Package org.tensorflow.framework

Enum Class FullTypeId

java.lang.Object
java.lang.Enum<FullTypeId>
org.tensorflow.framework.FullTypeId
All Implemented Interfaces:
com.google.protobuf.Internal.EnumLite, com.google.protobuf.ProtocolMessageEnum, Serializable, Comparable<FullTypeId>, Constable
public enum FullTypeId extends Enum<FullTypeId> implements com.google.protobuf.ProtocolMessageEnum
 LINT.IfChange
 Experimental. Represents the complete type information of a TensorFlow value.
Protobuf enum tensorflow.FullTypeId

  • Enum Constant Details

    • TFT_UNSET

      public static final FullTypeId TFT_UNSET
       The default represents an uninitialized values.
      TFT_UNSET = 0;

    • TFT_VAR

      public static final FullTypeId TFT_VAR
       Type variables may serve as placeholder for any other type ID in type
 templates.

 Examples:
   TFT_DATASET[TFT_VAR["T"]] is a Dataset returning a type indicated by "T".
   TFT_TENSOR[TFT_VAR["T"]] is a Tensor of n element type indicated by "T".
   TFT_TENSOR[TFT_VAR["T"]], TFT_TENSOR[TFT_VAR["T"]] are two tensors of
     identical element types.
   TFT_TENSOR[TFT_VAR["P"]], TFT_TENSOR[TFT_VAR["Q"]] are two tensors of
     independent element types.
      TFT_VAR = 1;

    • TFT_ANY

      public static final FullTypeId TFT_ANY
       Wildcard type. Describes a parameter of unknown type. In TensorFlow, that
 can mean either a "Top" type (accepts any type), or a dynamically typed
 object whose type is unknown in context.
 Important: "unknown" does not necessarily mean undeterminable!
      TFT_ANY = 2;

    • TFT_PRODUCT

      public static final FullTypeId TFT_PRODUCT
       The algebraic product type. This is an algebraic type that may be used just
 for logical grouping. Not to confused with TFT_TUPLE which describes a
 concrete object of several elements.

 Example:
   TFT_DATASET[TFT_PRODUCT[TFT_TENSOR[TFT_INT32], TFT_TENSOR[TFT_FLOAT64]]]
     is a Dataset producing two tensors, an integer one and a float one.
      TFT_PRODUCT = 3;

    • TFT_NAMED

      public static final FullTypeId TFT_NAMED
       Represents a named field, with the name stored in the attribute.

 Parametrization:
   TFT_NAMED[<type>]{<name>}
   * <type> is the type of the field
   * <name> is the field name, as string (thpugh can theoretically be an int
     as well)

 Example:
   TFT_RECORD[
     TFT_NAMED[TFT_TENSOR[TFT_INT32]]{'foo'},
     TFT_NAMED[TFT_TENSOR[TFT_FLOAT32]]{'bar'},
   ]
     is a structure with two fields, an int tensor "foo" and a float tensor
     "bar".
      TFT_NAMED = 4;

    • TFT_FOR_EACH

      public static final FullTypeId TFT_FOR_EACH
       Template definition. Expands the variables by repeating a template as
 arguments of container.

 Parametrization:
   TFT_FOR_EACH[<container_type>, <template>, <expansions>]
   * <container_type> is the type of the container that the template will be
     expanded into
   * <template> is any type definition that potentially contains type
     variables
   * <expansions> is a TFT_VAR and may include more types in the future

 Example:
   TFT_FOR_EACH[
         TFT_PRODUCT,
         TFT_TENSOR[TFT_VAR["t"]],
         TFT_VAR["t"]
     ]
     will substitute a T = TFT_INT32 to TFT_PRODUCT[TFT_TENSOR[TFT_INT32]]
     and a T = (TFT_INT32, TFT_INT64) to
     TFT_PRODUCT[TFT_TENSOR[TFT_INT32], TFT_TENSOR[TFT_INT64]].
      TFT_FOR_EACH = 20;

    • TFT_CALLABLE

      public static final FullTypeId TFT_CALLABLE
       Callable types describe functions and ops.

