إحباط | رفع استثناء لإحباط العملية عند استدعاء. |
الجميع | يحسب "المنطق و" العناصر عبر أبعاد الموتر. |
alltoall <T> | OP لتبادل البيانات عبر النسخ المتماثلة TPU. |
Anonymousiteratorv2 | حاوية لمورد Iterator. |
AnonymousMemorycache | |
AnonymousMultIdeViceIrator | حاوية لمورد ITerator متعدد الجهاز. |
مجهول المجهول | |
مجهول | |
أي | يحسب "المنطق أو" للعناصر عبر أبعاد التوتر. |
ApplicAdAgRadv2 <T> | تحديث "*var" وفقًا لمخطط Adagrad. |
assertcardinalitydataset | |
AssertNextDataset | تحول يؤكد التحولات التي تحدث بعد ذلك. |
التأكيد | يؤكد أن الشرط المحدد صحيح. |
تعيين <T> | تحديث "المرجع" عن طريق تعيين "قيمة" لها. |
issidadd <t> | تحديث "المرجع" عن طريق إضافة "قيمة" إليها. |
envisiddvariableOP | يضيف قيمة إلى القيمة الحالية للمتغير. |
issidsub <t> | تحديث "المرجع" عن طريق طرح "القيمة" منه. |
تعيين ubvariable | يطرح قيمة من القيمة الحالية للمتغير. |
envariableOp | يعين قيمة جديدة لمتغير. |
AutoshardDataset | ينشئ مجموعة بيانات تقوي مجموعة بيانات الإدخال. |
BandedTriangularsolve <T> | |
حاجز | يحدد الحاجز الذي يستمر عبر عمليات إعدام الرسوم البيانية المختلفة. |
Barrierclose | يغلق الحاجز المعطى. |
BarrierIncompletesize | يحسب عدد العناصر غير المكتملة في الحاجز المحدد. |
Barrierinsertmany | لكل مفتاح ، يعين القيمة المعنية للمكون المحدد. |
BarrierReadySize | يحسب عدد العناصر الكاملة في الحاجز المحدد. |
Barriertakemany | يأخذ عدد معين من العناصر المكتملة من حاجز. |
حزمة | الدُفعات جميع موترات الإدخال غير محددة. |
BatchMatmulv2 <T> | يضاعف شرائح اثنين من الموترات على دفعات. |
batchtospace <T> | Batchtospace لـ 4-D Tensors من Type T. |
batchtospacend <T> | Batchtospace ل ND Tensors من النوع T. |
Besseli0 <T يمتد الرقم> | |
Besseli1 <T يمتد الرقم> | |
Besselj0 <T يمتد الرقم> | |
Besselj1 <T يمتد الرقم> | |
Besselk0 <T يمتد الرقم> | |
Besselk0e <t يمتد الرقم> | |
Besselk1 <T يمتد الرقم> | |
Besselk1e <t يمتد الرقم> | |
Bessely0 <T يمتد الرقم> | |
Bessely1 <T يمتد الرقم> | |
bitcast <u> | Bitcasts توتر من نوع إلى آخر دون نسخ البيانات. |
blocklstm <t يمتد الرقم> | يحسب انتشار خلية LSTM إلى الأمام لجميع الخطوات الزمنية. |
blocklstmgrad <t يمتد الرقم> | يحسب انتشار خلية LSTM للخلف لتسلسل الوقت بأكمله. |
blocklstmgradv2 <t يمتد الرقم> | يحسب انتشار خلية LSTM للخلف لتسلسل الوقت بأكمله. |
blocklstmv2 <t يمتد الرقم> | يحسب انتشار خلية LSTM إلى الأمام لجميع الخطوات الزمنية. |
BOOSTEDTREESAGGGERESTATSATS | يجمع ملخص الإحصائيات المتراكمة للدفعة. |
BOOSTEDTREESBUCKETIZE | دلو كل ميزة تعتمد على حدود دلو. |
BOOSTEDTREESCALITERBESTFEATURESPLIT | يحسب المكاسب لكل ميزة ويعيد أفضل معلومات تقسيم ممكنة لهذه الميزة. |
BOOSTEDTREESCALITERBESTFEATURESPLITV2 | يحسب المكاسب لكل ميزة ويعيد أفضل معلومات تقسيم ممكن لكل عقدة. |
