중단 | 호출 될 때 프로세스를 중단하기 위해 예외를 제기하십시오. |
모두 | 텐서의 치수에 걸쳐 "논리적 및 요소"를 계산합니다. |
Alltoall <t> | TPU 복제품을 통해 데이터를 교환하기위한 OP. |
Anonymousiteratorv2 | 반복 자원 용 컨테이너. |
AnonymousmemoryCache | |
AnonymousmultideViceIterator | 멀티 장치 반복 자 리소스 용 컨테이너. |
AnonymousrandomSeedGenerator | |
AnonymousSeedGenerator | |
어느 | 텐서의 치수에 걸쳐 "논리적 또는"요소의 "논리"를 계산합니다. |
ApplyAdagradv2 <t> | Adagrad 체계에 따라 '*var'를 업데이트하십시오. |
AssertCardinalityDataset | |
AssertNextDataset | 다음에 어떤 변환이 발생하는지 주장하는 변환. |
이를 주장합니다 | 주어진 조건이 사실이라고 주장합니다. |
할당 <t> | '값'을 할당하여 'Ref'를 업데이트하십시오. |
할당 <t> | '값'을 추가하여 'Ref'를 업데이트하십시오. |
할당 AdtleDvariableop | 변수의 현재 값에 값을 추가합니다. |
할당 <t> | '값'을 빼서 'Ref'를 업데이트하십시오. |
antsubvariableop | 변수의 현재 값에서 값을 빼냅니다. |
antadivariableop | 변수에 새 값을 할당합니다. |
AutoShardDataset | 입력 데이터 세트를 제공하는 데이터 세트를 만듭니다. |
BandedTriangularSolve <t> | |
장벽 | 다른 그래프 실행에서 지속되는 장벽을 정의합니다. |
BarrierClose | 주어진 장벽을 닫습니다. |
BarrierEncompletesize | 주어진 장벽에서 불완전한 요소의 수를 계산합니다. |
Barrierinsertmany | 각 키에 대해 각 값을 지정된 구성 요소에 할당합니다. |
BarrierReadysize | 주어진 장벽에서 완전한 요소의 수를 계산합니다. |
Barriertakemany | 주어진 수의 완성 된 요소를 장벽에서 가져옵니다. |
일괄 | 모든 입력 텐서를 비경 적으로 배치합니다. |
Batchmatmulv2 <t> | 두 개의 텐서 조각에 배치로 곱합니다. |
Batchtospace <t> | 타입 T의 4D 텐서에 대한 배치 스페이스. |
Batchtospacend <t> | T 형의 ND 텐서에 대한 배치 스페이스. |
Besseli0 <t undumber> | |
besseli1 <t는 숫자를 확장합니다 | |
Besselj0 <t는 숫자를 확장합니다 | |
besselj1 <t는 숫자를 확장합니다 | |
Besselk0 <t는 숫자를 확장합니다 | |
Besselk0e <t는 숫자를 확장합니다 | |
besselk1 <t 숫자> | |
besselk1e <t는 숫자>를 확장합니다 | |
Bessely0 <t는 숫자>를 확장합니다 | |
Bessely1 <t는 숫자>를 확장합니다 | |
비트 캐스트 <u> | 데이터를 복사하지 않고 한 유형에서 다른 유형으로 텐서를 비트 캐스트합니다. |
blocklstm <t는 숫자>를 확장합니다 | 모든 시간 단계 동안 LSTM 셀 포워드 전파를 계산합니다. |
blocklstmgrad <t는 숫자>를 확장합니다 | 전체 시간 시퀀스에 대해 LSTM 셀 역전 전파를 계산합니다. |
blocklstmgradv2 <t는 숫자>를 확장합니다 | 전체 시간 시퀀스에 대해 LSTM 셀 역전 전파를 계산합니다. |
blocklstmv2 <t는 숫자>를 확장합니다 | 모든 시간 단계 동안 LSTM 셀 포워드 전파를 계산합니다. |
BoostedTreesaggregatestats | 집계 배치에 대한 축적 된 통계 요약을 집계합니다. |
BoostedTreesBucketize | 버킷 경계를 기반으로 각 기능을 버킷으로 만들 수 있습니다. |
BoostedTreescalculateBestFeaturesPlit | 각 기능에 대한 이득을 계산하고 기능에 대한 최상의 분할 정보를 반환합니다. |
BoostedTreescalculateBestFeaturesPlitv2 | 각 기능에 대한 이득을 계산하고 각 노드에 대해 최상의 분할 정보를 반환합니다. |
BoostedTreescalculateBestgainsperfeature | 각 기능에 대한 이득을 계산하고 기능에 대한 최상의 분할 정보를 반환합니다. |
BoostedTreescenterbias | 훈련 데이터 (바이어스)에서 이전을 계산하고 첫 번째 노드를 Logits의 사전에 채 웁니다. |
BoostedTreescreateensemble | 트리 앙상블 모델을 생성하고 손잡이를 반환합니다. |
BoostedTreescreatequantilestreamResource | Quantile 스트림에 대한 리소스를 만듭니다. |
BoostedTreesDeserializeEnsemble | 직렬화 된 트리 앙상블 구성을 요구하고 현재 트리를 대체합니다. 앙상블. |
boostedtreesensembleresourcehandleop | BoostedTreesensemblerSource에 대한 핸들을 만듭니다 |
boostedTreesexampledebugoutputs | 각 예제의 디버깅/모델 해석 가능성 출력. |
boostedtreesflushquantilesummaries | 각 Quantile 스트림 리소스에서 Quantile 요약을 플러시합니다. |
boostedtreesgetensemblestates | 트리 앙상블 리소스 스탬프 토큰, 나무 수 및 성장 통계를 검색합니다. |
boostedtreesmakequantilesummaries | 배치에 대한 Quantiles의 요약을 만듭니다. |
BoostedTreesmakestatsSummary | 배치에 대한 누적 통계 요약을합니다. |
BoostedTreespredict | 입력 인스턴스에서 여러 부가 회귀 앙상블 예측 변수를 실행하고 로그를 계산합니다. |
boostedtreesquantilestreamresourceaddsummaries | 각 Quantile 스트림 리소스에 Quantile 요약을 추가하십시오. |
boostedtreesquantilestreamresourcedeserialize | 버킷 경계와 준비된 플래그를 전류 양자 쿠 쿠터로 삼아야합니다. |
boostedtreesquantilestreamresourceflush | Quantile Stream 리소스의 요약을 플러시하십시오. |
boostedTreeseQuantilStreamResourceGetBucketBoundaries | 누적 된 요약에 따라 각 기능에 대한 버킷 경계를 생성하십시오. |
boostedtreesquantilestreamresourcehandleop | boostedtreesquantilestreamresource에 대한 핸들을 만듭니다. |
BoostedTreesserializeEnsemble | 트리 앙상블을 프로토로 직렬화합니다. |
BoostedTreessparseAggregatestats | 집계 배치에 대한 축적 된 통계 요약을 집계합니다. |
boostedTreessParsEcalculateBestFeaturesPlit | 각 기능에 대한 이득을 계산하고 기능에 대한 최상의 분할 정보를 반환합니다. |
부스트 트레이프레이닝 프레드 틱 | 입력 인스턴스에서 여러 부가 회귀 앙상블 예측 변수를 실행하고 캐시 된 로이트에 대한 업데이트를 계산합니다. |
boostedtreesupdateensemble | 자란 마지막 나무에 층을 추가하여 트리 앙상블을 업데이트합니다. 또는 새 나무를 시작함으로써. |
boostedtreesupdateensemblev2 | 자란 마지막 나무에 층을 추가하여 트리 앙상블을 업데이트합니다. 또는 새 나무를 시작함으로써. |
BroadcastDynamichape <t는 숫자>를 확장합니다 | 방송으로 S0 OP S1의 모양을 반환하십시오. |
BroadcastgradientArgs <t는 숫자>를 확장합니다 | 방송으로 S0 OP S1의 계산 구배에 대한 감소 지수를 반환하십시오. |
Broadcastto <t> | 호환적인 모양을 위해 배열을 방송합니다. |
버킷 화 | '경계'를 기반으로 '입력'을 버킷화합니다. |
CSRSPARSEMATRIXCOMPONENTS <T> | Batch` 색인 '에서 CSR 구성 요소를 읽습니다. |
CSRSPARSEMATRIXTODENSE <T> | CSRSPARSEMATRIX를 조밀하게 변환하십시오. |
CSRSPARSEMATTIXTOSPARSETENSOR <T> | (아마도 배치 된) csrsparesmatrix를 sparsetensor로 변환합니다. |
CSVDATASET | |
CSVDATASETV2 | |
ctclossv2 | 각 배치 항목에 대한 CTC 손실 (로그 확률)을 계산합니다. |
Cachedatasetv2 | |
Checknumericsv2 <t는 숫자>를 확장합니다 | nan, -inf 및 +inf 값에 대한 텐서를 점검합니다. |
fastestdataset을 선택하십시오 | |
ClipByValue <t> | 클립 텐서 값은 지정된 최소 및 최대로 값을냅니다. |
CollectiveGhather <t는 숫자를 확장합니다 | 동일한 유형과 모양의 여러 텐서를 상호 축적합니다. |
CollectiveGatherv2 <t는 숫자>를 확장합니다 | 동일한 유형과 모양의 여러 텐서를 상호 축적합니다. |
CollectivePermute <t> | 복제 된 TPU 인스턴스를 가로 질러 텐서를 분출시킵니다. |
Collectivereducev2 <t는 숫자>를 확장합니다 | 동일한 유형과 모양의 여러 텐서를 상호 감소시킵니다. |
결합 된 MaxSuppression | 욕심이 내림차순으로 경계 상자의 하위 집합을 선택합니다. 이 작업은 모든 클래스에서 배치 당 입력에서 Non_max_suppression을 수행합니다. |
압축 | 데이터 세트 요소를 압축합니다. |
computebatchsize | 데이터 세트 SANS 부분 배치의 정적 배치 크기를 계산합니다. |
<t> | 한 차원을 따라 텐서를 연결합니다. |
configuredentedtpu | 분산 TPU 시스템의 중앙 구조를 설정합니다. |
configuretpuembedding | 분산 된 TPU 시스템에서 tpuembedding을 설정합니다. |
