Package | Description |
---|---|
org.tensorflow.op | |
org.tensorflow.op.core |
Class and Description |
---|
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
Update 'ref' by assigning 'value' to it.
|
Assign.Options
Optional attributes for
Assign |
AssignAdd
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
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 |
BatchMatMulV2
Multiplies slices of two tensors in batches.
|
BatchMatMulV2.Options
Optional attributes for
BatchMatMulV2 |
BatchToSpace
BatchToSpace for 4-D tensors of type T.
|
BatchToSpaceNd
BatchToSpace for N-D tensors of type T.
|
Bitcast
Bitcasts a tensor from one type to another without copying data.
|
BroadcastDynamicShape
Return the shape of s0 op s1 with broadcast.
|
BroadcastTo
Broadcast an array for a compatible shape.
|
Bucketize
Bucketizes 'input' based on 'boundaries'.
|
ClipByValue
Clips tensor values to a specified min and max.
|
CombinedNonMaxSuppression
Greedily selects a subset of bounding boxes in descending order of score,
|
CombinedNonMaxSuppression.Options
Optional attributes for
CombinedNonMaxSuppression |
Concat
Concatenates tensors along one dimension.
|
Constant
An operator producing a constant value.
|
ConsumeMutexLock
This op consumes a lock created by `MutexLock`.
|
ControlTrigger
Does nothing.
|
CountUpTo
Increments 'ref' until it reaches 'limit'.
|
CudnnRNNCanonicalToParamsV2
Converts CudnnRNN params from canonical form to usable form.
|
CudnnRNNCanonicalToParamsV2.Options
Optional attributes for
CudnnRNNCanonicalToParamsV2 |
CudnnRNNParamsToCanonicalV2
Retrieves CudnnRNN params in canonical form.
|
CudnnRNNParamsToCanonicalV2.Options
Optional attributes for
CudnnRNNParamsToCanonicalV2 |
DecodePaddedRaw
Reinterpret the bytes of a string as a vector of numbers.
|
DecodePaddedRaw.Options
Optional attributes for
DecodePaddedRaw |
DeepCopy
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
Destroys the temporary variable and returns its final value.
|
DrawBoundingBoxesV2
Draw bounding boxes on a batch of images.
|
DynamicPartition
Partitions `data` into `num_partitions` tensors using indices from `partitions`.
|
DynamicStitch
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 |
Einsum
Tensor contraction according to Einstein summation convention.
|
Empty
Creates a tensor with the given shape.
|
Empty.Options
Optional attributes for
Empty |
EmptyTensorList
Creates and returns an empty tensor list.
|
EnsureShape
Ensures that the tensor's shape matches the expected shape.
|
EuclideanNorm
Computes the euclidean norm of elements across dimensions of a tensor.
|
EuclideanNorm.Options
Optional attributes for
EuclideanNorm |
ExpandDims
Inserts a dimension of 1 into a tensor's shape.
|
ExtractVolumePatches
Extract `patches` from `input` and put them in the "depth" output dimension.
|
Fill
Creates a tensor filled with a scalar value.
|
Fingerprint
Generates fingerprint values.
|
FusedBatchNormGradV3
Gradient for batch normalization.
|
FusedBatchNormGradV3.Options
Optional attributes for
FusedBatchNormGradV3 |
FusedBatchNormV3
Batch normalization.
|
FusedBatchNormV3.Options
Optional attributes for
FusedBatchNormV3 |
Gather
Gather slices from `params` axis `axis` according to `indices`.
|
Gather.Options
Optional attributes for
Gather |
GatherNd
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
Get the value of the tensor specified by its handle.
|
Gradients
Adds operations to compute the partial derivatives of sum of
y s w.r.t x s,
i.e., d(y_1 + y_2 + ...)/dx_1, d(y_1 + y_2 + ...)/dx_2... |
Gradients.Options
Optional attributes for
Gradients |
GuaranteeConst
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 |
HistogramFixedWidth
Return histogram of values.
|
Identity
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
|
ImmutableConst
Returns immutable tensor from memory region.
|
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
Adds v into specified rows of x.
|
InplaceSub
Subtracts `v` into specified rows of `x`.
|
InplaceUpdate
Updates specified rows with values in `v`.
|
IsVariableInitialized
Checks whether a tensor has been initialized.
|
LinSpace
Generates values in an interval.
|
LookupTableExport
Outputs all keys and values in the table.
|
LookupTableFind
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.
|
LookupTableSize
Computes the number of elements in the given table.
|
LoopCond
Forwards the input to the output.
|
Lu
Computes the LU decomposition of one or more square matrices.
|
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
|
MapUnstage.Options
Optional attributes for
MapUnstage |
MapUnstageNoKey
Op removes and returns a random (key, value)
|
MapUnstageNoKey.Options
Optional attributes for
MapUnstageNoKey |
MatrixDiagPartV2
Returns the batched diagonal part of a batched tensor.
|
MatrixDiagV2
Returns a batched diagonal tensor with given batched diagonal values.
|
MatrixSetDiagV2
Returns a batched matrix tensor with new batched diagonal values.
|
Max
Computes the maximum of elements across dimensions of a tensor.
|
Max.Options
Optional attributes for
Max |
Merge
Forwards the value of an available tensor from `inputs` to `output`.
|
Min
Computes the minimum of elements across dimensions of a tensor.
|
Min.Options
Optional attributes for
Min |
MirrorPad
Pads a tensor with mirrored values.
|
MulNoNan
Returns x * y element-wise.
|
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.
|
NextAfter
Returns the next representable value of `x1` in the direction of `x2`, element-wise.
|
NextIteration
Makes its input available to the next iteration.
|
NonMaxSuppressionV5
Greedily selects a subset of bounding boxes in descending order of score,
|
NonMaxSuppressionV5.Options
Optional attributes for
NonMaxSuppressionV5 |
NoOp
Does nothing.
|
OneHot
Returns a one-hot tensor.
|
OneHot.Options
Optional attributes for
OneHot |
OnesLike
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
|
OrderedMapStage.Options
Optional attributes for
OrderedMapStage |
OrderedMapUnstage
Op removes and returns the values associated with the key
|
OrderedMapUnstage.Options
Optional attributes for
OrderedMapUnstage |
OrderedMapUnstageNoKey
Op removes and returns the (key, value) element with the smallest
|
OrderedMapUnstageNoKey.Options
Optional attributes for
OrderedMapUnstageNoKey |
Pad
Pads a tensor.
|
ParallelConcat
Concatenates a list of `N` tensors along the first dimension.
|
ParallelDynamicStitch
Interleave the values from the `data` tensors into a single tensor.
|
Placeholder
A placeholder op for a value that will be fed into the computation.
|
Placeholder.Options
Optional attributes for
Placeholder |
PlaceholderWithDefault
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
Computes the product of elements across dimensions of a tensor.
|
Prod.Options
Optional attributes for
Prod |
QuantizedConcat
Concatenates quantized tensors along one dimension.
|
QuantizedConcatV2 |
QuantizedReshape
Reshapes a quantized tensor as per the Reshape op.
|
Range
Creates a sequence of numbers.
|
Rank
Returns the rank of a tensor.
|
ReadVariableOp
Reads the value of a variable.
|
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
Computes the maximum of elements across dimensions of a tensor.
|
ReduceMax.Options
Optional attributes for
ReduceMax |
ReduceMin
Computes the minimum of elements across dimensions of a tensor.
|
ReduceMin.Options
Optional attributes for
ReduceMin |
ReduceProd
Computes the product of elements across dimensions of a tensor.
|
ReduceProd.Options
Optional attributes for
ReduceProd |
ReduceSum
Computes the sum of elements across dimensions of a tensor.
|
ReduceSum.Options
Optional attributes for
ReduceSum |
RefNextIteration
Makes its input available to the next iteration.
|
RefSelect
Forwards the `index`th element of `inputs` to `output`.
|
RefSwitch
Forwards the ref tensor `data` to the output port determined by `pred`.
|
RemoteFusedGraphExecute
Execute a sub graph on a remote processor.
|
Reshape
Reshapes a tensor.
