org.tensorflow.op.core

Classes

Abort Raise a exception to abort the process when called. 
Abort.Options Optional attributes for Abort  
All Computes the "logical and" of elements across dimensions of a tensor. 
All.Options Optional attributes for All  
Any Computes the "logical or" of elements across dimensions of a tensor. 
Any.Options Optional attributes for Any  
AssertThat Asserts that the given condition is true. 
AssertThat.Options Optional attributes for AssertThat  
Assign<T extends TType> Update 'ref' by assigning 'value' to it. 
Assign.Options Optional attributes for Assign  
AssignAdd<T extends TType> Update 'ref' by adding 'value' to it. 
AssignAdd.Options Optional attributes for AssignAdd  
AssignAddVariableOp Adds a value to the current value of a variable. 
AssignSub<T extends TType> Update 'ref' by subtracting 'value' from it. 
AssignSub.Options Optional attributes for AssignSub  
AssignSubVariableOp Subtracts a value from the current value of a variable. 
AssignVariableOp Assigns a new value to a variable. 
Barrier Defines a barrier that persists across different graph executions. 
Barrier.Options Optional attributes for Barrier  
BarrierClose Closes the given barrier. 
BarrierClose.Options Optional attributes for BarrierClose  
BarrierIncompleteSize Computes the number of incomplete elements in the given barrier. 
BarrierInsertMany For each key, assigns the respective value to the specified component. 
BarrierReadySize Computes the number of complete elements in the given barrier. 
BarrierTakeMany Takes the given number of completed elements from a barrier. 
BarrierTakeMany.Options Optional attributes for BarrierTakeMany  
Batch Batches all input tensors nondeterministically. 
Batch.Options Optional attributes for Batch  
BatchToSpace<T extends TType> BatchToSpace for 4-D tensors of type T. 
BatchToSpaceNd<T extends TType> BatchToSpace for N-D tensors of type T. 
Bitcast<U extends TType> Bitcasts a tensor from one type to another without copying data. 
BooleanMask  
BooleanMask.Options Optional attributes for BooleanMask  
BooleanMaskUpdate  
BooleanMaskUpdate.Options Optional attributes for BooleanMaskUpdate  
BroadcastDynamicShape<T extends TNumber> Return the shape of s0 op s1 with broadcast. 
BroadcastGradientArgs<T extends TNumber> Return the reduction indices for computing gradients of s0 op s1 with broadcast. 
BroadcastTo<T extends TType> Broadcast an array for a compatible shape. 
Bucketize Bucketizes 'input' based on 'boundaries'. 
ClipByValue<T extends TType> Clips tensor values to a specified min and max. 
CollectiveGather<T extends TNumber> Mutually accumulates multiple tensors of identical type and shape. 
CollectiveGather.Options Optional attributes for CollectiveGather  
Concat<T extends TType> Concatenates tensors along one dimension. 
Constant<T extends TType> An operator producing a constant value. 
ConsumeMutexLock This op consumes a lock created by `MutexLock`. 
ControlTrigger Does nothing. 
Copy<T extends TType> Copy a tensor from CPU-to-CPU or GPU-to-GPU. 
Copy.Options Optional attributes for Copy  
CopyHost<T extends TType> Copy a tensor to host. 
CopyHost.Options Optional attributes for CopyHost  
CountUpTo<T extends TNumber> Increments 'ref' until it reaches 'limit'. 
DecodeProto The op extracts fields from a serialized protocol buffers message into tensors. 
DecodeProto.Options Optional attributes for DecodeProto  
DeepCopy<T extends TType> Makes a copy of `x`. 
DeleteSessionTensor Delete the tensor specified by its handle in the session. 
DestroyResourceOp Deletes the resource specified by the handle. 
DestroyResourceOp.Options Optional attributes for DestroyResourceOp  
DestroyTemporaryVariable<T extends TType> Destroys the temporary variable and returns its final value. 
DeviceIndex Return the index of device the op runs. 
DummyMemoryCache  
DynamicPartition<T extends TType> Partitions `data` into `num_partitions` tensors using indices from `partitions`. 
DynamicStitch<T extends TType> Interleave the values from the `data` tensors into a single tensor. 
EditDistance Computes the (possibly normalized) Levenshtein Edit Distance. 
EditDistance.Options Optional attributes for EditDistance  
Empty<T extends TType> Creates a tensor with the given shape. 
Empty.Options Optional attributes for Empty  
EmptyTensorList Creates and returns an empty tensor list. 
EmptyTensorMap Creates and returns an empty tensor map. 
EncodeProto The op serializes protobuf messages provided in the input tensors. 
EncodeProto.Options Optional attributes for EncodeProto  
EnsureShape<T extends TType> Ensures that the tensor's shape matches the expected shape. 
Enter<T extends TType> Creates or finds a child frame, and makes `data` available to the child frame. 
Enter.Options Optional attributes for Enter  
Exit<T extends TType> Exits the current frame to its parent frame. 
ExpandDims<T extends TType> Inserts a dimension of 1 into a tensor's shape. 
ExtractVolumePatches<T extends TNumber> Extract `patches` from `input` and put them in the `"depth"` output dimension. 
Fill<U extends TType> Creates a tensor filled with a scalar value. 
Fingerprint Generates fingerprint values. 
Gather<T extends TType> Gather slices from `params` axis `axis` according to `indices`. 
Gather.Options Optional attributes for Gather  
GatherNd<T extends TType> Gather slices from `params` into a Tensor with shape specified by `indices`. 
GetSessionHandle Store the input tensor in the state of the current session. 
GetSessionTensor<T extends TType> Get the value of the tensor specified by its handle. 
Gradients Adds operations to compute the partial derivatives of sum of ys w.r.t xs, i.e., d(y_1 + y_2 + ...)/dx_1, d(y_1 + y_2 + ...)/dx_2...

