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إحباط | رفع استثناء لإجهاض العملية عند استدعائها. |
إحباط.خيارات | السمات الاختيارية Abort |
القيمة المطلقة <T تمتد TNumber > | يحسب القيمة المطلقة للموتر. |
مجردةDataBuffer <T> | |
AbstractDataBufferWindow <B يمتد DataBuffer <?>> | |
AbstractDenseNdArray <T، U يمتد NdArray <T>> | |
AbstractNdArray <T، U يمتد NdArray <T>> | |
AbstractTF_Buffer | |
AbstractTF_Graph | |
AbstractTF_ImportGraphDefOptions | |
AbstractTF_Session | |
AbstractTF_SessionOptions | |
AbstractTF_Status | |
AbstractTF_Tensor | |
مجردةTFE_Context | |
AbstractTFE_ContextOptions | |
مجردةTFE_Op | |
AbstractTFE_TensorHandle | |
تراكم N <T يمتد TType > | إرجاع مجموع عناصر قائمة الموترات. |
تراكمتطبيقالتدرج | يطبق التدرج على تراكم معين. |
التراكمي العدد المتراكم | إرجاع عدد التدرجات المجمعة في المجمعات المحددة. |
تراكمSetGlobalStep | يقوم بتحديث المجمع بقيمة جديدة لـ global_step. |
AccumulatorTakeGradient <T يمتد TType > | يستخرج متوسط التدرج في ConditionalAccumulator المحدد. |
Acos <T يمتد TType > | يحسب acos للعنصر x. |
أكوش <T يمتد TType > | يحسب جيب التمام الزائدي العكسي للعنصر x. |
التنشيط <T يمتد TNumber > | فئة أساسية مجردة للتنشيط ملاحظة: يجب تعيين سمة |
ادادلتا | محسن ينفذ خوارزمية Adadelta. |
اداغراد | محسن يقوم بتنفيذ خوارزمية Adagrad. |
AdaGradDA | مُحسِّن يطبق خوارزمية Adagrad Dual-Averaging. |
آدم | محسن ينفذ خوارزمية آدم. |
أداماكس | المُحسِّن الذي يطبق خوارزمية Adamax. |
أضف <T يمتد TType > | يُرجع عنصر x + y. |
AddManySparseToTensorsMap | أضف `N`-minibatch `SparseTensor` إلى `SparseTensorsMap`، وأعد مقابض `N`. |
AddManySparseToTensorsMap.Options | السمات الاختيارية لـ AddManySparseToTensorsMap |
AddN <T يمتد TType > | أضف جميع عناصر موتر الإدخال الحكيمة. |
AddSparseToTensorsMap | قم بإضافة `SparseTensor` إلى `SparseTensorsMap` لإرجاع المقبض الخاص به. |
AddSparseToTensorsMap.Options | السمات الاختيارية لـ AddSparseToTensorsMap |
ضبط التباين <T يمتد TNumber > | ضبط تباين صورة واحدة أو أكثر. |
AdjustHue <T يمتد TNumber > | ضبط لون صورة واحدة أو أكثر. |
ضبط التشبع <T يمتد TNumber > | ضبط تشبع صورة واحدة أو أكثر. |
الجميع | يحسب "المنطقي و" للعناصر عبر أبعاد الموتر. |
الكل.الخيارات | سمات اختيارية All |
AllCandidateSampler | يُنشئ تسميات لأخذ العينات المرشحة باستخدام توزيع أحادي جرام مكتسب. |
AllCandidateSampler.Options | السمات الاختيارية لـ AllCandidateSampler |
وصف التخصيص | نوع Protobuf tensorflow.AllocationDescription |
تخصيص الوصف.Builder | نوع Protobuf tensorflow.AllocationDescription |
تخصيص الوصف أو البناء | |
تخصيص الوصفProtos | |
سجل التخصيص | An allocation/de-allocation operation performed by the allocator. |
تخصيص سجل.Builder | An allocation/de-allocation operation performed by the allocator. |
تخصيص سجل أو منشئ | |
تخصيص الذاكرة المستخدمة | نوع Protobuf tensorflow.AllocatorMemoryUsed |
AllocatorMemoryUsed.Builder | نوع Protobuf tensorflow.AllocatorMemoryUsed |
AllocatorMemoryUsedOrBuilder | |
AllReduce <T يمتد TNumber > | يقلل بشكل متبادل موترات متعددة من نفس النوع والشكل. |
AllReduce.Options | السمات الاختيارية لـ AllReduce |
AllToAll <T يمتد TType > | عملية لتبادل البيانات عبر نسخ TPU المتماثلة. |
الزاوية <U تمتد رقم TN > | إرجاع وسيطة رقم مركب. |
AnonymousIterator | حاوية لمورد مكرر. |
AnonymousMemoryCache | |
AnonymousMultiDeviceIterator | حاوية لمورد مكرر متعدد الأجهزة. |
AnonymousRandomSeedGenerator | |
AnonymousSeedGenerator | |
أي | يحسب "المنطقي أو" للعناصر عبر أبعاد الموتر. |
أي.خيارات | السمات الاختيارية Any |
أبيديف | Used to specify and override the default API & behavior in the generated code for client languages, from what you would get from the OpDef alone. |
ApiDef.Arg | نوع Protobuf tensorflow.ApiDef.Arg |
ApiDef.Arg.Builder | نوع Protobuf tensorflow.ApiDef.Arg |
ApiDef.ArgOrBuilder | |
ApiDef.Attr | Description of the graph-construction-time configuration of this Op. |
ApiDef.Attr.Builder | Description of the graph-construction-time configuration of this Op. |
ApiDef.AttrOrBuilder | |
ApiDef.Builder | Used to specify and override the default API & behavior in the generated code for client languages, from what you would get from the OpDef alone. |
ApiDef.Endpoint | If you specify any endpoint, this will replace all of the inherited endpoints. |
ApiDef.Endpoint.Builder | If you specify any endpoint, this will replace all of the inherited endpoints. |
ApiDef.EndpointOrBuilder | |
ApiDef.Visibility | Protobuf التعداد tensorflow.ApiDef.Visibility |
ApiDefOrBuilder | |
ApiDefProtos | |
أبيديفس | نوع Protobuf tensorflow.ApiDefs |
ApiDefs.Builder | نوع Protobuf tensorflow.ApiDefs |
ApiDefsOrBuilder | |
ApplyAdadelta <T يمتد TType > | قم بتحديث '*var' وفقًا لمخطط adadelta. |
ApplyAdadelta.Options | السمات الاختيارية لـ ApplyAdadelta |
ApplyAdagrad <T يمتد TType > | قم بتحديث '*var' وفقًا لمخطط adagrad. |
ApplyAdagrad.Options | السمات الاختيارية لـ ApplyAdagrad |
ApplyAdagradDa <T يمتد TType > | قم بتحديث '*var' وفقًا لمخطط adagrad القريب. |
ApplyAdagradDa.Options | السمات الاختيارية لـ ApplyAdagradDa |
ApplyAdagradV2 <T يمتد TType > | قم بتحديث '*var' وفقًا لمخطط adagrad. |
ApplyAdagradV2.Options | السمات الاختيارية لـ ApplyAdagradV2 |
ApplyAdam <T يمتد TType > | قم بتحديث '*var' وفقًا لخوارزمية Adam. |
ApplyAdam.Options | السمات الاختيارية لـ ApplyAdam |
ApplyAdaMax <T يمتد TType > | قم بتحديث '*var' وفقًا لخوارزمية AdaMax. |
ApplyAdaMax.Options | السمات الاختيارية لـ ApplyAdaMax |
ApplyAddSign <T يمتد TType > | قم بتحديث '*var' وفقًا لتحديث AddSign. |
ApplyAddSign.Options | السمات الاختيارية لـ ApplyAddSign |
ApplyCenteredRmsProp <T يمتد TType > | قم بتحديث '*var' وفقًا لخوارزمية RMSProp المركزية. |
ApplyCenteredRmsProp.Options | السمات الاختيارية لـ ApplyCenteredRmsProp |
ApplyFtrl <T يمتد TType > | قم بتحديث '*var' وفقًا لمخطط Ftrl-proximal. |
ApplyFtrl.Options | السمات الاختيارية لـ ApplyFtrl |
ApplyGradientDescent <T يمتد TType > | قم بتحديث '*var' بطرح 'alpha' * 'delta' منه. |
ApplyGradientDescent.Options | السمات الاختيارية لـ ApplyGradientDescent |
ApplyMomentum <T يمتد TType > | قم بتحديث '*var' وفقًا لمخطط الزخم. |
ApplyMomentum.Options | السمات الاختيارية لـ ApplyMomentum |
ApplyPowerSign <T يمتد TType > | قم بتحديث '*var' وفقًا لتحديث AddSign. |
ApplyPowerSign.Options | السمات الاختيارية لـ ApplyPowerSign |
ApplyProximalAdagrad <T يمتد TType > | قم بتحديث '*var' و'*accum' وفقًا لـ FOBOS بمعدل تعلم Adagrad. |
ApplyProximalAdagrad.Options | السمات الاختيارية لـ ApplyProximalAdagrad |
ApplyProximalGradientDescent <T يمتد TType > | قم بتحديث '*var' كخوارزمية FOBOS بمعدل تعلم ثابت. |
ApplyProximalGradientDescent.Options | السمات الاختيارية لـ ApplyProximalGradientDescent |
ApplyRmsProp <T يمتد TType > | قم بتحديث '*var' وفقًا لخوارزمية RMSProp. |
ApplyRmsProp.Options | السمات الاختيارية لـ ApplyRmsProp |
تقريبي | تُرجع القيمة الحقيقية لـ abs(xy) <عنصر التسامح. |
ApproximateEqual.Options | السمات الاختيارية لـ ApproximateEqual |
ArgMax <V يمتد TNumber > | إرجاع الفهرس بأكبر قيمة عبر أبعاد الموتر. |
ArgMin <V يمتد TNumber > | تُرجع الفهرس بأصغر قيمة عبر أبعاد الموتر. |
Asin <T يمتد TType > | يحسب الجيب المثلثي العكسي للعنصر x. |
Asinh <T يمتد TType > | يحسب الجيب الزائدي العكسي للعنصر x. |
AssertCardinalityDataset | |
AssertNextDataset | التحول الذي يؤكد التحولات التي تحدث بعد ذلك. |
AssertNextDataset | |
تأكيد ذلك | يؤكد أن الشرط المحدد صحيح. |
AssertThat.Options | السمات الاختيارية لـ AssertThat |
AssetFileDef | An asset file def for a single file or a set of sharded files with the same name. |
AssetFileDef.Builder | An asset file def for a single file or a set of sharded files with the same name. |
AssetFileDefOrBuilder | |
تعيين <T يمتد TType > | قم بتحديث "المرجع" عن طريق تعيين "قيمة" له. |
تعيين.خيارات | السمات الاختيارية Assign |
AssignAdd <T يمتد TType > | قم بتحديث "المرجع" بإضافة "قيمة" إليه. |
تعيين Add.Options | السمات الاختيارية لـ AssignAdd |
AssignAddVariableOp | يضيف قيمة إلى القيمة الحالية للمتغير. |
AssignSub <T يمتد TType > | قم بتحديث "المرجع" بطرح "القيمة" منه. |
AssignSub.Options | السمات الاختيارية لـ AssignSub |
AssignSubVariableOp | يطرح قيمة من القيمة الحالية للمتغير. |
AssignVariableOp | يعين قيمة جديدة لمتغير. |
سلسلة | يحول كل إدخال في الموتر المحدد إلى سلاسل. |
AsString.Options | السمات الاختيارية لـ AsString |
أتان <T يمتد TType > | يحسب الظل المثلثي العكسي للعنصر x. |
Atan2 <T يمتد TNumber > | يحسب قوس الزاوية للعنصر `y/x`، مع احترام علامات الوسائط. |
اتانه <T يمتد TType > | يحسب الظل الزائدي العكسي للعنصر x. |
AttrValue | Protocol buffer representing the value for an attr used to configure an Op. |
AttrValue.Builder | Protocol buffer representing the value for an attr used to configure an Op. |
AttrValue.ListValue | LINT.IfChangeنوع Protobuf tensorflow.AttrValue.ListValue |
AttrValue.ListValue.Builder | LINT.IfChangeنوع Protobuf tensorflow.AttrValue.ListValue |
AttrValue.ListValueOrBuilder | |
AttrValue.ValueCase | |
AttrValueOrBuilder | |
AttrValueProtos | |
مخطط الطيف الصوتي | ينتج تصورا للبيانات الصوتية مع مرور الوقت. |
AudioSpectrogram.Options | السمات الاختيارية لـ AudioSpectrogram |
ملخص صوتي | يقوم بإخراج مخزن مؤقت لبروتوكول "الملخص" مع الصوت. |
AudioSummary.Options | سمات اختيارية لـ AudioSummary |
خيارات التوازي التلقائي | نوع Protobuf tensorflow.AutoParallelOptions |
AutoParallelOptions.Builder | نوع Protobuf tensorflow.AutoParallelOptions |
AutoParallelOptionsOrBuilder | |
AutoShardDataset | ينشئ مجموعة بيانات تقسم مجموعة بيانات الإدخال. |
AutoShardDataset | ينشئ مجموعة بيانات تقسم مجموعة بيانات الإدخال. |
AutoShardDataset.Options | السمات الاختيارية لـ AutoShardDataset |
AutoShardDataset.Options | السمات الاختيارية لـ AutoShardDataset |
معلومات الجهاز المتوفرة | Matches DeviceAttributesنوع Protobuf tensorflow.AvailableDeviceInfo |
متاحDeviceInfo.Builder | Matches DeviceAttributesنوع Protobuf tensorflow.AvailableDeviceInfo |
متاحDeviceInfoOrBuilder | |
AvgPool <T يمتد TNumber > | ينفذ تجميع متوسط على المدخلات. |
AvgPool.Options | السمات الاختيارية لـ AvgPool |
AvgPool3d <T يمتد TNumber > | ينفذ تجميع متوسط ثلاثي الأبعاد على الإدخال. |
AvgPool3d.Options | السمات الاختيارية لـ AvgPool3d |
AvgPool3dGrad <T يمتد TNumber > | يحسب التدرجات لوظيفة التجميع المتوسطة. |
AvgPool3dGrad.Options | السمات الاختيارية لـ AvgPool3dGrad |
AvgPoolGrad <T يمتد TNumber > | يحسب التدرجات لوظيفة التجميع المتوسطة. |
AvgPoolGrad.Options | السمات الاختيارية لـ AvgPoolGrad |
ب
BandedTriangularSolve <T يمتد TType > | |
BandedTriangularSolve.Options | السمات الاختيارية لـ BandedTriangularSolve |
BandPart <T يمتد TType > | انسخ موترًا يضبط كل شيء خارج النطاق المركزي في كل مصفوفة داخلية على الصفر. |
حاجز | يحدد حاجزًا يستمر عبر عمليات تنفيذ الرسم البياني المختلفة. |
الحاجز. الخيارات | السمات الاختيارية Barrier |
إغلاق الحاجز | يغلق الحاجز المحدد. |
BarrierClose.Options | السمات الاختيارية لـ BarrierClose |
حجم الحاجز غير مكتمل | يحسب عدد العناصر غير المكتملة في الحاجز المحدد. |
BarrierInsertMany | لكل مفتاح، يعين القيمة المعنية للمكون المحدد. |
حجم الحاجز الجاهز | يحسب عدد العناصر الكاملة في الحاجز المحدد. |
BarrierTakeMany | يأخذ العدد المحدد من العناصر المكتملة من الحاجز. |
BarrierTakeMany.Options | السمات الاختيارية لـ BarrierTakeMany |
BaseInitializer <T يمتد TType > | فئة أساسية مجردة لجميع المُهيئين |
حزمة | دفعات جميع موترات الإدخال بشكل غير محدد. |
دفعة.خيارات | سمات اختيارية Batch |
BatchCholesky <T يمتد TNumber > | |
BatchCholeskyGrad <T يمتد TNumber > | |
BatchDataset | |
BatchDataset | ينشئ مجموعة بيانات تجمع عناصر `batch_size` من `input_dataset`. |
BatchDataset.Options | السمات الاختيارية لـ BatchDataset |
BatchFft | |
BatchFft2d | |
BatchFft3d | |
BatchIfft | |
BatchIfft2d | |
BatchIfft3d | |
BatchMatMul <T يمتد TType > | ضرب شرائح اثنين من الموتدين على دفعات. |
BatchMatMul.Options | السمات الاختيارية لـ BatchMatMul |
BatchMatrixBandPart <T يمتد TType > | |
BatchMatrixDeterminant <T يمتد TType > | |
BatchMatrixDiag <T يمتد TType > | |
BatchMatrixDiagPart <T يمتد TType > | |
BatchMatrixInverse <T يمتد TNumber > | |
BatchMatrixInverse.Options | السمات الاختيارية لـ BatchMatrixInverse |
BatchMatrixSetDiag <T يمتد TType > | |
BatchMatrixSolve <T يمتد TNumber > | |
BatchMatrixSolve.Options | سمات اختيارية ل BatchMatrixSolve |
BatchMatrixSolveLs <T يمتد TNumber > | |
BatchMatrixSolveLs.Options | السمات الاختيارية لـ BatchMatrixSolveLs |
BatchMatrixTriangularSolve <T يمتد TNumber > | |
BatchMatrixTriangularSolve.Options | السمات الاختيارية لـ BatchMatrixTriangularSolve |
BatchNormWithGlobalNormalization <T يمتد TType > | التطبيع دفعة. |
BatchNormWithGlobalNormalizationGrad <T يمتد TType > | التدرجات لتطبيع الدفعة. |
BatchSelfAdjointEig <T يمتد TNumber > | |
BatchSelfAdjointEig.Options | السمات الاختيارية لـ BatchSelfAdjointEig |
BatchSvd <T يمتد TType > | |
BatchSvd.Options | السمات الاختيارية لـ BatchSvd |
BatchToSpace <T يمتد TType > | BatchToSpace للموترات رباعية الأبعاد من النوع T. |
BatchToSpaceNd <T يمتد TType > | BatchToSpace لموترات ND من النوع T. |
إدخالات المعيار | نوع Protobuf tensorflow.BenchmarkEntries |
BenchmarkEntries.Builder | نوع Protobuf tensorflow.BenchmarkEntries |
BenchmarkEntriesOrBuilder | |
إدخال المعيار | Each unit test or benchmark in a test or benchmark run provides some set of information. |
BenchmarkEntry.Builder | Each unit test or benchmark in a test or benchmark run provides some set of information. |
BenchmarkEntryOrBuilder | |
BesselI0 <T يمتد TNumber > | |
BesselI0e <T يمتد TNumber > | |
BesselI1 <T يمتد TNumber > | |
BesselI1e <T يمتد TNumber > | |
BesselJ0 <T يمتد TNumber > | |
BesselJ1 <T يمتد TNumber > | |
BesselK0 <T يمتد TNumber > | |
BesselK0e <T يمتد TNumber > | |
BesselK1 <T يمتد TNumber > | |
BesselK1e <T يمتد TNumber > | |
BesselY0 <T يمتد TNumber > | |
BesselY1 <T يمتد TNumber > | |
Betainc <T يمتد TNumber > | حساب تكامل بيتا غير المكتمل المنتظم \\(I_x(a, b)\\). |
BfcMemoryMapProtos | |
Bfloat16Layout | تخطيط البيانات الذي يحول عوامات 32 بت من/إلى 16 بت، مع اقتطاع الأجزاء العشرية الخاصة بها إلى 7 بتات مع الحفاظ على الأس 8 بت بنفس الانحياز. |
BiasAdd <T يمتد TType > | يضيف "التحيز" إلى "القيمة". |
BiasAdd.Options | السمات الاختيارية لـ BiasAdd |
BiasAddGrad <T يمتد TType > | العملية الخلفية لـ "BiasAdd" على موتر "التحيز". |
BiasAddGrad.Options | السمات الاختيارية لـ BiasAddGrad |
BinaryCrossentropy | يحسب الخسارة عبر الإنتروبيا بين التسميات الحقيقية والتسميات المتوقعة. |
BinaryCrossentropy <T يمتد TNumber > | مقياس يحسب الخسارة الثنائية للإنتروبيا المتبادلة بين التسميات الحقيقية والتسميات المتوقعة. |
Bincount <T يمتد TNumber > | حساب عدد مرات ظهور كل قيمة في مصفوفة أعداد صحيحة. |
BinSummary | نوع Protobuf tensorflow.BinSummary |
BinSummary.Builder | نوع Protobuf tensorflow.BinSummary |
BinSummaryOrBuilder | |
البث الثنائي <U يمتد TType > | يقوم ببث موتر من نوع إلى آخر دون نسخ البيانات. |
BitwiseAnd <T يمتد TNumber > | يحسب Elementwise معامل البت AND لـ `x` و`y`. |
BitwiseOr <T يمتد TNumber > | يحسب Elementwise معامل البت OR لـ `x` و`y`. |
BitwiseXor <T يمتد TNumber > | يحسب Elementwise XOR للبت لـ `x` و`y`. |
BlockLSTM <T يمتد TNumber > | يحسب الانتشار الأمامي لخلية LSTM لجميع الخطوات الزمنية. |
BlockLSTM.Options | السمات الاختيارية لـ BlockLSTM |
BlockLSTMGrad <T يمتد TNumber > | يحسب الانتشار الخلفي لخلية LSTM للتسلسل الزمني بأكمله. |
BooleanDataBuffer | DataBuffer من القيم المنطقية. |
BooleanDataLayout <S يمتد DataBuffer <?>> | DataLayout الذي يحول البيانات المخزنة في المخزن المؤقت إلى بيانات منطقية. |
BooleanDenseNdArray | |
قناع منطقي | |
BooleanMask.Options | السمات الاختيارية لـ BooleanMask |
تحديث قناع منطقي | |
BooleanMaskUpdate.Options | السمات الاختيارية لـ BooleanMaskUpdate |
BooleanNdArray | NdArray من القيم المنطقية. |
BoolLayout | تخطيط البيانات الذي يحول القيم المنطقية من/إلى البايتات. |
BoostedTreesAggregateStats | تجميع ملخص الإحصائيات المتراكمة للدفعة. |
BoostedTreesBucketize | قم بتوزيع كل ميزة على أساس حدود المجموعة. |
BoostedTreesCalculateBestFeatureSplit | حساب المكاسب لكل ميزة وإرجاع أفضل معلومات تقسيم ممكنة للميزة. |
BoostedTreesCalculateBestFeatureSplit.Options | السمات الاختيارية لـ BoostedTreesCalculateBestFeatureSplit |
BoostedTreesCalculateBestFeatureSplitV2 | حساب المكاسب لكل ميزة وإرجاع أفضل معلومات التقسيم الممكنة لكل عقدة. |
الأشجار المعززة تحسب أفضل المكاسب لكل ميزة | حساب المكاسب لكل ميزة وإرجاع أفضل معلومات تقسيم ممكنة للميزة. |
BoostedTreesCenterBias | يحسب السابقة من بيانات التدريب (التحيز) ويملأ العقدة الأولى بالسجلات السابقة. |
BoostedTreesCreateEnsemble | ينشئ نموذج مجموعة شجرة ويعيد مؤشرًا إليه. |
BoostedTreesCreateQuantileStreamResource | إنشاء المورد للتدفقات الكمية. |
BoostedTreesCreateQuantileStreamResource.Options | السمات الاختيارية لـ BoostedTreesCreateQuantileStreamResource |
BoostedTreesDeserializeEnsemble | إلغاء تسلسل تكوين مجموعة الشجرة المتسلسلة واستبدال الشجرة الحالية فرقة. |
BoostedTreesEnsembleResourceHandleOp | ينشئ مؤشرًا إلى BoostedTreesEnsembleResource |
BoostedTreesEnsembleResourceHandleOp.Options | السمات الاختيارية لـ BoostedTreesEnsembleResourceHandleOp |
BoostedTreesExampleDebugOutputs | تصحيح الأخطاء/مخرجات تفسير النموذج لكل مثال. |
ملخصات BoostedTreesFlushQuantile | مسح الملخصات الكمية من كل مورد تيار الكمية. |
BoostedTreesGetEnsembleStates | يسترد رمز ختم موارد مجموعة الأشجار وعدد الأشجار والإحصائيات المتزايدة. |
BoostedTreesMakeQuantileSummaries | يجعل ملخص الكميات للدفعة. |
ملخص BoostedTreesMakeStats | يقدم ملخصًا للإحصائيات المتراكمة للدفعة. |
BoostedTreesPredict | يقوم بتشغيل تنبؤات مجموعة الانحدار الإضافي المتعددة على مثيلات الإدخال و يحسب السجل. |
BoostedTreesQuantileStreamResourceAddSummaries | أضف الملخصات الكمية إلى كل مورد تيار كمي. |
BoostedTreesQuantileStreamResourceDeserialize | قم بإلغاء تسلسل حدود الجرافة ووضع علامة جاهزة في QuantileAccumulator الحالي. |
BoostedTreesQuantileStreamResourceFlush | مسح الملخصات لمورد التدفق الكمي. |