 Parametrization:
   TFT_CALLABLE[<arg type>, <return type>]
   * <arg type> is the type of the arguments; TFT_PRODUCT represents
   multiple
     arguments.
   * <return type> is the return type; TFT_PRODUCT represents multiple
     return values (that means that callables returning multiple things
     don't necessarily return a single tuple).

 Example:
   TFT_CALLABLE[
     TFT_ANY,
     TFT_PRODUCT[TFT_TENSOR[TFT_INT32], TFT_TENSOR[TFT_FLOAT64]],
   ]
     is a callable with unspecified (for now) input arguments, and
     two return values of type tensor.
      TFT_CALLABLE = 100;

    • TFT_TENSOR

      public static final FullTypeId TFT_TENSOR
       The usual Tensor. This is a parametric type.

 Parametrization:
   TFT_TENSOR[<element type>, <shape type>]
   * <element type> is currently limited to one of the element types
     defined below.
   * <shape type> is not yet defined, and may only be TFT_UNKNOWN for now.

 A TFT_SHAPE type will be defined in the future.

 Example:
   TFT_TENSOR[TFT_INT32, TFT_UNKNOWN]
     is a Tensor of int32 element type and unknown shape.

 TODO(mdan): Define TFT_SHAPE and add more examples.
      TFT_TENSOR = 1000;

    • TFT_ARRAY

      public static final FullTypeId TFT_ARRAY
       Array (or tensorflow::TensorList in the variant type registry).
 Note: this is not to be confused with the deprecated `TensorArray*` ops
 which are not supported by FullType.
 This type represents a random-access list whose elements can be
 described by a single type. Although immutable, Array is expected to
 support efficient mutation semantics (i.e. element update) in the
 user-facing API.
 The element type may be generic or even TFT_ANY for a heterogenous list.

 Parametrization:
   TFT_ARRAY[<element type>]
   * <element type> may be any concrete type.

 Examples:
   TFT_ARRAY[TFT_TENSOR[TFT_INT32]] is a TensorArray holding int32 Tensors
     of any shape.
   TFT_ARRAY[TFT_TENSOR[TFT_UNKNOWN]] is a TensorArray holding Tensors of
     mixed element types.
   TFT_ARRAY[TFT_UNKNOWN] is a TensorArray holding any element type.
   TFT_ARRAY[] is equivalent to TFT_ARRAY[TFT_UNKNOWN].
   TFT_ARRAY[TFT_ARRAY[]] is an array or arrays (of unknown types).
      TFT_ARRAY = 1001;

    • TFT_OPTIONAL

      public static final FullTypeId TFT_OPTIONAL
       Optional (or tensorflow::OptionalVariant in the variant type registry).
 This type represents a value that may either hold an element of a single
 specified type, or nothing at all.

 Parametrization:
   TFT_OPTIONAL[<element type>]
   * <element type> may be any concrete type.

 Examples:
   TFT_OPTIONAL[TFT_TENSOR[TFT_INT32]] is an Optional holding an int32
     Tensor of any shape.
      TFT_OPTIONAL = 1002;

    • TFT_LITERAL

      public static final FullTypeId TFT_LITERAL
       Literal types describe compile-time constant values.
 Literal types may also participate in dependent types.

 Parametrization:
   TFT_LITERAL[<value type>]{<value>}
   * <value type> may be any concrete type compatible that can hold <value>
   * <value> is the type's attribute, and holds the actual literal value

 Examples:
   TFT_LITERAL[TFT_INT32]{1} is the compile-time constant 1.
      TFT_LITERAL = 1003;

    • TFT_ENCODED

      public static final FullTypeId TFT_ENCODED
       Encoding types describe a value of a certain type, encoded as a different
 type.

 Parametrization:
   TFT_ENCODED[<encoded type>, <encoding type>]
   * <encoded type> may be any type
   * <encoding type> may be any type

 Examples:
   TFT_ENCODING[TFT_INT32, TFT_STRING] is an integer encoded as string.
      TFT_ENCODED = 1004;

    • TFT_SHAPE_TENSOR

      public static final FullTypeId TFT_SHAPE_TENSOR
       The type of "shape tensors" where the runtime value is the shape of
 some tensor(s), i.e. the output of tf.shape.
 Shape tensors have special, host-only placement, in contrast to
 TFT_TENSOR[TFT_INT32] which is the type of a normal numeric tensor
 with no special placement.