If Options.dx() values are set, they are as the initial symbolic partial derivatives of some loss function L w.r.t. 
Gradients.Options Optional attributes for Gradients  
GuaranteeConst<T extends TType> Gives a guarantee to the TF runtime that the input tensor is a constant. 
HashTable Creates a non-initialized hash table. 
HashTable.Options Optional attributes for HashTable  
Helpers Container class for core methods which add or perform several operations and return one of them. 
HistogramFixedWidth<U extends TNumber> Return histogram of values. 
Identity<T extends TType> Return a tensor with the same shape and contents as the input tensor or value. 
IdentityN Returns a list of tensors with the same shapes and contents as the input

tensors. 
ImmutableConst<T extends TType> Returns immutable tensor from memory region. 
Init  
InitializeTable Table initializer that takes two tensors for keys and values respectively. 
InitializeTableFromTextFile Initializes a table from a text file. 
InitializeTableFromTextFile.Options Optional attributes for InitializeTableFromTextFile  
InplaceAdd<T extends TType> Adds v into specified rows of x. 
InplaceSub<T extends TType> Subtracts `v` into specified rows of `x`. 
InplaceUpdate<T extends TType> Updates specified rows 'i' with values 'v'. 
IsVariableInitialized Checks whether a tensor has been initialized. 
KthOrderStatistic Computes the Kth order statistic of a data set. 
LinSpace<T extends TNumber> Generates values in an interval. 
LookupTableExport<T extends TType, U extends TType> Outputs all keys and values in the table. 
LookupTableFind<U extends TType> Looks up keys in a table, outputs the corresponding values. 
LookupTableImport Replaces the contents of the table with the specified keys and values. 
LookupTableInsert Updates the table to associates keys with values. 
LookupTableRemove Removes keys and its associated values from a table. 
LookupTableSize Computes the number of elements in the given table. 
LoopCond Forwards the input to the output. 
LowerBound<U extends TNumber> Applies lower_bound(sorted_search_values, values) along each row. 
MakeUnique Make all elements in the non-Batch dimension unique, but \"close\" to