상수 <t> | 일정한 가치를 생성하는 연산자. |
소비량 록락 | 이 OP는`mutexlock`에 의해 생성 된 잠금 장치를 소비합니다. |
ControlTrigger | 아무것도하지 않습니다. |
복사 <t> | 텐서를 CPU에서 CPU로 복사하십시오. |
COPYHOST <T> | 텐서를 호스트로 복사하십시오. |
countupto <t는 숫자>를 확장합니다 | '제한'에 도달 할 때까지 'Ref'를 증가시킵니다. |
CrossReplicasum <t는 숫자>를 확장합니다 | 복제 된 TPU 인스턴스에 걸쳐 OP에서 합계 입력. |
cudnnrnnbackpropv3 <t uncumber> | cudnnrnnv3의 역전 단계. |
cudnnrnnncanonicaltoparamsv2 <t는 숫자>를 확장합니다 | cudnnrnn 매개 변수를 표준 형태에서 사용 가능한 형태로 변환합니다. |
cudnnrnnnparamstocanonicalv2 <t uncumber> | cudnnrnn 매개 변수를 표준 형태로 검색합니다. |
cudnnrnnv3 <t는 숫자를 확장합니다 | Cudnn이 지원하는 RNN. |
humulativelogsumexp <t는 숫자>를 확장합니다 | `axis '를 따라 텐서`x`의 누적 곱을 계산하십시오. |
DataServicedAtAset | |
DataSetCardInality | 'input_dataset'의 카디널리티를 반환합니다. |
DataSetfromgraph | 주어진`graph_def`에서 데이터 세트를 만듭니다. |
DataSettograpHv2 | 'input_dataset'을 나타내는 직렬화 된 GraphDef를 반환합니다. |
dawsn <t는 숫자>를 확장합니다 | |
디버그 그라디언트 <T> | 그라디언트 디버깅에 대한 ID OP. |
DebuggradientRefidentity <t> | 그라디언트 디버깅에 대한 ID OP. |
디버그 기지 <t> | 디버깅을위한 비 레프 유형 입력 텐서의 ID 매핑을 제공합니다. |
Debugidentityv2 <t> | 디버그 아이덴티티 v2 op. |
Debugnancount | Debug Nan Value Counter Op. |
Debugnumericsummary | 디버그 숫자 요약 op. |
debugnumericsummaryv2 <u는 숫자>를 확장합니다 | 디버그 숫자 요약 v2 op. |
decodeimage <t는 숫자>를 연장합니다 | decode_bmp, decode_gif, decode_jpeg 및 decode_png의 함수. |
DecodepaddedRaw <t는 숫자>를 확장합니다 | 문자열의 바이트를 숫자의 벡터로 재 해석하십시오. |
Decodeproto | OP는 직렬화 된 프로토콜 버퍼 메시지에서 텐서로 필드를 추출합니다. |
심해 <t> | `x`의 사본을 만듭니다. |
DELETEITERATOR | 반복 자원 용 컨테이너. |
deletememoryCache | |
deletemultideviceiterator | 반복 자원 용 컨테이너. |
deleterandomseedgenerator | |
deleteseedgenerator | |
deletesessionTensor | 세션에서 손잡이로 지정된 텐서를 삭제하십시오. |
DenseBincount <U 확장 번호> | 정수 배열에서 각 값의 발생 수를 계산합니다. |
densecountsparseoutput <u는 숫자를 확장합니다 | tf.tensor 입력에 대한 희소 출력 빈 계산을 수행합니다. |
densetocsrsparsematrix | 밀도가 높은 텐서를 CSRSPARSEMATRIX로 변환합니다. |
DestroveResourceop | 핸들에 의해 지정된 리소스를 삭제합니다. |
파괴를 파괴하십시오. <t> | 임시 변수를 파괴하고 최종 값을 반환합니다. |
DeviceIndex | OP가 실행하는 장치의 인덱스를 반환하십시오. |
DirectedInterleAvedataset | 고정 된 'n'데이터 세트 목록에서 '인터리베이타 세트'를 대체합니다. |
DrawBoundingboxesv2 <t는 숫자>를 확장합니다 | 이미지의 배치에 경계 상자를 그립니다. |
DummyiterationCounter | |
dummymemoryCache | |
더미 시드 게이터 | |
DynamicPartition <t> | `data '는`partitions'의 인덱스를 사용하여`num_partitions '텐서에 칸막이입니다. |
DynamicStitch <t> | '데이터'텐서의 값을 단일 텐서에 intrea하십시오. |
editdistance | (정규화 된) Levenshtein 편집 거리를 계산합니다. |
eig <u> | 하나 이상의 사각형 행렬의 고유 분해를 계산합니다. |
Einsum <t> | 아인슈타인 합산 협약에 따른 텐서 수축. |
비어 <t> | 주어진 모양으로 텐서를 만듭니다. |
emptytensorlist | 빈 텐서 목록을 생성하고 반환합니다. |
emptytensormap | 빈 텐서 맵을 생성하고 반환합니다. |
encoproto | OP는 입력 텐서에 제공된 Protobuf 메시지를 직렬화합니다. |
enqueuetpuembeddingintegerbatch | 입력 배치 텐서 목록을 tpuembedding에 넣는 OP. |
enqueuetpuembeddingRaggedTensorbatch | tf.nn.embedding_lookup ()을 사용하는 코드 포팅이 완화됩니다. |
enqueuetpuembeddingsparsebatch | sparsetensor의 tpuembedding 입력 지수를 흡수하는 OP. |
enqueuetpuembeddingsparsetensorbatch | tf.nn.embedding_lookup_sparse ()를 사용하는 코드 포팅이 완화됩니다. |
<t>를 보장합니다 | 텐서의 모양이 예상 모양과 일치하도록합니다. |
<T>를 입력하십시오 | 자식 프레임을 생성하거나 찾아서 '데이터'를 어린이 프레임에 사용할 수있게합니다. |
erfinv <t는 숫자>를 확장합니다 | |
euclideannorm <t> | 텐서의 치수에 걸쳐 유클리드 요소의 표준을 계산합니다. |
출구 <t> | 현재 프레임을 모래 프레임으로 종료합니다. |
Expanddims <t> | 1의 치수를 텐서 모양에 삽입합니다. |
실험적 이식 공사 | 입력 데이터 세트를 제공하는 데이터 세트를 만듭니다. |
실험적으로 제작 된 스타 타타 세트 | 'input_dataset'의 각 요소의 바이트 크기를 통계 분리기에 기록합니다. |
ExperimentalChooseFastestDataset | |
실험용 | 'input_dataset'의 카디널리티를 반환합니다. |
ExperimentalDatasettotFrecord | 주어진 데이터 세트를 tfrecord 형식을 사용하여 주어진 파일에 씁니다. |
ExperimentalDensetosparsebatchDataset | 입력 요소를 SparSetensor에 배치하는 데이터 세트를 만듭니다. |
ExperimentalLatencyStatsDataset | 통계 분리기에서 'input_dataset'요소를 생성하는 대기 시간을 기록합니다. |
실험용 파일 파일 스 다타 세트 | |
실험 maxintraopparallelismdataset | 최대 OP 인트라이트 병렬 처리를 무시하는 데이터 세트를 만듭니다. |
실험적 parseexampledataset | DT_String의 벡터로`example` protos를 포함하는 'input_dataset`을 구문 분석 기능을 나타내는'tensor` 또는 'sparsetensor` 객체의 데이터 세트로 포함합니다. |
실험적 프리 테트 레드 포 폴다타 세트 | 사용자 정의 스레드 풀을 사용하여 'input_dataset'을 계산하는 데이터 세트를 만듭니다. |
ExperimentalRandomDataset | 의사 숫자를 반환하는 데이터 세트를 만듭니다. |
ExperimentalRebatchDataset | 배치 크기를 변경하는 데이터 세트를 만듭니다. |
실험 sstatsagagatordataset | |
실험용 WINDOWDATASET | 'input_dataset'을 통해 슬라이딩 창을 전달하는 데이터 세트를 만듭니다. |
실험 QLDATASET | SQL 쿼리를 실행하고 결과 세트의 행을 방출하는 데이터 세트를 생성합니다. |
ExperimentalStatSaggregatorHandle | 통계 관리자 리소스를 만듭니다. |
ExperimentalStatSaggregatorSummary | 주어진 통계 관리자가 기록한 통계의 요약을 작성합니다. |
ExperimentalUnUnbatchDataset | 입력의 요소를 여러 요소로 분할하는 데이터 세트. |
expint <t는 숫자를 확장합니다 | |
ExtractGlimpSev2 | 입력 텐서에서 엿볼 수 있습니다. |
ExtractVolumePatches <t는 숫자>를 확장합니다 | `입력 '에서`패치'를 추출하고` "깊이"`출력 차원에 넣으십시오. |
채우기 <u> | 스칼라 값으로 채워진 텐서를 만듭니다. |
지문 | 지문 값을 생성합니다. |
FresnelCos <t는 숫자를 확장합니다 | |
Fresnelsin <t는 숫자를 확장합니다 | |
fusedbatchnormgradv3 <t 연장 번호, u는 숫자를 확장합니다 | 배치 정규화를위한 구배. |
fusedbatchnormv3 <t는 숫자를 확장하고 u는 숫자를 확장합니다 | 배치 정규화. |
groblockcell <t는 숫자를 확장합니다 | GRU 셀 포워드 전파를 1 단계로 계산합니다. |
grublockcellgrad <t는 숫자>를 확장합니다 | Computes the GRU cell back-propagation for 1 time step. |
Gather <T> | Gather slices from `params` axis `axis` according to `indices`. |
GatherNd <T> | Gather slices from `params` into a Tensor with shape specified by `indices`. |