|
ResourceApplyAdamWithAmsgrad
Update '*var' according to the Adam algorithm.
|
ResourceApplyAdamWithAmsgrad.Options
Optional attributes for
ResourceApplyAdamWithAmsgrad |
ResourceApplyKerasMomentum
Update '*var' according to the momentum scheme.
|
ResourceApplyKerasMomentum.Options
Optional attributes for
ResourceApplyKerasMomentum |
ResourceCountUpTo
Increments variable pointed to by 'resource' until it reaches 'limit'.
|
ResourceGather
Gather slices from the variable pointed to by `resource` according to `indices`.
|
ResourceGather.Options
Optional attributes for
ResourceGather |
ResourceGatherNd |
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 |
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
|
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`.
|
ResourceSparseApplyKerasMomentum
Update relevant entries in '*var' and '*accum' according to the momentum scheme.
|
ResourceSparseApplyKerasMomentum.Options
Optional attributes for
ResourceSparseApplyKerasMomentum |
ResourceStridedSliceAssign
Assign `value` to the sliced l-value reference of `ref`.
|
ResourceStridedSliceAssign.Options
Optional attributes for
ResourceStridedSliceAssign |
Reverse
Reverses specific dimensions of a tensor.
|
ReverseSequence
Reverses variable length slices.
|
ReverseSequence.Options
Optional attributes for
ReverseSequence |
Roll
Rolls the elements of a tensor along an axis.
|
Rpc
Perform batches of RPC requests.
|
Rpc.Options
Optional attributes for
Rpc |
ScaleAndTranslate |
ScaleAndTranslate.Options
Optional attributes for
ScaleAndTranslate |
ScatterAdd
Adds sparse updates to a variable reference.
|
ScatterAdd.Options
Optional attributes for
ScatterAdd |
ScatterDiv
Divides a variable reference by sparse updates.
|
ScatterDiv.Options
Optional attributes for
ScatterDiv |
ScatterMax
Reduces sparse updates into a variable reference using the `max` operation.
|
ScatterMax.Options
Optional attributes for
ScatterMax |
ScatterMin
Reduces sparse updates into a variable reference using the `min` operation.
|
ScatterMin.Options
Optional attributes for
ScatterMin |
ScatterMul
Multiplies sparse updates into a variable reference.
|
ScatterMul.Options
Optional attributes for
ScatterMul |
ScatterNd
Scatter `updates` into a new tensor according to `indices`.
|
ScatterNdAdd
Applies sparse addition to individual values or slices in a Variable.
|
ScatterNdAdd.Options
Optional attributes for
ScatterNdAdd |
ScatterNdNonAliasingAdd
Applies sparse addition to `input` using individual values or slices
|
ScatterNdSub
Applies sparse subtraction to individual values or slices in a Variable.
|
ScatterNdSub.Options
Optional attributes for
ScatterNdSub |
ScatterNdUpdate
Applies sparse `updates` to individual values or slices within a given
|
ScatterNdUpdate.Options
Optional attributes for
ScatterNdUpdate |
ScatterSub
Subtracts sparse updates to a variable reference.
|
ScatterSub.Options
Optional attributes for
ScatterSub |
ScatterUpdate
Applies sparse updates to a variable reference.
|
ScatterUpdate.Options
Optional attributes for
ScatterUpdate |
SelectV2 |
SetDiff1d
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
Returns the shape of a tensor.
|
ShapeN
Returns shape of tensors.
|
Size
Returns the size of a tensor.
|
Skipgram
Parses a text file and creates a batch of examples.
|
Skipgram.Options
Optional attributes for
Skipgram |
Slice
Return a slice from 'input'.
|
Snapshot
Returns a copy of the input tensor.
|
SpaceToBatchNd
SpaceToBatch for N-D tensors of type T.
|
Split
Splits a tensor into `num_split` tensors along one dimension.
|
SplitV
Splits a tensor into `num_split` tensors along one dimension.
|
Squeeze
Removes dimensions of size 1 from the shape of a tensor.
|
Squeeze.Options
Optional attributes for
Squeeze |
Stack
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 |
StatefulRandomBinomial |
StatefulStandardNormal
Outputs random values from a normal distribution.
|
StatefulStandardNormalV2
Outputs random values from a normal distribution.
|
StopGradient
Stops gradient computation.
|
StridedSlice
Return a strided slice from `input`.
|
StridedSlice.Options
Optional attributes for
StridedSlice |
StridedSliceAssign
Assign `value` to the sliced l-value reference of `ref`.
|
StridedSliceAssign.Options
Optional attributes for
StridedSliceAssign |
StridedSliceGrad
Returns the gradient of `StridedSlice`.
|
StridedSliceGrad.Options
Optional attributes for
StridedSliceGrad |
StringLower |
StringLower.Options
Optional attributes for
StringLower |
StringNGrams
Creates ngrams from ragged string data.
|
StringUpper |
StringUpper.Options
Optional attributes for
StringUpper |
Sum
Computes the sum of elements across dimensions of a tensor.
|
Sum.Options
Optional attributes for
Sum |
SwitchCond
Forwards `data` to the output port determined by `pred`.
|
TemporaryVariable
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
Concat the elements from the TensorArray into value `value`.
|
TensorArrayConcat.Options
Optional attributes for
TensorArrayConcat |
TensorArrayGather
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 |
TensorArrayPack.Options
Optional attributes for
TensorArrayPack |
TensorArrayRead
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.
|
TensorListConcat
Concats all tensors in the list along the 0th dimension.
|
TensorListConcat.Options
Optional attributes for
TensorListConcat |
TensorListConcatLists |
TensorListConcatV2
Concats all tensors in the list along the 0th dimension.
|
TensorListElementShape
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
Creates a Tensor by indexing into the TensorList.
|
TensorListGetItem |
TensorListLength
Returns the number of tensors in the input tensor list.
|
TensorListPopBack
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.
|
TensorListScatterV2
Creates a TensorList by indexing into a Tensor.
|
TensorListSetItem |
TensorListSplit
Splits a tensor into a list.
|
TensorListStack
Stacks all tensors in the list.
|
TensorListStack.Options
Optional attributes for
TensorListStack |
TensorScatterAdd
Adds sparse `updates` to an existing tensor according to `indices`.
|
TensorScatterSub
Subtracts sparse `updates` from an existing tensor according to `indices`.
|
TensorScatterUpdate
Scatter `updates` into an existing tensor according to `indices`.
|
TensorStridedSliceUpdate
Assign `value` to the sliced l-value reference of `input`.
|
TensorStridedSliceUpdate.Options
Optional attributes for
TensorStridedSliceUpdate |
Tile
Constructs a tensor by tiling a given tensor.
|
Timestamp
Provides the time since epoch in seconds.
|
TryRpc
Perform batches of RPC requests.
|
TryRpc.Options
Optional attributes for
TryRpc |
Unbatch
Reverses the operation of Batch for a single output Tensor.
|
Unbatch.Options
Optional attributes for
Unbatch |
UnbatchGrad
Gradient of Unbatch.
|
UnbatchGrad.Options
Optional attributes for
UnbatchGrad |
Unique
Finds unique elements along an axis of a tensor.
|
UniqueWithCounts
Finds unique elements along an axis of a tensor.
|
UnravelIndex
Converts an array of flat indices into a tuple of coordinate arrays.
|
UnsortedSegmentJoin
Joins the elements of `inputs` based on `segment_ids`.
|
UnsortedSegmentJoin.Options
Optional attributes for
UnsortedSegmentJoin |
Unstack
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 |
VarHandleOp
Creates a handle to a Variable resource.
|
VarHandleOp.Options
Optional attributes for
VarHandleOp |
Variable
Holds state in the form of a tensor that persists across steps.
|
Variable.Options
Optional attributes for
Variable |
VariableShape
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.
|
Where3
Selects elements from `x` or `y`, depending on `condition`.
|
Zeros
An operator creating a constant initialized with zeros of the shape given by `dims`.
|
ZerosLike
Returns a tensor of zeros with the same shape and type as x.