BoostedTreesQuantileStreamResourceFlush.Options | السمات الاختيارية لـ BoostedTreesQuantileStreamResourceFlush |
BoostedTreesQuantileStreamResourceGetBucketBoundaries | قم بإنشاء حدود المجموعة لكل ميزة بناءً على الملخصات المتراكمة. |
BoostedTreesQuantileStreamResourceHandleOp | ينشئ مؤشرًا إلى BoostedTreesQuantileStreamResource. |
BoostedTreesQuantileStreamResourceHandleOp.Options | السمات الاختيارية لـ BoostedTreesQuantileStreamResourceHandleOp |
BoostedTreesSerializeEnsemble | إجراء تسلسل لمجموعة الشجرة إلى نموذج أولي. |
BoostedTreesSparseAggregateStats | تجميع ملخص الإحصائيات المتراكمة للدفعة. |
BoostedTreesSparseCalculateBestFeatureSplit | حساب المكاسب لكل ميزة وإرجاع أفضل معلومات تقسيم ممكنة للميزة. |
BoostedTreesSparseCalculateBestFeatureSplit.Options | السمات الاختيارية لـ BoostedTreesSparseCalculateBestFeatureSplit |
BoostedTreesTrainingPredict | يقوم بتشغيل تنبؤات مجموعة الانحدار الإضافي المتعددة على مثيلات الإدخال و يحسب التحديث إلى السجلات المخزنة مؤقتا. |
BoostedTreesUpdateEnsemble | يقوم بتحديث مجموعة الأشجار إما بإضافة طبقة إلى آخر شجرة يتم زراعتها أو عن طريق بدء شجرة جديدة. |
BoostedTreesUpdateEnsembleV2 | يقوم بتحديث مجموعة الأشجار عن طريق إضافة طبقة إلى آخر شجرة يتم زراعتها أو عن طريق بدء شجرة جديدة. |
BoostedTreesUpdateEnsembleV2.Options | السمات الاختيارية لـ BoostedTreesUpdateEnsembleV2 |
BoundedTensorSpecProto | A protobuf to represent tf.BoundedTensorSpec. |
BoundedTensorSpecProto.Builder | A protobuf to represent tf.BoundedTensorSpec. |
BoundedTensorSpecProtoOrBuilder | |
BroadcastDynamicShape <T يمتد TNumber > | إرجاع شكل s0 op s1 مع البث. |
BroadcastGradientArgs <T يمتد TNumber > | قم بإرجاع مؤشرات التخفيض لتدرجات الحوسبة لـ s0 op s1 مع البث. |
BroadcastHelper <T يمتد TType > | مشغل مساعد لإجراء عمليات البث بنمط XLA يتم بث `lhs` و`rhs` إلى نفس الترتيب، عن طريق إضافة أبعاد الحجم 1 إلى أي من `lhs` و`rhs` له رتبة أقل، باستخدام قواعد البث الخاصة بـ XLA للمشغلين الثنائيين. |
BroadcastRecv <T يمتد TType > | يستقبل بث قيمة موتر من جهاز آخر. |
BroadcastRecv.Options | السمات الاختيارية لـ BroadcastRecv |
BroadcastSend <T يمتد TType > | يبث قيمة موتر إلى جهاز واحد أو أكثر. |
BroadcastSend.Options | السمات الاختيارية لـ BroadcastSend |
BroadcastTo <T يمتد TType > | بث مصفوفة للحصول على شكل متوافق. |
دلو | يقوم بتجميع "المدخلات" بناءً على "الحدود". |
تكوين البناء | نوع Protobuf tensorflow.BuildConfiguration |
BuildConfiguration.Builder | نوع Protobuf tensorflow.BuildConfiguration |
BuildConfigurationOrBuilder | |
BundleEntryProto | Describes the metadata related to a checkpointed tensor. |
BundleEntryProto.Builder | Describes the metadata related to a checkpointed tensor. |
BundleEntryProtoOrBuilder | |
BundleHeaderProto | Special header that is associated with a bundle. |
BundleHeaderProto.Builder | Special header that is associated with a bundle. |
BundleHeaderProto.Endianness | An enum indicating the endianness of the platform that produced this bundle. |
BundleHeaderProtoOrBuilder | |
ByteDataBuffer | DataBuffer من البايتات. |
ByteDataLayout <S يمتد DataBuffer <?>> | DataLayout الذي يحول البيانات المخزنة في المخزن المؤقت إلى بايت. |
ByteDenseNdArray | |
ByteNdArray | NdArray من البايتات. |
ByteSequenceProvider <T> | ينتج تسلسل البايتات المراد تخزينها في ByteSequenceTensorBuffer . |
ByteSequenceTensorBuffer | مخزن مؤقت لتخزين بيانات موتر السلسلة. |
BytesList | Containers to hold repeated fundamental values. |
BytesList.Builder | Containers to hold repeated fundamental values. |
BytesListOrBuilder | |
BytesProducedStatsDataset | يسجل حجم البايتات لكل عنصر من عناصر "input_dataset" في StatsAggregator. |
BytesProducedStatsDataset | يسجل حجم البايتات لكل عنصر من عناصر "input_dataset" في StatsAggregator. |
ج
CacheDataset | ينشئ مجموعة بيانات تخزن العناصر مؤقتًا من `input_dataset`. |
CacheDatasetV2 | |
CallableOptions | Defines a subgraph in another `GraphDef` as a set of feed points and nodes to be fetched or executed. |
CallableOptions.Builder | Defines a subgraph in another `GraphDef` as a set of feed points and nodes to be fetched or executed. |
CallableOptionsOrBuilder | |
Cast <U يمتد TType > | تحويل x من النوع SrcT إلى y من DstT. |
Cast.Options | سمات اختيارية Cast |
CastHelper | فئة مساعدة لصب المعامل |
الانتروبيا الفئوية | يحسب خسارة الانتروبيا بين التسميات والتنبؤات. |
CategoricalCrossentropy <T يمتد TNumber > | مقياس يحسب الخسارة الفئوية للإنتروبيا المتبادلة بين التسميات الحقيقية والتسميات المتوقعة. |
المفصلة الفئوية | يحسب خسارة المفصلة الفئوية بين التسميات والتنبؤات. |
المفصلة القاطعة <T تمتد TNumber > | مقياس يحسب مقياس فقدان المفصلة الفئوي بين التسميات والتنبؤات. |
السقف <T يمتد TNumber > | يُرجع أصغر عدد صحيح من حيث العنصر لا يقل عن x. |
CheckNumerics <T يمتد TNumber > | يتحقق الموتر من قيم NaN و-Inf و+Inf. |
تشوليسكي <T يمتد TType > | يحسب تحليل تشوليسكي لمصفوفة مربعة واحدة أو أكثر. |
CholeskyGrad <T يمتد TNumber > | يحسب التدرج العكسي للوضع العكسي لخوارزمية Cholesky. |
اختر أسرع مجموعة بيانات | |
اختر أسرع مجموعة بيانات | |
ClipByValue <T يمتد TType > | يقطع قيم الموتر إلى الحد الأدنى والحد الأقصى المحددين. |
إغلاق الملخص الكاتب | |
ClusterDef | Defines a TensorFlow cluster as a set of jobs. |
ClusterDef.Builder | Defines a TensorFlow cluster as a set of jobs. |
ClusterDefOrBuilder | |
ClusterDeviceFilters | Defines the device filters for jobs in a cluster. |
ClusterDeviceFilters.Builder | Defines the device filters for jobs in a cluster. |
ClusterDeviceFiltersOrBuilder | |
ClusterOutput <T يمتد TType > | عامل التشغيل الذي يربط مخرجات حساب XLA بعقد الرسم البياني للمستهلك الأخرى. |
ClusterProtos | |
شفرة | The canonical error codes for TensorFlow APIs. |
موقع الكود | Code location information: A stack trace with host-name information. |
CodeLocation.Builder | Code location information: A stack trace with host-name information. |
CodeLocationOrBuilder | |
CollectionDef | CollectionDef should cover most collections. |
CollectionDef.AnyList | AnyList is used for collecting Any protos. |
CollectionDef.AnyList.Builder | AnyList is used for collecting Any protos. |
CollectionDef.AnyListOrBuilder | |
CollectionDef.Builder | CollectionDef should cover most collections. |
CollectionDef.BytesList | BytesList is used for collecting strings and serialized protobufs. |
CollectionDef.BytesList.Builder | BytesList is used for collecting strings and serialized protobufs. |
CollectionDef.BytesListOrBuilder | |
CollectionDef.FloatList | FloatList is used for collecting float values. |
CollectionDef.FloatList.Builder | FloatList is used for collecting float values. |
CollectionDef.FloatListOrBuilder | |
CollectionDef.Int64List | Int64List is used for collecting int, int64 and long values. |
CollectionDef.Int64List.Builder | Int64List is used for collecting int, int64 and long values. |
CollectionDef.Int64ListOrBuilder | |
CollectionDef.KindCase | |
CollectionDef.NodeList | NodeList is used for collecting nodes in graph. |
CollectionDef.NodeList.Builder | NodeList is used for collecting nodes in graph. |
CollectionDef.NodeListOrBuilder | |
CollectionDefOrBuilder | |
CollectiveGather <T يمتد TNumber > | يتراكم بشكل متبادل عدة موترات من نفس النوع والشكل. |
CollectiveGather.Options | السمات الاختيارية لـ CollectiveGather |
CollectivePermute <T يمتد TType > | عملية لتبديل الموترات عبر مثيلات TPU المكررة. |
CombinedNonMaxSuppression | يختار بجشع مجموعة فرعية من المربعات المحيطة بترتيب تنازلي للنتيجة، تنفذ هذه العملية قمعًا غير أقصى على المدخلات لكل دفعة، عبر جميع الفئات. |
CombinedNonMaxSuppression.Options | السمات الاختيارية لـ CombinedNonMaxSuppression |
معرف الالتزام | نوع Protobuf tensorflow.CommitId |
CommitId.Builder | نوع Protobuf tensorflow.CommitId |
CommitId.KindCase | |
CommitIdOrBuilder | |
قارن وBitpack | قارن قيم "الإدخال" بـ "العتبة" واجمع البتات الناتجة في "uint8". |
نتيجة التجميع | إرجاع نتيجة تجميع TPU. |
ترجمة نجاحالتأكيد | يؤكد أن التجميع نجح. |
مجمع <U يمتد TType > | تحويل رقمين حقيقيين إلى عدد مركب. |
ComplexAbs <U يمتد TNumber > | يحسب القيمة المطلقة المعقدة للموتر. |
CompressElement | يضغط عنصر مجموعة البيانات. |
Compute_func_Pointer_TF_OpKernelContext | |
حساب عدد الزيارات العرضية | يحسب معرفات المواضع في Sampled_candidates التي تطابق true_labels. |
ComputeAccidentalHits.Options | السمات الاختيارية لـ ComputeAccidentalHits |
ComputeBatchSize | يحسب حجم الدفعة الثابتة لمجموعة البيانات بدون دفعات جزئية. |
Concat <T يمتد TType > | يسلسل الموترات على طول بعد واحد. |
سلسلة البيانات | ينشئ مجموعة بيانات تربط `input_dataset` مع `another_dataset`. |
وظيفة الخرسانة | رسم بياني يمكن استدعاؤه كدالة واحدة، مع توقيع الإدخال والإخراج. |
CondContextDef | Protocol buffer representing a CondContext object. |
CondContextDef.Builder | Protocol buffer representing a CondContext object. |
CondContextDefOrBuilder | |
المتراكمة الشرطية | تراكم مشروط لتجميع التدرجات. |
ConditionalAccumulator.Options | السمات الاختيارية لـ ConditionalAccumulator |
ConfigProto | Session configuration parameters. |
ConfigProto.Builder | Session configuration parameters. |
ConfigProto.Experimental | Everything inside Experimental is subject to change and is not subject to API stability guarantees in https://www.tensorflow.org/guide/version_compat. |
ConfigProto.Experimental.Builder | Everything inside Experimental is subject to change and is not subject to API stability guarantees in https://www.tensorflow.org/guide/version_compat. |
ConfigProto.Experimental.MlirBridgeRollout | An enum that describes the state of the MLIR bridge rollout. |
ConfigProto.ExperimentalOrBuilder | |
ConfigProtoOrBuilder | |
ConfigProtos | |
تكوين الموزعةTPU | يقوم بإعداد الهياكل المركزية لنظام TPU الموزع. |
تكوين DistributedTPU.Options | السمات الاختيارية لـ ConfigureDistributedTPU |
تكوينTPUEmbedding | يقوم بإعداد TPUEmbedding في نظام TPU الموزع. |
Conj <T يمتد TType > | إرجاع المرافق المركب لعدد مركب. |
ConjugateTranspose <T يمتد TType > | خلط أبعاد x وفقًا للتبديل وربط النتيجة. |
ثابت <T يمتد TType > | مُهيئ يقوم بإنشاء موترات ذات قيمة ثابتة. |
ثابت <T يمتد TType > | عامل ينتج قيمة ثابتة. |
القيد | الفئة الأساسية للقيود. |
يستهلكMutexLock | تستهلك هذه العملية قفلًا تم إنشاؤه بواسطة "MutexLock". |
ControlFlowContextDef | Container for any kind of control flow context. |
ControlFlowContextDef.Builder | Container for any kind of control flow context. |
ControlFlowContextDef.CtxtCase | |
ControlFlowContextDefOrBuilder | |
ControlFlowProtos | |
ControlTrigger | لا يفعل شيئا. |
التحويل <T يمتد نوع TT > | يلتف عامل التشغيل XLA ConvgeneralDilated، الموثق في https://www.tensorflow.org/performance/xla/operation_semantics#conv_convolution . |
Conv2d <T يمتد TNumber > | يحسب التلافيف ثنائي الأبعاد مع موترات "الإدخال" و"التصفية" رباعية الأبعاد. |
Conv2d.Options | السمات الاختيارية لـ Conv2d |
Conv2dBackpropFilter <T يمتد TNumber > | يحسب تدرجات الالتواء فيما يتعلق بالمرشح. |
Conv2dBackpropFilter.Options | السمات الاختيارية لـ Conv2dBackpropFilter |
Conv2dBackpropInput <T يمتد TNumber > | يحسب تدرجات الإلتواء فيما يتعلق بالإدخال. |
Conv2dBackpropInput.Options | السمات الاختيارية لـ Conv2dBackpropInput |
Conv3d <T يمتد TNumber > | يحسب التلافيف ثلاثي الأبعاد مع موترات "الإدخال" و"التصفية" خماسية الأبعاد. |
Conv3d.Options | السمات الاختيارية لـ Conv3d |
Conv3dBackpropFilter <T يمتد TNumber > | يحسب تدرجات الالتواء ثلاثي الأبعاد بالنسبة للمرشح. |
Conv3dBackpropFilter.Options | السمات الاختيارية لـ Conv3dBackpropFilter |
Conv3dBackpropInput <U يمتد TNumber > | يحسب تدرجات الالتواء ثلاثي الأبعاد فيما يتعلق بالإدخال. |
Conv3dBackpropInput.Options | السمات الاختيارية لـ Conv3dBackpropInput |
انسخ <T يمتد TType > | انسخ الموتر من وحدة المعالجة المركزية (CPU) إلى وحدة المعالجة المركزية (CPU) أو وحدة معالجة الرسومات (GPU) إلى وحدة معالجة الرسومات (GPU). |
نسخ.خيارات | السمات الاختيارية Copy |
CopyHost <T يمتد TType > | انسخ الموتر إلى المضيف. |
CopyHost.Options | السمات الاختيارية لـ CopyHost |
كوس <T يمتد TType > | يحسب جتا x من حيث العناصر. |
كوش <T يمتد TType > | يحسب جيب التمام الزائدي للعنصر x. |
جيب التمام التشابه | يحسب تشابه جيب التمام بين التسميات والتنبؤات. |
تشابه جيب التمام <T يمتد TNumber > | مقياس يحسب مقياس تشابه جيب التمام بين التسميات والتنبؤات. |
CostGraphDef | نوع Protobuf tensorflow.CostGraphDef |
CostGraphDef.AggreatedCost | Total cost of this graph, typically used for balancing decisions. |
CostGraphDef.AggreatedCost.Builder | Total cost of this graph, typically used for balancing decisions. |
CostGraphDef.AggreatedCostOrBuilder | |
CostGraphDef.Builder | نوع Protobuf tensorflow.CostGraphDef |
CostGraphDef.Node | نوع Protobuf tensorflow.CostGraphDef.Node |
CostGraphDef.Node.Builder | نوع Protobuf tensorflow.CostGraphDef.Node |
CostGraphDef.Node.InputInfo | Inputs of this node. |
CostGraphDef.Node.InputInfo.Builder | Inputs of this node. |
CostGraphDef.Node.InputInfoOrBuilder | |
CostGraphDef.Node.OutputInfo | Outputs of this node. |
CostGraphDef.Node.OutputInfo.Builder | Outputs of this node. |
CostGraphDef.Node.OutputInfoOrBuilder | |
CostGraphDef.NodeOrBuilder | |
CostGraphDefOrBuilder | |
CostGraphProtos | |
CountUpTo <T يمتد TNumber > | يزيد "المرجع" حتى يصل إلى "الحد". |
معلومات وحدة المعالجة المركزية | نوع Protobuf tensorflow.CPUInfo |
CPUInfo.Builder | نوع Protobuf tensorflow.CPUInfo |
CPUInfoOrBuilder | |
Create_func_TF_OpKernelConstruction | |
إنشاء ملخصDbWriter | |
إنشاء ملخص ملف الكاتب | |
CropAndResize | يستخرج المحاصيل من موتر الصورة المدخلة ويغير حجمها. |
CropAndResize.Options | سمات اختيارية لـ CropAndResize |
CropAndResizeGradBoxes | يحسب التدرج في Crop_and_resize Op WRT موتر مربعات الإدخال. |
CropAndResizeGradBoxes.Options | السمات الاختيارية لـ CropAndResizeGradBoxes |
CropAndResizeGradImage <T يمتد TNumber > | يحسب التدرج في Crop_and_resize Op WRT موتر الصورة المدخلة. |
CropAndResizeGradImage.Options | السمات الاختيارية لـ CropAndResizeGradImage |
تقاطع <T يمتد TNumber > | حساب المنتج الاتجاهي الزوجي. |
CrossReplicaSum <T يمتد TNumber > | عملية لجمع المدخلات عبر مثيلات TPU المكررة. |
CSRSparseMatrixComponents <T يمتد TType > | يقرأ مكونات المسؤولية الاجتماعية للشركات على دفعات "الفهرس". |
CSRSparseMatrixToDense <T يمتد TType > | قم بتحويل CSRSparseMatrix (ربما على دفعات) إلى كثيف. |
CSRSparseMatrixToSparseTensor <T يمتد TType > | تحويل CSRSparesMatrix (ربما على دفعات) إلى SparseTensor. |
CSVDataset | |
CSVDataset | |
CSVDatasetV2 | |
CtcBeamSearchDecoder <T يمتد TNumber > | ينفذ فك تشفير بحث الشعاع على السجلات الواردة في الإدخال. |
CtcBeamSearchDecoder.Options | السمات الاختيارية لـ CtcBeamSearchDecoder |
CtcGreedyDecoder <T يمتد TNumber > | ينفذ فك التشفير الجشع على السجلات الواردة في المدخلات. |
CtcGreedyDecoder.Options | السمات الاختيارية لـ CtcGreedyDecoder |
CtcLoss <T يمتد TNumber > | حساب خسارة CTC (احتمال السجل) لكل إدخال دفعة. |
CtcLoss.Options | السمات الاختيارية لـ CtcLoss |
CTCLosV2 | حساب خسارة CTC (احتمال السجل) لكل إدخال دفعة. |
CTCLossV2.Options | السمات الاختيارية لـ CTCLossV2 |
CudnnRNN <T يمتد TNumber > | شبكة RNN مدعومة بـ cuDNN. |
CudnnRNN.Options | السمات الاختيارية لـ CudnnRNN |
CudnnRNNBackprop <T يمتد TNumber > | خطوة Backprop لـ CudnnRNNV3. |
CudnnRNNBackprop.Options | السمات الاختيارية لـ CudnnRNNBackprop |
CudnnRNNCanonicalToParams <T يمتد TNumber > | يحول معلمات CudnnRNN من النموذج الأساسي إلى النموذج القابل للاستخدام. |
CudnnRNNConicalToParams.Options | السمات الاختيارية لـ CudnnRNNCanonicalToParams |
CudnnRnnParamsSize <U يمتد TNumber > | حساب حجم الأوزان التي يمكن استخدامها بواسطة نموذج Cudnn RNN. |
CudnnRnnParamsSize.Options | السمات الاختيارية لـ CudnnRnnParamsSize |
CudnnRNNParamsToCanonical <T يمتد TNumber > | يسترد معلمات CudnnRNN في شكل أساسي. |
CudnnRNNParamsToCanonical.Options | السمات الاختيارية لـ CudnnRNNParamsToCanonical |
Cumprod <T يمتد TType > | حساب المنتج التراكمي للموتر `x` على طول `المحور`. |
Cumprod.Options | السمات الاختيارية لـ Cumprod |
كومسوم <T يمتد TType > | احسب المجموع التراكمي للموتر `x` على طول `المحور`. |
Cumsum.Options | السمات الاختيارية لـ Cumsum |
CumulativeLogsumexp <T يمتد TNumber > | حساب المنتج التراكمي للموتر `x` على طول `المحور`. |
التراكميةLogsumexp.Options | السمات الاختيارية لـ CumulativeLogsumexp |
د
مخزن البيانات <T> | حاوية بيانات من نوع معين. |
DataBufferAdapterFactory | مصنع محولات المخزن المؤقت للبيانات. |
مخازن البيانات | فئة مساعد لإنشاء مثيلات DataBuffer . |
DataBufferWindow <B يمتد DataBuffer <?>> | حاوية قابلة للتغيير لعرض جزء من DataBuffer . |
فئة البيانات | Protobuf التعداد tensorflow.DataClass |
DataFormatDimMap <T يمتد TNumber > | إرجاع فهرس البعد بتنسيق بيانات الوجهة المعطى للرقم الموجود تنسيق البيانات المصدر. |
DataFormatDimMap.Options | السمات الاختيارية لـ DataFormatDimMap |
DataFormatVecPermute <T يمتد TNumber > | تبديل موتر الإدخال من "src_format" إلى "dst_format". |
DataFormatVecPermute.Options | سمات اختيارية لـ DataFormatVecPermute |
Datalayout <s يمتد databuffer <؟> ، t> | يحول البيانات المخزنة في المخزن المؤقت إلى نوع معين. |
Datalayouts | يعرض مثيلات DataLayout لتنسيقات البيانات المستخدمة بشكل متكرر في حساب الجبر الخطي. |
DataServiceRataSet | |
DataServusedataSet.options | سمات اختيارية لـ DataServiceDataset |
مجموعة البيانات | يمثل قائمة كبيرة من العناصر المستقلة (العينات) ، وتسمح بإجراء التكرار والتحولات عبر هذه العناصر. |
DatasetCardinality | إرجاع Cardinality من `input_dataset`. |
DatasetCardinality | إرجاع Cardinality من `input_dataset`. |
DatasetFromgraph | ينشئ مجموعة بيانات من "Graph_Def` المعطى". |
DataSetIrator | يمثل حالة التكرار من خلال tf.data datset. |
DatasetOptional | يمثل الاختياري نتيجة عملية getNext مجموعة البيانات التي قد تفشل ، عند الوصول إلى نهاية مجموعة البيانات. |
datasettograph | إرجاع GraphDef التسلسلي الذي يمثل `input_dataset`. |
datasettograph.options | سمات اختيارية ل DatasetToGraph |
datasettoseSeleement | يخرج العنصر المفرد من مجموعة البيانات المحددة. |