 Examples:
   TFT_SHAPE_TENSOR[TFT_INT32] is the most common
   TFT_SHAPE_TENSOR[TFT_INT64] is also allowed
      TFT_SHAPE_TENSOR = 1005;

    • TFT_BOOL

      public static final FullTypeId TFT_BOOL
       The bool element type.
 TODO(mdan): Quantized types, legacy representations (e.g. ref)
      TFT_BOOL = 200;

    • TFT_UINT8

      public static final FullTypeId TFT_UINT8
       Integer element types.
      TFT_UINT8 = 201;

    • TFT_UINT16

      public static final FullTypeId TFT_UINT16
      TFT_UINT16 = 202;

    • TFT_UINT32

      public static final FullTypeId TFT_UINT32
      TFT_UINT32 = 203;

    • TFT_UINT64

      public static final FullTypeId TFT_UINT64
      TFT_UINT64 = 204;

    • TFT_INT8

      public static final FullTypeId TFT_INT8
      TFT_INT8 = 205;

    • TFT_INT16

      public static final FullTypeId TFT_INT16
      TFT_INT16 = 206;

    • TFT_INT32

      public static final FullTypeId TFT_INT32
      TFT_INT32 = 207;

    • TFT_INT64

      public static final FullTypeId TFT_INT64
      TFT_INT64 = 208;

    • TFT_HALF

      public static final FullTypeId TFT_HALF
       Floating-point element types.
      TFT_HALF = 209;

    • TFT_FLOAT

      public static final FullTypeId TFT_FLOAT
      TFT_FLOAT = 210;

    • TFT_DOUBLE

      public static final FullTypeId TFT_DOUBLE
      TFT_DOUBLE = 211;

    • TFT_BFLOAT16

      public static final FullTypeId TFT_BFLOAT16
      TFT_BFLOAT16 = 215;

    • TFT_COMPLEX64

      public static final FullTypeId TFT_COMPLEX64
       Complex element types.
 TODO(mdan): Represent as TFT_COMPLEX[TFT_DOUBLE] instead?
      TFT_COMPLEX64 = 212;

    • TFT_COMPLEX128

      public static final FullTypeId TFT_COMPLEX128
      TFT_COMPLEX128 = 213;

    • TFT_STRING

      public static final FullTypeId TFT_STRING
       The string element type.
      TFT_STRING = 214;

    • TFT_DATASET

      public static final FullTypeId TFT_DATASET
       Datasets created by tf.data ops and APIs. Datasets have generator/iterable
 semantics, that is, one can construct an iterator from them. Like
 Array, they are considered to return elements that can be described
 by a single type. Unlike Array, they do not support random access or
 mutation, and can potentially produce an infinite number of elements.
 A datasets can produce logical structures (e.g. multiple elements). This
 is expressed using TFT_PRODUCT.


 Parametrization: TFT_DATASET[<element type>].
   * <element type> may be a concrete type or a type symbol. It represents
     the data type of the elements produced by the dataset.

 Examples:
   TFT_DATSET[TFT_TENSOR[TFT_INT32]] is a Dataset producing single int32
     Tensors of unknown shape.
   TFT_DATSET[TFT_PRODUCT[TFT_TENSOR[TFT_INT32], TFT_TENSOR[TFT_FLOAT32]] is
     a Dataset producing pairs of Tensors, one integer and one float.
 Note: The high ID number is to prepare for the eventuality that Datasets
 will be supported by user types in the future.
      TFT_DATASET = 10102;

    • TFT_RAGGED

      public static final FullTypeId TFT_RAGGED
       A ragged tensor created by tf.ragged ops and APIs.

 Parametrization: TFT_RAGGED[<element_type>].
      TFT_RAGGED = 10103;

    • TFT_ITERATOR

      public static final FullTypeId TFT_ITERATOR
       Iterators created by tf.data ops and APIs. Very similar to Datasets, except
 they are mutable.