|
Class and Description |
---|
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 |
AllToAll
An Op to exchange data across TPU replicas.
|
AnonymousIteratorV2
A container for an iterator resource.
|
AnonymousMemoryCache |
AnonymousMultiDeviceIterator
A container for a multi device iterator resource.
|
AnonymousRandomSeedGenerator |
Any
Computes the "logical or" of elements across dimensions of a tensor.
|
Any.Options
Optional attributes for
Any |
ApplyAdagradV2
Update '*var' according to the adagrad scheme.
|
ApplyAdagradV2.Options
Optional attributes for
ApplyAdagradV2 |
AssertNextDataset
A transformation that asserts which transformations happen next.
|
AssertThat
Asserts that the given condition is true.
|
AssertThat.Options
Optional attributes for
AssertThat |
Assign
Update 'ref' by assigning 'value' to it.
|
Assign.Options
Optional attributes for
Assign |
AssignAdd
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
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.
|
AutoShardDataset
Creates a dataset that shards the input dataset.
|
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 |
BatchMatMulV2
Multiplies slices of two tensors in batches.
|
BatchMatMulV2.Options
Optional attributes for
BatchMatMulV2 |
BatchToSpace
BatchToSpace for 4-D tensors of type T.
|
BatchToSpaceNd
BatchToSpace for N-D tensors of type T.
|
Bitcast
Bitcasts a tensor from one type to another without copying data.
|
BlockLSTM
Computes the LSTM cell forward propagation for all the time steps.
|
BlockLSTM.Options
Optional attributes for
BlockLSTM |
BlockLSTMGrad
Computes the LSTM cell backward propagation for the entire time sequence.
|
BlockLSTMGradV2
Computes the LSTM cell backward propagation for the entire time sequence.
|
BlockLSTMV2
Computes the LSTM cell forward propagation for all the time steps.
|
BlockLSTMV2.Options
Optional attributes for
BlockLSTMV2 |
BoostedTreesAggregateStats
Aggregates the summary of accumulated stats for the batch.
|
BoostedTreesBucketize
Bucketize each feature based on bucket boundaries.
|
BoostedTreesCalculateBestFeatureSplit
Calculates gains for each feature and returns the best possible split information for the feature.
|
BoostedTreesCalculateBestFeatureSplit.Options
Optional attributes for
BoostedTreesCalculateBestFeatureSplit |
BoostedTreesCalculateBestGainsPerFeature
Calculates gains for each feature and returns the best possible split information for the feature.
|
BoostedTreesCenterBias
Calculates the prior from the training data (the bias) and fills in the first node with the logits' prior.
|
BoostedTreesCreateEnsemble
Creates a tree ensemble model and returns a handle to it.
|
BoostedTreesCreateQuantileStreamResource
Create the Resource for Quantile Streams.
|
BoostedTreesCreateQuantileStreamResource.Options
Optional attributes for
BoostedTreesCreateQuantileStreamResource |
BoostedTreesDeserializeEnsemble
Deserializes a serialized tree ensemble config and replaces current tree
|
BoostedTreesEnsembleResourceHandleOp
Creates a handle to a BoostedTreesEnsembleResource
|
BoostedTreesEnsembleResourceHandleOp.Options
Optional attributes for
BoostedTreesEnsembleResourceHandleOp |
BoostedTreesExampleDebugOutputs
Debugging/model interpretability outputs for each example.
|
BoostedTreesFlushQuantileSummaries
Flush the quantile summaries from each quantile stream resource.
|
BoostedTreesGetEnsembleStates
Retrieves the tree ensemble resource stamp token, number of trees and growing statistics.
|
BoostedTreesMakeQuantileSummaries
Makes the summary of quantiles for the batch.
|
BoostedTreesMakeStatsSummary
Makes the summary of accumulated stats for the batch.
|
BoostedTreesPredict
Runs multiple additive regression ensemble predictors on input instances and
|
BoostedTreesQuantileStreamResourceAddSummaries
Add the quantile summaries to each quantile stream resource.
|
BoostedTreesQuantileStreamResourceDeserialize
Deserialize bucket boundaries and ready flag into current QuantileAccumulator.
|
BoostedTreesQuantileStreamResourceFlush
Flush the summaries for a quantile stream resource.
|
BoostedTreesQuantileStreamResourceFlush.Options
Optional attributes for
BoostedTreesQuantileStreamResourceFlush |
BoostedTreesQuantileStreamResourceGetBucketBoundaries
Generate the bucket boundaries for each feature based on accumulated summaries.
|
BoostedTreesQuantileStreamResourceHandleOp
Creates a handle to a BoostedTreesQuantileStreamResource.
|
BoostedTreesQuantileStreamResourceHandleOp.Options
Optional attributes for
BoostedTreesQuantileStreamResourceHandleOp |
BoostedTreesSerializeEnsemble
Serializes the tree ensemble to a proto.
|
BoostedTreesSparseAggregateStats
Aggregates the summary of accumulated stats for the batch.
|
BoostedTreesSparseCalculateBestFeatureSplit
Calculates gains for each feature and returns the best possible split information for the feature.
|
BoostedTreesSparseCalculateBestFeatureSplit.Options
Optional attributes for
BoostedTreesSparseCalculateBestFeatureSplit |
BoostedTreesTrainingPredict
Runs multiple additive regression ensemble predictors on input instances and
|
BoostedTreesUpdateEnsemble
Updates the tree ensemble by either adding a layer to the last tree being grown
|
BoostedTreesUpdateEnsembleV2
Updates the tree ensemble by adding a layer to the last tree being grown
|
BroadcastDynamicShape
Return the shape of s0 op s1 with broadcast.
|
BroadcastGradientArgs
Return the reduction indices for computing gradients of s0 op s1 with broadcast.
|
BroadcastTo
Broadcast an array for a compatible shape.
|
Bucketize
Bucketizes 'input' based on 'boundaries'.
|
CacheDatasetV2 |
ChooseFastestDataset |
ClipByValue
Clips tensor values to a specified min and max.
|
CollectiveGather
Mutually accumulates multiple tensors of identical type and shape.
|
CollectiveGather.Options
Optional attributes for
CollectiveGather |
CollectivePermute
An Op to permute tensors across replicated TPU instances.
|
CombinedNonMaxSuppression
Greedily selects a subset of bounding boxes in descending order of score,
|
CombinedNonMaxSuppression.Options
Optional attributes for
CombinedNonMaxSuppression |
Concat
Concatenates tensors along one dimension.
|
ConfigureDistributedTPU
Sets up the centralized structures for a distributed TPU system.
|
ConfigureDistributedTPU.Options
Optional attributes for
ConfigureDistributedTPU |
ConfigureTPUEmbedding
Sets up TPUEmbedding in a distributed TPU system.
|
Constant
An operator producing a constant value.
|
ConsumeMutexLock
This op consumes a lock created by `MutexLock`.
|
ControlTrigger
Does nothing.
|
CountUpTo
Increments 'ref' until it reaches 'limit'.
|
CrossReplicaSum
An Op to sum inputs across replicated TPU instances.
|
CSVDataset |
CudnnRNNBackpropV3
Backprop step of CudnnRNNV3.
|
CudnnRNNBackpropV3.Options
Optional attributes for
CudnnRNNBackpropV3 |
CudnnRNNCanonicalToParamsV2
Converts CudnnRNN params from canonical form to usable form.
|
CudnnRNNCanonicalToParamsV2.Options
Optional attributes for
CudnnRNNCanonicalToParamsV2 |
CudnnRNNParamsToCanonicalV2
Retrieves CudnnRNN params in canonical form.
|
CudnnRNNParamsToCanonicalV2.Options
Optional attributes for
CudnnRNNParamsToCanonicalV2 |
CudnnRNNV3
A RNN backed by cuDNN.
|
CudnnRNNV3.Options
Optional attributes for
CudnnRNNV3 |
CumulativeLogsumexp
Compute the cumulative product of the tensor `x` along `axis`.
|
CumulativeLogsumexp.Options
Optional attributes for
CumulativeLogsumexp |
DatasetCardinality
Returns the cardinality of `input_dataset`.