datasettotfrecord | يكتب مجموعة البيانات المحددة إلى الملف المحدد باستخدام تنسيق Tfrecord. |
datasettotfrecord | يكتب مجموعة البيانات المحددة إلى الملف المحدد باستخدام تنسيق Tfrecord. |
DataStorageVisitor <r> | قم بزيارة تخزين دعم مثيلات DataBuffer . |
نوع البيانات | (== suppress_warning documentation-presence ==) LINT.IfChangeprotobuf enum tensorflow.DataType |
Dawsn <t يمتد tnumber > | |
deallocator_pointer_long_pointer | |
Debugevent | An Event related to the debugging of a TensorFlow program. |
debugevent.builder | An Event related to the debugging of a TensorFlow program. |
debugevent.whatcase | |
DebugeventorBuilder | |
DebugeventProtos | |
DebuggedDevice | A device on which ops and/or tensors are instrumented by the debugger. |
DebuggedDevice.builder | A device on which ops and/or tensors are instrumented by the debugger. |
DebuggedDeviceorBuilder | |
تصحيح الأخطاء | A debugger-instrumented graph. |
DebuggedGraph.Builder | A debugger-instrumented graph. |
DebuggedGraphorBuilder | |
تصحيح الأخطاء | نوع protobuf tensorflow.DebuggedSourceFile |
DebuggedSourceFile.Builder | نوع protobuf tensorflow.DebuggedSourceFile |
DebuggedSourceFileorBuilder | |
DebuggedSourceFiles | نوع protobuf tensorflow.DebuggedSourceFiles |
DebuggedSourceFiles.Builder | نوع protobuf tensorflow.DebuggedSourceFiles |
DebuggedSourceFilesorBuilder | |
تصحيح DebugrgradientIdentity <t يمتد ttype > | الهوية OP لتصحيح الأخطاء التدرج. |
DebuggrgradientRefidentity <t يمتد ttype > | الهوية OP لتصحيح الأخطاء التدرج. |
تصحيح الأخطاء <t يمتد ttype > | Debug Identity V2 OP. |
Debugidentity.options | سمات اختيارية لتصحيح DebugIdentity |
debugmetadata | Metadata about the debugger and the debugged TensorFlow program. |
debugmetadata.builder | Metadata about the debugger and the debugged TensorFlow program. |
debugmetadataorbuilder | |
Debugnancount | Debug NAN قيمة عداد العداد. |
debugnancount.options | سمات اختيارية DebugNanCount |
debugnumericssummary <U يمتد tnumber > | Debug Numeric Summary v2 op. |
debugnumericssummary.options | سمات اختيارية DebugNumericsSummary |
تصحيح الأخطاء | Options for initializing DebuggerState in TensorFlow Debugger (tfdbg). |
Debugoptions.builder | Options for initializing DebuggerState in TensorFlow Debugger (tfdbg). |
DebugoptionsorBuilder | |
Debugprotos | |
DebugtensorWatch | Option for watching a node in TensorFlow Debugger (tfdbg). |
debugtensorwatch.builder | Option for watching a node in TensorFlow Debugger (tfdbg). |
DebugtensorWatchorBuilder | |
decodeandcropjpeg | فك تشفير صورة واختصاص صورة JPEG إلى موتر UINT8. |
decodeandcropjpeg.options | سمات اختيارية لـ DecodeAndCropJpeg |
decodeBase64 | فك تشفير الأوتار التي آمنت Web-Safe64. |
decodeBMP | فك تشفير الإطار الأول من صورة مشفرة BMP إلى موتر UINT8. |
decodeBMP.Options | سمات اختيارية لـ DecodeBmp |
decodecressed | تخفيض الضغط على السلاسل. |
decodecressed.options | سمات اختيارية لـ DecodeCompressed |
decodecsv | تحويل سجلات CSV إلى Tensors. |
decodecsv.options | سمات اختيارية لـ DecodeCsv |
decodegif | فك تشفير الإطار (S) للصورة المشفرة GIF إلى موتر UINT8. |
decodeimage <t يمتد tnumber > | دالة لـ decode_bmp و decode_gif و decode_jpeg و decode_png. |
decodeimage.options | سمات اختيارية لـ DecodeImage |
decodejpeg | فك تشفير صورة مشفرة JPEG إلى موتر UINT8. |
decodejpeg.options | سمات اختيارية لـ DecodeJpeg |
decodejsonexample | تحويل سجلات مثال مشفرة JSON إلى سلاسل المخزن المؤقت للبروتوكول الثنائي. |
decodepaddedraw <t يمتد tnumber > | إعادة تفسير بايت سلسلة كمتجهات للأرقام. |
decodepaddedraw.options | سمات اختيارية لـ DecodePaddedRaw |
decodepng <t يمتد tnumber > | فك تشفير صورة مشفرة PNG إلى uint8 أو uint16 الموتر. |
decodepng.options | سمات اختيارية لـ DecodePng |
DecodeProto | يستخلص OP الحقول من رسالة بروتوكول تسلسلي إلى موترات. |
decodeproto.options | سمات اختيارية لـ DecodeProto |
decoderaw <t يمتد ttype > | إعادة تفسير بايت سلسلة كمتجهات للأرقام. |
decoderaw.options | سمات اختيارية DecodeRaw |
decodewav | فك تشفير ملف WAV 16 بت على موتر عائم. |
decodewav.options | سمات اختيارية لـ DecodeWav |
DeepCopy <t يمتد ttype > | يجعل نسخة من `x`. |
DELETE_FUNC_POINTER | |
Deleteiterator | حاوية لمورد Iterator. |
DELETEMEMORYCACHE | |
DeletemultideViceIrator | حاوية لمورد Iterator. |
DeLeterOmseedGenerator | |
deleteseedgenerator | |
DeletesessionTensor | احذف الموتر المحدد بمقبضه في الجلسة. |
DenseBincount <U يمتد tnumber > | يحسب عدد حوادث كل قيمة في مجموعة عدد صحيح. |
DenseBincount.options | سمات اختيارية لـ DenseBincount |
densecountsparseoutput <U يمتد tnumber > | يؤدي عد صندوق المخرجات المتفرقة لإدخال TF.Tensor. |
densecountsparseoutput.options | سمات اختيارية لـ DenseCountSparseOutput |
DensendArray <T> | |
densetocsrsparsematrix | يحول موتر كثيف إلى (ربما مزجّن) csrsparsematrix. |
الكثافة densetensetoperation <t يمتد ttype > | يطبق عملية المجموعة على طول البعد الأخير من مدخلات 2 `tensor`. |
الكثافة | سمات اختيارية ل DenseToDenseSetOperation |
كثافة parkbatchdataset | ينشئ مجموعة بيانات تقوم بإدخال عناصر إدخال في sparsetensor. |
كثافة parkbatchdataset | ينشئ مجموعة بيانات تقوم بإدخال عناصر إدخال في sparsetensor. |
الكثافة sparsesetoperation <t يمتد ttype > | يطبق العملية المحددة على طول البعد الأخير لـ "Tensor" و "SparSetensor". |
كثافة parsesetoperation.options | سمات اختيارية ل DenseToSparseSetOperation |
العمق <t يمتد ttype > | DeptHtoSpace for Tensors من النوع T. |
DeptHtospace.Options | سمات اختيارية DepthToSpace |
DepthWiseConv2Dnative <t يمتد tnumber > | يحسب الالتفاف ثنائي الأبعاد يعطى موترات 4-D و "مرشح". |
depthwiseconv2dnative.options | سمات اختيارية لـ DepthwiseConv2dNative |
DepthWiseConv2DnativeBackPropfilter <t يمتد tnumber > | يحسب تدرجات الالتفاف على عمق فيما يتعلق بالمرشح. |
depthwiseconv2dnativeBackPropfilter.options | سمات اختيارية لـ DepthwiseConv2dNativeBackpropFilter |
DepthWiseConv2DnativeBackPropinput <t يمتد tnumber > | يحسب التدرجات من الالتفاف على عمق فيما يتعلق بالمدخلات. |
depthwiseconv2dnativeBackPropinput.options | سمات اختيارية لـ DepthwiseConv2dNativeBackpropInput |
dequantive <u يمتد tnumber > | إزالة موتر "الإدخال" في موتر تعويم أو BFLOAT16. |
تخلص من | يأخذ مدخلات UINT32 المعبأة ويفصل المدخلات إلى UINT8 للقيام بها التخلص من الجهاز. |
dequantize.options | سمات اختيارية للتخلص Dequantize |
deserializeiterator | يحول الموتر المتغير المعطى إلى متكرر ويخزنه في المورد المحدد. |
deserializemanysparse <t يمتد ttype > | تخلص من وسلس `sparsetens" من مصغرة متسلسلة. |
DeserializesParse <U يمتد ttype > | deserialize `sparsetensor` كائنات. |
DorterResourceop | يحذف المورد المحدد بواسطة المقبض. |
DorterResourceOp.options | سمات اختيارية لـ DestroyResourceOp |
DestroytemporaryVariable <t يمتد ttype > | يدمر المتغير المؤقت ويعيد قيمته النهائية. |
det <t يمتد ttype > | يحسب المحدد لمصفوفات مربعة واحدة أو أكثر. |
DeviceAttributes | protobuf نوع tensorflow.DeviceAttributes |
deviceattributes.builder | protobuf نوع tensorflow.DeviceAttributes |
DeviceAttributesorBuilder | |
deviceattributesprotos | |
DeviceFiltersprotos | |
DeviceIndex | إرجاع فهرس الجهاز يعمل OP. |
انحراف | protobuf نوع tensorflow.DeviceLocality |
devicelocality.builder | protobuf نوع tensorflow.DeviceLocality |
devicelocalityorbuilder | |
DeviceProperties | protobuf نوع tensorflow.DeviceProperties |
DeviceProperties.builder | protobuf نوع tensorflow.DeviceProperties |
DevicePropertiesorBuilder | |
DevicePropertiesProtos | |
Desicespec | يمثل مواصفات (ربما جزئية) لجهاز TensorFlow. |
Desicespec.builder | فئة البناء لبناء فئة DeviceSpec . |
Desicespec.deviceType | |
devicestepstats | نوع protobuf tensorflow.DeviceStepStats |
devicestepstats.builder | نوع protobuf tensorflow.DeviceStepStats |
devicestepstatsorbuilder | |
ديكتفالوي | Represents a Python dict keyed by `str`. |
dictvalue.builder | Represents a Python dict keyed by `str`. |
dictvalueorbuilder | |
Digamma <t يمتد tnumber > | يحسب PSI ، مشتق LGAMMA (سجل القيمة المطلقة لـ `gamma (x)`) ، العنصر. |
تمديد 2d <t يمتد tnumber > | يحسب التمدد الرمادي من موترات 4-D و 3-D "مرشح". |
deved2dbackPropFilter <t يمتد tnumber > | يحسب تدرج تمدد المورفولوجي ثنائي الأبعاد فيما يتعلق بالمرشح. |
deved2dbackPropInput <t يمتد tnumber > | يحسب تدرج تمدد المورفولوجي ثنائي الأبعاد فيما يتعلق بالمدخلات. |
البعد | |
Dimensionalspace | |
الموجهة ErganInterleavedataset | بديل لـ `interleavedataset` على قائمة ثابتة من مجموعات البيانات. |
الموجهة ErganInterleavedataset | بديل لـ `interleavedataset` على قائمة ثابتة من مجموعات البيانات. |
div <t يمتد ttype > | إرجاع x / y العنصر. |
Divnonan <t يمتد ttype > | إرجاع 0 إذا كان المقام هو الصفر. |
النقطة <t يمتد ttype > | يلف مشغل XLA dotgeneral ، موثق في https://www.tensorflow.org/performance/xla/operation_semantics#dotgeneral. |
Doubledatabuffer | DataBuffer من الزوجي. |
doubledatalayout <s يمتد databuffer <؟ >> | DataLayout الذي يحول البيانات المخزنة في المخزن المؤقت إلى الزوجي. |
doubledensendarray | |
Doublendarray | NdArray من الزوجي. |
مربعات DrawBoundings <T يمتد tnumber > | ارسم مربعات محددة على مجموعة من الصور. |
DummyTerationCounter | |
dummymemorycache | |
DummySeedgenerator | |
DynamicPartition <t يمتد ttype > | أقسام "البيانات" في "num_partitions" باستخدام مؤشرات من "الأقسام". |
DynamicsLice <t يمتد ttype > | يلف مشغل XLA DynamicsLice ، موثق في https://www.tensorflow.org/performance/xla/operation_semantics#dynamicslice. |
DynamicStitch <t يمتد ttype > | interleave القيم من `data` engesors في موتر واحد. |
DynamicupDatesLice <t يمتد ttype > | يلف مشغل XLA DynamicupDatesLice ، موثق في https://www.tensorflow.org/performance/xla/operation_semantics#dynamicupdateslice. |
ه
إيجار | بيئة لتنفيذ عمليات تنسورفورو بفارغ الصبر. |
eagersession.deviceplacepolicy | يتحكم في كيفية التصرف عندما نحاول تشغيل عملية على جهاز معين ولكن بعض موترات الإدخال ليست على هذا الجهاز. |
eagersession.options | |
editdistance | يحسب مسافة تحرير Levenshtein (ربما تطبيع). |
editdistance.options | سمات اختيارية EditDistance |
eig <u يمتد ttype > | يحسب تحلل eigen لمصفوفات مربعة واحدة أو أكثر. |
eig.options | سمات اختيارية لـ Eig |
einsum <t يمتد ttype > | تقلص التوتر وفقا لاتفاقية إينشتاين ملخص. |
einsum <t يمتد ttype > | OP الذي يدعم Einsum OP الأساسي مع 2 مدخلات وإخراج واحد. |
Elu <t يمتد tnumber > | يحسب الخطي الأسي: `exp (الميزات) - 1` إذا كان <0 ،" الميزات "خلاف ذلك. |
Elu <t يمتد tfloating > | وحدة خطية الأسية. |
elugrad <t يمتد tnumber > | يحسب التدرجات لعملية الخطي الأسي (ELU). |
التضمين | OP تمكين تمايز التضمينات TPU. |
فارغ <t يمتد ttype > | يخلق موتر مع الشكل المعطى. |
فارغة | سمات اختيارية Empty |
فارغة | ينشئ وإرجاع قائمة موتر فارغة. |
فارغة | يخلق وإرجاع خريطة موتر فارغة. |
EncodeBase64 | قم بتشفير السلاسل إلى تنسيق Base64 الآمن على الويب. |
EncodeBase64.Options | سمات اختيارية لـ EncodeBase64 |
Encodejpeg | jpeg-encode صورة. |
encodejpeg.options | سمات اختيارية لـ EncodeJpeg |
EncodejpegvariableDiableDicality | JPEG تشفير صورة الإدخال مع جودة الضغط المقدمة. |
encodepng | PNG-encode صورة. |
encodepng.options | سمات اختيارية لـ EncodePng |
الترميز | يقوم OP بتسلسل رسائل protobuf المقدمة في موتر الإدخال. |
Encodeproto.options | سمات اختيارية EncodeProto |
EncoDewav | ترميز بيانات الصوت باستخدام تنسيق ملف WAV. |
نقطة النهاية | التعليقات التوضيحية المستخدمة لتمييز طريقة لفئة شرحية مع @Operator والتي يجب أن تنشئ نقطة النهاية إلى ERROR(Ops/org.tensorflow.op.Ops Ops) أو واحدة من مجموعاتها. |
enqueuetpuembeddingintegerbatch | OP الذي يمنح قائمة من موتر الدُفعات الإدخال إلى tpuembedding. |
enqueuetpuembeddingintegerbatch.options | سمات اختيارية لـ EnqueueTPUEmbeddingIntegerBatch |
enqueuetpuembeddingRaggedTensorBatch | يخفف من نقل الكود الذي يستخدم tf.nn.embedding_lookup (). |
enqueuetpuembeddingRaggedTensorBatch.options | سمات اختيارية لـ EnqueueTPUEmbeddingRaggedTensorBatch |
enqueuetpuembeddingsparsebatch | OP الذي يثني مؤشرات إدخال tpuembedding من sparsetensor. |
enqueuetpuembeddingsparsebatch.options | سمات اختيارية لـ EnqueueTPUEmbeddingSparseBatch |
enqueuetpuembeddingsparsetensorbatch | يخفف من نقل الكود الذي يستخدم tf.nn.embedding_lookup_sparse (). |
enqueuetpuembeddingsparsetensorbatch.options | سمات اختيارية لـ EnqueueTPUEmbeddingSparseTensorBatch |
usureShape <t يمتد ttype > | يضمن أن شكل الموتر يطابق الشكل المتوقع. |
أدخل <t يمتد ttype > | يخلق أو يجد إطارًا طفلًا ، ويجعل "بيانات" متاحًا لإطار الطفل. |
Enter.options | سمات اختيارية Enter |
دخول | نوع protobuf tensorflow.EntryValue |
الدخول | نوع protobuf tensorflow.EntryValue |
intringValue.Kindcase | |
intingValueorBuilder | |
متساوي | إرجاع قيمة الحقيقة (x == y) العنصر. |
equal.options | سمات اختيارية على Equal |
erf <t يمتد tnumber > | يحسب وظيفة خطأ Gauss من `x` عنصر العنصر. |
erfc <t يمتد tnumber > | يحسب وظيفة الخطأ التكميلي لـ `x` element-wise. |
erfinv <t يمتد tnumber > | |
errorcodes | |
errorcodesprotos | |
Euclideannorm <t يمتد ttype > | يحسب القاعدة الإقليدية للعناصر عبر أبعاد التوتر. |
الإقليم الإقليدي | سمات اختيارية لـ EuclideanNorm |
حدث | Protocol buffer representing an event that happened during the execution of a Brain model. |
Event.Builder | Protocol buffer representing an event that happened during the execution of a Brain model. |
الحدث | |
eventorbuilder | |
EventProtos | |
مثال | نوع protobuf tensorflow.Example |
مثال | نوع protobuf tensorflow.Example |
مثال | |
exampleparserconfiguration | نوع protobuf tensorflow.ExampleParserConfiguration |
exampleparserconfiguration.builder | نوع protobuf tensorflow.ExampleParserConfiguration |
exampleParserConfigurationorBuilder | |
مثال ParserConfigurationProtos | |
exampleprotos | |
ينفذ | OP الذي يقوم بتحميل وتنفيذ برنامج TPU على جهاز TPU. |
التنفيذيين | OP الذي ينفذ برنامجًا مع تحديثات متغيرة في المكان اختياري. |
تنفيذ | Data relating to the eager execution of an op or a Graph. |
التنفيذ | Data relating to the eager execution of an op or a Graph. |
ExecutionEnvironment | يحدد بيئة لإنشاء وتنفيذ Operation TensorFlow S. |
ExecutionEnvironment.types | |
ExecutionorBuilder | |
الخروج <t يمتد ttype > | يخرج الإطار الحالي إلى إطاره الأم. |
exp <t يمتد ttype > | يحسب الأسية من X Element-Wise. |
expansdims <t يمتد ttype > | إدراج بعد 1 في شكل الموتر. |
Expint <t يمتد tnumber > | |
expm1 <t يمتد ttype > | يحسب `exp (x) - 1` عنصر. |
الأسي <t يمتد tfloating > | وظيفة التنشيط الأسية. |
ExtractGlimpse | يستخلص لمحة عن موتر الإدخال. |
extractglimpse.options | سمات اختيارية لاستخراج ExtractGlimpse |
stractimagePatches <t يمتد ttype > | استخراج "البقع" من "الصور" ووضعها في بعد الإخراج "العمق". |
extractjpegshape <t يمتد tnumber > | استخراج معلومات الشكل لصورة JPEG مشفرة. |
extractvolumepatches <t يمتد tnumber > | استخراج "البقع" من "المدخلات" ووضعها في "عمق" "البعد الإخراج. |
ف
حقيقة | إخراج حقيقة عن العوامل. |
fakequantwithminmaxargs | قم بتعيين موتر "المدخلات" المزيفة ، وتكتب العائم إلى "مخرجات" من نفس النوع. |
fakequantwithminmaxargs.options | سمات اختيارية لـ FakeQuantWithMinMaxArgs |
fakequantwithminmaxargsgradient | حساب التدرجات لعملية FAPEQUANTWITHMINMAXARGS. |
fakequantwithminmaxargsgradient.options | سمات اختيارية لـ FakeQuantWithMinMaxArgsGradient |
fakequantwithminmaxvars | Quanted-ided tensor "المدخلات" من النوع تعويم عبر أرقام التعويم العالمية قم بتعليق التوتر المزيف "مدخلات" من النوع العائم عبر عوامل التعويم العالمية "Min" و "Max` إلى" المخرجات "من نفس الشكل مثل" المدخلات ". |
fakequantwithminmaxvars.options | سمات اختيارية لـ FakeQuantWithMinMaxVars |
fakequantwithminmaxvarsgradient | حساب التدرجات لعملية FAPEQUANTWITHMINMAXVARS. |
fakequantwithminmaxvarsgradient.options | سمات اختيارية لـ FakeQuantWithMinMaxVarsGradient |
fakequantwithminmaxvarsperchannel | قم بتوزيع موتر "المدخلات" من النوع العائم عبر عوامات لكل قناة Quantive-Quantive endists `‘ tensor من النوع تعويم لكل قناة وواحدة من الأشكال: `[d]` ، `[b ، d]` `` [b ، h ، w ، d] `عبر كل قناة تعويم` `` `` `` ` Min` و "Max" من الشكل "[D] إلى" مخرجات "من نفس شكل" المدخلات ". |
fakequantwithminmaxvarsperchannel.options | سمات اختيارية لـ FakeQuantWithMinMaxVarsPerChannel |
fakequantwithminmaxvarsperchannelgradient | حساب التدرجات لعملية FAPEQUANTWITHMINMAXVARSPERCHANNEL. |
fakequantwithminmaxvarsperchannelgradient.options | سمات اختيارية لـ FakeQuantWithMinMaxVarsPerChannelGradient |
fastElementSequence <t ، U يمتد ndarray <t >> | تسلسل إعادة تدوير نفس مثيل NdArray عند تكرار عناصرها |
ميزة | Containers for non-sequential data. |
ميزة | Containers for non-sequential data. |
ميزة. kindcase | |
ميزة التكوين | نوع protobuf tensorflow.FeatureConfiguration |
featureConfiguration.builder | نوع protobuf tensorflow.FeatureConfiguration |
featureConfiguration.configcase | |
featureConfigurationorBuilder | |
المميز | Containers for sequential data. |
المميز | Containers for sequential data. |
feathureListorBuilder | |
المميزون | نوع protobuf tensorflow.FeatureLists |
المميزون | نوع protobuf tensorflow.FeatureLists |
المميزات | |
الميزات | |
الميزات | |
سمات | protobuf نوع tensorflow.Features |
الميزات | protobuf نوع tensorflow.Features |
ميزات | |
fft <t يمتد ttype > | تحويل فورييه السريع. |
FFT2D <T يمتد ttype > | 2D Fast Fourier Transform. |
FFT3D <T يمتد ttype > | 3D Fast Fourier تحويل. |
FIFOQUEUE | قائمة انتظار تنتج عناصر في أول ترتيب أول. |
fifoqueue.options | سمات اختيارية لـ FifoQueue |
ملء <U يمتد ttype > | يخلق موتر مملوءة بقيمة العددية. |
FilterBylastComponentDataset | ينشئ مجموعة بيانات تحتوي على عناصر من المكون الأول من `input_dataset` لها حقيقة في المكون الأخير. |
بصمة | يولد قيم البصمات. |
FixedLenFeatureProto | نوع protobuf tensorflow.FixedLenFeatureProto |
FlexLenFeatureProto.Builder | نوع protobuf tensorflow.FixedLenFeatureProto |
ثابتة extureprotoorbuilder | |
ثابت LengthRecordDataset | |
ثابت LengthRecordReader | القارئ الذي يخرج السجلات ذات الطول الثابت من ملف. |
ثابت الطول RerecordReader.options | سمات اختيارية لـ FixedLengthRecordReader |