 Parametrization: TFT_ITERATOR[<element type>].
   * <element type> may be a concrete type or a type symbol. It represents
     the data type of the elements produced by the dataset.
      TFT_ITERATOR = 10104;

    • TFT_MUTEX_LOCK

      public static final FullTypeId TFT_MUTEX_LOCK
       A mutex lock tensor, produced by tf.raw_ops.MutexLock.
 Unlike strict execution models, where ownership of a lock is denoted by
 "running after the lock has been acquired", in non-strict mode, lock
 ownership is in the true sense: "the op argument representing the lock is
 available".
 Mutex locks are the dynamic counterpart of control dependencies.
 TODO(mdan): Properly document this thing.

 Parametrization: TFT_MUTEX_LOCK[].
      TFT_MUTEX_LOCK = 10202;

    • TFT_LEGACY_VARIANT

      public static final FullTypeId TFT_LEGACY_VARIANT
       The equivalent of a Tensor with DT_VARIANT dtype, kept here to simplify
 translation. This type should not normally appear after type inference.
 Note that LEGACY_VARIANT != ANY: TENSOR[INT32] is a subtype of ANY, but is
 not a subtype of LEGACY_VARIANT.
      TFT_LEGACY_VARIANT = 10203;

    • UNRECOGNIZED

      public static final FullTypeId UNRECOGNIZED

  • Field Details

    • TFT_UNSET_VALUE

      public static final int TFT_UNSET_VALUE
       The default represents an uninitialized values.
      TFT_UNSET = 0;
      See Also:

    • TFT_VAR_VALUE

      public static final int TFT_VAR_VALUE
       Type variables may serve as placeholder for any other type ID in type
 templates.

 Examples:
   TFT_DATASET[TFT_VAR["T"]] is a Dataset returning a type indicated by "T".
   TFT_TENSOR[TFT_VAR["T"]] is a Tensor of n element type indicated by "T".
   TFT_TENSOR[TFT_VAR["T"]], TFT_TENSOR[TFT_VAR["T"]] are two tensors of
     identical element types.
   TFT_TENSOR[TFT_VAR["P"]], TFT_TENSOR[TFT_VAR["Q"]] are two tensors of
     independent element types.
      TFT_VAR = 1;
      See Also:

    • TFT_ANY_VALUE

      public static final int TFT_ANY_VALUE
       Wildcard type. Describes a parameter of unknown type. In TensorFlow, that
 can mean either a "Top" type (accepts any type), or a dynamically typed
 object whose type is unknown in context.
 Important: "unknown" does not necessarily mean undeterminable!
      TFT_ANY = 2;
      See Also:

    • TFT_PRODUCT_VALUE

      public static final int TFT_PRODUCT_VALUE
       The algebraic product type. This is an algebraic type that may be used just
 for logical grouping. Not to confused with TFT_TUPLE which describes a
 concrete object of several elements.

 Example:
   TFT_DATASET[TFT_PRODUCT[TFT_TENSOR[TFT_INT32], TFT_TENSOR[TFT_FLOAT64]]]
     is a Dataset producing two tensors, an integer one and a float one.
      TFT_PRODUCT = 3;
      See Also:

    • TFT_NAMED_VALUE

      public static final int TFT_NAMED_VALUE
       Represents a named field, with the name stored in the attribute.

 Parametrization:
   TFT_NAMED[<type>]{<name>}
   * <type> is the type of the field
   * <name> is the field name, as string (thpugh can theoretically be an int
     as well)

 Example:
   TFT_RECORD[
     TFT_NAMED[TFT_TENSOR[TFT_INT32]]{'foo'},
     TFT_NAMED[TFT_TENSOR[TFT_FLOAT32]]{'bar'},
   ]
     is a structure with two fields, an int tensor "foo" and a float tensor
     "bar".
      TFT_NAMED = 4;
      See Also:

    • TFT_FOR_EACH_VALUE

      public static final int TFT_FOR_EACH_VALUE
       Template definition. Expands the variables by repeating a template as
 arguments of container.