BOOSTEDTREESCALITERBESTGAINSPERFEATURE | يحسب المكاسب لكل ميزة ويعيد أفضل معلومات تقسيم ممكنة لهذه الميزة. |
BOOSTEDTREESCENTERBIAS | يحسب المسبق من بيانات التدريب (التحيز) ويملأ العقدة الأولى مع مسبق سجلات. |
BOOSTEDTREESCREATENSEMBLE | ينشئ نموذج فرقة شجرة ويعيد مقبض عليه. |
BOOSTEDTRESCREATEVENILESTEREAMRESORCE | إنشاء مورد للتيارات الكمية. |
BOOSTEDTREESDESERIALIZEENSEMBLE | يفرز تكوين مجموعة الأشجار المسلسل ويحل محل الشجرة الحالية فرقة. |
BOOSTEDTREESENSEMBLERSORCEHANDLEOP | يخلق مقبضًا مع BoostEdTreesenSemblerSource |
BOOSTEDTREESEXAMPLEDEBUGUTPUTs | تصحيح الأخطاء/مخرجات تفسير النموذج لكل مثال. |
BOOSTEDTREESFLUSHQUANTILESUMMIRAMARIS | قم بتدفق الملخصات الكمية من كل مورد تيار كمي. |
BOOSTEDTREESGETENSEMBLESTATES | يسترجع رمز ختم الموارد لمجموعة الشجرة ، وعدد الأشجار والإحصاءات المتنامية. |
BOOSTEDTREESMAKEQUANTILESUMMARIS | يجعل ملخص الكميات للدفعة. |
BOOSTEDTREESMAKESTATSSUMMARY | يجعل ملخص الإحصائيات المتراكمة للدفعة. |
BOOSTEDTREESPREDICT | يدير متعددة تنبؤات فرقة الانحدار الإضافي على مثيلات الإدخال و يحسب السجلات. |
BOOSTEDTREESQUANTILESTEARMRESORCEADDSUMMIRS | أضف الملخصات الكمية إلى كل مورد دفق كمي. |
BOOSTEDTREESQUANTILESTEREAMRESORCEREDESERIALIZE | حدود دلو تخلص من الدلو والعلم الجاهز في الكمية الكمية الحالية. |
BOOSTEDTREESQUANTILESTEARMRESORCEFLUSH | قم بتدفق الملخصات لمورد تيار كمي. |
BOOSTEDTREESQUANTILESTEARMRESORCETBUCKETBOUNDIRAIRS | قم بإنشاء حدود الجرافة لكل ميزة استنادًا إلى الملخصات المتراكمة. |
BOOSTEDTREESQUANTILESTEARMRESORCEHANDLEOP | يخلق مقبضًا على BOOSTEDTREESQUANTILESTEARMRESORCE. |
BOOSTEDTREESSERIALIZEENSEMBLE | تسلسل مجموعة الشجرة إلى بروتو. |
BOOSTEDTREESSPARSEAGGREGATESTATS | يجمع ملخص الإحصائيات المتراكمة للدفعة. |
BOOSTEDTREESSPARSECALITYBESTFEATURESPLIT | يحسب المكاسب لكل ميزة ويعيد أفضل معلومات تقسيم ممكنة لهذه الميزة. |
BOOSTEDTREESTRAINING | يدير متعددة تنبؤات فرقة الانحدار الإضافي على مثيلات الإدخال و يحسب التحديث إلى سجلات المخزونات المخزنة مؤقتًا. |
BOOSTEDTREESUPDATEENSEMBLE | يقوم بتحديث مجموعة الشجرة إما بإضافة طبقة إلى الشجرة الأخيرة التي يتم زراعها أو عن طريق بدء شجرة جديدة. |
BOOSTEDTREESUPDATEENSEMBLEV2 | يقوم بتحديث مجموعة الشجرة عن طريق إضافة طبقة إلى الشجرة الأخيرة التي يتم زراعها أو عن طريق بدء شجرة جديدة. |
BroadcastDynamicshape <T يمتد الرقم> | إرجاع شكل S0 OP S1 مع البث. |
BroudcastgradientArgs <t يمتد الرقم> | إرجاع مؤشرات التخفيض للحصول على تدرجات الحوسبة من S0 OP S1 مع البث. |
البث <t> | بث صفيف لشكل متوافق. |
دلو | دلو "المدخلات" على أساس "الحدود". |
csrsparsematrixComponents <T> | يقرأ مكونات CSR في الدفعة `index`. |
csrsparsematrixTodense <T> | تحويل CSRSParsEmatrix (ربما مزجّن) إلى كثافة. |