their initial value. 
MapClear Op removes all elements in the underlying container. 
MapClear.Options Optional attributes for MapClear  
MapIncompleteSize Op returns the number of incomplete elements in the underlying container. 
MapIncompleteSize.Options Optional attributes for MapIncompleteSize  
MapPeek Op peeks at the values at the specified key. 
MapPeek.Options Optional attributes for MapPeek  
MapSize Op returns the number of elements in the underlying container. 
MapSize.Options Optional attributes for MapSize  
MapStage Stage (key, values) in the underlying container which behaves like a hashtable. 
MapStage.Options Optional attributes for MapStage  
MapUnstage Op removes and returns the values associated with the key

from the underlying container. 
MapUnstage.Options Optional attributes for MapUnstage  
MapUnstageNoKey Op removes and returns a random (key, value)

from the underlying container. 
MapUnstageNoKey.Options Optional attributes for MapUnstageNoKey  
Max<T extends TType> Computes the maximum of elements across dimensions of a tensor. 
Max.Options Optional attributes for Max  
Merge<T extends TType> Forwards the value of an available tensor from `inputs` to `output`. 
Min<T extends TType> Computes the minimum of elements across dimensions of a tensor. 
Min.Options Optional attributes for Min  
MirrorPad<T extends TType> Pads a tensor with mirrored values. 
MirrorPadGrad<T extends TType> Gradient op for `MirrorPad` op. 
MlirPassthroughOp Wraps an arbitrary MLIR computation expressed as a module with a main() function. 
MutableDenseHashTable Creates an empty hash table that uses tensors as the backing store. 
MutableDenseHashTable.Options Optional attributes for MutableDenseHashTable  
MutableHashTable Creates an empty hash table. 
MutableHashTable.Options Optional attributes for MutableHashTable  
MutableHashTableOfTensors Creates an empty hash table. 
MutableHashTableOfTensors.Options Optional attributes for MutableHashTableOfTensors  
Mutex Creates a Mutex resource that can be locked by `MutexLock`. 
Mutex.Options Optional attributes for Mutex  
MutexLock Locks a mutex resource. 
NcclAllReduce<T extends TNumber> Outputs a tensor containing the reduction across all input tensors. 
NcclBroadcast<T extends TNumber> Sends `input` to all devices that are connected to the output. 
NcclReduce<T extends TNumber> Reduces `input` from `num_devices` using `reduction` to a single device. 
NextIteration<T extends TType> Makes its input available to the next iteration. 
NoOp Does nothing. 
OneHot<U extends TType> Returns a one-hot tensor. 
OneHot.Options Optional attributes for OneHot  
Ones<T extends TType> An operator creating a constant initialized with ones of the shape given by `dims`. 
OnesLike<T extends TType> Returns a tensor of ones with the same shape and type as x. 
OrderedMapClear Op removes all elements in the underlying container. 
OrderedMapClear.Options Optional attributes for OrderedMapClear  
OrderedMapIncompleteSize Op returns the number of incomplete elements in the underlying container. 
OrderedMapIncompleteSize.Options Optional attributes for OrderedMapIncompleteSize  
OrderedMapPeek Op peeks at the values at the specified key. 
OrderedMapPeek.Options Optional attributes for OrderedMapPeek  
OrderedMapSize Op returns the number of elements in the underlying container. 
OrderedMapSize.Options Optional attributes for OrderedMapSize  
OrderedMapStage Stage (key, values) in the underlying container which behaves like a ordered

associative container. 
OrderedMapStage.Options Optional attributes for OrderedMapStage  
OrderedMapUnstage Op removes and returns the values associated with the key

from the underlying container. 
OrderedMapUnstage.Options Optional attributes for OrderedMapUnstage  
OrderedMapUnstageNoKey Op removes and returns the (key, value) element with the smallest