 Parametrization:
   TFT_FOR_EACH[<container_type>, <template>, <expansions>]
   * <container_type> is the type of the container that the template will be
     expanded into
   * <template> is any type definition that potentially contains type
     variables
   * <expansions> is a TFT_VAR and may include more types in the future

 Example:
   TFT_FOR_EACH[
         TFT_PRODUCT,
         TFT_TENSOR[TFT_VAR["t"]],
         TFT_VAR["t"]
     ]
     will substitute a T = TFT_INT32 to TFT_PRODUCT[TFT_TENSOR[TFT_INT32]]
     and a T = (TFT_INT32, TFT_INT64) to
     TFT_PRODUCT[TFT_TENSOR[TFT_INT32], TFT_TENSOR[TFT_INT64]].
      TFT_FOR_EACH = 20;
      See Also:

    • TFT_CALLABLE_VALUE

      public static final int TFT_CALLABLE_VALUE
       Callable types describe functions and ops.

 Parametrization:
   TFT_CALLABLE[<arg type>, <return type>]
   * <arg type> is the type of the arguments; TFT_PRODUCT represents
   multiple
     arguments.
   * <return type> is the return type; TFT_PRODUCT represents multiple
     return values (that means that callables returning multiple things
     don't necessarily return a single tuple).

 Example:
   TFT_CALLABLE[
     TFT_ANY,
     TFT_PRODUCT[TFT_TENSOR[TFT_INT32], TFT_TENSOR[TFT_FLOAT64]],
   ]
     is a callable with unspecified (for now) input arguments, and
     two return values of type tensor.
      TFT_CALLABLE = 100;
      See Also:

    • TFT_TENSOR_VALUE

      public static final int TFT_TENSOR_VALUE
       The usual Tensor. This is a parametric type.

 Parametrization:
   TFT_TENSOR[<element type>, <shape type>]
   * <element type> is currently limited to one of the element types
     defined below.
   * <shape type> is not yet defined, and may only be TFT_UNKNOWN for now.

 A TFT_SHAPE type will be defined in the future.

 Example:
   TFT_TENSOR[TFT_INT32, TFT_UNKNOWN]
     is a Tensor of int32 element type and unknown shape.

 TODO(mdan): Define TFT_SHAPE and add more examples.
      TFT_TENSOR = 1000;
      See Also:

    • TFT_ARRAY_VALUE

      public static final int TFT_ARRAY_VALUE
       Array (or tensorflow::TensorList in the variant type registry).
 Note: this is not to be confused with the deprecated `TensorArray*` ops
 which are not supported by FullType.
 This type represents a random-access list whose elements can be
 described by a single type. Although immutable, Array is expected to
 support efficient mutation semantics (i.e. element update) in the
 user-facing API.
 The element type may be generic or even TFT_ANY for a heterogenous list.

 Parametrization:
   TFT_ARRAY[<element type>]
   * <element type> may be any concrete type.

 Examples:
   TFT_ARRAY[TFT_TENSOR[TFT_INT32]] is a TensorArray holding int32 Tensors
     of any shape.
   TFT_ARRAY[TFT_TENSOR[TFT_UNKNOWN]] is a TensorArray holding Tensors of
     mixed element types.
   TFT_ARRAY[TFT_UNKNOWN] is a TensorArray holding any element type.
   TFT_ARRAY[] is equivalent to TFT_ARRAY[TFT_UNKNOWN].
   TFT_ARRAY[TFT_ARRAY[]] is an array or arrays (of unknown types).
      TFT_ARRAY = 1001;
      See Also:

    • TFT_OPTIONAL_VALUE

      public static final int TFT_OPTIONAL_VALUE
       Optional (or tensorflow::OptionalVariant in the variant type registry).
 This type represents a value that may either hold an element of a single
 specified type, or nothing at all.

 Parametrization:
   TFT_OPTIONAL[<element type>]
   * <element type> may be any concrete type.

 Examples:
   TFT_OPTIONAL[TFT_TENSOR[TFT_INT32]] is an Optional holding an int32
     Tensor of any shape.
      TFT_OPTIONAL = 1002;
      See Also:

    • TFT_LITERAL_VALUE

      public static final int TFT_LITERAL_VALUE
       Literal types describe compile-time constant values.
 Literal types may also participate in dependent types.