ثابتة ungramcandidatesampler | يولد ملصقات لأخذ عينات من المرشحين مع توزيع Unigram المستفاد. |
ثابتة ungramcandidatesampler.options | سمات اختيارية لـ FixedUnigramCandidateSampler |
float16layout | تخطيط البيانات الذي يحول عوامات 32 بت من/إلى 16 بت ، وفقًا لمواصفات النقطة العائمة نصف الدقة IEEE-754. |
Floatdatabuffer | DataBuffer من العوامات. |
floatdatalayout <s يمتد databuffer <؟ >> | DataLayout الذي يحول البيانات المخزنة في المخزن المؤقت إلى العوامات. |
floatdensendarray | |
قائمة Floatlist | نوع protobuf tensorflow.FloatList |
floatlist.builder | نوع protobuf tensorflow.FloatList |
FloatlistorBuilder | |
Floatndarray | NdArray من العوامات. |
الأرضية <t يمتد tnumber > | إرجاع العنصر الأكبر عدد صحيح لا يزيد عن x. |
Floordiv <t يمتد ttype > | إرجاع x // y element-wise. |
Floormod <t يمتد tnumber > | إرجاع العنصر المتبقي من التقسيم. |
FlushSummarywriter | |
fractionalavgpool <t يمتد tnumber > | يؤدي متوسط التجميع الكسري على المدخلات. |
fractionalavgpool.options | سمات اختيارية FractionalAvgPool |
fractionalavgpoolgradger <t يمتد tnumber > | يحسب التدرج من وظيفة fractionalavgpool. |
fractionalavgpoolgrad.options | سمات اختيارية لـ FractionalAvgPoolGrad |
fractionalmaxpool <t يمتد tnumber > | يؤدي تجميع الأقصى الكسري على المدخلات. |
fractionalmaxpool.options | سمات اختيارية FractionalMaxPool |
fractionalalaxpoolgradger <t يمتد tnumber > | يحسب التدرج من وظيفة fractionalmaxpool. |
fractionalmaxpoolgrad.options | سمات اختيارية FractionalMaxPoolGrad |
Fresnelcos <t يمتد tnumber > | |
fresnelsin <t يمتد tnumber > | |
Ftrl | المحسن الذي ينفذ خوارزمية FTRL. |
وظيفة | A function can be instantiated when the runtime can bind every attr with a value. |
FunctionDef.Argattrs | Attributes for function arguments. |
functionDef.Argattrs.builder | Attributes for function arguments. |
FunctionDef.ArgattrSorBuilder | |
FunctionDef.Builder | A function can be instantiated when the runtime can bind every attr with a value. |
الدالة | A library is a set of named functions. |
FunctionDeflibrary.builder | A library is a set of named functions. |
FunctionDeflibraryorBuilder | |
وظيفة deforbuilder | |
وظيفة | |
FunctionSpec | Represents `FunctionSpec` used in `Function`. |
وظيفة spec.builder | Represents `FunctionSpec` used in `Function`. |
وظيفة spec.experimentalcompile | Whether the function should be compiled by XLA. |
وظيفة specorbuilder | |
تنصهر batchnorm <t يمتد tnumber ، u يمتد tnumber > | تطبيع الدُفعات. |
DuseBatchNorm.options | سمات اختيارية لـ FusedBatchNorm |
DuseBatchNormgrad <T يمتد tnumber ، U يمتد tnumber > | التدرج لتطبيع الدُفعات. |
DOSERBATCHNORMGRARGRAGR.OPTIONS | سمات اختيارية لـ FusedBatchNormGrad |
يقوم VusedPadConv2d <T بتوسيع tnumber > | يؤدي حشوة كمعالجة مسبقة أثناء الالتفاف. |
OfusedResizeAndPadConv2d <t يمتد tnumber > | ينفذ تغيير الحجم والحشو كمعالجة مسبقة أثناء الالتواء. |
OfusedResizeAndpadConv2d.options | سمات اختيارية لـ FusedResizeAndPadConv2d |
ز
تجمع <t يمتد tnumber > | يتراكم المتبادل موترات متعددة من النوع المتطابق والشكل. |
جمع <t يمتد ttype > | جمع شرائح من محور "params" "المحور" وفقًا لـ "المؤشرات". |
جمع <t يمتد ttype > | يلف مشغل XLA Gather الموثق في https://www.tensorflow.org/xla/operation_semantics#gather |
Gather.options | سمات اختيارية Gather |
Gather.options | سمات اختيارية Gather |
gathernd <t يمتد ttype > | جمع شرائح من "params" إلى موتر مع الشكل المحدد بواسطة "المؤشرات". |
gatherv2 <t يمتد tnumber > | يتراكم المتبادل موترات متعددة من النوع المتطابق والشكل. |
gatherv2.options | سمات اختيارية لـ GatherV2 |
generateBoundingBoxProposals | ينتج هذا المرجع منطقة من المصالح من مربعات مربعات محددة (BBOX_DELTAS) مشفرة وفقًا لـ EQ.2 في ARXIV: 1506.01497 يختار OP أعلى صناديق التسجيل `pre_nms_topn` ، يدللها فيما يتعلق بالمراسي ، ويطبق قمعًا غير أقصى على صناديق متداخلة بأعلى من` nms_threshold` تقاطع الاتجاه (IOU) ، حيث يتجاهل الصناديق حيث يكون الجانب الأقصر أقل من `` `` `` `` `` `` `` `` `` `` min_size`. |
generateBoundingBoxProposals.options | سمات اختيارية لـ GenerateBoundingBoxProposals |
generatevocabremapping | إعطاء طريق إلى ملفات المفردات الجديدة والقديمة ، إرجاع الموتر الطول `num_new_vocab` ، حيث يحتوي `remapping [i]` على رقم الصف في المفردات القديمة التي تتوافق مع الصف "أنا في المفردات الجديدة (بدءًا من السطر" new_vocab_offset` وما يصل إلى `num_new_vocab`) ، أو`-------------------------------- 1` إذا كان الدخول `أنا في المفردات الجديدة ليس في المفردات القديمة. |
generatevocabremapping.options | سمات اختيارية لـ GenerateVocabRemapping |
GetSessionHandle | تخزين موتر المدخلات في حالة الجلسة الحالية. |
GetSessionTensor <t يمتد ttype > | احصل على قيمة الموتر المحدد من خلال مقبضه. |
Glorot <t يمتد tfloating > | تهيئة Glorot ، وتسمى أيضا كزافييه التهيئة. |
Gpuinfo | protobuf نوع tensorflow.GPUInfo |
Gpuinfo.builder | protobuf نوع tensorflow.GPUInfo |
Gpuinfoorbuilder | |
Gpuoptions | نوع protobuf tensorflow.GPUOptions |
Gpuoptions.builder | نوع protobuf tensorflow.GPUOptions |
Gpuoptions.experimental | نوع protobuf tensorflow.GPUOptions.Experimental |
Gpuoptions.experimental.builder | نوع protobuf tensorflow.GPUOptions.Experimental |
Gpuoptions.experimental.virtualDevices | Configuration for breaking down a visible GPU into multiple "virtual" devices. |
Gpuoptions.experimental.virtualDevices.builder | Configuration for breaking down a visible GPU into multiple "virtual" devices. |
Gpuoptions.experimental.virtualDevicesorBuilder | |
Gpuoptions.experimentalorbuilder | |
Gpuoptionsorbuilder | |
GradientDef | GradientDef defines the gradient function of a function defined in a function library. |
GradientDef.Builder | GradientDef defines the gradient function of a function defined in a function library. |
GradientDeforBuilder | |
التدرج | محسن النسب العشوائي الأساسي. |
التدرجات | يضيف عمليات لحساب المشتقات الجزئية من مجموع y s wrt x s ، ie ، d(y_1 + y_2 + ...)/dx_1, d(y_1 + y_2 + ...)/dx_2... |
التدرجات | سمات اختيارية Gradients |
رسم بياني | رسم بياني لتدفق البيانات يمثل حساب Tensorflow. |
graph.whilesubgraphbuilder | تستخدم لإنشاء إنشاء فئة مجردة تتجاوز طريقة buildsubgraph لبناء خريطة فرعية مشروطة أو الجسم لبعض الوقت. |
GraphDebuginfo | نوع protobuf tensorflow.GraphDebugInfo |
GraphDebuginfo.builder | نوع protobuf tensorflow.GraphDebugInfo |
graphdebuginfo.filelinecol | This represents a file/line location in the source code. |
graphdebuginfo.filelinecol.builder | This represents a file/line location in the source code. |
graphdebuginfo.filelinecolorbuilder | |
GraphDebuginfo.stacktrace | This represents a stack trace which is a ordered list of `FileLineCol`. |
graphdebuginfo.stacktrace.builder | This represents a stack trace which is a ordered list of `FileLineCol`. |
graphdebuginfo.stacktraceorbuilder | |
GraphDebuginFoorBuilder | |
GraphDebuginFoprotos | |
GraphDef | Represents the graph of operationsprotobuf نوع tensorflow.GraphDef |
GraphDef.Builder | Represents the graph of operationsprotobuf نوع tensorflow.GraphDef |
GraphDeforBuilder | |
GraphExecutiontrace | Data relating to an execution of a Graph (e.g., an eager execution of a FuncGraph). |
GraphExecutiontrace.builder | Data relating to an execution of a Graph (e.g., an eager execution of a FuncGraph). |
GraphExecutionTraceorBuilder | |
GraphOpcreation | The creation of an op in a TensorFlow Graph (e.g., FuncGraph in TF2). |
graphopcreation.builder | The creation of an op in a TensorFlow Graph (e.g., FuncGraph in TF2). |
GraphOpcreationorBuilder | |
Graphoperation | تنفيذ Operation تمت إضافتها كعقدة إلى Graph . |
GraphoperationBuilder | OperationBuilder لإضافة GraphOperation S إلى Graph . |
Graphoptions | protobuf نوع tensorflow.GraphOptions |
graphoptions.builder | protobuf نوع tensorflow.GraphOptions |
graphoptionsorbuilder | |
GraphProtos | |
GraphTransferConstnodeInfo | نوع protobuf tensorflow.GraphTransferConstNodeInfo |
graphtransferconstnodeinfo.builder | نوع protobuf tensorflow.GraphTransferConstNodeInfo |
graphtransferconstnodeinfoorbuilder | |
graphtransfergraphinputnodeinfo | protobuf نوع tensorflow.GraphTransferGraphInputNodeInfo |
graphtransfergraphinputnodeinfo.builder | protobuf نوع tensorflow.GraphTransferGraphInputNodeInfo |
graphtransfergraphinputnodeinfoorbuilder | |
graphtransfergraphoutputnodeinfo | نوع protobuf tensorflow.GraphTransferGraphOutputNodeInfo |
graphtransfergraphoutputnodeinfo.builder | نوع protobuf tensorflow.GraphTransferGraphOutputNodeInfo |
graphtransfergraphoutputnodeinfoorbuilder | |
GraphTransferinfo | Protocol buffer representing a handle to a tensorflow resource. |
Graphtransferinfo.builder | Protocol buffer representing a handle to a tensorflow resource. |
Graphtransferinfo.dest | protobuf enum tensorflow.GraphTransferInfo.Destination |
GraphTransferInfoorBuilder | |
GraphTransferinFoproto | |
graphtransfernodeinfo | نوع protobuf tensorflow.GraphTransferNodeInfo |
graphtransfernodeinfo.builder | نوع protobuf tensorflow.GraphTransferNodeInfo |
graphtransfernodeinfoorbuilder | |
GraphTransfernodeInput | protobuf نوع tensorflow.GraphTransferNodeInput |
graphtransfernodeinput.builder | protobuf نوع tensorflow.GraphTransferNodeInput |
graphtransfernodeinputinfo | protobuf نوع tensorflow.GraphTransferNodeInputInfo |
graphtransfernodeinputinfo.builder | protobuf نوع tensorflow.GraphTransferNodeInputInfo |
graphtransfernodeinputInfoorBuilder | |
GraphTransferNodeInputorBuilder | |
GraphTransferNodeOutputInfo | protobuf نوع tensorflow.GraphTransferNodeOutputInfo |
graphtransfernodeOutputinfo.builder | protobuf نوع tensorflow.GraphTransferNodeOutputInfo |
GraphTransferNodeOutputInfoorBuilder | |
أكبر | إرجاع قيمة الحقيقة للعنصر (x> y). |
أكبر | إرجاع قيمة الحقيقة (x> = y) العنصر. |
Grublockcell <t يمتد tnumber > | يحسب انتشار خلية GRU للأمام لخطوة زمنية واحدة. |
Grublockcellgrad <T يمتد tnumber > | يحسب التراجع الخلفي لخلية GRU لخطوة زمنية واحدة. |
ضمان <T يمتد ttype > | يعطي ضمانًا لوقت تشغيل TF بأن موتر الإدخال ثابت. |
ح
hardsigmoid <t يمتد tfloating > | تنشيط sigmoid الصعب. |
علامة التجزئة | يخلق جدول التجزئة غير المخلوطة. |
hashtable.options | سمات اختيارية لعلامة HashTable |
انه يمتد tfloating > | هو تهيئة. |
مساعدين | فئة الحاويات للطرق الأساسية التي تضيف أو تنفيذ العديد من العمليات وإعادة واحدة منها. |
المفصلة | يحسب فقدان المفصلة بين الملصقات والتنبؤات. |
المفصلات <t يمتد tnumber > | مقياس يحسب مقياس فقد المفصل بين الملصقات والتنبؤات. |
THERMAROMFIXEDWIDTH <U يمتد tnumber > | إرجاع الرسم البياني للقيم. |
Histogramproto | Serialization format for histogram module in core/lib/histogram/histogram.hprotobuf نوع tensorflow.HistogramProto |
Histogramproto.builder | Serialization format for histogram module in core/lib/histogram/histogram.hprotobuf نوع tensorflow.HistogramProto |
Histogramprotoorbuilder | |
THEBOMORMOMSUMMARY | يخرج مخزن بروتوكول "ملخص" مع رسم بياني. |
hsvtorgb <t يمتد tnumber > | تحويل صورة واحدة أو أكثر من HSV إلى RGB. |
هوبر | يحسب فقدان هوبر بين الملصقات والتنبؤات. |
أنا
الهوية <t يمتد tfloating > | التهيئة التي تولد مصفوفة الهوية. |
الهوية <t يمتد ttype > | إرجاع موتر بنفس الشكل والمحتويات مثل موتر الإدخال أو القيمة. |
الهوية | إرجاع قائمة من التوترات بنفس الأشكال والمحتويات مثل الإدخال التوتر. |
هوية | القارئ الذي يخرج العمل في قائمة الانتظار كمفتاح وقيمة. |
IdentityReader.options | سمات اختيارية لـ IdentityReader |
ifft <t يمتد ttype > | عكسي سريع فورييه تحويل. |
ifft2d <t يمتد ttype > | عكسية 2D Fast Fourier تحويل. |
ifft3d <t يمتد ttype > | عكسية 3D سريع فورييه تحويل. |
igamma <t يمتد tnumber > | قم بحساب وظيفة جاما غير المنتظمة المنتظمة `p (a ، x)`. |
igammac <t يمتد tnumber > | قم بحساب وظيفة جاما غير المكتملة العليا غير المكتملة `q (a ، x)`. |
igammagrada <t يمتد tnumber > | يحسب التدرج من `igamma (a ، x)` wrt `a`. |
تجاهل | ينشئ مجموعة بيانات تحتوي على عناصر "input_dataset` تجاهل الأخطاء. |
تجاهل | ينشئ مجموعة بيانات تحتوي على عناصر "input_dataset` تجاهل الأخطاء. |
agnorerorsdataset.options | سمات اختيارية IgnoreErrorsDataset |
agnorerorsdataset.options | سمات اختيارية IgnoreErrorsDataset |
غير شرعي | استثناء يتم إلقاؤه عند إكمال العملية بسبب رتبة الصفيف المستهدف. |
Imag <U يمتد tnumber > | إرجاع الجزء الخيالي من الرقم المعقد. |
ImageProjectivetRansformv2 <t يمتد tnumber > | يطبق التحويل المحدد على كل صورة من الصور. |
ImageProjectivetRansformv2.Options | سمات اختيارية لـ ImageProjectiveTransformV2 |
ImageProjectivetRansformv3 <t يمتد tnumber > | يطبق التحويل المحدد على كل صورة من الصور. |
ImageProjectivetRansformv3.Options | سمات اختيارية لـ ImageProjectiveTransformV3 |
صور | يخرج مخزن بروتوكول "ملخص" مع الصور. |
الصور | سمات اختيارية ImageSummary |
ImmutableConst <t يمتد ttype > | إرجاع الموتر غير القابل للتغيير من منطقة الذاكرة. |
استيراد | |
فِهرِس | فهرس يستخدم لتقطيع عرض من صفيف n-dimensional. |
مفهرس | |
IndexedPositioniTerator.CoordsLongConsumer | |
المؤشرات | فئة المساعد لإنشاء كائنات Index . |
infeeddequeue <t يمتد ttype > | OP العنصر النائب لقيمة سيتم تغذية في الحساب. |
infeeddequeuetuple | يجلب قيم متعددة من infeed باعتباره tuple XLA. |
infeedenqueue | OP الذي يغذي قيمة موتر واحد في الحساب. |
infeedenqueue.options | سمات اختيارية لـ InfeedEnqueue |
infeedenqueueprelinearizedbuffer | OP الذي enqueues عازلة مسبقا في tpu infeed. |
infeedenqueueprelinearizedbuffer.options | سمات اختيارية لـ InfeedEnqueuePrelinearizedBuffer |
infeedenqueuetuple | يغذي قيم موتر متعددة في الحساب باعتباره tuple XLA. |
infeedenqueuetuple.options | سمات اختيارية لـ InfeedEnqueueTuple |
init | |
التهيئة <t يمتد ttype > | واجهة للمهيئات |
initializetable | تهيئة الجدول التي تأخذ اثنين من الموترات للمفاتيح والقيم على التوالي. |
initializetablefromdataset | |
initializetableFromTextFile | تهيئة جدول من ملف نصي. |
initializetableFromTextFile.options | سمات اختيارية لـ InitializeTableFromTextFile |
inplaceadd <t يمتد ttype > | يضيف V إلى صفوف محددة من x. |
inplacesub <t يمتد ttype > | يطرح `v` في صفوف محددة من` x`. |
في placeupdate <t يمتد ttype > | التحديثات المحددة صفوف "أنا" مع القيم "V". |
int64list | نوع protobuf tensorflow.Int64List |
int64list.builder | نوع protobuf tensorflow.Int64List |
int64ListorBuilder | |
intdatabuffer | DataBuffer من ints. |
intdatalayout <s يمتد databuffer <؟ >> | DataLayout الذي يحول البيانات المخزنة في المخزن المؤقت إلى ints. |
intdensendarray | |
interconnectlink | Protobuf type tensorflow.InterconnectLink |
InterconnectLink.Builder | Protobuf type tensorflow.InterconnectLink |
InterconnectLinkOrBuilder | |
IntNdArray | An NdArray of integers. |
InTopK | Says whether the targets are in the top `K` predictions. |
Inv <T extends TType > | Computes the inverse of one or more square invertible matrices or their adjoints (conjugate transposes). |
Inv.Options | Optional attributes for Inv |
Invert <T extends TNumber > | Invert (flip) each bit of supported types; for example, type `uint8` value 01010101 becomes 10101010. |
InvertPermutation <T extends TNumber > | Computes the inverse permutation of a tensor. |
InvGrad <T extends TType > | Computes the gradient for the inverse of `x` wrt its input. |
Irfft <U extends TNumber > | Inverse real-valued fast Fourier transform. |
Irfft2d <U extends TNumber > | Inverse 2D real-valued fast Fourier transform. |
Irfft3d <U extends TNumber > | Inverse 3D real-valued fast Fourier transform. |
IsBoostedTreesEnsembleInitialized | Checks whether a tree ensemble has been initialized. |
IsBoostedTreesQuantileStreamResourceInitialized | Checks whether a quantile stream has been initialized. |
IsFinite | Returns which elements of x are finite. |
IsInf | Returns which elements of x are Inf. |
IsNan | Returns which elements of x are NaN. |
IsotonicRegression <U extends TNumber > | Solves a batch of isotonic regression problems. |
IsVariableInitialized | Checks whether a tensor has been initialized. |
Iterator | |
IteratorFromStringHandle | |
IteratorFromStringHandle.Options | Optional attributes for IteratorFromStringHandle |
IteratorGetDevice | Returns the name of the device on which `resource` has been placed. |
IteratorGetDevice | Returns the name of the device on which `resource` has been placed. |
IteratorGetNext | Gets the next output from the given iterator . |
IteratorGetNextAsOptional | Gets the next output from the given iterator as an Optional variant. |
IteratorGetNextSync | Gets the next output from the given iterator. |
IteratorToStringHandle | Converts the given `resource_handle` representing an iterator to a string. |
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JobDef | Defines a single job in a TensorFlow cluster. |
JobDef.Builder | Defines a single job in a TensorFlow cluster. |
JobDefOrBuilder | |
JobDeviceFilters | Defines the device filters for tasks in a job. |
JobDeviceFilters.Builder | Defines the device filters for tasks in a job. |
JobDeviceFiltersOrBuilder | |
ينضم | Joins the strings in the given list of string tensors into one tensor; with the given separator (default is an empty separator). |
Join.Options | Optional attributes for Join |
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KernelDef | Protobuf type tensorflow.KernelDef |
KernelDef.AttrConstraint | Protobuf type tensorflow.KernelDef.AttrConstraint |
KernelDef.AttrConstraint.Builder | Protobuf type tensorflow.KernelDef.AttrConstraint |
KernelDef.AttrConstraintOrBuilder | |
KernelDef.Builder | Protobuf type tensorflow.KernelDef |
KernelDefOrBuilder | |
KernelDefProtos | |
KernelList | A collection of KernelDefsProtobuf type tensorflow.KernelList |
KernelList.Builder | A collection of KernelDefsProtobuf type tensorflow.KernelList |
KernelListOrBuilder | |
KeyValueSort <T extends TNumber , U extends TType > | Wraps the XLA Sort operator, documented at https://www.tensorflow.org/performance/xla/operation_semantics#sort . |
KLDivergence | Computes Kullback-Leibler divergence loss between labels and predictions. |