GenerateBoundingBoxProposals | This op produces Region of Interests from given bounding boxes(bbox_deltas) encoded wrt anchors according to eq.2 in arXiv:1506.01497 The op selects top `pre_nms_topn` scoring boxes, decodes them with respect to anchors, applies non-maximal suppression on overlapping boxes with higher than `nms_threshold` intersection-over-union (iou) value, discarding boxes where shorter side is less than `min_size`. |
GetSessionHandle | Store the input tensor in the state of the current session. |
GetSessionTensor <T> | Get the value of the tensor specified by its handle. |
Gradients | Adds operations to compute the partial derivatives of sum of y s wrt x s, ie, 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 wrt |
GuaranteeConst <T> | Gives a guarantee to the TF runtime that the input tensor is a constant. |
HashTable | Creates a non-initialized hash table. |
HistogramFixedWidth <U extends Number> | Return histogram of values. |
Identity <T> | 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. |
IgnoreErrorsDataset | Creates a dataset that contains the elements of `input_dataset` ignoring errors. |
ImageProjectiveTransformV2 <T extends Number> | Applies the given transform to each of the images. |
ImageProjectiveTransformV3 <T extends Number> | Applies the given transform to each of the images. |
ImmutableConst <T> | Returns immutable tensor from memory region. |
InfeedDequeue <T> | 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. |
InfeedEnqueuePrelinearizedBuffer | An op which enqueues prelinearized buffer into TPU infeed. |
InfeedEnqueueTuple | Feeds multiple Tensor values into the computation as an XLA tuple. |
InitializeTable | Table initializer that takes two tensors for keys and values respectively. |
InitializeTableFromDataset | |
InitializeTableFromTextFile | Initializes a table from a text file. |
InplaceAdd <T> | Adds v into specified rows of x. |
InplaceSub <T> | Subtracts `v` into specified rows of `x`. |
InplaceUpdate <T> | Updates specified rows 'i' with values '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. |
IsotonicRegression <U extends Number> | Solves a batch of isotonic regression problems. |
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. |
KthOrderStatistic | Computes the Kth order statistic of a data set. |
LMDBDataset | Creates a dataset that emits the key-value pairs in one or more LMDB files. |
LSTMBlockCell <T extends Number> | Computes the LSTM cell forward propagation for 1 time step. |
LSTMBlockCellGrad <T extends Number> | Computes the LSTM cell backward propagation for 1 timestep. |
LinSpace <T extends Number> | Generates values in an interval. |
LoadTPUEmbeddingADAMParameters | Load ADAM embedding parameters. |
LoadTPUEmbeddingADAMParametersGradAccumDebug | Load ADAM embedding parameters with debug support. |
LoadTPUEmbeddingAdadeltaParameters | Load Adadelta embedding parameters. |
LoadTPUEmbeddingAdadeltaParametersGradAccumDebug | Load Adadelta parameters with debug support. |
LoadTPUEmbeddingAdagradParameters | Load Adagrad embedding parameters. |
LoadTPUEmbeddingAdagradParametersGradAccumDebug | Load Adagrad embedding parameters with debug support. |
LoadTPUEmbeddingCenteredRMSPropParameters | Load centered RMSProp embedding parameters. |
LoadTPUEmbeddingFTRLParameters | Load FTRL embedding parameters. |
LoadTPUEmbeddingFTRLParametersGradAccumDebug | Load FTRL embedding parameters with debug support. |
LoadTPUEmbeddingMDLAdagradLightParameters | Load MDL Adagrad Light embedding parameters. |
LoadTPUEmbeddingMomentumParameters | Load Momentum embedding parameters. |
LoadTPUEmbeddingMomentumParametersGradAccumDebug | Load Momentum embedding parameters with debug support. |
LoadTPUEmbeddingProximalAdagradParameters | Load proximal Adagrad embedding parameters. |
LoadTPUEmbeddingProximalAdagradParametersGradAccumDebug | Load proximal Adagrad embedding parameters with debug support. |
LoadTPUEmbeddingProximalYogiParameters | |
LoadTPUEmbeddingProximalYogiParametersGradAccumDebug | |
LoadTPUEmbeddingRMSPropParameters | Load RMSProp embedding parameters. |
LoadTPUEmbeddingRMSPropParametersGradAccumDebug | Load RMSProp embedding parameters with debug support. |
LoadTPUEmbeddingStochasticGradientDescentParameters | Load SGD embedding parameters. |
LoadTPUEmbeddingStochasticGradientDescentParametersGradAccumDebug | Load SGD embedding parameters. |
LookupTableExport <T, U> | Outputs all keys and values in the table. |
LookupTableFind <U> | 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 Number> | Applies lower_bound(sorted_search_values, values) along each row. |
Lu <T, U extends Number> | Computes the LU decomposition of one or more square matrices. |
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. |
MapIncompleteSize | Op returns the number of incomplete elements in the underlying container. |
MapPeek | Op peeks at the values at the specified key. |
MapSize | Op returns the number of elements in the underlying container. |
MapStage | Stage (key, values) in the underlying container which behaves like a hashtable. |
MapUnstage | Op removes and returns the values associated with the key from the underlying container. |
MapUnstageNoKey | Op removes and returns a random (key, value) from the underlying container. |