 Parametrization:
   TFT_LITERAL[<value type>]{<value>}
   * <value type> may be any concrete type compatible that can hold <value>
   * <value> is the type's attribute, and holds the actual literal value

 Examples:
   TFT_LITERAL[TFT_INT32]{1} is the compile-time constant 1.
      TFT_LITERAL = 1003;
      See Also:

    • TFT_ENCODED_VALUE

      public static final int TFT_ENCODED_VALUE
       Encoding types describe a value of a certain type, encoded as a different
 type.

 Parametrization:
   TFT_ENCODED[<encoded type>, <encoding type>]
   * <encoded type> may be any type
   * <encoding type> may be any type

 Examples:
   TFT_ENCODING[TFT_INT32, TFT_STRING] is an integer encoded as string.
      TFT_ENCODED = 1004;
      See Also:

    • TFT_SHAPE_TENSOR_VALUE

      public static final int TFT_SHAPE_TENSOR_VALUE
       The type of "shape tensors" where the runtime value is the shape of
 some tensor(s), i.e. the output of tf.shape.
 Shape tensors have special, host-only placement, in contrast to
 TFT_TENSOR[TFT_INT32] which is the type of a normal numeric tensor
 with no special placement.

 Examples:
   TFT_SHAPE_TENSOR[TFT_INT32] is the most common
   TFT_SHAPE_TENSOR[TFT_INT64] is also allowed
      TFT_SHAPE_TENSOR = 1005;
      See Also:

    • TFT_BOOL_VALUE

      public static final int TFT_BOOL_VALUE
       The bool element type.
 TODO(mdan): Quantized types, legacy representations (e.g. ref)
      TFT_BOOL = 200;
      See Also:

    • TFT_UINT8_VALUE

      public static final int TFT_UINT8_VALUE
       Integer element types.
      TFT_UINT8 = 201;
      See Also:

    • TFT_UINT16_VALUE

      public static final int TFT_UINT16_VALUE
      TFT_UINT16 = 202;
      See Also:

    • TFT_UINT32_VALUE

      public static final int TFT_UINT32_VALUE
      TFT_UINT32 = 203;
      See Also:

    • TFT_UINT64_VALUE

      public static final int TFT_UINT64_VALUE
      TFT_UINT64 = 204;
      See Also:

    • TFT_INT8_VALUE

      public static final int TFT_INT8_VALUE
      TFT_INT8 = 205;
      See Also:

    • TFT_INT16_VALUE

      public static final int TFT_INT16_VALUE
      TFT_INT16 = 206;
      See Also:

    • TFT_INT32_VALUE

      public static final int TFT_INT32_VALUE
      TFT_INT32 = 207;
      See Also:

    • TFT_INT64_VALUE

      public static final int TFT_INT64_VALUE
      TFT_INT64 = 208;
      See Also:

    • TFT_HALF_VALUE

      public static final int TFT_HALF_VALUE
       Floating-point element types.
      TFT_HALF = 209;
      See Also:

    • TFT_FLOAT_VALUE

      public static final int TFT_FLOAT_VALUE
      TFT_FLOAT = 210;
      See Also:

    • TFT_DOUBLE_VALUE

      public static final int TFT_DOUBLE_VALUE
      TFT_DOUBLE = 211;
      See Also:

    • TFT_BFLOAT16_VALUE

      public static final int TFT_BFLOAT16_VALUE
      TFT_BFLOAT16 = 215;
      See Also:

    • TFT_COMPLEX64_VALUE

      public static final int TFT_COMPLEX64_VALUE
       Complex element types.
 TODO(mdan): Represent as TFT_COMPLEX[TFT_DOUBLE] instead?
      TFT_COMPLEX64 = 212;
      See Also:

    • TFT_COMPLEX128_VALUE

      public static final int TFT_COMPLEX128_VALUE
      TFT_COMPLEX128 = 213;
      See Also:

    • TFT_STRING_VALUE

      public static final int TFT_STRING_VALUE
       The string element type.
      TFT_STRING = 214;
      See Also:

    • TFT_DATASET_VALUE

      public static final int TFT_DATASET_VALUE
       Datasets created by tf.data ops and APIs. Datasets have generator/iterable
 semantics, that is, one can construct an iterator from them. Like
 Array, they are considered to return elements that can be described
 by a single type. Unlike Array, they do not support random access or
 mutation, and can potentially produce an infinite number of elements.
 A datasets can produce logical structures (e.g. multiple elements). This
 is expressed using TFT_PRODUCT.