KLDivergence <T extends TNumber > | A metric that computes the Kullback-Leibler divergence loss metric between labels and predictions. |
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. |
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L2Loss <T extends TNumber > | L2 Loss. |
LatencyStatsDataset | Records the latency of producing `input_dataset` elements in a StatsAggregator. |
LatencyStatsDataset | Records the latency of producing `input_dataset` elements in a StatsAggregator. |
LeakyRelu <T extends TNumber > | Computes rectified linear: `max(features, features * alpha)`. |
LeakyRelu.Options | Optional attributes for LeakyRelu |
LeakyReluGrad <T extends TNumber > | Computes rectified linear gradients for a LeakyRelu operation. |
LeakyReluGrad.Options | Optional attributes for LeakyReluGrad |
LearnedUnigramCandidateSampler | Generates labels for candidate sampling with a learned unigram distribution. |
LearnedUnigramCandidateSampler.Options | Optional attributes for LearnedUnigramCandidateSampler |
LeCun <T extends TFloating > | LeCun normal initializer. |
LeftShift <T extends TNumber > | Elementwise computes the bitwise left-shift of `x` and `y`. |
أقل | Returns the truth value of (x < y) element-wise. |
LessEqual | Returns the truth value of (x <= y) element-wise. |
Lgamma <T extends TNumber > | Computes the log of the absolute value of `Gamma(x)` element-wise. |
Linear <U extends TNumber > | Linear activation function (pass-through). |
LinSpace <T extends TNumber > | Generates values in an interval. |
Listener_BytePointer | |
Listener_String | |
ListValue | Represents a Python list. |
ListValue.Builder | Represents a Python list. |
ListValueOrBuilder | |
LMDBDataset | Creates a dataset that emits the key-value pairs in one or more LMDB files. |
LmdbDataset | |
LmdbReader | A Reader that outputs the records from a LMDB file. |
LmdbReader.Options | Optional attributes for LmdbReader |
LoadAndRemapMatrix | Loads a 2-D (matrix) `Tensor` with name `old_tensor_name` from the checkpoint at `ckpt_path` and potentially reorders its rows and columns using the specified remappings. |
LoadAndRemapMatrix.Options | Optional attributes for LoadAndRemapMatrix |
LoadTPUEmbeddingAdadeltaParameters | Load Adadelta embedding parameters. |
LoadTPUEmbeddingAdadeltaParameters.Options | Optional attributes for LoadTPUEmbeddingAdadeltaParameters |
LoadTPUEmbeddingAdadeltaParametersGradAccumDebug | Load Adadelta parameters with debug support. |
LoadTPUEmbeddingAdadeltaParametersGradAccumDebug.Options | Optional attributes for LoadTPUEmbeddingAdadeltaParametersGradAccumDebug |
LoadTPUEmbeddingAdagradParameters | Load Adagrad embedding parameters. |
LoadTPUEmbeddingAdagradParameters.Options | Optional attributes for LoadTPUEmbeddingAdagradParameters |
LoadTPUEmbeddingAdagradParametersGradAccumDebug | Load Adagrad embedding parameters with debug support. |
LoadTPUEmbeddingAdagradParametersGradAccumDebug.Options | Optional attributes for LoadTPUEmbeddingAdagradParametersGradAccumDebug |
LoadTPUEmbeddingADAMParameters | Load ADAM embedding parameters. |
LoadTPUEmbeddingADAMParameters.Options | Optional attributes for LoadTPUEmbeddingADAMParameters |
LoadTPUEmbeddingADAMParametersGradAccumDebug | Load ADAM embedding parameters with debug support. |
LoadTPUEmbeddingADAMParametersGradAccumDebug.Options | Optional attributes for LoadTPUEmbeddingADAMParametersGradAccumDebug |
LoadTPUEmbeddingCenteredRMSPropParameters | Load centered RMSProp embedding parameters. |
LoadTPUEmbeddingCenteredRMSPropParameters.Options | Optional attributes for LoadTPUEmbeddingCenteredRMSPropParameters |
LoadTPUEmbeddingFTRLParameters | Load FTRL embedding parameters. |
LoadTPUEmbeddingFTRLParameters.Options | Optional attributes for LoadTPUEmbeddingFTRLParameters |
LoadTPUEmbeddingFTRLParametersGradAccumDebug | Load FTRL embedding parameters with debug support. |
LoadTPUEmbeddingFTRLParametersGradAccumDebug.Options | Optional attributes for LoadTPUEmbeddingFTRLParametersGradAccumDebug |
LoadTPUEmbeddingMDLAdagradLightParameters | Load MDL Adagrad Light embedding parameters. |
LoadTPUEmbeddingMDLAdagradLightParameters.Options | Optional attributes for LoadTPUEmbeddingMDLAdagradLightParameters |
LoadTPUEmbeddingMomentumParameters | Load Momentum embedding parameters. |
LoadTPUEmbeddingMomentumParameters.Options | Optional attributes for LoadTPUEmbeddingMomentumParameters |
LoadTPUEmbeddingMomentumParametersGradAccumDebug | Load Momentum embedding parameters with debug support. |
LoadTPUEmbeddingMomentumParametersGradAccumDebug.Options | Optional attributes for LoadTPUEmbeddingMomentumParametersGradAccumDebug |
LoadTPUEmbeddingProximalAdagradParameters | Load proximal Adagrad embedding parameters. |
LoadTPUEmbeddingProximalAdagradParameters.Options | Optional attributes for LoadTPUEmbeddingProximalAdagradParameters |
LoadTPUEmbeddingProximalAdagradParametersGradAccumDebug | Load proximal Adagrad embedding parameters with debug support. |
LoadTPUEmbeddingProximalAdagradParametersGradAccumDebug.Options | Optional attributes for LoadTPUEmbeddingProximalAdagradParametersGradAccumDebug |
LoadTPUEmbeddingProximalYogiParameters | |
LoadTPUEmbeddingProximalYogiParameters.Options | Optional attributes for LoadTPUEmbeddingProximalYogiParameters |
LoadTPUEmbeddingProximalYogiParametersGradAccumDebug | |
LoadTPUEmbeddingProximalYogiParametersGradAccumDebug.Options | Optional attributes for LoadTPUEmbeddingProximalYogiParametersGradAccumDebug |
LoadTPUEmbeddingRMSPropParameters | Load RMSProp embedding parameters. |
LoadTPUEmbeddingRMSPropParameters.Options | Optional attributes for LoadTPUEmbeddingRMSPropParameters |
LoadTPUEmbeddingRMSPropParametersGradAccumDebug | Load RMSProp embedding parameters with debug support. |
LoadTPUEmbeddingRMSPropParametersGradAccumDebug.Options | Optional attributes for LoadTPUEmbeddingRMSPropParametersGradAccumDebug |
LoadTPUEmbeddingStochasticGradientDescentParameters | Load SGD embedding parameters. |
LoadTPUEmbeddingStochasticGradientDescentParameters.Options | Optional attributes for LoadTPUEmbeddingStochasticGradientDescentParameters |
LoadTPUEmbeddingStochasticGradientDescentParametersGradAccumDebug | Load SGD embedding parameters. |
LoadTPUEmbeddingStochasticGradientDescentParametersGradAccumDebug.Options | Optional attributes for LoadTPUEmbeddingStochasticGradientDescentParametersGradAccumDebug |
LocalLinks | Protobuf type tensorflow.LocalLinks |
LocalLinks.Builder | Protobuf type tensorflow.LocalLinks |
LocalLinksOrBuilder | |
LocalResponseNormalization <T extends TNumber > | Local Response Normalization. |
LocalResponseNormalization.Options | Optional attributes for LocalResponseNormalization |
LocalResponseNormalizationGrad <T extends TNumber > | Gradients for Local Response Normalization. |
LocalResponseNormalizationGrad.Options | Optional attributes for LocalResponseNormalizationGrad |
Log <T extends TType > | Computes natural logarithm of x element-wise. |
Log1p <T extends TType > | Computes natural logarithm of (1 + x) element-wise. |
LogCosh | Computes Computes the logarithm of the hyperbolic cosine of the prediction error. |
LogCoshError <T extends TNumber > | A metric that computes the logarithm of the hyperbolic cosine of the prediction error metric between labels and predictions. |
LogicalAnd | Returns the truth value of x AND y element-wise. |
LogicalNot | Returns the truth value of `NOT x` element-wise. |
LogicalOr | Returns the truth value of x OR y element-wise. |
LogMatrixDeterminant <T extends TType > | Computes the sign and the log of the absolute value of the determinant of one or more square matrices. |
LogMemoryProtos | |
LogMessage | Protocol buffer used for logging messages to the events file. |
LogMessage.Builder | Protocol buffer used for logging messages to the events file. |
LogMessage.Level | Protobuf enum tensorflow.LogMessage.Level |
LogMessageOrBuilder | |
LogSoftmax <T extends TNumber > | Computes log softmax activations. |
LogUniformCandidateSampler | Generates labels for candidate sampling with a log-uniform distribution. |
LogUniformCandidateSampler.Options | Optional attributes for LogUniformCandidateSampler |
LongDataBuffer | A DataBuffer of longs. |
LongDataLayout <S extends DataBuffer <?>> | A DataLayout that converts data stored in a buffer to longs. |
LongDenseNdArray | |
LongNdArray | An NdArray of longs. |
LookupTableExport <T extends TType , U extends TType > | Outputs all keys and values in the table. |
LookupTableFind <U extends TType > | Looks up keys in a table, outputs the corresponding values. |
LookupTableImport | Replaces the contents of the table with the specified keys and values. |
LookupTableInsert | Updates the table to associates keys with values. |
LookupTableRemove | Removes keys and its associated values from a table. |
LookupTableSize | Computes the number of elements in the given table. |
LoopCond | Forwards the input to the output. |
خسارة | |
خسائر | Built-in loss functions. |
LossesHelper | These are helper methods for Losses and Metrics and will be module private when Java modularity is applied to TensorFlow Java. |
LossMetric <T extends TNumber > | Interface for Metrics that wrap Loss functions. |
LossTuple <T extends TNumber > | A helper class for loss methods to return labels, target, and sampleWeights |
أدنى | Converts all uppercase characters into their respective lowercase replacements. |
Lower.Options | Optional attributes for Lower |
LowerBound <U extends TNumber > | Applies lower_bound(sorted_search_values, values) along each row. |
LSTMBlockCell <T extends TNumber > | Computes the LSTM cell forward propagation for 1 time step. |
LSTMBlockCell.Options | Optional attributes for LSTMBlockCell |
LSTMBlockCellGrad <T extends TNumber > | Computes the LSTM cell backward propagation for 1 timestep. |
Lu <T extends TType , U extends TNumber > | Computes the LU decomposition of one or more square matrices. |
م
MachineConfiguration | Protobuf type tensorflow.MachineConfiguration |
MachineConfiguration.Builder | Protobuf type tensorflow.MachineConfiguration |
MachineConfigurationOrBuilder | |
MakeIterator | Makes a new iterator from the given `dataset` and stores it in `iterator`. |
MakeUnique | Make all elements in the non-Batch dimension unique, but \"close\" to their initial value. |
MapClear | Op removes all elements in the underlying container. |
MapClear.Options | Optional attributes for MapClear |
MapDataset | |
MapIncompleteSize | Op returns the number of incomplete elements in the underlying container. |
MapIncompleteSize.Options | Optional attributes for MapIncompleteSize |
MapIterator | |
MapOptional | |
MapPeek | Op peeks at the values at the specified key. |
MapPeek.Options | Optional attributes for MapPeek |
MapSize | Op returns the number of elements in the underlying container. |
MapSize.Options | Optional attributes for MapSize |
MapStage | Stage (key, values) in the underlying container which behaves like a hashtable. |
MapStage.Options | Optional attributes for MapStage |
MapUnstage | Op removes and returns the values associated with the key from the underlying container. |
MapUnstage.Options | Optional attributes for MapUnstage |
MapUnstageNoKey | Op removes and returns a random (key, value) from the underlying container. |
MapUnstageNoKey.Options | Optional attributes for MapUnstageNoKey |
MatchingFiles | Returns the set of files matching one or more glob patterns. |
MatchingFilesDataset | |
MatchingFilesDataset | |
MatMul <T extends TType > | Multiply the matrix "a" by the matrix "b". |
MatMul.Options | Optional attributes for MatMul |
MatrixDiag <T extends TType > | Returns a batched diagonal tensor with given batched diagonal values. |
MatrixDiagPart <T extends TType > | Returns the batched diagonal part of a batched tensor. |
MatrixDiagPartV3 <T extends TType > | Returns the batched diagonal part of a batched tensor. |
MatrixDiagPartV3.Options | Optional attributes for MatrixDiagPartV3 |
MatrixDiagV3 <T extends TType > | Returns a batched diagonal tensor with given batched diagonal values. |
MatrixDiagV3.Options | Optional attributes for MatrixDiagV3 |
MatrixLogarithm <T extends TType > | Computes the matrix logarithm of one or more square matrices: \\(log(exp(A)) = A\\) This op is only defined for complex matrices. |
MatrixSetDiag <T extends TType > | Returns a batched matrix tensor with new batched diagonal values. |
MatrixSetDiag.Options | Optional attributes for MatrixSetDiag |
MatrixSolveLs <T extends TType > | Solves one or more linear least-squares problems. |
MatrixSolveLs.Options | Optional attributes for MatrixSolveLs |
Max <T extends TType > | Computes the maximum of elements across dimensions of a tensor. |
Max.Options | Optional attributes for Max |
Maximum <T extends TNumber > | Returns the max of x and y (ie |
MaxIntraOpParallelismDataset | Creates a dataset that overrides the maximum intra-op parallelism. |
MaxIntraOpParallelismDataset | Creates a dataset that overrides the maximum intra-op parallelism. |
MaxNorm | Constrains the weights incident to each hidden unit to have a norm less than or equal to a desired value. |
MaxPool <T extends TType > | Performs max pooling on the input. |
MaxPool.Options | Optional attributes for MaxPool |
MaxPool3d <T extends TNumber > | Performs 3D max pooling on the input. |
MaxPool3d.Options | Optional attributes for MaxPool3d |
MaxPool3dGrad <U extends TNumber > | Computes gradients of 3D max pooling function. |
MaxPool3dGrad.Options | Optional attributes for MaxPool3dGrad |
MaxPool3dGradGrad <T extends TNumber > | Computes second-order gradients of the maxpooling function. |
MaxPool3dGradGrad.Options | Optional attributes for MaxPool3dGradGrad |
MaxPoolGrad <T extends TNumber > | Computes gradients of the maxpooling function. |
MaxPoolGrad.Options | Optional attributes for MaxPoolGrad |
MaxPoolGradGrad <T extends TNumber > | Computes second-order gradients of the maxpooling function. |
MaxPoolGradGrad.Options | Optional attributes for MaxPoolGradGrad |
MaxPoolGradGradWithArgmax <T extends TNumber > | Computes second-order gradients of the maxpooling function. |
MaxPoolGradGradWithArgmax.Options | Optional attributes for MaxPoolGradGradWithArgmax |
MaxPoolGradWithArgmax <T extends TNumber > | Computes gradients of the maxpooling function. |
MaxPoolGradWithArgmax.Options | Optional attributes for MaxPoolGradWithArgmax |
MaxPoolWithArgmax <T extends TNumber , U extends TNumber > | Performs max pooling on the input and outputs both max values and indices. |
MaxPoolWithArgmax.Options | Optional attributes for MaxPoolWithArgmax |
Mean <T extends TNumber > | A metric that that implements a weighted mean WEIGHTED_MEAN |
Mean <T extends TType > | Computes the mean of elements across dimensions of a tensor. |
Mean.Options | Optional attributes for Mean |
MeanAbsoluteError | Computes the mean of absolute difference between labels and predictions. |
MeanAbsoluteError <T extends TNumber > | A metric that computes the mean of absolute difference between labels and predictions. |
MeanAbsolutePercentageError | Computes the mean absolute percentage error between labels and predictions. |
MeanAbsolutePercentageError <T extends TNumber > | A metric that computes the mean of absolute difference between labels and predictions. |
MeanMetricWrapper <T extends TNumber > | A class that bridges a stateless loss function with the Mean metric using a reduction of WEIGHTED_MEAN . |
MeanSquaredError | Computes the mean of squares of errors between labels and predictions. |
MeanSquaredError <T extends TNumber > | A metric that computes the mean of absolute difference between labels and predictions. |
MeanSquaredLogarithmicError | Computes the mean squared logarithmic errors between labels and predictions. |
MeanSquaredLogarithmicError <T extends TNumber > | A metric that computes the mean of absolute difference between labels and predictions. |
MemAllocatorStats | Some of the data from AllocatorStatsProtobuf type tensorflow.MemAllocatorStats |
MemAllocatorStats.Builder | Some of the data from AllocatorStatsProtobuf type tensorflow.MemAllocatorStats |
MemAllocatorStatsOrBuilder | |
MemChunk | Protobuf type tensorflow.MemChunk |
MemChunk.Builder | Protobuf type tensorflow.MemChunk |
MemChunkOrBuilder | |
MemmappedFileSystemDirectory | A directory of regions in a memmapped file. |
MemmappedFileSystemDirectory.Builder | A directory of regions in a memmapped file. |
MemmappedFileSystemDirectoryElement | A message that describes one region of memmapped file. |
MemmappedFileSystemDirectoryElement.Builder | A message that describes one region of memmapped file. |
MemmappedFileSystemDirectoryElementOrBuilder | |
MemmappedFileSystemDirectoryOrBuilder | |
MemmappedFileSystemProtos | |
MemoryDump | Protobuf type tensorflow.MemoryDump |
MemoryDump.Builder | Protobuf type tensorflow.MemoryDump |
MemoryDumpOrBuilder | |
MemoryInfo | Protobuf type tensorflow.MemoryInfo |
MemoryInfo.Builder | Protobuf type tensorflow.MemoryInfo |
MemoryInfoOrBuilder | |
MemoryLogRawAllocation | Protobuf type tensorflow.MemoryLogRawAllocation |
MemoryLogRawAllocation.Builder | Protobuf type tensorflow.MemoryLogRawAllocation |
MemoryLogRawAllocationOrBuilder | |
MemoryLogRawDeallocation | Protobuf type tensorflow.MemoryLogRawDeallocation |
MemoryLogRawDeallocation.Builder | Protobuf type tensorflow.MemoryLogRawDeallocation |
MemoryLogRawDeallocationOrBuilder | |
MemoryLogStep | Protobuf type tensorflow.MemoryLogStep |