MatrixDiagPartV2 <T> | Returns the batched diagonal part of a batched tensor. |
MatrixDiagPartV3 <T> | Returns the batched diagonal part of a batched tensor. |
MatrixDiagV2 <T> | Returns a batched diagonal tensor with given batched diagonal values. |
MatrixDiagV3 <T> | Returns a batched diagonal tensor with given batched diagonal values. |
MatrixSetDiagV2 <T> | Returns a batched matrix tensor with new batched diagonal values. |
MatrixSetDiagV3 <T> | Returns a batched matrix tensor with new batched diagonal values. |
Max <T> | Computes the maximum of elements across dimensions of a tensor. |
MaxIntraOpParallelismDataset | Creates a dataset that overrides the maximum intra-op parallelism. |
Merge <T> | Forwards the value of an available tensor from `inputs` to `output`. |
Min <T> | Computes the minimum of elements across dimensions of a tensor. |
MirrorPad <T> | Pads a tensor with mirrored values. |
MirrorPadGrad <T> | Gradient op for `MirrorPad` op. |
MlirPassthroughOp | Wraps an arbitrary MLIR computation expressed as a module with a main() function. |
MulNoNan <T> | Returns x * y element-wise. |
MutableDenseHashTable | Creates an empty hash table that uses tensors as the backing store. |
MutableHashTable | Creates an empty hash table. |
MutableHashTableOfTensors | Creates an empty hash table. |
뮤텍스 | Creates a Mutex resource that can be locked by `MutexLock`. |
MutexLock | Locks a mutex resource. |
NcclAllReduce <T extends Number> | Outputs a tensor containing the reduction across all input tensors. |
NcclBroadcast <T extends Number> | Sends `input` to all devices that are connected to the output. |
NcclReduce <T extends Number> | Reduces `input` from `num_devices` using `reduction` to a single device. |
Ndtri <T extends Number> | |
NearestNeighbors | Selects the k nearest centers for each point. |
NextAfter <T extends Number> | Returns the next representable value of `x1` in the direction of `x2`, element-wise. |
NextIteration <T> | Makes its input available to the next iteration. |
NoOp | Does nothing. |
NonDeterministicInts <U> | Non-deterministically generates some integers. |
NonMaxSuppressionV5 <T extends Number> | Greedily selects a subset of bounding boxes in descending order of score, pruning away boxes that have high intersection-over-union (IOU) overlap with previously selected boxes. |
NonSerializableDataset | |
OneHot <U> | Returns a one-hot tensor. |
OnesLike <T> | Returns a tensor of ones with the same shape and type as x. |
OptimizeDatasetV2 | Creates a dataset by applying related optimizations to `input_dataset`. |
OrderedMapClear | Op removes all elements in the underlying container. |
OrderedMapIncompleteSize | Op returns the number of incomplete elements in the underlying container. |
OrderedMapPeek | Op peeks at the values at the specified key. |
OrderedMapSize | Op returns the number of elements in the underlying container. |
OrderedMapStage | Stage (key, values) in the underlying container which behaves like a ordered associative container. |
OrderedMapUnstage | Op removes and returns the values associated with the key from the underlying container. |
OrderedMapUnstageNoKey | Op removes and returns the (key, value) element with the smallest key from the underlying container. |
OutfeedDequeue <T> | Retrieves a single tensor from the computation outfeed. |
OutfeedDequeueTuple | Retrieve multiple values from the computation outfeed. |
OutfeedDequeueTupleV2 | Retrieve multiple values from the computation outfeed. |
OutfeedDequeueV2 <T> | Retrieves a single tensor from the computation outfeed. |
OutfeedEnqueue | Enqueue a Tensor on the computation outfeed. |
OutfeedEnqueueTuple | Enqueue multiple Tensor values on the computation outfeed. |
Pad <T> | Pads a tensor. |
ParallelConcat <T> | Concatenates a list of `N` tensors along the first dimension. |
ParallelDynamicStitch <T> | Interleave the values from the `data` tensors into a single tensor. |
ParseExampleDatasetV2 | Transforms `input_dataset` containing `Example` protos as vectors of DT_STRING into a dataset of `Tensor` or `SparseTensor` objects representing the parsed features. |
ParseExampleV2 | Transforms a vector of tf.Example protos (as strings) into typed tensors. |
ParseSequenceExampleV2 | Transforms a vector of tf.io.SequenceExample protos (as strings) into typed tensors. |
Placeholder <T> | A placeholder op for a value that will be fed into the computation. |
PlaceholderWithDefault <T> | 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. |
PrelinearizeTuple | An op which linearizes multiple Tensor values to an opaque variant tensor. |
PrimitiveOp | A base class for Op implementations that are backed by a single Operation . |
인쇄 | Prints a string scalar. |
PrivateThreadPoolDataset | Creates a dataset that uses a custom thread pool to compute `input_dataset`. |
Prod <T> | Computes the product of elements across dimensions of a tensor. |
QuantizeAndDequantizeV4 <T extends Number> | Returns the gradient of `QuantizeAndDequantizeV4`. |
QuantizeAndDequantizeV4Grad <T extends Number> | Returns the gradient of `QuantizeAndDequantizeV4`. |
QuantizedConcat <T> | Concatenates quantized tensors along one dimension. |
QuantizedConv2DAndRelu <V> | |