key from the underlying container. 
OrderedMapUnstageNoKey.Options Optional attributes for OrderedMapUnstageNoKey  
Pad<T extends TType> Pads a tensor. 
ParallelConcat<T extends TType> Concatenates a list of `N` tensors along the first dimension. 
ParallelDynamicStitch<T extends TType> Interleave the values from the `data` tensors into a single tensor. 
Placeholder<T extends TType> A placeholder op for a value that will be fed into the computation. 
Placeholder.Options Optional attributes for Placeholder  
PlaceholderWithDefault<T extends TType> A placeholder op that passes through `input` when its output is not fed. 
Print Prints a string scalar. 
Print.Options Optional attributes for Print  
Prod<T extends TType> Computes the product of elements across dimensions of a tensor. 
Prod.Options Optional attributes for Prod  
QuantizedReshape<T extends TType> Reshapes a quantized tensor as per the Reshape op. 
Range<T extends TNumber> Creates a sequence of numbers. 
Rank Returns the rank of a tensor. 
ReadVariableOp<T extends TType> Reads the value of a variable. 
Recv<T extends TType> Receives the named tensor from send_device on recv_device. 
Recv.Options Optional attributes for Recv  
ReduceAll Computes the "logical and" of elements across dimensions of a tensor. 
ReduceAll.Options Optional attributes for ReduceAll  
ReduceAny Computes the "logical or" of elements across dimensions of a tensor. 
ReduceAny.Options Optional attributes for ReduceAny  
ReduceMax<T extends TType> Computes the maximum of elements across dimensions of a tensor. 
ReduceMax.Options Optional attributes for ReduceMax  
ReduceMin<T extends TType> Computes the minimum of elements across dimensions of a tensor. 
ReduceMin.Options Optional attributes for ReduceMin  
ReduceProd<T extends TType> Computes the product of elements across dimensions of a tensor. 
ReduceProd.Options Optional attributes for ReduceProd  
ReduceSum<T extends TType> Computes the sum of elements across dimensions of a tensor. 
ReduceSum.Options Optional attributes for ReduceSum  
RefEnter<T extends TType> Creates or finds a child frame, and makes `data` available to the child frame. 
RefEnter.Options Optional attributes for RefEnter  
RefExit<T extends TType> Exits the current frame to its parent frame. 
RefIdentity<T extends TType> Return the same ref tensor as the input ref tensor. 
RefMerge<T extends TType> Forwards the value of an available tensor from `inputs` to `output`. 
RefNextIteration<T extends TType> Makes its input available to the next iteration. 
RefSelect<T extends TType> Forwards the `index`th element of `inputs` to `output`. 
RefSwitch<T extends TType> Forwards the ref tensor `data` to the output port determined by `pred`. 
RemoteFusedGraphExecute Execute a sub graph on a remote processor. 
Reshape<T extends TType> Reshapes a tensor. 
ResourceCountUpTo<T extends TNumber> Increments variable pointed to by 'resource' until it reaches 'limit'. 
ResourceGather<U extends TType> Gather slices from the variable pointed to by `resource` according to `indices`. 
ResourceGather.Options Optional attributes for ResourceGather  
ResourceGatherNd<U extends TType>  
ResourceScatterAdd Adds sparse updates to the variable referenced by `resource`. 
ResourceScatterDiv Divides sparse updates into the variable referenced by `resource`. 
ResourceScatterMax Reduces sparse updates into the variable referenced by `resource` using the `max` operation. 
ResourceScatterMin Reduces sparse updates into the variable referenced by `resource` using the `min` operation. 
ResourceScatterMul Multiplies sparse updates into the variable referenced by `resource`. 
ResourceScatterNdAdd Applies sparse addition to individual values or slices in a Variable. 
ResourceScatterNdAdd.Options Optional attributes for ResourceScatterNdAdd  
ResourceScatterNdMax  
ResourceScatterNdMax.Options Optional attributes for ResourceScatterNdMax  
ResourceScatterNdMin  
ResourceScatterNdMin.Options Optional attributes for ResourceScatterNdMin  
ResourceScatterNdSub Applies sparse subtraction to individual values or slices in a Variable. 
ResourceScatterNdSub.Options Optional attributes for ResourceScatterNdSub  
ResourceScatterNdUpdate Applies sparse `updates` to individual values or slices within a given