csrsparsematrixtoSparSetensor <T> | يحول CSRSParesMatrix (ربما مزجّه) إلى sparsetensor. |
CSVDATASET | |
CSVDATASETV2 | |
CTClossv2 | يحسب فقدان CTC (احتمال السجل) لكل إدخال دفعة. |
cachedatasetv2 | |
checkNumericsv2 <T يمتد الرقم> | يتحقق موتر لقيم NAN ، -inf و +INF. |
اختر STAFTESTDATASET | |
ClipByValue <T> | مقاطع القيم الموتر إلى دقيقة محددة وحد أقصى. |
الجماعي <T يمتد الرقم> | يتراكم المتبادل موترات متعددة من النوع المتطابق والشكل. |
collectivegatherv2 <t يمتد الرقم> | يتراكم المتبادل موترات متعددة من النوع المتطابق والشكل. |
collectivepermute <T> | OP لتصور الموترات عبر مثيلات TPU المتكررة. |
collectivereducev2 <t يمتد الرقم> | يقلل المتبادل بين الموترات المتعددة من النوع المتطابق والشكل. |
CombinedNonmaxSupression | يختار جشع مجموعة فرعية من الصناديق المحيطة بترتيب تنازلي للنتيجة ، تنفذ هذه العملية non_max_supression على المدخلات لكل دفعة ، عبر جميع الفئات. |
الانضغاط | يضغط عنصر مجموعة البيانات. |
computeBatchSize | يحسب حجم الدُفعة الثابتة لمجموعة البيانات بلا دفعات جزئية. |
Concat <T> | تسلسل الموتر على طول بعد واحد. |
configuredistributedTPU | إعداد الهياكل المركزية لنظام TPU موزع. |
configureTpuembedding | إعداد tpuembedding في نظام TPU موزع. |
ثابت <T> | مشغل ينتج قيمة ثابتة. |
Consumemutexlock | يستهلك هذا المرجع قفلًا تم إنشاؤه بواسطة "mutexlock". |
ControlTrigger | لا شيء. |
نسخ <T> | انسخ موتر من وحدة المعالجة المركزية إلى CPU أو GPU إلى GPU. |
copyhost <t> | انسخ موتر للاستضافة. |
countupto <t يمتد الرقم> | الزيادات "المرجع" حتى يصل إلى "الحد". |
crossreplicasum <t يمتد الرقم> | OP لتلخيص المدخلات عبر مثيلات TPU المتكررة. |
CudnnrnnnbackPropv3 <t يمتد الرقم> | خطوة backprop من cudnnrnnv3. |
cudnnrnncanonicaltoparamsv2 <t يمتد الرقم> | يحول cudnnrnn params من الشكل الكنسي إلى شكل قابل للاستخدام. |
cudnnrnnnnparamstocanonicalv2 <t يمتد الرقم> | يسترجع cudnnrnn params في الشكل الكنسي. |
cudnnrnnv3 <t يمتد الرقم> | RNN مدعوم من قبل كودن. |
Cumulativelogsumexp <T يمتد الرقم> | حساب المنتج التراكمي من الموتر `x` على طول" المحور ". |
DataServiceRataSet | |
DatasetCardinality | إرجاع Cardinality من `input_dataset`. |
DatasetFromgraph | ينشئ مجموعة بيانات من "Graph_Def` المعطى". |
DatasetTographV2 | إرجاع GraphDef التسلسلي الذي يمثل `input_dataset`. |
Dawsn <t يمتد الرقم> | |
DebuGrgradientIdentity <T> | الهوية OP لتصحيح الأخطاء التدرج. |
debuggradientRefidentity <T> | الهوية OP لتصحيح الأخطاء التدرج. |
تصحيح الأخطاء <T> | يوفر رسم خرائط للهوية لمتوسع إدخال النوع غير REF لتصحيح الأخطاء. |
debugidentityv2 <T> | Debug Identity V2 OP. |
Debugnancount | Debug NAN قيمة عداد العداد. |
Debugnumericsummary | ملخص Debug Numeric OP. |
debugnumericsummaryv2 <U يمتد الرقم> | Debug Numeric Summary v2 op. |