MemoryLogStep.Builder | Protobuf type tensorflow.MemoryLogStep |
MemoryLogStepOrBuilder | |
MemoryLogTensorAllocation | Protobuf type tensorflow.MemoryLogTensorAllocation |
MemoryLogTensorAllocation.Builder | Protobuf type tensorflow.MemoryLogTensorAllocation |
MemoryLogTensorAllocationOrBuilder | |
MemoryLogTensorDeallocation | Protobuf type tensorflow.MemoryLogTensorDeallocation |
MemoryLogTensorDeallocation.Builder | Protobuf type tensorflow.MemoryLogTensorDeallocation |
MemoryLogTensorDeallocationOrBuilder | |
MemoryLogTensorOutput | Protobuf type tensorflow.MemoryLogTensorOutput |
MemoryLogTensorOutput.Builder | Protobuf type tensorflow.MemoryLogTensorOutput |
MemoryLogTensorOutputOrBuilder | |
MemoryStats | For memory tracking. |
MemoryStats.Builder | For memory tracking. |
MemoryStatsOrBuilder | |
Merge <T extends TType > | Forwards the value of an available tensor from `inputs` to `output`. |
MergeSummary | Merges summaries. |
MergeV2Checkpoints | V2 format specific: merges the metadata files of sharded checkpoints. |
MergeV2Checkpoints.Options | Optional attributes for MergeV2Checkpoints |
MetaGraphDef | NOTE: This protocol buffer is evolving, and will go through revisions in the coming months. |
MetaGraphDef.Builder | NOTE: This protocol buffer is evolving, and will go through revisions in the coming months. |
MetaGraphDef.MetaInfoDef | Meta information regarding the graph to be exported. |
MetaGraphDef.MetaInfoDef.Builder | Meta information regarding the graph to be exported. |
MetaGraphDef.MetaInfoDefOrBuilder | |
MetaGraphDefOrBuilder | |
MetaGraphProtos | |
Metric <T extends TNumber > | Base class for Metrics |
MetricEntry | Protobuf type tensorflow.MetricEntry |
MetricEntry.Builder | Protobuf type tensorflow.MetricEntry |
MetricEntryOrBuilder | |
MetricReduction | Defines the different types of metric reductions |
المقاييس | Helper class with built-in metrics functions. |
MetricsHelper | These are helper methods for Metrics and will be module private when Java modularity is applied to TensorFlow Java. |
Mfcc | Transforms a spectrogram into a form that's useful for speech recognition. |
Mfcc.Options | Optional attributes for Mfcc |
Min <T extends TType > | Computes the minimum of elements across dimensions of a tensor. |
Min.Options | Optional attributes for Min |
Minimum <T extends TNumber > | Returns the min of x and y (ie |
MinMaxNorm | Constrains the weights to have the norm between a lower bound and an upper bound. |
MirrorPad <T extends TType > | Pads a tensor with mirrored values. |
MirrorPadGrad <T extends TType > | Gradient op for `MirrorPad` op. |
MiscDataBufferFactory | Factory of miscellaneous data buffers |
MlirPassthroughOp | Wraps an arbitrary MLIR computation expressed as a module with a main() function. |
Mod <T extends TNumber > | Returns element-wise remainder of division. |
ModelDataset | Identity transformation that models performance. |
ModelDataset.Options | Optional attributes for ModelDataset |
دَفعَة | Stochastic gradient descent plus momentum, either nesterov or traditional. |
Mul <T extends TType > | Returns x * y element-wise. |
MulNoNan <T extends TType > | Returns x * y element-wise. |
MultiDeviceIterator | Creates a MultiDeviceIterator resource. |
MultiDeviceIteratorFromStringHandle | Generates a MultiDeviceIterator resource from its provided string handle. |
MultiDeviceIteratorFromStringHandle.Options | Optional attributes for MultiDeviceIteratorFromStringHandle |
MultiDeviceIteratorGetNextFromShard | Gets next element for the provided shard number. |
MultiDeviceIteratorInit | Initializes the multi device iterator with the given dataset. |
MultiDeviceIteratorToStringHandle | Produces a string handle for the given MultiDeviceIterator. |
Multinomial <U extends TNumber > | Draws samples from a multinomial distribution. |
Multinomial.Options | Optional attributes for Multinomial |
MutableDenseHashTable | Creates an empty hash table that uses tensors as the backing store. |
MutableDenseHashTable.Options | Optional attributes for MutableDenseHashTable |
MutableHashTable | Creates an empty hash table. |
MutableHashTable.Options | Optional attributes for MutableHashTable |
MutableHashTableOfTensors | Creates an empty hash table. |
MutableHashTableOfTensors.Options | Optional attributes for MutableHashTableOfTensors |
موتيكس | Creates a Mutex resource that can be locked by `MutexLock`. |
Mutex.Options | Optional attributes for Mutex |
MutexLock | Locks a mutex resource. |
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Nadam | Nadam Optimizer that implements the NAdam algorithm. |
NameAttrList | A list of attr names and their values. |
NameAttrList.Builder | A list of attr names and their values. |
NameAttrListOrBuilder | |
NamedDevice | Protobuf type tensorflow.NamedDevice |
NamedDevice.Builder | Protobuf type tensorflow.NamedDevice |
NamedDeviceOrBuilder | |
NamedTensorProto | A pair of tensor name and tensor values. |
NamedTensorProto.Builder | A pair of tensor name and tensor values. |
NamedTensorProtoOrBuilder | |
NamedTensorProtos | |
NamedTupleValue | Represents Python's namedtuple. |
NamedTupleValue.Builder | Represents Python's namedtuple. |
NamedTupleValueOrBuilder | |
NcclAllReduce <T extends TNumber > | Outputs a tensor containing the reduction across all input tensors. |
NcclAllReduce <T extends TNumber > | Outputs a tensor containing the reduction across all input tensors. |
NcclBroadcast <T extends TNumber > | Sends `input` to all devices that are connected to the output. |
NcclBroadcast <T extends TNumber > | Sends `input` to all devices that are connected to the output. |
NcclReduce <T extends TNumber > | Reduces `input` from `num_devices` using `reduction` to a single device. |
NcclReduce <T extends TNumber > | Reduces `input` from `num_devices` using `reduction` to a single device. |
NdArray <T> | A data structure of N-dimensions. |
NdArrays | Utility class for instantiating NdArray objects. |
NdArraySequence <T extends NdArray <?>> | A sequence of elements of an N-dimensional array. |
Ndtri <T extends TNumber > | |
NearestNeighbors | Selects the k nearest centers for each point. |
Neg <T extends TType > | Computes numerical negative value element-wise. |
NegTrain | Training via negative sampling. |
NextAfter <T extends TNumber > | Returns the next representable value of `x1` in the direction of `x2`, element-wise. |
NextIteration <T extends TType > | Makes its input available to the next iteration. |
NioDataBufferFactory | Factory of JDK NIO-based data buffers |
NodeDef | Protobuf type tensorflow.NodeDef |
NodeDef.Builder | Protobuf type tensorflow.NodeDef |
NodeDef.ExperimentalDebugInfo | Protobuf type tensorflow.NodeDef.ExperimentalDebugInfo |
NodeDef.ExperimentalDebugInfo.Builder | Protobuf type tensorflow.NodeDef.ExperimentalDebugInfo |
NodeDef.ExperimentalDebugInfoOrBuilder | |
NodeDefOrBuilder | |
NodeExecStats | Time/size stats recorded for a single execution of a graph node. |
NodeExecStats.Builder | Time/size stats recorded for a single execution of a graph node. |
NodeExecStatsOrBuilder | |
NodeOutput | Output sizes recorded for a single execution of a graph node. |
NodeOutput.Builder | Output sizes recorded for a single execution of a graph node. |
NodeOutputOrBuilder | |
NodeProto | |
NonDeterministicInts <U extends TType > | Non-deterministically generates some integers. |
NoneValue | Represents None. |
NoneValue.Builder | Represents None. |
NoneValueOrBuilder | |
NonMaxSuppression <T extends TNumber > | 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. |
NonMaxSuppression.Options | Optional attributes for NonMaxSuppression |
NonMaxSuppressionWithOverlaps | Greedily selects a subset of bounding boxes in descending order of score, pruning away boxes that have high overlaps with previously selected boxes. |
NonNeg | Constrains the weights to be non-negative. |
NonSerializableDataset | |
NonSerializableDataset | |
NoOp | Does nothing. |
NotBroadcastableException | Exception that indicates that static shapes are not able to broadcast among each other during arithmetic operations. |
NotEqual | Returns the truth value of (x != y) element-wise. |
NotEqual.Options | Optional attributes for NotEqual |
NthElement <T extends TNumber > | Finds values of the `n`-th order statistic for the last dimension. |
NthElement.Options | Optional attributes for NthElement |
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OneHot <U extends TType > | Returns a one-hot tensor. |
OneHot.Options | Optional attributes for OneHot |
Ones <T extends TType > | Initializer that generates tensors initialized to 1. |
Ones <T extends TType > | An operator creating a constant initialized with ones of the shape given by `dims`. |
OnesLike <T extends TType > | Returns a tensor of ones with the same shape and type as x. |
مرجع سابق | A logical unit of computation. |
OpDef | Defines an operation. |
OpDef.ArgDef | For describing inputs and outputs. |
OpDef.ArgDef.Builder | For describing inputs and outputs. |
OpDef.ArgDefOrBuilder | |
OpDef.AttrDef | Description of the graph-construction-time configuration of this Op. |
OpDef.AttrDef.Builder | Description of the graph-construction-time configuration of this Op. |
OpDef.AttrDefOrBuilder | |
OpDef.Builder | Defines an operation. |
OpDefOrBuilder | |
OpDefProtos | |
OpDeprecation | Information about version-dependent deprecation of an opProtobuf type tensorflow.OpDeprecation |
OpDeprecation.Builder | Information about version-dependent deprecation of an opProtobuf type tensorflow.OpDeprecation |
OpDeprecationOrBuilder | |
Operand <T extends TType > | Interface implemented by operands of a TensorFlow operation. |
Operands | Utilities for manipulating operand related types and lists. |
عملية | Performs computation on Tensors. |
OperationBuilder | A builder for Operation s. |
المشغل | Annotation used by classes to make TensorFlow operations conveniently accessible via org.tensorflow.op.Ops or one of its groups. |
OpList | A collection of OpDefsProtobuf type tensorflow.OpList |
OpList.Builder | A collection of OpDefsProtobuf type tensorflow.OpList |
OpListOrBuilder | |
OptimizeDataset | Creates a dataset by applying optimizations to `input_dataset`. |
OptimizeDataset.Options | Optional attributes for OptimizeDataset |
OptimizeDatasetV2 | Creates a dataset by applying related optimizations to `input_dataset`. |
OptimizeDatasetV2.Options | Optional attributes for OptimizeDatasetV2 |
Optimizer | Base class for gradient optimizers. |
Optimizer.GradAndVar <T extends TType > | A class that holds a paired gradient and variable. |
Optimizer.Options | Optional attributes for Optimizer |
OptimizerOptions | Options passed to the graph optimizerProtobuf type tensorflow.OptimizerOptions |
OptimizerOptions.Builder | Options passed to the graph optimizerProtobuf type tensorflow.OptimizerOptions |
OptimizerOptions.GlobalJitLevel | Control the use of the compiler/jit. |
OptimizerOptions.Level | Optimization levelProtobuf enum tensorflow.OptimizerOptions.Level |
OptimizerOptionsOrBuilder | |
Optimizers | Enumerator used to create a new Optimizer with default parameters. |
OptionalFromValue | Constructs an Optional variant from a tuple of tensors. |
OptionalGetValue | Returns the value stored in an Optional variant or raises an error if none exists. |
OptionalHasValue | Returns true if and only if the given Optional variant has a value. |
OptionalNone | Creates an Optional variant with no value. |
OrderedMapClear | Op removes all elements in the underlying container. |
OrderedMapClear.Options | Optional attributes for OrderedMapClear |
OrderedMapIncompleteSize | Op returns the number of incomplete elements in the underlying container. |
OrderedMapIncompleteSize.Options | Optional attributes for OrderedMapIncompleteSize |
OrderedMapPeek | Op peeks at the values at the specified key. |
OrderedMapPeek.Options | Optional attributes for OrderedMapPeek |
OrderedMapSize | Op returns the number of elements in the underlying container. |
OrderedMapSize.Options | Optional attributes for OrderedMapSize |
OrderedMapStage | Stage (key, values) in the underlying container which behaves like a ordered associative container. |
OrderedMapStage.Options | Optional attributes for OrderedMapStage |
OrderedMapUnstage | Op removes and returns the values associated with the key from the underlying container. |
OrderedMapUnstage.Options | Optional attributes for OrderedMapUnstage |
OrderedMapUnstageNoKey | Op removes and returns the (key, value) element with the smallest key from the underlying container. |
OrderedMapUnstageNoKey.Options | Optional attributes for OrderedMapUnstageNoKey |
OrdinalSelector | A TPU core selector Op. |
Orthogonal <T extends TFloating > | Initializer that generates an orthogonal matrix. |
OutfeedDequeue <T extends TType > | Retrieves a single tensor from the computation outfeed. |
OutfeedDequeue.Options | Optional attributes for OutfeedDequeue |
OutfeedDequeueTuple | Retrieve multiple values from the computation outfeed. |
OutfeedDequeueTuple.Options | Optional attributes for OutfeedDequeueTuple |
OutfeedDequeueTupleV2 | Retrieve multiple values from the computation outfeed. |
OutfeedDequeueV2 <T extends TType > | 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. |
Output <T extends TType > | A symbolic handle to a tensor produced by an Operation . |
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Pad <T extends TType > | Pads a tensor. |
Pad <T extends TType > | Wraps the XLA Pad operator, documented at https://www.tensorflow.org/performance/xla/operation_semantics#pad . |
PaddedBatchDataset | Creates a dataset that batches and pads `batch_size` elements from the input. |
PaddedBatchDataset.Options | Optional attributes for PaddedBatchDataset |
PaddingFifoQueue | A queue that produces elements in first-in first-out order. |
PaddingFifoQueue.Options | Optional attributes for PaddingFifoQueue |
PairValue | Represents a (key, value) pair. |
PairValue.Builder | Represents a (key, value) pair. |
PairValueOrBuilder | |
ParallelConcat <T extends TType > | Concatenates a list of `N` tensors along the first dimension. |
ParallelDynamicStitch <T extends TType > | Interleave the values from the `data` tensors into a single tensor. |
ParameterizedTruncatedNormal <U extends TNumber > | Outputs random values from a normal distribution. |
ParameterizedTruncatedNormal.Options | Optional attributes for ParameterizedTruncatedNormal |
ParseExample | Transforms a vector of tf.Example protos (as strings) into typed tensors. |
ParseExampleDataset | Transforms `input_dataset` containing `Example` protos as vectors of DT_STRING into a dataset of `Tensor` or `SparseTensor` objects representing the parsed features. |
ParseExampleDataset.Options | Optional attributes for ParseExampleDataset |
ParseSequenceExample | Transforms a vector of tf.io.SequenceExample protos (as strings) into typed tensors. |
ParseSequenceExample.Options | Optional attributes for ParseSequenceExample |
ParseSingleExample | Transforms a tf.Example proto (as a string) into typed tensors. |
ParseSingleSequenceExample | Transforms a scalar brain.SequenceExample proto (as strings) into typed tensors. |
ParseSingleSequenceExample.Options | Optional attributes for ParseSingleSequenceExample |
ParseTensor <T extends TType > | Transforms a serialized tensorflow.TensorProto proto into a Tensor. |
PartitionedInput <T extends TType > | An op that groups a list of partitioned inputs together. |
PartitionedInput.Options | Optional attributes for PartitionedInput |
PartitionedOutput <T extends TType > | An op that demultiplexes a tensor to be sharded by XLA to a list of partitioned outputs outside the XLA computation. |
PartitionedOutput.Options | Optional attributes for PartitionedOutput |
Placeholder <T extends TType > | A placeholder op for a value that will be fed into the computation. |
Placeholder.Options | Optional attributes for Placeholder |
PlaceholderWithDefault <T extends TType > | A placeholder op that passes through `input` when its output is not fed. |
PlatformInfo | Protobuf type tensorflow.PlatformInfo |
PlatformInfo.Builder | Protobuf type tensorflow.PlatformInfo |
PlatformInfoOrBuilder | |
بواسون | Computes the Poisson loss between labels and predictions. |
Poisson <T extends TNumber > | A metric that computes the poisson loss metric between labels and predictions. |
Polygamma <T extends TNumber > | Compute the polygamma function \\(\psi^{(n)}(x)\\). |
PopulationCount | Computes element-wise population count (aka |
PositionIterator | |
Pow <T extends TType > | Computes the power of one value to another. |
PrefetchDataset | Creates a dataset that asynchronously prefetches elements from `input_dataset`. |
PrefetchDataset.Options | Optional attributes for PrefetchDataset |
Prelinearize | An op which linearizes one Tensor value to an opaque variant tensor. |
Prelinearize.Options | Optional attributes for Prelinearize |
PrelinearizeTuple | An op which linearizes multiple Tensor values to an opaque variant tensor. |
PrelinearizeTuple.Options | Optional attributes for PrelinearizeTuple |
PreventGradient <T extends TType > | An identity op that triggers an error if a gradient is requested. |
PreventGradient.Options | Optional attributes for PreventGradient |
مطبعة | Prints a string scalar. |
Print.Options | Optional attributes for Print |
PriorityQueue | A queue that produces elements sorted by the first component value. |
PriorityQueue.Options | Optional attributes for PriorityQueue |