variable according to `indices`. 
ResourceScatterNdUpdate.Options Optional attributes for ResourceScatterNdUpdate  
ResourceScatterSub Subtracts sparse updates from the variable referenced by `resource`. 
ResourceScatterUpdate Assigns sparse updates to the variable referenced by `resource`. 
ResourceStridedSliceAssign Assign `value` to the sliced l-value reference of `ref`. 
ResourceStridedSliceAssign.Options Optional attributes for ResourceStridedSliceAssign  
Reverse<T extends TType> Reverses specific dimensions of a tensor. 
ReverseSequence<T extends TType> Reverses variable length slices. 
ReverseSequence.Options Optional attributes for ReverseSequence  
Roll<T extends TType> Rolls the elements of a tensor along an axis. 
Rpc Perform batches of RPC requests. 
Rpc.Options Optional attributes for Rpc  
ScatterAdd<T extends TType> Adds sparse updates to a variable reference. 
ScatterAdd.Options Optional attributes for ScatterAdd  
ScatterDiv<T extends TType> Divides a variable reference by sparse updates. 
ScatterDiv.Options Optional attributes for ScatterDiv  
ScatterMax<T extends TNumber> Reduces sparse updates into a variable reference using the `max` operation. 
ScatterMax.Options Optional attributes for ScatterMax  
ScatterMin<T extends TNumber> Reduces sparse updates into a variable reference using the `min` operation. 
ScatterMin.Options Optional attributes for ScatterMin  
ScatterMul<T extends TType> Multiplies sparse updates into a variable reference. 
ScatterMul.Options Optional attributes for ScatterMul  
ScatterNd<U extends TType> Scatter `updates` into a new tensor according to `indices`. 
ScatterNdAdd<T extends TType> Applies sparse addition to individual values or slices in a Variable. 
ScatterNdAdd.Options Optional attributes for ScatterNdAdd  
ScatterNdMax<T extends TType> Computes element-wise maximum. 
ScatterNdMax.Options Optional attributes for ScatterNdMax  
ScatterNdMin<T extends TType> Computes element-wise minimum. 
ScatterNdMin.Options Optional attributes for ScatterNdMin  
ScatterNdNonAliasingAdd<T extends TType> Applies sparse addition to `input` using individual values or slices

from `updates` according to indices `indices`. 
ScatterNdSub<T extends TType> Applies sparse subtraction to individual values or slices in a Variable. 
ScatterNdSub.Options Optional attributes for ScatterNdSub  
ScatterNdUpdate<T extends TType> Applies sparse `updates` to individual values or slices within a given