 Parametrization: TFT_DATASET[<element type>].
   * <element type> may be a concrete type or a type symbol. It represents
     the data type of the elements produced by the dataset.

 Examples:
   TFT_DATSET[TFT_TENSOR[TFT_INT32]] is a Dataset producing single int32
     Tensors of unknown shape.
   TFT_DATSET[TFT_PRODUCT[TFT_TENSOR[TFT_INT32], TFT_TENSOR[TFT_FLOAT32]] is
     a Dataset producing pairs of Tensors, one integer and one float.
 Note: The high ID number is to prepare for the eventuality that Datasets
 will be supported by user types in the future.
      TFT_DATASET = 10102;
      See Also:

    • TFT_RAGGED_VALUE

      public static final int TFT_RAGGED_VALUE
       A ragged tensor created by tf.ragged ops and APIs.

 Parametrization: TFT_RAGGED[<element_type>].
      TFT_RAGGED = 10103;
      See Also:

    • TFT_ITERATOR_VALUE

      public static final int TFT_ITERATOR_VALUE
       Iterators created by tf.data ops and APIs. Very similar to Datasets, except
 they are mutable.


 Parametrization: TFT_ITERATOR[<element type>].
   * <element type> may be a concrete type or a type symbol. It represents
     the data type of the elements produced by the dataset.
      TFT_ITERATOR = 10104;
      See Also:

    • TFT_MUTEX_LOCK_VALUE

      public static final int TFT_MUTEX_LOCK_VALUE
       A mutex lock tensor, produced by tf.raw_ops.MutexLock.
 Unlike strict execution models, where ownership of a lock is denoted by
 "running after the lock has been acquired", in non-strict mode, lock
 ownership is in the true sense: "the op argument representing the lock is
 available".
 Mutex locks are the dynamic counterpart of control dependencies.
 TODO(mdan): Properly document this thing.

 Parametrization: TFT_MUTEX_LOCK[].
      TFT_MUTEX_LOCK = 10202;
      See Also:

    • TFT_LEGACY_VARIANT_VALUE

      public static final int TFT_LEGACY_VARIANT_VALUE
       The equivalent of a Tensor with DT_VARIANT dtype, kept here to simplify
 translation. This type should not normally appear after type inference.
 Note that LEGACY_VARIANT != ANY: TENSOR[INT32] is a subtype of ANY, but is
 not a subtype of LEGACY_VARIANT.
      TFT_LEGACY_VARIANT = 10203;
      See Also:

  • Method Details

    • values

      public static FullTypeId[] values()
      Returns an array containing the constants of this enum class, in the order they are declared.
      Returns:
      an array containing the constants of this enum class, in the order they are declared

    • valueOf

      public static FullTypeId valueOf(String name)
      Returns the enum constant of this class with the specified name. The string must match exactly an identifier used to declare an enum constant in this class. (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 class 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 FullTypeId valueOf(int value)
      Deprecated.
      Returns the enum constant of this class with the specified name. The string must match exactly an identifier used to declare an enum constant in this class. (Extraneous whitespace characters are not permitted.)
      Parameters:
      value - the name of the enum constant to be returned.
      Returns:
      the enum constant with the specified name
      Throws:
      IllegalArgumentException - if this enum class has no constant with the specified name
      NullPointerException - if the argument is null

    • forNumber

      public static FullTypeId 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<FullTypeId> 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 FullTypeId valueOf(com.google.protobuf.Descriptors.EnumValueDescriptor desc)
      Returns the enum constant of this class with the specified name. The string must match exactly an identifier used to declare an enum constant in this class. (Extraneous whitespace characters are not permitted.)
      Parameters:
      desc - the name of the enum constant to be returned.
      Returns:
      the enum constant with the specified name
      Throws:
      IllegalArgumentException - if this enum class has no constant with the specified name
      NullPointerException - if the argument is null