QuantizedConv2DAndReluAndRequantize <V> | |
QuantizedConv2DAndRequantize <V> | |
QuantizedConv2DPerChannel <V> | Computes QuantizedConv2D per channel. |
QuantizedConv2DWithBias <V> | |
QuantizedConv2DWithBiasAndRelu <V> | |
QuantizedConv2DWithBiasAndReluAndRequantize <W> | |
QuantizedConv2DWithBiasAndRequantize <W> | |
QuantizedConv2DWithBiasSignedSumAndReluAndRequantize <X> | |
QuantizedConv2DWithBiasSumAndRelu <V> | |
QuantizedConv2DWithBiasSumAndReluAndRequantize <X> | |
QuantizedDepthwiseConv2D <V> | Computes quantized depthwise Conv2D. |
QuantizedDepthwiseConv2DWithBias <V> | Computes quantized depthwise Conv2D with Bias. |
QuantizedDepthwiseConv2DWithBiasAndRelu <V> | Computes quantized depthwise Conv2D with Bias and Relu. |
QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize <W> | Computes quantized depthwise Conv2D with Bias, Relu and Requantize. |
QuantizedMatMulWithBias <W> | Performs a quantized matrix multiplication of `a` by the matrix `b` with bias add. |
QuantizedMatMulWithBiasAndDequantize <W extends Number> | |
QuantizedMatMulWithBiasAndRelu <V> | Perform a quantized matrix multiplication of `a` by the matrix `b` with bias add and relu fusion. |
QuantizedMatMulWithBiasAndReluAndRequantize <W> | Perform a quantized matrix multiplication of `a` by the matrix `b` with bias add and relu and requantize fusion. |
QuantizedMatMulWithBiasAndRequantize <W> | |
QuantizedReshape <T> | Reshapes a quantized tensor as per the Reshape op. |
RaggedBincount <U extends Number> | Counts the number of occurrences of each value in an integer array. |
RaggedCountSparseOutput <U extends Number> | Performs sparse-output bin counting for a ragged tensor input. |
RaggedCross <T, U extends Number> | Generates a feature cross from a list of tensors, and returns it as a RaggedTensor. |
RaggedGather <T extends Number, U> | Gather ragged slices from `params` axis `0` according to `indices`. |
RaggedRange <U extends Number, T extends Number> | Returns a `RaggedTensor` containing the specified sequences of numbers. |
RaggedTensorFromVariant <U extends Number, T> | Decodes a `variant` Tensor into a `RaggedTensor`. |
RaggedTensorToSparse <U> | Converts a `RaggedTensor` into a `SparseTensor` with the same values. |
RaggedTensorToTensor <U> | Create a dense tensor from a ragged tensor, possibly altering its shape. |
RaggedTensorToVariant | Encodes a `RaggedTensor` into a `variant` Tensor. |
RaggedTensorToVariantGradient <U> | Helper used to compute the gradient for `RaggedTensorToVariant`. |
Range <T extends Number> | Creates a sequence of numbers. |
계급 | Returns the rank of a tensor. |
ReadVariableOp <T> | Reads the value of a variable. |
RebatchDataset | Creates a dataset that changes the batch size. |
RebatchDatasetV2 | Creates a dataset that changes the batch size. |
Recv <T> | Receives the named tensor from send_device on recv_device. |
RecvTPUEmbeddingActivations | An op that receives embedding activations on the TPU. |
ReduceAll | Computes the "logical and" of elements across dimensions of a tensor. |
ReduceAny | Computes the "logical or" of elements across dimensions of a tensor. |
ReduceMax <T> | Computes the maximum of elements across dimensions of a tensor. |
ReduceMin <T> | Computes the minimum of elements across dimensions of a tensor. |
ReduceProd <T> | Computes the product of elements across dimensions of a tensor. |
ReduceSum <T> | Computes the sum of elements across dimensions of a tensor. |
RefEnter <T> | Creates or finds a child frame, and makes `data` available to the child frame. |
RefExit <T> | Exits the current frame to its parent frame. |
RefIdentity <T> | Return the same ref tensor as the input ref tensor. |
RefMerge <T> | Forwards the value of an available tensor from `inputs` to `output`. |
RefNextIteration <T> | Makes its input available to the next iteration. |
RefSelect <T> | Forwards the `index`th element of `inputs` to `output`. |
RefSwitch <T> | Forwards the ref tensor `data` to the output port determined by `pred`. |
RegisterDataset | Registers a dataset with the tf.data service. |
RemoteFusedGraphExecute | Execute a sub graph on a remote processor. |
RequantizationRangePerChannel | Computes requantization range per channel. |
RequantizePerChannel <U> | Requantizes input with min and max values known per channel. |
Reshape <T> | 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 <T> | Extracts the average gradient in the given ConditionalAccumulator. |
ResourceApplyAdagradV2 | Update '*var' according to the adagrad scheme. |
ResourceApplyAdamWithAmsgrad | Adam 알고리즘에 따라 '*var'를 업데이트합니다. |
ResourceApplyKerasMomentum | Update '*var' according to the momentum scheme. |
ResourceConditionalAccumulator | A conditional accumulator for aggregating gradients. |
ResourceCountUpTo <T extends Number> | Increments variable pointed to by 'resource' until it reaches 'limit'. |
ResourceGather <U> | Gather slices from the variable pointed to by `resource` according to `indices`. |
ResourceGatherNd <U> | |
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. |
ResourceScatterNdMax | |
ResourceScatterNdMin | |
ResourceScatterNdSub | Applies sparse subtraction to individual values or slices in a Variable. |