variable according to `indices`. 
ScatterNdUpdate.Options Optional attributes for ScatterNdUpdate  
ScatterSub<T extends TType> Subtracts sparse updates to a variable reference. 
ScatterSub.Options Optional attributes for ScatterSub  
ScatterUpdate<T extends TType> Applies sparse updates to a variable reference. 
ScatterUpdate.Options Optional attributes for ScatterUpdate  
Select<T extends TType>  
Send Sends the named tensor from send_device to recv_device. 
Send.Options Optional attributes for Send  
SetDiff1d<T extends TType, U extends TNumber> Computes the difference between two lists of numbers or strings. 
SetSize Number of unique elements along last dimension of input `set`. 
SetSize.Options Optional attributes for SetSize  
Shape<U extends TNumber> Returns the shape of a tensor. 
ShapeN<U extends TNumber> Returns shape of tensors. 
Shapes An operator providing methods on org.tensorflow.op.core.Shape tensors and 1d operands that represent the dimensions of a shape. 
Size<U extends TNumber> Returns the size of a tensor. 
Skipgram Parses a text file and creates a batch of examples. 
Skipgram.Options Optional attributes for Skipgram  
Slice<T extends TType> Return a slice from 'input'. 
Snapshot<T extends TType> Returns a copy of the input tensor. 
SpaceToBatchNd<T extends TType> SpaceToBatch for N-D tensors of type T. 
Split<T extends TType> Splits a tensor into `num_split` tensors along one dimension. 
SplitV<T extends TType> Splits a tensor into `num_split` tensors along one dimension. 
Squeeze<T extends TType> Removes dimensions of size 1 from the shape of a tensor. 
Squeeze.Options Optional attributes for Squeeze  
Stack<T extends TType> Packs a list of `N` rank-`R` tensors into one rank-`(R+1)` tensor. 
Stack.Options Optional attributes for Stack  
Stage Stage values similar to a lightweight Enqueue. 
Stage.Options Optional attributes for Stage  
StageClear Op removes all elements in the underlying container. 
StageClear.Options Optional attributes for StageClear  
StagePeek Op peeks at the values at the specified index. 
StagePeek.Options Optional attributes for StagePeek  
StageSize Op returns the number of elements in the underlying container. 
StageSize.Options Optional attributes for StageSize  
StopGradient<T extends TType> Stops gradient computation. 
StridedSlice<T extends TType> Return a strided slice from `input`. 
StridedSlice.Options Optional attributes for StridedSlice  
StridedSliceAssign<T extends TType> Assign `value` to the sliced l-value reference of `ref`. 
StridedSliceAssign.Options Optional attributes for StridedSliceAssign  
StridedSliceGrad<U extends TType> Returns the gradient of `StridedSlice`. 
StridedSliceGrad.Options Optional attributes for StridedSliceGrad  
StridedSliceHelper Helper endpoint methods for Python like indexing. 
Sum<T extends TType> Computes the sum of elements across dimensions of a tensor. 
Sum.Options Optional attributes for Sum  
SwitchCond<T extends TType> Forwards `data` to the output port determined by `pred`. 
TemporaryVariable<T extends TType> Returns a tensor that may be mutated, but only persists within a single step. 
TemporaryVariable.Options Optional attributes for TemporaryVariable  
TensorArray An array of Tensors of given size. 
TensorArray.Options Optional attributes for TensorArray  
TensorArrayClose Delete the TensorArray from its resource container. 
TensorArrayConcat<T extends TType> Concat the elements from the TensorArray into value `value`. 
TensorArrayConcat.Options Optional attributes for TensorArrayConcat  
TensorArrayGather<T extends TType> Gather specific elements from the TensorArray into output `value`. 
TensorArrayGather.Options Optional attributes for TensorArrayGather  
TensorArrayGrad Creates a TensorArray for storing the gradients of values in the given handle. 
TensorArrayGradWithShape Creates a TensorArray for storing multiple gradients of values in the given handle. 
TensorArrayPack<T extends TType>  
TensorArrayPack.Options Optional attributes for TensorArrayPack  
TensorArrayRead<T extends TType> Read an element from the TensorArray into output `value`. 
TensorArrayScatter Scatter the data from the input value into specific TensorArray elements. 
TensorArraySize Get the current size of the TensorArray. 
TensorArraySplit Split the data from the input value into TensorArray elements. 
TensorArrayUnpack  
TensorArrayWrite Push an element onto the tensor_array. 
TensorForestCreateTreeVariable Creates a tree resource and returns a handle to it. 
TensorForestTreeDeserialize Deserializes a proto into the tree handle  
TensorForestTreeIsInitializedOp Checks whether a tree has been initialized. 
TensorForestTreePredict Output the logits for the given input data  
TensorForestTreeResourceHandleOp Creates a handle to a TensorForestTreeResource  