|
DatasetFromGraph
Creates a dataset from the given `graph_def`.
|
DebugGradientIdentity
Identity op for gradient debugging.
|
DebugGradientRefIdentity
Identity op for gradient debugging.
|
DecodePaddedRaw
Reinterpret the bytes of a string as a vector of numbers.
|
DecodePaddedRaw.Options
Optional attributes for
DecodePaddedRaw |
DecodeProto
The op extracts fields from a serialized protocol buffers message into tensors.
|
DecodeProto.Options
Optional attributes for
DecodeProto |
DeepCopy
Makes a copy of `x`.
|
DeleteIterator
A container for an iterator resource.
|
DeleteMemoryCache |
DeleteMultiDeviceIterator
A container for an iterator resource.
|
DeleteRandomSeedGenerator |
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
Destroys the temporary variable and returns its final value.
|
DirectedInterleaveDataset
A substitute for `InterleaveDataset` on a fixed list of `N` datasets.
|
DrawBoundingBoxesV2
Draw bounding boxes on a batch of images.
|
DynamicPartition
Partitions `data` into `num_partitions` tensors using indices from `partitions`.
|
DynamicStitch
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 |
Einsum
Tensor contraction according to Einstein summation convention.
|
Empty
Creates a tensor with the given shape.
|
Empty.Options
Optional attributes for
Empty |
EmptyTensorList
Creates and returns an empty tensor list.
|
EncodeProto
The op serializes protobuf messages provided in the input tensors.
|
EncodeProto.Options
Optional attributes for
EncodeProto |
EnqueueTPUEmbeddingIntegerBatch
An op that enqueues a list of input batch tensors to TPUEmbedding.
|
EnqueueTPUEmbeddingIntegerBatch.Options
Optional attributes for
EnqueueTPUEmbeddingIntegerBatch |
EnqueueTPUEmbeddingSparseBatch
An op that enqueues TPUEmbedding input indices from a SparseTensor.
|
EnqueueTPUEmbeddingSparseBatch.Options
Optional attributes for
EnqueueTPUEmbeddingSparseBatch |
EnqueueTPUEmbeddingSparseTensorBatch
Eases the porting of code that uses tf.nn.embedding_lookup_sparse().
|
EnqueueTPUEmbeddingSparseTensorBatch.Options
Optional attributes for
EnqueueTPUEmbeddingSparseTensorBatch |
EnsureShape
Ensures that the tensor's shape matches the expected shape.
|
Enter
Creates or finds a child frame, and makes `data` available to the child frame.
|
Enter.Options
Optional attributes for
Enter |
EuclideanNorm
Computes the euclidean norm of elements across dimensions of a tensor.
|
EuclideanNorm.Options
Optional attributes for
EuclideanNorm |
Exit
Exits the current frame to its parent frame.
|
ExpandDims
Inserts a dimension of 1 into a tensor's shape.
|
ExperimentalAutoShardDataset
Creates a dataset that shards the input dataset.
|
ExperimentalBytesProducedStatsDataset
Records the bytes size of each element of `input_dataset` in a StatsAggregator.
|
ExperimentalChooseFastestDataset |
ExperimentalDatasetCardinality
Returns the cardinality of `input_dataset`.
|
ExperimentalDatasetToTFRecord
Writes the given dataset to the given file using the TFRecord format.
|
ExperimentalDenseToSparseBatchDataset
Creates a dataset that batches input elements into a SparseTensor.
|
ExperimentalLatencyStatsDataset
Records the latency of producing `input_dataset` elements in a StatsAggregator.
|
ExperimentalMatchingFilesDataset |
ExperimentalMaxIntraOpParallelismDataset
Creates a dataset that overrides the maximum intra-op parallelism.
|
ExperimentalParseExampleDataset
Transforms `input_dataset` containing `Example` protos as vectors of DT_STRING into a dataset of `Tensor` or `SparseTensor` objects representing the parsed features.
|
ExperimentalParseExampleDataset.Options
Optional attributes for
ExperimentalParseExampleDataset |
ExperimentalPrivateThreadPoolDataset
Creates a dataset that uses a custom thread pool to compute `input_dataset`.
|
ExperimentalRandomDataset
Creates a Dataset that returns pseudorandom numbers.
|
ExperimentalRebatchDataset
Creates a dataset that changes the batch size.
|
ExperimentalRebatchDataset.Options
Optional attributes for
ExperimentalRebatchDataset |
ExperimentalSetStatsAggregatorDataset |
ExperimentalSlidingWindowDataset
Creates a dataset that passes a sliding window over `input_dataset`.
|
ExperimentalSqlDataset
Creates a dataset that executes a SQL query and emits rows of the result set.
|
ExperimentalStatsAggregatorHandle
Creates a statistics manager resource.
|
ExperimentalStatsAggregatorHandle.Options
Optional attributes for
ExperimentalStatsAggregatorHandle |
ExperimentalStatsAggregatorSummary
Produces a summary of any statistics recorded by the given statistics manager.
|
ExperimentalUnbatchDataset
A dataset that splits the elements of its input into multiple elements.
|
ExtractVolumePatches
Extract `patches` from `input` and put them in the "depth" output dimension.
|
Fill
Creates a tensor filled with a scalar value.
|
Fingerprint
Generates fingerprint values.
|
FusedBatchNormGradV3
Gradient for batch normalization.
|
FusedBatchNormGradV3.Options
Optional attributes for
FusedBatchNormGradV3 |
FusedBatchNormV3
Batch normalization.
|
FusedBatchNormV3.Options
Optional attributes for
FusedBatchNormV3 |
Gather
Gather slices from `params` axis `axis` according to `indices`.
|
Gather.Options
Optional attributes for
Gather |
GatherNd
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
Get the value of the tensor specified by its handle.
|
Gradients
Adds operations to compute the partial derivatives of sum of
y s w.r.t x s,
i.e., d(y_1 + y_2 + ...)/dx_1, d(y_1 + y_2 + ...)/dx_2... |
Gradients.Options
Optional attributes for
Gradients |
GRUBlockCell
Computes the GRU cell forward propagation for 1 time step.
|
GRUBlockCellGrad
Computes the GRU cell back-propagation for 1 time step.
|
GuaranteeConst
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 |
HistogramFixedWidth
Return histogram of values.
|
Identity
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
|
IgnoreErrorsDataset
Creates a dataset that contains the elements of `input_dataset` ignoring errors.
|
ImmutableConst
Returns immutable tensor from memory region.
|
InfeedDequeue
A placeholder op for a value that will be fed into the computation.
|
InfeedDequeueTuple
Fetches multiple values from infeed as an XLA tuple.
|
InfeedEnqueue
An op which feeds a single Tensor value into the computation.
|
InfeedEnqueue.Options
Optional attributes for
InfeedEnqueue |
InfeedEnqueuePrelinearizedBuffer
An op which enqueues prelinearized buffer into TPU infeed.
|
InfeedEnqueuePrelinearizedBuffer.Options
Optional attributes for
InfeedEnqueuePrelinearizedBuffer |
InfeedEnqueueTuple
Feeds multiple Tensor values into the computation as an XLA tuple.
|
InfeedEnqueueTuple.Options
Optional attributes for
InfeedEnqueueTuple |
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
Adds v into specified rows of x.
|
InplaceSub
Subtracts `v` into specified rows of `x`.
|
InplaceUpdate
Updates specified rows with values in `v`.
|
IsBoostedTreesEnsembleInitialized
Checks whether a tree ensemble has been initialized.
|
IsBoostedTreesQuantileStreamResourceInitialized
Checks whether a quantile stream has been initialized.
|
IsVariableInitialized
Checks whether a tensor has been initialized.
|
IteratorGetDevice
Returns the name of the device on which `resource` has been placed.
|
KMC2ChainInitialization
Returns the index of a data point that should be added to the seed set.
|
KmeansPlusPlusInitialization
Selects num_to_sample rows of input using the KMeans++ criterion.
|
LinSpace
Generates values in an interval.
