuilder extends MessageOrBuilder
69.  final class WeightedFeature extends GeneratedMessageV3 with WeightedFeatureOrBuilder

    Represents a weighted feature that is encoded as a combination of raw base
    features. The `weight_feature` should be a float feature with identical
    shape as the `feature`. This is useful for representing weights associated
    with categorical tokens (e.g. a TFIDF weight associated with each token).
    TODO(b/142122960): Handle WeightedCategorical end to end in TFX (validation,
    TFX Unit Testing, etc)
    

    Represents a weighted feature that is encoded as a combination of raw base
    features. The `weight_feature` should be a float feature with identical
    shape as the `feature`. This is useful for representing weights associated
    with categorical tokens (e.g. a TFIDF weight associated with each token).
    TODO(b/142122960): Handle WeightedCategorical end to end in TFX (validation,
    TFX Unit Testing, etc)
    

    Protobuf type tensorflow.metadata.v0.WeightedFeature

70.  trait WeightedFeatureOrBuilder extends MessageOrBuilder