PrivateThreadPoolDataset | Creates a dataset that uses a custom thread pool to compute `input_dataset`. |
PrivateThreadPoolDataset | Creates a dataset that uses a custom thread pool to compute `input_dataset`. |
Prod <T extends TType > | Computes the product of elements across dimensions of a tensor. |
Prod.Options | Optional attributes for Prod |
ProfileOptions | Next ID: 11Protobuf type tensorflow.ProfileOptions |
ProfileOptions.Builder | Next ID: 11Protobuf type tensorflow.ProfileOptions |
ProfileOptions.DeviceType | Protobuf enum tensorflow.ProfileOptions.DeviceType |
ProfileOptionsOrBuilder | |
ProfilerOptionsProtos |
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Qr <T extends TType > | Computes the QR decompositions of one or more matrices. |
Qr.Options | Optional attributes for Qr |
Quantize <T extends TType > | Quantize the 'input' tensor of type float to 'output' tensor of type 'T'. |
Quantize.Options | Optional attributes for Quantize |
QuantizeAndDequantize <T extends TNumber > | Quantizes then dequantizes a tensor. |
QuantizeAndDequantize.Options | Optional attributes for QuantizeAndDequantize |
QuantizeAndDequantizeV3 <T extends TNumber > | Quantizes then dequantizes a tensor. |
QuantizeAndDequantizeV3.Options | Optional attributes for QuantizeAndDequantizeV3 |
QuantizeAndDequantizeV4 <T extends TNumber > | Returns the gradient of `quantization.QuantizeAndDequantizeV4`. |
QuantizeAndDequantizeV4.Options | Optional attributes for QuantizeAndDequantizeV4 |
QuantizeAndDequantizeV4Grad <T extends TNumber > | Returns the gradient of `QuantizeAndDequantizeV4`. |
QuantizeAndDequantizeV4Grad.Options | Optional attributes for QuantizeAndDequantizeV4Grad |
QuantizedAdd <V extends TType > | Returns x + y element-wise, working on quantized buffers. |
QuantizedAvgPool <T extends TType > | Produces the average pool of the input tensor for quantized types. |
QuantizedBatchNormWithGlobalNormalization <U extends TType > | Quantized Batch normalization. |
QuantizedBiasAdd <V extends TType > | Adds Tensor 'bias' to Tensor 'input' for Quantized types. |
QuantizedConcat <T extends TType > | Concatenates quantized tensors along one dimension. |
QuantizedConv2d <V extends TType > | Computes a 2D convolution given quantized 4D input and filter tensors. |
QuantizedConv2d.Options | Optional attributes for QuantizedConv2d |
QuantizedConv2DAndRelu <V extends TType > | |
QuantizedConv2DAndRelu.Options | Optional attributes for QuantizedConv2DAndRelu |
QuantizedConv2DAndReluAndRequantize <V extends TType > | |
QuantizedConv2DAndReluAndRequantize.Options | Optional attributes for QuantizedConv2DAndReluAndRequantize |
QuantizedConv2DAndRequantize <V extends TType > | |
QuantizedConv2DAndRequantize.Options | Optional attributes for QuantizedConv2DAndRequantize |
QuantizedConv2DPerChannel <V extends TType > | Computes QuantizedConv2D per channel. |
QuantizedConv2DPerChannel.Options | Optional attributes for QuantizedConv2DPerChannel |
QuantizedConv2DWithBias <V extends TType > | |
QuantizedConv2DWithBias.Options | Optional attributes for QuantizedConv2DWithBias |
QuantizedConv2DWithBiasAndRelu <V extends TType > | |
QuantizedConv2DWithBiasAndRelu.Options | Optional attributes for QuantizedConv2DWithBiasAndRelu |
QuantizedConv2DWithBiasAndReluAndRequantize <W extends TType > | |
QuantizedConv2DWithBiasAndReluAndRequantize.Options | Optional attributes for QuantizedConv2DWithBiasAndReluAndRequantize |
QuantizedConv2DWithBiasAndRequantize <W extends TType > | |
QuantizedConv2DWithBiasAndRequantize.Options | Optional attributes for QuantizedConv2DWithBiasAndRequantize |
QuantizedConv2DWithBiasSignedSumAndReluAndRequantize <X extends TType > | |
QuantizedConv2DWithBiasSignedSumAndReluAndRequantize.Options | Optional attributes for QuantizedConv2DWithBiasSignedSumAndReluAndRequantize |
QuantizedConv2DWithBiasSumAndRelu <V extends TType > | |
QuantizedConv2DWithBiasSumAndRelu.Options | Optional attributes for QuantizedConv2DWithBiasSumAndRelu |
QuantizedConv2DWithBiasSumAndReluAndRequantize <X extends TType > | |
QuantizedConv2DWithBiasSumAndReluAndRequantize.Options | Optional attributes for QuantizedConv2DWithBiasSumAndReluAndRequantize |
QuantizedDepthwiseConv2D <V extends TType > | Computes quantized depthwise Conv2D. |
QuantizedDepthwiseConv2D.Options | Optional attributes for QuantizedDepthwiseConv2D |
QuantizedDepthwiseConv2DWithBias <V extends TType > | Computes quantized depthwise Conv2D with Bias. |
QuantizedDepthwiseConv2DWithBias.Options | Optional attributes for QuantizedDepthwiseConv2DWithBias |
QuantizedDepthwiseConv2DWithBiasAndRelu <V extends TType > | Computes quantized depthwise Conv2D with Bias and Relu. |
QuantizedDepthwiseConv2DWithBiasAndRelu.Options | Optional attributes for QuantizedDepthwiseConv2DWithBiasAndRelu |
QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize <W extends TType > | Computes quantized depthwise Conv2D with Bias, Relu and Requantize. |
QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize.Options | Optional attributes for QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize |
QuantizedInstanceNorm <T extends TType > | Quantized Instance normalization. |
QuantizedInstanceNorm.Options | Optional attributes for QuantizedInstanceNorm |
QuantizedMatMul <V extends TType > | Perform a quantized matrix multiplication of `a` by the matrix `b`. |
QuantizedMatMul.Options | Optional attributes for QuantizedMatMul |
QuantizedMatMulWithBias <W extends TType > | Performs a quantized matrix multiplication of `a` by the matrix `b` with bias add. |
QuantizedMatMulWithBias.Options | Optional attributes for QuantizedMatMulWithBias |
QuantizedMatMulWithBiasAndDequantize <W extends TNumber > | |
QuantizedMatMulWithBiasAndDequantize.Options | Optional attributes for QuantizedMatMulWithBiasAndDequantize |
QuantizedMatMulWithBiasAndRelu <V extends TType > | Perform a quantized matrix multiplication of `a` by the matrix `b` with bias add and relu fusion. |
QuantizedMatMulWithBiasAndRelu.Options | Optional attributes for QuantizedMatMulWithBiasAndRelu |
QuantizedMatMulWithBiasAndReluAndRequantize <W extends TType > | Perform a quantized matrix multiplication of `a` by the matrix `b` with bias add and relu and requantize fusion. |
QuantizedMatMulWithBiasAndReluAndRequantize.Options | Optional attributes for QuantizedMatMulWithBiasAndReluAndRequantize |
QuantizedMatMulWithBiasAndRequantize <W extends TType > | |
QuantizedMatMulWithBiasAndRequantize.Options | Optional attributes for QuantizedMatMulWithBiasAndRequantize |
QuantizedMaxPool <T extends TType > | Produces the max pool of the input tensor for quantized types. |
QuantizedMul <V extends TType > | Returns x * y element-wise, working on quantized buffers. |
QuantizeDownAndShrinkRange <U extends TType > | Convert the quantized 'input' tensor into a lower-precision 'output', using the actual distribution of the values to maximize the usage of the lower bit depth and adjusting the output min and max ranges accordingly. |
QuantizedRelu <U extends TType > | Computes Quantized Rectified Linear: `max(features, 0)` |
QuantizedRelu6 <U extends TType > | Computes Quantized Rectified Linear 6: `min(max(features, 0), 6)` |
QuantizedReluX <U extends TType > | Computes Quantized Rectified Linear X: `min(max(features, 0), max_value)` |
QuantizedReshape <T extends TType > | Reshapes a quantized tensor as per the Reshape op. |
QuantizedResizeBilinear <T extends TType > | Resize quantized `images` to `size` using quantized bilinear interpolation. |
QuantizedResizeBilinear.Options | Optional attributes for QuantizedResizeBilinear |
QueueClose | Closes the given queue. |
QueueClose.Options | Optional attributes for QueueClose |
QueueDequeue | Dequeues a tuple of one or more tensors from the given queue. |
QueueDequeue.Options | Optional attributes for QueueDequeue |
QueueDequeueMany | Dequeues `n` tuples of one or more tensors from the given queue. |
QueueDequeueMany.Options | Optional attributes for QueueDequeueMany |
QueueDequeueUpTo | Dequeues `n` tuples of one or more tensors from the given queue. |
QueueDequeueUpTo.Options | Optional attributes for QueueDequeueUpTo |
QueueEnqueue | Enqueues a tuple of one or more tensors in the given queue. |
QueueEnqueue.Options | Optional attributes for QueueEnqueue |
QueueEnqueueMany | Enqueues zero or more tuples of one or more tensors in the given queue. |
QueueEnqueueMany.Options | Optional attributes for QueueEnqueueMany |
QueueIsClosed | Returns true if queue is closed. |
QueueRunnerDef | Protocol buffer representing a QueueRunner. |
QueueRunnerDef.Builder | Protocol buffer representing a QueueRunner. |
QueueRunnerDefOrBuilder | |
QueueRunnerProtos | |
QueueSize | Computes the number of elements in the given queue. |
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RaggedBincount <U extends TNumber > | Counts the number of occurrences of each value in an integer array. |
RaggedBincount.Options | Optional attributes for RaggedBincount |
RaggedCountSparseOutput <U extends TNumber > | Performs sparse-output bin counting for a ragged tensor input. |
RaggedCountSparseOutput.Options | Optional attributes for RaggedCountSparseOutput |
RaggedCross <T extends TType , U extends TNumber > | Generates a feature cross from a list of tensors, and returns it as a RaggedTensor. |
RaggedGather <T extends TNumber , U extends TType > | Gather ragged slices from `params` axis `0` according to `indices`. |
RaggedRange <U extends TNumber , T extends TNumber > | Returns a `RaggedTensor` containing the specified sequences of numbers. |
RaggedTensorFromVariant <U extends TNumber , T extends TType > | Decodes a `variant` Tensor into a `RaggedTensor`. |
RaggedTensorToSparse <U extends TType > | Converts a `RaggedTensor` into a `SparseTensor` with the same values. |
RaggedTensorToTensor <U extends TType > | Create a dense tensor from a ragged tensor, possibly altering its shape. |
RaggedTensorToVariant | Encodes a `RaggedTensor` into a `variant` Tensor. |
RaggedTensorToVariantGradient <U extends TType > | Helper used to compute the gradient for `RaggedTensorToVariant`. |
RandomCrop <T extends TNumber > | Randomly crop `image`. |
RandomCrop.Options | Optional attributes for RandomCrop |
RandomDataset | Creates a Dataset that returns pseudorandom numbers. |
RandomDataset | Creates a Dataset that returns pseudorandom numbers. |
RandomGamma <U extends TNumber > | Outputs random values from the Gamma distribution(s) described by alpha. |
RandomGamma.Options | Optional attributes for RandomGamma |
RandomGammaGrad <T extends TNumber > | Computes the derivative of a Gamma random sample wrt |
RandomNormal <T extends TFloating > | Initializer that generates tensors with a normal distribution. |
RandomPoisson <V extends TNumber > | Outputs random values from the Poisson distribution(s) described by rate. |
RandomPoisson.Options | Optional attributes for RandomPoisson |
RandomShuffle <T extends TType > | Randomly shuffles a tensor along its first dimension. |
RandomShuffle.Options | Optional attributes for RandomShuffle |
RandomShuffleQueue | A queue that randomizes the order of elements. |
RandomShuffleQueue.Options | Optional attributes for RandomShuffleQueue |
RandomStandardNormal <U extends TNumber > | Outputs random values from a normal distribution. |
RandomStandardNormal.Options | Optional attributes for RandomStandardNormal |
RandomUniform <T extends TNumber > | Initializer that generates tensors with a uniform distribution. |
RandomUniform <U extends TNumber > | Outputs random values from a uniform distribution. |
RandomUniform.Options | Optional attributes for RandomUniform |
RandomUniformInt <U extends TNumber > | Outputs random integers from a uniform distribution. |
RandomUniformInt.Options | Optional attributes for RandomUniformInt |
Range <T extends TNumber > | Creates a sequence of numbers. |
RangeDataset | Creates a dataset with a range of values. |
رتبة | Returns the rank of a tensor. |
RawDataBufferFactory | Factory of raw data buffers |
RawOp | A base class for Op implementations that are backed by a single Operation . |
RawTensor | A tensor which memory has not been mapped to a data space directly accessible from the JVM. |
ReaderBaseProtos | |
ReaderBaseState | For serializing and restoring the state of ReaderBase, see reader_base.h for details. |
ReaderBaseState.Builder | For serializing and restoring the state of ReaderBase, see reader_base.h for details. |
ReaderBaseStateOrBuilder | |
ReaderNumRecordsProduced | Returns the number of records this Reader has produced. |
ReaderNumWorkUnitsCompleted | Returns the number of work units this Reader has finished processing. |
ReaderRead | Returns the next record (key, value pair) produced by a Reader. |
ReaderReadUpTo | Returns up to `num_records` (key, value) pairs produced by a Reader. |
ReaderReset | Restore a Reader to its initial clean state. |
ReaderRestoreState | Restore a reader to a previously saved state. |
ReaderSerializeState | Produce a string tensor that encodes the state of a Reader. |
ReadFile | Reads and outputs the entire contents of the input filename. |
ReadVariableOp <T extends TType > | Reads the value of a variable. |
Real <U extends TNumber > | Returns the real part of a complex number. |
RealDiv <T extends TType > | Returns x / y element-wise for real types. |
RebatchDataset | Creates a dataset that changes the batch size. |
RebatchDataset | Creates a dataset that changes the batch size. |
RebatchDataset.Options | Optional attributes for RebatchDataset |
RebatchDataset.Options | Optional attributes for RebatchDataset |
RebatchDatasetV2 | Creates a dataset that changes the batch size. |
Reciprocal <T extends TType > | Computes the reciprocal of x element-wise. |
ReciprocalGrad <T extends TType > | Computes the gradient for the inverse of `x` wrt its input. |
RecordInput | Emits randomized records. |
RecordInput.Options | Optional attributes for RecordInput |
Recv <T extends TType > | Receives the named tensor from send_device on recv_device. |
Recv <T extends TType > | Receives the named tensor from another XLA computation. |
Recv.Options | Optional attributes for Recv |
RecvTPUEmbeddingActivations | An op that receives embedding activations on the TPU. |
Reduce <T extends TNumber > | Encapsulates metrics that perform a reduce operation on the metric values. |
Reduce <T extends TNumber > | Mutually reduces multiple tensors of identical type and shape. |
Reduce.Options | Optional attributes for Reduce |
ReduceAll | Computes the "logical and" of elements across dimensions of a tensor. |
ReduceAll.Options | Optional attributes for ReduceAll |
ReduceAny | Computes the "logical or" of elements across dimensions of a tensor. |
ReduceAny.Options | Optional attributes for ReduceAny |
ReduceJoin | Joins a string Tensor across the given dimensions. |
ReduceJoin.Options | Optional attributes for ReduceJoin |
ReduceMax <T extends TType > | Computes the maximum of elements across dimensions of a tensor. |
ReduceMax.Options | Optional attributes for ReduceMax |
ReduceMin <T extends TType > | Computes the minimum of elements across dimensions of a tensor. |
ReduceMin.Options | Optional attributes for ReduceMin |
ReduceProd <T extends TType > | Computes the product of elements across dimensions of a tensor. |
ReduceProd.Options | Optional attributes for ReduceProd |
ReduceSum <T extends TType > | Computes the sum of elements across dimensions of a tensor. |
ReduceSum.Options | Optional attributes for ReduceSum |
ReduceV2 <T extends TNumber > | Mutually reduces multiple tensors of identical type and shape. |
ReduceV2.Options | Optional attributes for ReduceV2 |
تخفيض | Type of Loss Reduction |
RefEnter <T extends TType > | Creates or finds a child frame, and makes `data` available to the child frame. |
RefEnter.Options | Optional attributes for RefEnter |
RefExit <T extends TType > | Exits the current frame to its parent frame. |
RefIdentity <T extends TType > | Return the same ref tensor as the input ref tensor. |
RefMerge <T extends TType > | Forwards the value of an available tensor from `inputs` to `output`. |
RefNextIteration <T extends TType > | Makes its input available to the next iteration. |
RefSelect <T extends TType > | Forwards the `index`th element of `inputs` to `output`. |
RefSwitch <T extends TType > | Forwards the ref tensor `data` to the output port determined by `pred`. |
RegexFullMatch | Check if the input matches the regex pattern. |
RegexReplace | Replaces matches of the `pattern` regular expression in `input` with the replacement string provided in `rewrite`. |
RegexReplace.Options | Optional attributes for RegexReplace |
RegisterDataset | Registers a dataset with the tf.data service. |
RelativeDimensionalSpace | |
Relu <T extends TType > | Computes rectified linear: `max(features, 0)`. |
ReLU <T extends TNumber > | Rectified Linear Unit(ReLU) activation. |
Relu6 <T extends TNumber > | Computes rectified linear 6: `min(max(features, 0), 6)`. |
Relu6Grad <T extends TNumber > | Computes rectified linear 6 gradients for a Relu6 operation. |
ReluGrad <T extends TNumber > | Computes rectified linear gradients for a Relu operation. |
RemoteFusedGraphExecute | Execute a sub graph on a remote processor. |
RemoteFusedGraphExecuteInfo | Protocol buffer representing a handle to a tensorflow resource. |
RemoteFusedGraphExecuteInfo.Builder | Protocol buffer representing a handle to a tensorflow resource. |
RemoteFusedGraphExecuteInfo.TensorShapeTypeProto | Protobuf type tensorflow.RemoteFusedGraphExecuteInfo.TensorShapeTypeProto |