TensorForestTreeResourceHandleOp.Options Optional attributes for TensorForestTreeResourceHandleOp  
TensorForestTreeSerialize Serializes the tree handle to a proto  
TensorForestTreeSize Get the number of nodes in a tree  
TensorListConcat<U extends TType> Concats all tensors in the list along the 0th dimension. 
TensorListConcatLists  
TensorListElementShape<T extends TNumber> The shape of the elements of the given list, as a tensor. 
TensorListFromTensor Creates a TensorList which, when stacked, has the value of `tensor`. 
TensorListGather<T extends TType> Creates a Tensor by indexing into the TensorList. 
TensorListGetItem<T extends TType>  
TensorListLength Returns the number of tensors in the input tensor list. 
TensorListPopBack<T extends TType> Returns the last element of the input list as well as a list with all but that element. 
TensorListPushBack Returns a list which has the passed-in `Tensor` as last element and the other elements of the given list in `input_handle`. 
TensorListPushBackBatch  
TensorListReserve List of the given size with empty elements. 
TensorListResize Resizes the list. 
TensorListScatter Creates a TensorList by indexing into a Tensor. 
TensorListScatterIntoExistingList Scatters tensor at indices in an input list. 
TensorListSetItem  
TensorListSplit Splits a tensor into a list. 
TensorListStack<T extends TType> Stacks all tensors in the list. 
TensorListStack.Options Optional attributes for TensorListStack  
TensorMapErase Returns a tensor map with item from given key erased. 
TensorMapHasKey Returns whether the given key exists in the map. 
TensorMapInsert Returns a map that is the 'input_handle' with the given key-value pair inserted. 
TensorMapLookup<U extends TType> Returns the value from a given key in a tensor map. 
TensorMapSize Returns the number of tensors in the input tensor map. 
TensorMapStackKeys<T extends TType> Returns a Tensor stack of all keys in a tensor map. 
TensorScatterNdAdd<T extends TType> Adds sparse `updates` to an existing tensor according to `indices`. 
TensorScatterNdMax<T extends TType>  
TensorScatterNdMin<T extends TType>  
TensorScatterNdSub<T extends TType> Subtracts sparse `updates` from an existing tensor according to `indices`. 
TensorScatterNdUpdate<T extends TType> Scatter `updates` into an existing tensor according to `indices`. 
TensorStridedSliceUpdate<T extends TType> Assign `value` to the sliced l-value reference of `input`. 
TensorStridedSliceUpdate.Options Optional attributes for TensorStridedSliceUpdate  
Tile<T extends TType> Constructs a tensor by tiling a given tensor. 
Timestamp Provides the time since epoch in seconds. 
TopKUnique Returns the TopK unique values in the array in sorted order. 
TopKWithUnique Returns the TopK values in the array in sorted order. 
TryRpc Perform batches of RPC requests. 
TryRpc.Options Optional attributes for TryRpc  
Unbatch<T extends TType> Reverses the operation of Batch for a single output Tensor. 
Unbatch.Options Optional attributes for Unbatch  
UnbatchGrad<T extends TType> Gradient of Unbatch. 
UnbatchGrad.Options Optional attributes for UnbatchGrad  
Unique<T extends TType, V extends TNumber> Finds unique elements along an axis of a tensor. 
UniqueWithCounts<T extends TType, V extends TNumber> Finds unique elements along an axis of a tensor. 
UnravelIndex<T extends TNumber> Converts an array of flat indices into a tuple of coordinate arrays. 
Unstack<T extends TType> Unpacks a given dimension of a rank-`R` tensor into `num` rank-`(R-1)` tensors. 
Unstack.Options Optional attributes for Unstack  
Unstage Op is similar to a lightweight Dequeue. 
Unstage.Options Optional attributes for Unstage  
UpperBound<U extends TNumber> Applies upper_bound(sorted_search_values, values) along each row. 
VarHandleOp Creates a handle to a Variable resource. 
VarHandleOp.Options Optional attributes for VarHandleOp  
Variable<T extends TType> Holds state in the form of a tensor that persists across steps. 
Variable.Options Optional attributes for Variable  
VariableShape<T extends TNumber> Returns the shape of the variable pointed to by `resource`. 
VarIsInitializedOp Checks whether a resource handle-based variable has been initialized. 
Where Returns locations of nonzero / true values in a tensor. 
XlaSpmdFullToShardShape<T extends TType> An op used by XLA SPMD partitioner to switch from automatic partitioning to

manual partitioning. 
XlaSpmdShardToFullShape<T extends TType> An op used by XLA SPMD partitioner to switch from manual partitioning to

automatic partitioning. 
Zeros<T extends TType> An operator creating a constant initialized with zeros of the shape given by `dims`. 
ZerosLike<T extends TType> Returns a tensor of zeros with the same shape and type as x.