decodeimage <t يمتد الرقم> | دالة لـ decode_bmp و decode_gif و decode_jpeg و decode_png. |
decodepaddedraw <t يمتد الرقم> | إعادة تفسير بايت سلسلة كمتجهات للأرقام. |
DecodeProto | يستخلص OP الحقول من رسالة بروتوكول تسلسلي إلى موترات. |
DeepCopy <T> | يجعل نسخة من `x`. |
Deleteiterator | حاوية لمورد Iterator. |
DELETEMEMORYCACHE | |
DeletemultideViceIrator | حاوية لمورد Iterator. |
DeLeterOmseedGenerator | |
deleteseedgenerator | |
DeletesessionTensor | احذف الموتر المحدد بمقبضه في الجلسة. |
DenseBincount <U يمتد الرقم> | يحسب عدد حوادث كل قيمة في مجموعة عدد صحيح. |
densecountsparseoutput <U يمتد الرقم> | يؤدي عد صندوق المخرجات المتفرقة لإدخال TF.Tensor. |
densetocsrsparsematrix | يحول موتر كثيف إلى (ربما مزجّن) csrsparsematrix. |
DorterResourceop | يحذف المورد المحدد بواسطة المقبض. |
DestroytemporaryVariable <T> | يدمر المتغير المؤقت ويعيد قيمته النهائية. |
DeviceIndex | إرجاع فهرس الجهاز يعمل OP. |
الموجهة ErganInterleavedataset | بديل لـ `interleavedataset` على قائمة ثابتة من مجموعات البيانات. |
DrawBoundingBoxESV2 <T يمتد الرقم> | ارسم مربعات محددة على مجموعة من الصور. |
DummyTerationCounter | |
dummymemorycache | |
DummySeedgenerator | |
DynamicPartition <T> | أقسام "البيانات" في "num_partitions" باستخدام مؤشرات من "الأقسام". |
DynamicStitch <T> | interleave القيم من `data` engesors في موتر واحد. |
editdistance | يحسب مسافة تحرير Levenshtein (ربما تطبيع). |
eig <u> | يحسب تحلل eigen لمصفوفات مربعة واحدة أو أكثر. |
einsum <T> | تقلص التوتر وفقا لاتفاقية إينشتاين ملخص. |
فارغة <T> | يخلق موتر مع الشكل المعطى. |
فارغة | ينشئ وإرجاع قائمة موتر فارغة. |
فارغة | يخلق وإرجاع خريطة موتر فارغة. |
الترميز | يقوم OP بتسلسل رسائل protobuf المقدمة في موتر الإدخال. |
enqueuetpuembeddingintegerbatch | OP الذي يمنح قائمة من موتر الدُفعات الإدخال إلى tpuembedding. |
enqueuetpuembeddingRaggedTensorBatch | يخفف من نقل الكود الذي يستخدم tf.nn.embedding_lookup (). |
enqueuetpuembeddingsparsebatch | OP الذي يثني مؤشرات إدخال tpuembedding من sparsetensor. |
enqueuetpuembeddingsparsetensorbatch | يخفف من نقل الكود الذي يستخدم tf.nn.embedding_lookup_sparse (). |
usureShape <T> | يضمن أن شكل الموتر يطابق الشكل المتوقع. |
أدخل <T> | يخلق أو يجد إطارًا طفلًا ، ويجعل "بيانات" متاحًا لإطار الطفل. |
erfinv <t يمتد الرقم> | |
إقليديانوم <T> | يحسب القاعدة الإقليدية للعناصر عبر أبعاد التوتر. |
الخروج <T> | يخرج الإطار الحالي إلى إطاره الأم. |
expantdims <t> | إدراج بعد 1 في شكل الموتر. |
التجريبيات | ينشئ مجموعة بيانات تقوي مجموعة بيانات الإدخال. |
التجريبي reprocedstatsdataset | يسجل حجم البايت لكل عنصر من عناصر `input_dataset` في statsaggregator. |
التجريبي rocareStifestDataset | |
