| 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. |