|
LMDBDataset |
LoadTPUEmbeddingAdadeltaParameters
Load Adadelta embedding parameters.
|
LoadTPUEmbeddingAdadeltaParameters.Options
Optional attributes for
LoadTPUEmbeddingAdadeltaParameters |
LoadTPUEmbeddingAdadeltaParametersGradAccumDebug
Load Adadelta parameters with debug support.
|
LoadTPUEmbeddingAdadeltaParametersGradAccumDebug.Options
Optional attributes for
LoadTPUEmbeddingAdadeltaParametersGradAccumDebug |
LoadTPUEmbeddingAdagradParameters
Load Adagrad embedding parameters.
|
LoadTPUEmbeddingAdagradParameters.Options
Optional attributes for
LoadTPUEmbeddingAdagradParameters |
LoadTPUEmbeddingAdagradParametersGradAccumDebug
Load Adagrad embedding parameters with debug support.
|
LoadTPUEmbeddingAdagradParametersGradAccumDebug.Options
Optional attributes for
LoadTPUEmbeddingAdagradParametersGradAccumDebug |
LoadTPUEmbeddingADAMParameters
Load ADAM embedding parameters.
|
LoadTPUEmbeddingADAMParameters.Options
Optional attributes for
LoadTPUEmbeddingADAMParameters |
LoadTPUEmbeddingADAMParametersGradAccumDebug
Load ADAM embedding parameters with debug support.
|
LoadTPUEmbeddingADAMParametersGradAccumDebug.Options
Optional attributes for
LoadTPUEmbeddingADAMParametersGradAccumDebug |
LoadTPUEmbeddingCenteredRMSPropParameters
Load centered RMSProp embedding parameters.
|
LoadTPUEmbeddingCenteredRMSPropParameters.Options
Optional attributes for
LoadTPUEmbeddingCenteredRMSPropParameters |
LoadTPUEmbeddingFTRLParameters
Load FTRL embedding parameters.
|
LoadTPUEmbeddingFTRLParameters.Options
Optional attributes for
LoadTPUEmbeddingFTRLParameters |
LoadTPUEmbeddingFTRLParametersGradAccumDebug
Load FTRL embedding parameters with debug support.
|
LoadTPUEmbeddingFTRLParametersGradAccumDebug.Options
Optional attributes for
LoadTPUEmbeddingFTRLParametersGradAccumDebug |
LoadTPUEmbeddingMDLAdagradLightParameters
Load MDL Adagrad Light embedding parameters.
|
LoadTPUEmbeddingMDLAdagradLightParameters.Options
Optional attributes for
LoadTPUEmbeddingMDLAdagradLightParameters |
LoadTPUEmbeddingMomentumParameters
Load Momentum embedding parameters.
|
LoadTPUEmbeddingMomentumParameters.Options
Optional attributes for
LoadTPUEmbeddingMomentumParameters |
LoadTPUEmbeddingMomentumParametersGradAccumDebug
Load Momentum embedding parameters with debug support.
|
LoadTPUEmbeddingMomentumParametersGradAccumDebug.Options
Optional attributes for
LoadTPUEmbeddingMomentumParametersGradAccumDebug |
LoadTPUEmbeddingProximalAdagradParameters
Load proximal Adagrad embedding parameters.
|
LoadTPUEmbeddingProximalAdagradParameters.Options
Optional attributes for
LoadTPUEmbeddingProximalAdagradParameters |
LoadTPUEmbeddingProximalAdagradParametersGradAccumDebug
Load proximal Adagrad embedding parameters with debug support.
|
LoadTPUEmbeddingProximalAdagradParametersGradAccumDebug.Options
Optional attributes for
LoadTPUEmbeddingProximalAdagradParametersGradAccumDebug |
LoadTPUEmbeddingRMSPropParameters
Load RMSProp embedding parameters.
|
LoadTPUEmbeddingRMSPropParameters.Options
Optional attributes for
LoadTPUEmbeddingRMSPropParameters |
LoadTPUEmbeddingRMSPropParametersGradAccumDebug
Load RMSProp embedding parameters with debug support.
|
LoadTPUEmbeddingRMSPropParametersGradAccumDebug.Options
Optional attributes for
LoadTPUEmbeddingRMSPropParametersGradAccumDebug |
LoadTPUEmbeddingStochasticGradientDescentParameters
Load SGD embedding parameters.
|
LoadTPUEmbeddingStochasticGradientDescentParameters.Options
Optional attributes for
LoadTPUEmbeddingStochasticGradientDescentParameters |
LookupTableExport
Outputs all keys and values in the table.
|
LookupTableFind
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
Applies lower_bound(sorted_search_values, values) along each row.
|
LSTMBlockCell
Computes the LSTM cell forward propagation for 1 time step.
|
LSTMBlockCell.Options
Optional attributes for
LSTMBlockCell |
LSTMBlockCellGrad
Computes the LSTM cell backward propagation for 1 timestep.
|
Lu
Computes the LU decomposition of one or more square matrices.
|
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
|
MapUnstage.Options
Optional attributes for
MapUnstage |
MapUnstageNoKey
Op removes and returns a random (key, value)
|
MapUnstageNoKey.Options
Optional attributes for
MapUnstageNoKey |
MatrixDiagPartV2
Returns the batched diagonal part of a batched tensor.
|
MatrixDiagV2
Returns a batched diagonal tensor with given batched diagonal values.
|
MatrixSetDiagV2
Returns a batched matrix tensor with new batched diagonal values.
|
Max
Computes the maximum of elements across dimensions of a tensor.
|
Max.Options
Optional attributes for
Max |
MaxIntraOpParallelismDataset
Creates a dataset that overrides the maximum intra-op parallelism.
|
Merge
Forwards the value of an available tensor from `inputs` to `output`.
|
Min
Computes the minimum of elements across dimensions of a tensor.
|
Min.Options
Optional attributes for
Min |
MirrorPad
Pads a tensor with mirrored values.
|
MirrorPadGrad
Gradient op for `MirrorPad` op.
|
MulNoNan
Returns x * y element-wise.
|
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
Outputs a tensor containing the reduction across all input tensors.
|
NcclBroadcast
Sends `input` to all devices that are connected to the output.
|
NcclReduce
Reduces `input` from `num_devices` using `reduction` to a single device.
|
NearestNeighbors
Selects the k nearest centers for each point.
|
NextAfter
Returns the next representable value of `x1` in the direction of `x2`, element-wise.
|
NextIteration
Makes its input available to the next iteration.
|
NonDeterministicInts
Non-deterministically generates some integers.
|
NonMaxSuppressionV5
Greedily selects a subset of bounding boxes in descending order of score,
|
NonMaxSuppressionV5.Options
Optional attributes for
NonMaxSuppressionV5 |
NonSerializableDataset |
NoOp
Does nothing.
|
OneHot
Returns a one-hot tensor.
|
OneHot.Options
Optional attributes for
OneHot |
OnesLike
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
|
OrderedMapStage.Options
Optional attributes for
OrderedMapStage |
OrderedMapUnstage
Op removes and returns the values associated with the key
|
OrderedMapUnstage.Options
Optional attributes for
OrderedMapUnstage |
OrderedMapUnstageNoKey
Op removes and returns the (key, value) element with the smallest
|
OrderedMapUnstageNoKey.Options
Optional attributes for
OrderedMapUnstageNoKey |
OutfeedDequeue
Retrieves a single tensor from the computation outfeed.
|
OutfeedDequeue.Options
Optional attributes for
OutfeedDequeue |
OutfeedDequeueTuple
Retrieve multiple values from the computation outfeed.
|
OutfeedDequeueTuple.Options
Optional attributes for
OutfeedDequeueTuple |
OutfeedEnqueue
Enqueue a Tensor on the computation outfeed.
|
OutfeedEnqueueTuple
Enqueue multiple Tensor values on the computation outfeed.
|
Pad
Pads a tensor.
|
ParallelConcat
Concatenates a list of `N` tensors along the first dimension.
|
ParallelDynamicStitch
Interleave the values from the `data` tensors into a single tensor.
|
Placeholder
A placeholder op for a value that will be fed into the computation.