ResourceScatterNdUpdate | Applies sparse `updates` to individual values or slices within a given variable according to `indices`. |
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. |
ResourceSparseApplyKerasMomentum | Update relevant entries in '*var' and '*accum' according to the momentum scheme. |
ResourceStridedSliceAssign | Assign `value` to the sliced l-value reference of `ref`. |
RetrieveTPUEmbeddingADAMParameters | Retrieve ADAM embedding parameters. |
RetrieveTPUEmbeddingADAMParametersGradAccumDebug | Retrieve ADAM embedding parameters with debug support. |
RetrieveTPUEmbeddingAdadeltaParameters | Retrieve Adadelta embedding parameters. |
RetrieveTPUEmbeddingAdadeltaParametersGradAccumDebug | Retrieve Adadelta embedding parameters with debug support. |
RetrieveTPUEmbeddingAdagradParameters | Retrieve Adagrad embedding parameters. |
RetrieveTPUEmbeddingAdagradParametersGradAccumDebug | Retrieve Adagrad embedding parameters with debug support. |
RetrieveTPUEmbeddingCenteredRMSPropParameters | Retrieve centered RMSProp embedding parameters. |
RetrieveTPUEmbeddingFTRLParameters | Retrieve FTRL embedding parameters. |
RetrieveTPUEmbeddingFTRLParametersGradAccumDebug | Retrieve FTRL embedding parameters with debug support. |
RetrieveTPUEmbeddingMDLAdagradLightParameters | Retrieve MDL Adagrad Light embedding parameters. |
RetrieveTPUEmbeddingMomentumParameters | Retrieve Momentum embedding parameters. |
RetrieveTPUEmbeddingMomentumParametersGradAccumDebug | Retrieve Momentum embedding parameters with debug support. |
RetrieveTPUEmbeddingProximalAdagradParameters | Retrieve proximal Adagrad embedding parameters. |
RetrieveTPUEmbeddingProximalAdagradParametersGradAccumDebug | Retrieve proximal Adagrad embedding parameters with debug support. |
RetrieveTPUEmbeddingProximalYogiParameters | |
RetrieveTPUEmbeddingProximalYogiParametersGradAccumDebug | |
RetrieveTPUEmbeddingRMSPropParameters | Retrieve RMSProp embedding parameters. |
RetrieveTPUEmbeddingRMSPropParametersGradAccumDebug | Retrieve RMSProp embedding parameters with debug support. |
RetrieveTPUEmbeddingStochasticGradientDescentParameters | Retrieve SGD embedding parameters. |
RetrieveTPUEmbeddingStochasticGradientDescentParametersGradAccumDebug | Retrieve SGD embedding parameters with debug support. |
Reverse <T> | Reverses specific dimensions of a tensor. |
ReverseSequence <T> | Reverses variable length slices. |
RngReadAndSkip | Advance the counter of a counter-based RNG. |
RngSkip | Advance the counter of a counter-based RNG. |
Roll <T> | Rolls the elements of a tensor along an axis. |
Rpc | Perform batches of RPC requests. |
SamplingDataset | Creates a dataset that takes a Bernoulli sample of the contents of another dataset. |
ScaleAndTranslate | |
ScaleAndTranslateGrad <T extends Number> | |
ScatterAdd <T> | Adds sparse updates to a variable reference. |
ScatterDiv <T> | Divides a variable reference by sparse updates. |
ScatterMax <T extends Number> | Reduces sparse updates into a variable reference using the `max` operation. |
ScatterMin <T extends Number> | Reduces sparse updates into a variable reference using the `min` operation. |
ScatterMul <T> | Multiplies sparse updates into a variable reference. |
ScatterNd <U> | Scatter `updates` into a new tensor according to `indices`. |
ScatterNdAdd <T> | Applies sparse addition to individual values or slices in a Variable. |
ScatterNdMax <T> | Computes element-wise maximum. |
ScatterNdMin <T> | Computes element-wise minimum. |
ScatterNdNonAliasingAdd <T> | 개별 값이나 조각을 사용하여 '입력'에 희소 추가를 적용합니다. 인덱스 `인덱스`에 따른 `업데이트`에서. |
ScatterNdSub <T> | Applies sparse subtraction to individual values or slices in a Variable. |
ScatterNdUpdate <T> | Applies sparse `updates` to individual values or slices within a given variable according to `indices`. |
ScatterSub <T> | Subtracts sparse updates to a variable reference. |
ScatterUpdate <T> | Applies sparse updates to a variable reference. |
SelectV2 <T> | |
보내다 | Sends the named tensor from send_device to recv_device. |
SendTPUEmbeddingGradients | Performs gradient updates of embedding tables. |
SetDiff1d <T, U extends Number> | Computes the difference between two lists of numbers or strings. |
SetSize | Number of unique elements along last dimension of input `set`. |
Shape <U extends Number> | Returns the shape of a tensor. |
ShapeN <U extends Number> | Returns shape of tensors. |
ShardDataset | Creates a `Dataset` that includes only 1/`num_shards` of this dataset. |
ShuffleAndRepeatDatasetV2 | |
ShuffleDatasetV2 | |
ShuffleDatasetV3 | |
ShutdownDistributedTPU | Shuts down a running distributed TPU system. |
Size <U extends Number> | Returns the size of a tensor. |
Skipgram | Parses a text file and creates a batch of examples. |
SleepDataset | |
Slice <T> | Return a slice from 'input'. |
SlidingWindowDataset | Creates a dataset that passes a sliding window over `input_dataset`. |
Snapshot <T> | Returns a copy of the input tensor. |
SnapshotDataset | Creates a dataset that will write to / read from a snapshot. |
SobolSample <T extends Number> | Generates points from the Sobol sequence. |
SpaceToBatchNd <T> | SpaceToBatch for ND tensors of type T. |