التجربة | إرجاع Cardinality من `input_dataset`. |
التجربة | يكتب مجموعة البيانات المحددة إلى الملف المحدد باستخدام تنسيق Tfrecord. |
rexperalensetosparsebatchdataset | ينشئ مجموعة بيانات تقوم بإدخال عناصر إدخال في sparsetensor. |
التجربة | يسجل زمن انتقال إنتاج `input_dataset` في statsaggregator. |
ExperimalAtchingFilesDataset | |
ExperimalaxintraOpParalisalismDataset | ينشئ مجموعة بيانات تتجاوز الحد الأقصى للتوازي داخل OP. |
التجريبي ParseExampleDataset | يحول `input_dataset` الذي يحتوي على "مثال" كمواقف لـ DT_String إلى مجموعة بيانات من كائنات "Tensor" أو "SparSetensor" التي تمثل الميزات المحلية. |
التجريبي privatethreadpooldataset | يقوم بإنشاء مجموعة بيانات تستخدم تجمع مؤشرات ترابط مخصص لحساب `input_dataset`. |
التجريبية | ينشئ مجموعة بيانات تُرجع أرقام الكاذبة. |
التجريبية | ينشئ مجموعة بيانات تغير حجم الدُفعة. |
rexperialetstatsagggregatordataset | |
rexperiorslidingwindowdataset | ينشئ مجموعة بيانات تمرر نافذة منزلق فوق `input_dataset`. |
التجريبيات QLDATASET | ينشئ مجموعة بيانات تنفذ استعلام SQL وينبعث صفوف من مجموعة النتائج. |
التجريبي statsaggregatorHandle | يخلق مورد مدير الإحصاء. |
التجريبي statsaggregorsummary | ينتج ملخصًا لأي إحصائيات سجلها مدير الإحصاء المعطى. |
التجريبي inclunbatchdataset | مجموعة بيانات تقسم عناصر مدخلاتها إلى عناصر متعددة. |
Expint <t يمتد الرقم> | |
extractglimpsev2 | يستخلص لمحة عن موتر الإدخال. |
extractvolumepatches <t يمتد الرقم> | استخراج "البقع" من "المدخلات" ووضعها في "عمق" "البعد الإخراج. |
املأ <u> | يخلق موتر مملوءة بقيمة العددية. |
بصمة | يولد قيم البصمات. |
Fresnelcos <t يمتد الرقم> | |
Fresnelsin <t يمتد الرقم> | |
تمتد الرقم DOUSBATCHNORMGRARGV3 <T ، ويمتد الرقم> | Gradient for batch normalization. |
FusedBatchNormV3 <T extends Number, U extends Number> | Batch normalization. |
GRUBlockCell <T extends Number> | Computes the GRU cell forward propagation for 1 time step. |
GRUBlockCellGrad <T extends Number> | 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. |
Mutex | 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 . |
مطبعة | 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. |
رتبة | 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 | Update '*var' according to the Adam algorithm. |
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> | Applies sparse addition to `input` using individual values or slices from `updates` according to indices `indices`. |
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> | |
يرسل | 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. |
منصة | 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`. |
أين | 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. |