|
Placeholder.Options
Optional attributes for
Placeholder |
PlaceholderWithDefault
A placeholder op that passes through `input` when its output is not fed.
|
Prelinearize
An op which linearizes one Tensor value to an opaque variant tensor.
|
Prelinearize.Options
Optional attributes for
Prelinearize |
PrelinearizeTuple
An op which linearizes multiple Tensor values to an opaque variant tensor.
|
PrelinearizeTuple.Options
Optional attributes for
PrelinearizeTuple |
Print
Prints a string scalar.
|
Print.Options
Optional attributes for
Print |
PrivateThreadPoolDataset
Creates a dataset that uses a custom thread pool to compute `input_dataset`.
|
Prod
Computes the product of elements across dimensions of a tensor.
|
Prod.Options
Optional attributes for
Prod |
QuantizedConcat
Concatenates quantized tensors along one dimension.
|
QuantizedConcatV2 |
QuantizedConv2DAndRelu |
QuantizedConv2DAndRelu.Options
Optional attributes for
QuantizedConv2DAndRelu |
QuantizedConv2DAndReluAndRequantize |
QuantizedConv2DAndReluAndRequantize.Options
Optional attributes for
QuantizedConv2DAndReluAndRequantize |
QuantizedConv2DAndRequantize |
QuantizedConv2DAndRequantize.Options
Optional attributes for
QuantizedConv2DAndRequantize |
QuantizedConv2DPerChannel
Computes QuantizedConv2D per channel.
|
QuantizedConv2DPerChannel.Options
Optional attributes for
QuantizedConv2DPerChannel |
QuantizedConv2DWithBias |
QuantizedConv2DWithBias.Options
Optional attributes for
QuantizedConv2DWithBias |
QuantizedConv2DWithBiasAndRelu |
QuantizedConv2DWithBiasAndRelu.Options
Optional attributes for
QuantizedConv2DWithBiasAndRelu |
QuantizedConv2DWithBiasAndReluAndRequantize |
QuantizedConv2DWithBiasAndReluAndRequantize.Options
Optional attributes for
QuantizedConv2DWithBiasAndReluAndRequantize |
QuantizedConv2DWithBiasAndRequantize |
QuantizedConv2DWithBiasAndRequantize.Options
Optional attributes for
QuantizedConv2DWithBiasAndRequantize |
QuantizedConv2DWithBiasSignedSumAndReluAndRequantize |
QuantizedConv2DWithBiasSignedSumAndReluAndRequantize.Options
Optional attributes for
QuantizedConv2DWithBiasSignedSumAndReluAndRequantize |
QuantizedConv2DWithBiasSumAndRelu |
QuantizedConv2DWithBiasSumAndRelu.Options
Optional attributes for
QuantizedConv2DWithBiasSumAndRelu |
QuantizedConv2DWithBiasSumAndReluAndRequantize |
QuantizedConv2DWithBiasSumAndReluAndRequantize.Options
Optional attributes for
QuantizedConv2DWithBiasSumAndReluAndRequantize |
QuantizedDepthwiseConv2D
Computes quantized depthwise Conv2D.
|
QuantizedDepthwiseConv2D.Options
Optional attributes for
QuantizedDepthwiseConv2D |
QuantizedDepthwiseConv2DWithBias
Computes quantized depthwise Conv2D with Bias.
|
QuantizedDepthwiseConv2DWithBias.Options
Optional attributes for
QuantizedDepthwiseConv2DWithBias |
QuantizedDepthwiseConv2DWithBiasAndRelu
Computes quantized depthwise Conv2D with Bias and Relu.
|
QuantizedDepthwiseConv2DWithBiasAndRelu.Options
Optional attributes for
QuantizedDepthwiseConv2DWithBiasAndRelu |
QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize
Computes quantized depthwise Conv2D with Bias, Relu and Requantize.
|
QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize.Options
Optional attributes for
QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize |
QuantizedMatMulWithBias
Performs a quantized matrix multiplication of `a` by the matrix `b` with bias
add.
|
QuantizedMatMulWithBias.Options
Optional attributes for
QuantizedMatMulWithBias |
QuantizedMatMulWithBiasAndRelu
Perform a quantized matrix multiplication of `a` by the matrix `b` with bias
add and relu fusion.
|
QuantizedMatMulWithBiasAndRelu.Options
Optional attributes for
QuantizedMatMulWithBiasAndRelu |
QuantizedMatMulWithBiasAndReluAndRequantize
Perform a quantized matrix multiplication of `a` by the matrix `b` with bias
add and relu and requantize fusion.
|
QuantizedMatMulWithBiasAndReluAndRequantize.Options
Optional attributes for
QuantizedMatMulWithBiasAndReluAndRequantize |
QuantizedReshape
Reshapes a quantized tensor as per the Reshape op.
|
RaggedGather
Gather ragged slices from `params` axis `0` according to `indices`.
|
RaggedRange
Returns a `RaggedTensor` containing the specified sequences of numbers.
|
RaggedTensorFromVariant
Decodes a `variant` Tensor into a `RaggedTensor`.
|
RaggedTensorToSparse
Converts a `RaggedTensor` into a `SparseTensor` with the same values.
|
RaggedTensorToTensor
Create a dense tensor from a ragged tensor, possibly altering its shape.
|
RaggedTensorToVariant
Encodes a `RaggedTensor` into a `variant` Tensor.
|
Range
Creates a sequence of numbers.
|
Rank
Returns the rank of a tensor.
|
ReadVariableOp
Reads the value of a variable.
|
RebatchDataset
Creates a dataset that changes the batch size.
|
RebatchDataset.Options
Optional attributes for
RebatchDataset |
RecvTPUEmbeddingActivations
An op that receives embedding activations on the TPU.
|
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
Computes the maximum of elements across dimensions of a tensor.
|
ReduceMax.Options
Optional attributes for
ReduceMax |
ReduceMin
Computes the minimum of elements across dimensions of a tensor.
|
ReduceMin.Options
Optional attributes for
ReduceMin |
ReduceProd
Computes the product of elements across dimensions of a tensor.
|
ReduceProd.Options
Optional attributes for
ReduceProd |
ReduceSum
Computes the sum of elements across dimensions of a tensor.
|
ReduceSum.Options
Optional attributes for
ReduceSum |
RefEnter
Creates or finds a child frame, and makes `data` available to the child frame.
|
RefEnter.Options
Optional attributes for
RefEnter |
RefExit
Exits the current frame to its parent frame.
|
RefIdentity
Return the same ref tensor as the input ref tensor.
|
RefMerge
Forwards the value of an available tensor from `inputs` to `output`.
|
RefNextIteration
Makes its input available to the next iteration.
|
RefSelect
Forwards the `index`th element of `inputs` to `output`.
|
RefSwitch
Forwards the ref tensor `data` to the output port determined by `pred`.
|
RemoteFusedGraphExecute
Execute a sub graph on a remote processor.
|
RequantizationRangePerChannel
Computes requantization range per channel.
|
RequantizePerChannel
Requantizes input with min and max values known per channel.
|
Reshape
Reshapes a tensor.
|
ResourceAccumulatorApplyGradient
Applies a gradient to a given accumulator.
|
ResourceAccumulatorNumAccumulated
Returns the number of gradients aggregated in the given accumulators.
|
ResourceAccumulatorSetGlobalStep
Updates the accumulator with a new value for global_step.
|
ResourceAccumulatorTakeGradient
Extracts the average gradient in the given ConditionalAccumulator.
|
ResourceApplyAdagradV2
Update '*var' according to the adagrad scheme.
|
ResourceApplyAdagradV2.Options
Optional attributes for
ResourceApplyAdagradV2 |
ResourceApplyAdamWithAmsgrad
Update '*var' according to the Adam algorithm.
|
ResourceApplyAdamWithAmsgrad.Options
Optional attributes for
ResourceApplyAdamWithAmsgrad |
ResourceApplyKerasMomentum
Update '*var' according to the momentum scheme.