SparseApplyAdagradV2 <T> | Update relevant entries in '*var' and '*accum' according to the adagrad scheme. |
SparseBincount <U extends Number> | Counts the number of occurrences of each value in an integer array. |
SparseCountSparseOutput <U extends Number> | Performs sparse-output bin counting for a sparse tensor input. |
SparseCrossHashed | Generates sparse cross from a list of sparse and dense tensors. |
SparseCrossV2 | Generates sparse cross from a list of sparse and dense tensors. |
SparseMatrixAdd | Sparse addition of two CSR matrices, C = alpha * A + beta * B. |
SparseMatrixMatMul <T> | Matrix-multiplies a sparse matrix with a dense matrix. |
SparseMatrixMul | Element-wise multiplication of a sparse matrix with a dense tensor. |
SparseMatrixNNZ | Returns the number of nonzeroes of `sparse_matrix`. |
SparseMatrixOrderingAMD | Computes the Approximate Minimum Degree (AMD) ordering of `input`. |
SparseMatrixSoftmax | Calculates the softmax of a CSRSparseMatrix. |
SparseMatrixSoftmaxGrad | Calculates the gradient of the SparseMatrixSoftmax op. |
SparseMatrixSparseCholesky | Computes the sparse Cholesky decomposition of `input`. |
SparseMatrixSparseMatMul | Sparse-matrix-multiplies two CSR matrices `a` and `b`. |
SparseMatrixTranspose | Transposes the inner (matrix) dimensions of a CSRSparseMatrix. |
SparseMatrixZeros | Creates an all-zeros CSRSparseMatrix with shape `dense_shape`. |
SparseTensorToCSRSparseMatrix | Converts a SparseTensor to a (possibly batched) CSRSparseMatrix. |
Spence <T extends Number> | |
Split <T> | Splits a tensor into `num_split` tensors along one dimension. |
SplitV <T> | Splits a tensor into `num_split` tensors along one dimension. |
Squeeze <T> | Removes dimensions of size 1 from the shape of a tensor. |
Stack <T> | Packs a list of `N` rank-`R` tensors into one rank-`(R+1)` tensor. |
단계 | Stage values similar to a lightweight Enqueue. |
StageClear | Op removes all elements in the underlying container. |
StagePeek | Op peeks at the values at the specified index. |
StageSize | Op returns the number of elements in the underlying container. |
StatefulRandomBinomial <V extends Number> | |
StatefulStandardNormal <U> | Outputs random values from a normal distribution. |
StatefulStandardNormalV2 <U> | Outputs random values from a normal distribution. |
StatefulTruncatedNormal <U> | Outputs random values from a truncated normal distribution. |
StatefulUniform <U> | Outputs random values from a uniform distribution. |
StatefulUniformFullInt <U> | Outputs random integers from a uniform distribution. |
StatefulUniformInt <U> | Outputs random integers from a uniform distribution. |
StatelessParameterizedTruncatedNormal <V extends Number> | |
StatelessRandomBinomial <W extends Number> | Outputs deterministic pseudorandom random numbers from a binomial distribution. |
StatelessRandomGammaV2 <V extends Number> | Outputs deterministic pseudorandom random numbers from a gamma distribution. |
StatelessRandomGetKeyCounterAlg | Picks the best algorithm based on device, and scrambles seed into key and counter. |
StatelessRandomNormalV2 <U extends Number> | Outputs deterministic pseudorandom values from a normal distribution. |
StatelessRandomPoisson <W extends Number> | Outputs deterministic pseudorandom random numbers from a Poisson distribution. |
StatelessRandomUniformFullInt <V extends Number> | Outputs deterministic pseudorandom random integers from a uniform distribution. |
StatelessRandomUniformFullIntV2 <U extends Number> | Outputs deterministic pseudorandom random integers from a uniform distribution. |
StatelessRandomUniformIntV2 <U extends Number> | Outputs deterministic pseudorandom random integers from a uniform distribution. |
StatelessRandomUniformV2 <U extends Number> | Outputs deterministic pseudorandom random values from a uniform distribution. |
StatelessSampleDistortedBoundingBox <T extends Number> | Generate a randomly distorted bounding box for an image deterministically. |
StatelessTruncatedNormalV2 <U extends Number> | Outputs deterministic pseudorandom values from a truncated normal distribution. |
StatsAggregatorHandleV2 | |
StatsAggregatorSetSummaryWriter | Set a summary_writer_interface to record statistics using given stats_aggregator. |
StopGradient <T> | Stops gradient computation. |
StridedSlice <T> | Return a strided slice from `input`. |
StridedSliceAssign <T> | Assign `value` to the sliced l-value reference of `ref`. |
StridedSliceGrad <U> | Returns the gradient of `StridedSlice`. |
StringLower | Converts all uppercase characters into their respective lowercase replacements. |
StringNGrams <T extends Number> | Creates ngrams from ragged string data. |
StringUpper | Converts all lowercase characters into their respective uppercase replacements. |
Sum <T> | Computes the sum of elements across dimensions of a tensor. |
SwitchCond <T> | Forwards `data` to the output port determined by `pred`. |
TPUCompilationResult | Returns the result of a TPU compilation. |
TPUCompileSucceededAssert | Asserts that compilation succeeded. |
TPUEmbeddingActivations | An op enabling differentiation of TPU Embeddings. |
TPUExecute | Op that loads and executes a TPU program on a TPU device. |