|
ResourceApplyKerasMomentum.Options
Optional attributes for
ResourceApplyKerasMomentum |
ResourceConditionalAccumulator
A conditional accumulator for aggregating gradients.
|
ResourceConditionalAccumulator.Options
Optional attributes for
ResourceConditionalAccumulator |
ResourceCountUpTo
Increments variable pointed to by 'resource' until it reaches 'limit'.
|
ResourceGather
Gather slices from the variable pointed to by `resource` according to `indices`.
|
ResourceGather.Options
Optional attributes for
ResourceGather |
ResourceGatherNd |
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 |
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
|
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`.
|
ResourceSparseApplyAdagradV2
Update relevant entries in '*var' and '*accum' according to the adagrad scheme.
|
ResourceSparseApplyAdagradV2.Options
Optional attributes for
ResourceSparseApplyAdagradV2 |
ResourceSparseApplyKerasMomentum
Update relevant entries in '*var' and '*accum' according to the momentum scheme.
|
ResourceSparseApplyKerasMomentum.Options
Optional attributes for
ResourceSparseApplyKerasMomentum |
ResourceStridedSliceAssign
Assign `value` to the sliced l-value reference of `ref`.
|
ResourceStridedSliceAssign.Options
Optional attributes for
ResourceStridedSliceAssign |
RetrieveTPUEmbeddingAdadeltaParameters
Retrieve Adadelta embedding parameters.
|
RetrieveTPUEmbeddingAdadeltaParameters.Options
Optional attributes for
RetrieveTPUEmbeddingAdadeltaParameters |
RetrieveTPUEmbeddingAdadeltaParametersGradAccumDebug
Retrieve Adadelta embedding parameters with debug support.
|
RetrieveTPUEmbeddingAdadeltaParametersGradAccumDebug.Options
Optional attributes for
RetrieveTPUEmbeddingAdadeltaParametersGradAccumDebug |
RetrieveTPUEmbeddingAdagradParameters
Retrieve Adagrad embedding parameters.
|
RetrieveTPUEmbeddingAdagradParameters.Options
Optional attributes for
RetrieveTPUEmbeddingAdagradParameters |
RetrieveTPUEmbeddingAdagradParametersGradAccumDebug
Retrieve Adagrad embedding parameters with debug support.
|
RetrieveTPUEmbeddingAdagradParametersGradAccumDebug.Options
Optional attributes for
RetrieveTPUEmbeddingAdagradParametersGradAccumDebug |
RetrieveTPUEmbeddingADAMParameters
Retrieve ADAM embedding parameters.
|
RetrieveTPUEmbeddingADAMParameters.Options
Optional attributes for
RetrieveTPUEmbeddingADAMParameters |
RetrieveTPUEmbeddingADAMParametersGradAccumDebug
Retrieve ADAM embedding parameters with debug support.
|
RetrieveTPUEmbeddingADAMParametersGradAccumDebug.Options
Optional attributes for
RetrieveTPUEmbeddingADAMParametersGradAccumDebug |
RetrieveTPUEmbeddingCenteredRMSPropParameters
Retrieve centered RMSProp embedding parameters.
|
RetrieveTPUEmbeddingCenteredRMSPropParameters.Options
Optional attributes for
RetrieveTPUEmbeddingCenteredRMSPropParameters |
RetrieveTPUEmbeddingFTRLParameters
Retrieve FTRL embedding parameters.
|
RetrieveTPUEmbeddingFTRLParameters.Options
Optional attributes for
RetrieveTPUEmbeddingFTRLParameters |
RetrieveTPUEmbeddingFTRLParametersGradAccumDebug
Retrieve FTRL embedding parameters with debug support.
|
RetrieveTPUEmbeddingFTRLParametersGradAccumDebug.Options
Optional attributes for
RetrieveTPUEmbeddingFTRLParametersGradAccumDebug |
RetrieveTPUEmbeddingMDLAdagradLightParameters
Retrieve MDL Adagrad Light embedding parameters.
|
RetrieveTPUEmbeddingMDLAdagradLightParameters.Options
Optional attributes for
RetrieveTPUEmbeddingMDLAdagradLightParameters |
RetrieveTPUEmbeddingMomentumParameters
Retrieve Momentum embedding parameters.
|
RetrieveTPUEmbeddingMomentumParameters.Options
Optional attributes for
RetrieveTPUEmbeddingMomentumParameters |
RetrieveTPUEmbeddingMomentumParametersGradAccumDebug
Retrieve Momentum embedding parameters with debug support.
|
RetrieveTPUEmbeddingMomentumParametersGradAccumDebug.Options
Optional attributes for
RetrieveTPUEmbeddingMomentumParametersGradAccumDebug |
RetrieveTPUEmbeddingProximalAdagradParameters
Retrieve proximal Adagrad embedding parameters.
|
RetrieveTPUEmbeddingProximalAdagradParameters.Options
Optional attributes for
RetrieveTPUEmbeddingProximalAdagradParameters |
RetrieveTPUEmbeddingProximalAdagradParametersGradAccumDebug
Retrieve proximal Adagrad embedding parameters with debug support.
|
RetrieveTPUEmbeddingProximalAdagradParametersGradAccumDebug.Options
Optional attributes for
RetrieveTPUEmbeddingProximalAdagradParametersGradAccumDebug |
RetrieveTPUEmbeddingRMSPropParameters
Retrieve RMSProp embedding parameters.
|
RetrieveTPUEmbeddingRMSPropParameters.Options
Optional attributes for
RetrieveTPUEmbeddingRMSPropParameters |
RetrieveTPUEmbeddingRMSPropParametersGradAccumDebug
Retrieve RMSProp embedding parameters with debug support.
|
RetrieveTPUEmbeddingRMSPropParametersGradAccumDebug.Options
Optional attributes for
RetrieveTPUEmbeddingRMSPropParametersGradAccumDebug |
RetrieveTPUEmbeddingStochasticGradientDescentParameters
Retrieve SGD embedding parameters.
|
RetrieveTPUEmbeddingStochasticGradientDescentParameters.Options
Optional attributes for
RetrieveTPUEmbeddingStochasticGradientDescentParameters |
Reverse
Reverses specific dimensions of a tensor.
|
ReverseSequence
Reverses variable length slices.
|
ReverseSequence.Options
Optional attributes for
ReverseSequence |
RngSkip
Advance the counter of a counter-based RNG.
|
Roll
Rolls the elements of a tensor along an axis.
|
Rpc
Perform batches of RPC requests.
|
Rpc.Options
Optional attributes for
Rpc |
SamplingDataset
Creates a dataset that takes a Bernoulli sample of the contents of another dataset.
|
ScaleAndTranslate |
ScaleAndTranslate.Options
Optional attributes for
ScaleAndTranslate |
ScaleAndTranslateGrad |
ScaleAndTranslateGrad.Options
Optional attributes for
ScaleAndTranslateGrad |
ScatterAdd
Adds sparse updates to a variable reference.
|
ScatterAdd.Options
Optional attributes for
ScatterAdd |
ScatterDiv
Divides a variable reference by sparse updates.
|
ScatterDiv.Options
Optional attributes for
ScatterDiv |
ScatterMax
Reduces sparse updates into a variable reference using the `max` operation.
|
ScatterMax.Options
Optional attributes for
ScatterMax |
ScatterMin
Reduces sparse updates into a variable reference using the `min` operation.
|
ScatterMin.Options
Optional attributes for
ScatterMin |
ScatterMul
Multiplies sparse updates into a variable reference.
|
ScatterMul.Options
Optional attributes for
ScatterMul |
ScatterNd
Scatter `updates` into a new tensor according to `indices`.
|
ScatterNdAdd
Applies sparse addition to individual values or slices in a Variable.
|
ScatterNdAdd.Options
Optional attributes for
ScatterNdAdd |
ScatterNdNonAliasingAdd
Applies sparse addition to `input` using individual values or slices
|
ScatterNdSub
Applies sparse subtraction to individual values or slices in a Variable.
|
ScatterNdSub.Options
Optional attributes for
ScatterNdSub |
ScatterNdUpdate
Applies sparse `updates` to individual values or slices within a given
|
ScatterNdUpdate.Options
Optional attributes for
ScatterNdUpdate |
ScatterSub
Subtracts sparse updates to a variable reference.