TPUExecuteAndUpdateVariables | Op that executes a program with optional in-place variable updates. |
TPUOrdinalSelector | A TPU core selector Op. |
TPUPartitionedInput <T> | An op that groups a list of partitioned inputs together. |
TPUPartitionedOutput <T> | An op that demultiplexes a tensor to be sharded by XLA to a list of partitioned outputs outside the XLA computation. |
TPUReplicateMetadata | Metadata indicating how the TPU computation should be replicated. |
TPUReplicatedInput <T> | Connects N inputs to an N-way replicated TPU computation. |
TPUReplicatedOutput <T> | Connects N outputs from an N-way replicated TPU computation. |
TemporaryVariable <T> | Returns a tensor that may be mutated, but only persists within a single step. |
TensorArray | An array of Tensors of given size. |
TensorArrayClose | Delete the TensorArray from its resource container. |
TensorArrayConcat <T> | Concat the elements from the TensorArray into value `value`. |
TensorArrayGather <T> | Gather specific elements from the TensorArray into output `value`. |
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> | |
TensorArrayRead <T> | 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 |
TensorForestTreeSerialize | Serializes the tree handle to a proto |
TensorForestTreeSize | Get the number of nodes in a tree |
TensorListConcat <T> | Concats all tensors in the list along the 0th dimension. |
TensorListConcatLists | |
TensorListConcatV2 <U> | Concats all tensors in the list along the 0th dimension. |
TensorListElementShape <T extends Number> | 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> | Creates a Tensor by indexing into the TensorList. |
TensorListGetItem <T> | |
TensorListLength | Returns the number of tensors in the input tensor list. |
TensorListPopBack <T> | 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 <T> | Stacks all tensors in the list. |
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> | Returns the value from a given key in a tensor map. |
TensorMapSize | Returns the number of tensors in the input tensor map. |
TensorMapStackKeys <T> | Returns a Tensor stack of all keys in a tensor map. |
TensorScatterAdd <T> | Adds sparse `updates` to an existing tensor according to `indices`. |
TensorScatterMax <T> | |
TensorScatterMin <T> | |
TensorScatterSub <T> | Subtracts sparse `updates` from an existing tensor according to `indices`. |
TensorScatterUpdate <T> | Scatter `updates` into an existing tensor according to `indices`. |
TensorStridedSliceUpdate <T> | Assign `value` to the sliced l-value reference of `input`. |
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`. |
Tile <T> | Constructs a tensor by tiling a given tensor. |
Timestamp | Provides the time since epoch in seconds. |
ToBool | Converts a tensor to a scalar predicate. |
TopKUnique | Returns the TopK unique values in the array in sorted order. |
TopKWithUnique | Returns the TopK values in the array in sorted order. |
TridiagonalMatMul <T> | Calculate product with tridiagonal matrix. |
TridiagonalSolve <T> | Solves tridiagonal systems of equations. |
TryRpc | Perform batches of RPC requests. |
Unbatch <T> | Reverses the operation of Batch for a single output Tensor. |
UnbatchGrad <T> | Gradient of Unbatch. |
UncompressElement | Uncompresses a compressed dataset element. |
UnicodeDecode <T extends Number> | Decodes each string in `input` into a sequence of Unicode code points. |
UnicodeEncode | Encode a tensor of ints into unicode strings. |
Unique <T, V extends Number> | Finds unique elements along an axis of a tensor. |
UniqueDataset | Creates a dataset that contains the unique elements of `input_dataset`. |
UniqueWithCounts <T, V extends Number> | Finds unique elements along an axis of a tensor. |
UnravelIndex <T extends Number> | Converts an array of flat indices into a tuple of coordinate arrays. |
UnsortedSegmentJoin | Joins the elements of `inputs` based on `segment_ids`. |
Unstack <T> | Unpacks a given dimension of a rank-`R` tensor into `num` rank-`(R-1)` tensors. |
Unstage | Op is similar to a lightweight Dequeue. |
UnwrapDatasetVariant | |
UpperBound <U extends Number> | Applies upper_bound(sorted_search_values, values) along each row. |
VarHandleOp | Creates a handle to a Variable resource. |
VarIsInitializedOp | Checks whether a resource handle-based variable has been initialized. |
Variable <T> | Holds state in the form of a tensor that persists across steps. |
VariableShape <T extends Number> | Returns the shape of the variable pointed to by `resource`. |
어디 | Returns locations of nonzero / true values in a tensor. |
Where3 <T> | Selects elements from `x` or `y`, depending on `condition`. |
WorkerHeartbeat | Worker heartbeat op. |
WrapDatasetVariant | |
WriteRawProtoSummary | Writes a serialized proto summary. |
XlaRecvFromHost <T> | An op to receive a tensor from the host. |
XlaSendToHost | An op to send a tensor to the host. |
Xlog1py <T> | Returns 0 if x == 0, and x * log1p(y) otherwise, elementwise. |
Zeros <T> | An operator creating a constant initialized with zeros of the shape given by `dims`. |
ZerosLike <T> | Returns a tensor of zeros with the same shape and type as x. |