|
ScatterSub.Options
Optional attributes for
ScatterSub |
ScatterUpdate
Applies sparse updates to a variable reference.
|
ScatterUpdate.Options
Optional attributes for
ScatterUpdate |
SelectV2 |
SendTPUEmbeddingGradients
Performs gradient updates of embedding tables.
|
SetDiff1d
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
Returns the shape of a tensor.
|
ShapeN
Returns shape of tensors.
|
ShardDataset
Creates a `Dataset` that includes only 1/`num_shards` of this dataset.
|
ShardDataset.Options
Optional attributes for
ShardDataset |
ShuffleDatasetV2 |
ShutdownDistributedTPU
Shuts down a running distributed TPU system.
|
Size
Returns the size of a tensor.
|
Skipgram
Parses a text file and creates a batch of examples.
|
Skipgram.Options
Optional attributes for
Skipgram |
SleepDataset |
Slice
Return a slice from 'input'.
|
SlidingWindowDataset
Creates a dataset that passes a sliding window over `input_dataset`.
|
Snapshot
Returns a copy of the input tensor.
|
SnapshotDataset
Creates a dataset that will write to / read from a snapshot.
|
SnapshotDataset.Options
Optional attributes for
SnapshotDataset |
SpaceToBatchNd
SpaceToBatch for N-D tensors of type T.
|
SparseApplyAdagradV2
Update relevant entries in '*var' and '*accum' according to the adagrad scheme.
|
SparseApplyAdagradV2.Options
Optional attributes for
SparseApplyAdagradV2 |
Split
Splits a tensor into `num_split` tensors along one dimension.
|
SplitV
Splits a tensor into `num_split` tensors along one dimension.
|
Squeeze
Removes dimensions of size 1 from the shape of a tensor.
|
Squeeze.Options
Optional attributes for
Squeeze |
Stack
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 |
StatefulRandomBinomial |
StatefulStandardNormal
Outputs random values from a normal distribution.
|
StatefulStandardNormalV2
Outputs random values from a normal distribution.
|
StatefulTruncatedNormal
Outputs random values from a truncated normal distribution.
|
StatefulUniform
Outputs random values from a uniform distribution.
|
StatefulUniformFullInt
Outputs random integers from a uniform distribution.
|
StatefulUniformInt
Outputs random integers from a uniform distribution.
|
StatsAggregatorHandleV2 |
StatsAggregatorHandleV2.Options
Optional attributes for
StatsAggregatorHandleV2 |
StatsAggregatorSetSummaryWriter
Set a summary_writer_interface to record statistics using given stats_aggregator.
|
StopGradient
Stops gradient computation.
|
StridedSlice
Return a strided slice from `input`.
|
StridedSlice.Options
Optional attributes for
StridedSlice |
StridedSliceAssign
Assign `value` to the sliced l-value reference of `ref`.
|
StridedSliceAssign.Options
Optional attributes for
StridedSliceAssign |
StridedSliceGrad
Returns the gradient of `StridedSlice`.
|
StridedSliceGrad.Options
Optional attributes for
StridedSliceGrad |
StringLower |
StringLower.Options
Optional attributes for
StringLower |
StringNGrams
Creates ngrams from ragged string data.
|
StringUpper |
StringUpper.Options
Optional attributes for
StringUpper |
Sum
Computes the sum of elements across dimensions of a tensor.
|
Sum.Options
Optional attributes for
Sum |
SwitchCond
Forwards `data` to the output port determined by `pred`.
|
TemporaryVariable
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
Concat the elements from the TensorArray into value `value`.
|
TensorArrayConcat.Options
Optional attributes for
TensorArrayConcat |
TensorArrayGather
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 |
TensorArrayPack.Options
Optional attributes for
TensorArrayPack |
TensorArrayRead
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
Concats all tensors in the list along the 0th dimension.
|
TensorListConcat.Options
Optional attributes for
TensorListConcat |
TensorListConcatLists |
TensorListConcatV2
Concats all tensors in the list along the 0th dimension.
|
TensorListElementShape
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
Creates a Tensor by indexing into the TensorList.
|
TensorListGetItem |
TensorListLength
Returns the number of tensors in the input tensor list.
|
TensorListPopBack
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.
|
TensorListScatterV2
Creates a TensorList by indexing into a Tensor.
|
TensorListSetItem |
TensorListSplit
Splits a tensor into a list.
|
TensorListStack
Stacks all tensors in the list.
|
TensorListStack.Options
Optional attributes for
TensorListStack |
TensorScatterAdd
Adds sparse `updates` to an existing tensor according to `indices`.
|
TensorScatterSub
Subtracts sparse `updates` from an existing tensor according to `indices`.
|
TensorScatterUpdate
Scatter `updates` into an existing tensor according to `indices`.
|
TensorStridedSliceUpdate
Assign `value` to the sliced l-value reference of `input`.
|
TensorStridedSliceUpdate.Options
Optional attributes for
TensorStridedSliceUpdate |
ThreadPoolDataset
Creates a dataset that uses a custom thread pool to compute `input_dataset`.
|
ThreadPoolHandle
Creates a dataset that uses a custom thread pool to compute `input_dataset`.
|
ThreadPoolHandle.Options
Optional attributes for
ThreadPoolHandle |
Tile
Constructs a tensor by tiling a given tensor.
|
Timestamp
Provides the time since epoch in seconds.
|
TPUCompilationResult
CompilationResultProto indicating the status of the TPU compilation.
|
TPUEmbeddingActivations
An op enabling differentiation of TPU Embeddings.
|
TPUOrdinalSelector
A TPU core selector Op.
|
TPUReplicatedInput
Connects N inputs to an N-way replicated TPU computation.
|
TPUReplicatedOutput
Connects outputs of an N-way replicated computation to N outputs.
|
TPUReplicateMetadata
Metadata indicaitng how the TPU computation should be replicated.
|
TPUReplicateMetadata.Options
Optional attributes for
TPUReplicateMetadata |
TridiagonalMatMul
Calculate product with tridiagonal matrix.
|
TridiagonalSolve
Solves tridiagonal systems of equations.
|
TridiagonalSolve.Options
Optional attributes for
TridiagonalSolve |
TryRpc
Perform batches of RPC requests.
|
TryRpc.Options
Optional attributes for
TryRpc |
Unbatch
Reverses the operation of Batch for a single output Tensor.
|
Unbatch.Options
Optional attributes for
Unbatch |
UnbatchGrad
Gradient of Unbatch.
|
UnbatchGrad.Options
Optional attributes for
UnbatchGrad |
UnicodeDecode
Decodes each string in `input` into a sequence of Unicode code points.
|
UnicodeDecode.Options
Optional attributes for
UnicodeDecode |
UnicodeEncode
Encode a tensor of ints into unicode strings.
|
UnicodeEncode.Options
Optional attributes for
UnicodeEncode |
Unique
Finds unique elements along an axis of a tensor.
|
UniqueDataset
Creates a dataset that contains the unique elements of `input_dataset`.
|
UniqueWithCounts
Finds unique elements along an axis of a tensor.
|
UnravelIndex
Converts an array of flat indices into a tuple of coordinate arrays.
|
UnsortedSegmentJoin
Joins the elements of `inputs` based on `segment_ids`.
|
UnsortedSegmentJoin.Options
Optional attributes for
UnsortedSegmentJoin |
Unstack
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 |
UnwrapDatasetVariant |
UpperBound
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
Holds state in the form of a tensor that persists across steps.
|
Variable.Options
Optional attributes for
Variable |
VariableShape
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.
|
Where3
Selects elements from `x` or `y`, depending on `condition`.
|
WorkerHeartbeat
Worker heartbeat op.
|
WrapDatasetVariant |
WriteRawProtoSummary |
Zeros
An operator creating a constant initialized with zeros of the shape given by `dims`.
|
ZerosLike
Returns a tensor of zeros with the same shape and type as x.
|
Copyright © 2022. All rights reserved.