RemoteFusedGraphExecuteInfo.TensorShapeTypeProto.Builder | Protobuf type tensorflow.RemoteFusedGraphExecuteInfo.TensorShapeTypeProto |
RemoteFusedGraphExecuteInfo.TensorShapeTypeProtoOrBuilder | |
RemoteFusedGraphExecuteInfoOrBuilder | |
RemoteFusedGraphExecuteInfoProto | |
RemoteProfilerSessionManagerOptions | Options for remote profiler session manager. |
RemoteProfilerSessionManagerOptions.Builder | Options for remote profiler session manager. |
RemoteProfilerSessionManagerOptionsOrBuilder | |
RemoteTensorHandle | Protobuf type tensorflow.eager.RemoteTensorHandle |
RemoteTensorHandle.Builder | Protobuf type tensorflow.eager.RemoteTensorHandle |
RemoteTensorHandleOrBuilder | |
RemoteTensorHandleProtos | |
RepeatDataset | Creates a dataset that emits the outputs of `input_dataset` `count` times. |
ReplicaId | Replica ID. |
ReplicatedInput <T extends TType > | Connects N inputs to an N-way replicated TPU computation. |
ReplicatedInput.Options | Optional attributes for ReplicatedInput |
ReplicatedOutput <T extends TType > | Connects N outputs from an N-way replicated TPU computation. |
ReplicateMetadata | Metadata indicating how the TPU computation should be replicated. |
ReplicateMetadata.Options | Optional attributes for ReplicateMetadata |
RequantizationRange | Computes a range that covers the actual values present in a quantized tensor. |
RequantizationRangePerChannel | Computes requantization range per channel. |
Requantize <U extends TType > | Converts the quantized `input` tensor into a lower-precision `output`. |
RequantizePerChannel <U extends TType > | Requantizes input with min and max values known per channel. |
RequestedExitCode | Protobuf type tensorflow.RequestedExitCode |
RequestedExitCode.Builder | Protobuf type tensorflow.RequestedExitCode |
RequestedExitCodeOrBuilder | |
Reshape <T extends TType > | Reshapes a tensor. |
ResizeArea | Resize `images` to `size` using area interpolation. |
ResizeArea.Options | Optional attributes for ResizeArea |
ResizeBicubic | Resize `images` to `size` using bicubic interpolation. |
ResizeBicubic.Options | Optional attributes for ResizeBicubic |
ResizeBicubicGrad <T extends TNumber > | Computes the gradient of bicubic interpolation. |
ResizeBicubicGrad.Options | Optional attributes for ResizeBicubicGrad |
ResizeBilinear | Resize `images` to `size` using bilinear interpolation. |
ResizeBilinear.Options | Optional attributes for ResizeBilinear |
ResizeBilinearGrad <T extends TNumber > | Computes the gradient of bilinear interpolation. |
ResizeBilinearGrad.Options | Optional attributes for ResizeBilinearGrad |
ResizeNearestNeighbor <T extends TNumber > | Resize `images` to `size` using nearest neighbor interpolation. |
ResizeNearestNeighbor.Options | Optional attributes for ResizeNearestNeighbor |
ResizeNearestNeighborGrad <T extends TNumber > | Computes the gradient of nearest neighbor interpolation. |
ResizeNearestNeighborGrad.Options | Optional attributes for ResizeNearestNeighborGrad |
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 extends TType > | Extracts the average gradient in the given ConditionalAccumulator. |
ResourceApplyAdadelta | Update '*var' according to the adadelta scheme. |
ResourceApplyAdadelta.Options | Optional attributes for ResourceApplyAdadelta |
ResourceApplyAdagrad | Update '*var' according to the adagrad scheme. |
ResourceApplyAdagrad.Options | Optional attributes for ResourceApplyAdagrad |
ResourceApplyAdagradDa | Update '*var' according to the proximal adagrad scheme. |
ResourceApplyAdagradDa.Options | Optional attributes for ResourceApplyAdagradDa |
ResourceApplyAdam | Update '*var' according to the Adam algorithm. |
ResourceApplyAdam.Options | Optional attributes for ResourceApplyAdam |
ResourceApplyAdaMax | Update '*var' according to the AdaMax algorithm. |
ResourceApplyAdaMax.Options | Optional attributes for ResourceApplyAdaMax |
ResourceApplyAdamWithAmsgrad | Update '*var' according to the Adam algorithm. |
ResourceApplyAdamWithAmsgrad.Options | Optional attributes for ResourceApplyAdamWithAmsgrad |
ResourceApplyAddSign | Update '*var' according to the AddSign update. |
ResourceApplyAddSign.Options | Optional attributes for ResourceApplyAddSign |
ResourceApplyCenteredRmsProp | Update '*var' according to the centered RMSProp algorithm. |
ResourceApplyCenteredRmsProp.Options | Optional attributes for ResourceApplyCenteredRmsProp |
ResourceApplyFtrl | Update '*var' according to the Ftrl-proximal scheme. |
ResourceApplyFtrl.Options | Optional attributes for ResourceApplyFtrl |
ResourceApplyGradientDescent | Update '*var' by subtracting 'alpha' * 'delta' from it. |
ResourceApplyGradientDescent.Options | Optional attributes for ResourceApplyGradientDescent |
ResourceApplyKerasMomentum | Update '*var' according to the momentum scheme. |
ResourceApplyKerasMomentum.Options | Optional attributes for ResourceApplyKerasMomentum |
ResourceApplyMomentum | Update '*var' according to the momentum scheme. |
ResourceApplyMomentum.Options | Optional attributes for ResourceApplyMomentum |
ResourceApplyPowerSign | Update '*var' according to the AddSign update. |
ResourceApplyPowerSign.Options | Optional attributes for ResourceApplyPowerSign |
ResourceApplyProximalAdagrad | Update '*var' and '*accum' according to FOBOS with Adagrad learning rate. |
ResourceApplyProximalAdagrad.Options | Optional attributes for ResourceApplyProximalAdagrad |
ResourceApplyProximalGradientDescent | Update '*var' as FOBOS algorithm with fixed learning rate. |
ResourceApplyProximalGradientDescent.Options | Optional attributes for ResourceApplyProximalGradientDescent |
ResourceApplyRmsProp | Update '*var' according to the RMSProp algorithm. |
ResourceApplyRmsProp.Options | Optional attributes for ResourceApplyRmsProp |
ResourceConditionalAccumulator | A conditional accumulator for aggregating gradients. |
ResourceConditionalAccumulator.Options | Optional attributes for ResourceConditionalAccumulator |
ResourceCountUpTo <T extends TNumber > | Increments variable pointed to by 'resource' until it reaches 'limit'. |
ResourceDtypeAndShape | Protobuf type tensorflow.eager.ResourceDtypeAndShape |
ResourceDtypeAndShape.Builder | Protobuf type tensorflow.eager.ResourceDtypeAndShape |
ResourceDtypeAndShapeOrBuilder | |
ResourceGather <U extends TType > | Gather slices from the variable pointed to by `resource` according to `indices`. |
ResourceGather.Options | Optional attributes for ResourceGather |
ResourceGatherNd <U extends TType > | |
ResourceHandle | |
ResourceHandleProto | Protocol buffer representing a handle to a tensorflow resource. |
ResourceHandleProto.Builder | Protocol buffer representing a handle to a tensorflow resource. |
ResourceHandleProto.DtypeAndShape | Protocol buffer representing a pair of (data type, tensor shape). |
ResourceHandleProto.DtypeAndShape.Builder | Protocol buffer representing a pair of (data type, tensor shape). |
ResourceHandleProto.DtypeAndShapeOrBuilder | |
ResourceHandleProtoOrBuilder | |
ResourceScatterAdd | Adds sparse updates to the variable referenced by `resource`. |
ResourceScatterDiv | Divides sparse updates into the variable referenced by `resource`. |
ResourceScatterMax | Reduces sparse updates into the variable referenced by `resource` using the `max` operation. |
ResourceScatterMin | Reduces sparse updates into the variable referenced by `resource` using the `min` operation. |
ResourceScatterMul | Multiplies sparse updates into the variable referenced by `resource`. |
ResourceScatterNdAdd | Applies sparse addition to individual values or slices in a Variable. |
ResourceScatterNdAdd.Options | Optional attributes for ResourceScatterNdAdd |
ResourceScatterNdMax | |
ResourceScatterNdMax.Options | Optional attributes for ResourceScatterNdMax |
ResourceScatterNdMin | |
ResourceScatterNdMin.Options | Optional attributes for ResourceScatterNdMin |
ResourceScatterNdSub | Applies sparse subtraction to individual values or slices in a Variable. |
ResourceScatterNdSub.Options | Optional attributes for ResourceScatterNdSub |
ResourceScatterNdUpdate | Applies sparse `updates` to individual values or slices within a given variable according to `indices`. |
ResourceScatterNdUpdate.Options | Optional attributes for ResourceScatterNdUpdate |
ResourceScatterSub | Subtracts sparse updates from the variable referenced by `resource`. |
ResourceScatterUpdate | Assigns sparse updates to the variable referenced by `resource`. |
ResourceSparseApplyAdadelta | var: Should be from a Variable(). |
ResourceSparseApplyAdadelta.Options | Optional attributes for ResourceSparseApplyAdadelta |
ResourceSparseApplyAdagrad | Update relevant entries in '*var' and '*accum' according to the adagrad scheme. |
ResourceSparseApplyAdagrad.Options | Optional attributes for ResourceSparseApplyAdagrad |
ResourceSparseApplyAdagradDa | Update entries in '*var' and '*accum' according to the proximal adagrad scheme. |
ResourceSparseApplyAdagradDa.Options | Optional attributes for ResourceSparseApplyAdagradDa |
ResourceSparseApplyAdagradV2 | Update relevant entries in '*var' and '*accum' according to the adagrad scheme. |
ResourceSparseApplyAdagradV2.Options | Optional attributes for ResourceSparseApplyAdagradV2 |
ResourceSparseApplyCenteredRmsProp | Update '*var' according to the centered RMSProp algorithm. |
ResourceSparseApplyCenteredRmsProp.Options | Optional attributes for ResourceSparseApplyCenteredRmsProp |
ResourceSparseApplyFtrl | Update relevant entries in '*var' according to the Ftrl-proximal scheme. |
ResourceSparseApplyFtrl.Options | Optional attributes for ResourceSparseApplyFtrl |
ResourceSparseApplyKerasMomentum | Update relevant entries in '*var' and '*accum' according to the momentum scheme. |
ResourceSparseApplyKerasMomentum.Options | Optional attributes for ResourceSparseApplyKerasMomentum |
ResourceSparseApplyMomentum | Update relevant entries in '*var' and '*accum' according to the momentum scheme. |
ResourceSparseApplyMomentum.Options | Optional attributes for ResourceSparseApplyMomentum |
ResourceSparseApplyProximalAdagrad | Sparse update entries in '*var' and '*accum' according to FOBOS algorithm. |
ResourceSparseApplyProximalAdagrad.Options | Optional attributes for ResourceSparseApplyProximalAdagrad |
ResourceSparseApplyProximalGradientDescent | Sparse update '*var' as FOBOS algorithm with fixed learning rate. |
ResourceSparseApplyProximalGradientDescent.Options | Optional attributes for ResourceSparseApplyProximalGradientDescent |
ResourceSparseApplyRmsProp | Update '*var' according to the RMSProp algorithm. |
ResourceSparseApplyRmsProp.Options | Optional attributes for ResourceSparseApplyRmsProp |
ResourceStridedSliceAssign | Assign `value` to the sliced l-value reference of `ref`. |
ResourceStridedSliceAssign.Options | Optional attributes for ResourceStridedSliceAssign |
يعيد | Restores tensors from a V2 checkpoint. |
RestoreSlice <T extends TType > | Restores a tensor from checkpoint files. |
RestoreSlice.Options | Optional attributes for RestoreSlice |
RetrieveTPUEmbeddingAdadeltaParameters | Retrieve Adadelta embedding parameters. |
RetrieveTPUEmbeddingAdadeltaParameters.Options | Optional attributes for RetrieveTPUEmbeddingAdadeltaParameters |
RetrieveTPUEmbeddingAdadeltaParametersGradAccumDebug | Retrieve Adadelta embedding parameters with debug support. |
RetrieveTPUEmbeddingAdadeltaParametersGradAccumDebug.Options | Optional attributes for RetrieveTPUEmbeddingAdadeltaParametersGradAccumDebug |
RetrieveTPUEmbeddingAdagradParameters | Retrieve Adagrad embedding parameters. |
RetrieveTPUEmbeddingAdagradParameters.Options | Optional attributes for RetrieveTPUEmbeddingAdagradParameters |
RetrieveTPUEmbeddingAdagradParametersGradAccumDebug | Retrieve Adagrad embedding parameters with debug support. |
RetrieveTPUEmbeddingAdagradParametersGradAccumDebug.Options | Optional attributes for RetrieveTPUEmbeddingAdagradParametersGradAccumDebug |
RetrieveTPUEmbeddingADAMParameters | Retrieve ADAM embedding parameters. |
RetrieveTPUEmbeddingADAMParameters.Options | Optional attributes for RetrieveTPUEmbeddingADAMParameters |
RetrieveTPUEmbeddingADAMParametersGradAccumDebug | Retrieve ADAM embedding parameters with debug support. |
RetrieveTPUEmbeddingADAMParametersGradAccumDebug.Options | Optional attributes for RetrieveTPUEmbeddingADAMParametersGradAccumDebug |
RetrieveTPUEmbeddingCenteredRMSPropParameters | Retrieve centered RMSProp embedding parameters. |
RetrieveTPUEmbeddingCenteredRMSPropParameters.Options | Optional attributes for RetrieveTPUEmbeddingCenteredRMSPropParameters |
RetrieveTPUEmbeddingFTRLParameters | Retrieve FTRL embedding parameters. |
RetrieveTPUEmbeddingFTRLParameters.Options | Optional attributes for RetrieveTPUEmbeddingFTRLParameters |
RetrieveTPUEmbeddingFTRLParametersGradAccumDebug | Retrieve FTRL embedding parameters with debug support. |
RetrieveTPUEmbeddingFTRLParametersGradAccumDebug.Options | Optional attributes for RetrieveTPUEmbeddingFTRLParametersGradAccumDebug |
RetrieveTPUEmbeddingMDLAdagradLightParameters | Retrieve MDL Adagrad Light embedding parameters. |
RetrieveTPUEmbeddingMDLAdagradLightParameters.Options | Optional attributes for RetrieveTPUEmbeddingMDLAdagradLightParameters |
RetrieveTPUEmbeddingMomentumParameters | Retrieve Momentum embedding parameters. |
RetrieveTPUEmbeddingMomentumParameters.Options | Optional attributes for RetrieveTPUEmbeddingMomentumParameters |
RetrieveTPUEmbeddingMomentumParametersGradAccumDebug | Retrieve Momentum embedding parameters with debug support. |
RetrieveTPUEmbeddingMomentumParametersGradAccumDebug.Options | Optional attributes for RetrieveTPUEmbeddingMomentumParametersGradAccumDebug |
RetrieveTPUEmbeddingProximalAdagradParameters | Retrieve proximal Adagrad embedding parameters. |
RetrieveTPUEmbeddingProximalAdagradParameters.Options | Optional attributes for RetrieveTPUEmbeddingProximalAdagradParameters |
RetrieveTPUEmbeddingProximalAdagradParametersGradAccumDebug | Retrieve proximal Adagrad embedding parameters with debug support. |
RetrieveTPUEmbeddingProximalAdagradParametersGradAccumDebug.Options | Optional attributes for RetrieveTPUEmbeddingProximalAdagradParametersGradAccumDebug |
RetrieveTPUEmbeddingProximalYogiParameters | |
RetrieveTPUEmbeddingProximalYogiParameters.Options | Optional attributes for RetrieveTPUEmbeddingProximalYogiParameters |
RetrieveTPUEmbeddingProximalYogiParametersGradAccumDebug | |
RetrieveTPUEmbeddingProximalYogiParametersGradAccumDebug.Options | Optional attributes for RetrieveTPUEmbeddingProximalYogiParametersGradAccumDebug |
RetrieveTPUEmbeddingRMSPropParameters | Retrieve RMSProp embedding parameters. |
RetrieveTPUEmbeddingRMSPropParameters.Options | Optional attributes for RetrieveTPUEmbeddingRMSPropParameters |
RetrieveTPUEmbeddingRMSPropParametersGradAccumDebug | Retrieve RMSProp embedding parameters with debug support. |
RetrieveTPUEmbeddingRMSPropParametersGradAccumDebug.Options | Optional attributes for RetrieveTPUEmbeddingRMSPropParametersGradAccumDebug |
RetrieveTPUEmbeddingStochasticGradientDescentParameters | Retrieve SGD embedding parameters. |
RetrieveTPUEmbeddingStochasticGradientDescentParameters.Options | Optional attributes for RetrieveTPUEmbeddingStochasticGradientDescentParameters |
RetrieveTPUEmbeddingStochasticGradientDescentParametersGradAccumDebug | Retrieve SGD embedding parameters with debug support. |
RetrieveTPUEmbeddingStochasticGradientDescentParametersGradAccumDebug.Options | Optional attributes for RetrieveTPUEmbeddingStochasticGradientDescentParametersGradAccumDebug |
Reverse <T extends TType > | Reverses specific dimensions of a tensor. |
ReverseSequence <T extends TType > | Reverses variable length slices. |
ReverseSequence.Options | Optional attributes for ReverseSequence |
RewriterConfig | Graph rewriting is experimental and subject to change, not covered by any API stability guarantees. |
RewriterConfig.Builder | Graph rewriting is experimental and subject to change, not covered by any API stability guarantees. |
RewriterConfig.CpuLayout | Enum for layout conversion between NCHW and NHWC on CPU. |
RewriterConfig.CustomGraphOptimizer | Message to describe custom graph optimizer and its parametersProtobuf type tensorflow.RewriterConfig.CustomGraphOptimizer |
RewriterConfig.CustomGraphOptimizer.Builder | Message to describe custom graph optimizer and its parametersProtobuf type tensorflow.RewriterConfig.CustomGraphOptimizer |
RewriterConfig.CustomGraphOptimizerOrBuilder | |
RewriterConfig.MemOptType | Protobuf enum tensorflow.RewriterConfig.MemOptType |
RewriterConfig.NumIterationsType | Enum controlling the number of times to run optimizers. |
RewriterConfig.Toggle | Protobuf enum tensorflow.RewriterConfig.Toggle |
RewriterConfigOrBuilder | |
RewriterConfigProtos | |
Rfft <U extends TType > | Real-valued fast Fourier transform. |
Rfft2d <U extends TType > | 2D real-valued fast Fourier transform. |
Rfft3d <U extends TType > | 3D real-valued fast Fourier transform. |
RgbToHsv <T extends TNumber > | Converts one or more images from RGB to HSV. |
RightShift <T extends TNumber > | Elementwise computes the bitwise right-shift of `x` and `y`. |
Rint <T extends TNumber > | Returns element-wise integer closest to x. |
RMSProp | Optimizer that implements the RMSProp algorithm. |
RngReadAndSkip | Advance the counter of a counter-based RNG. |
RngSkip | Advance the counter of a counter-based RNG. |
Roll <T extends TType > | Rolls the elements of a tensor along an axis. |
Round <T extends TType > | Rounds the values of a tensor to the nearest integer, element-wise. |
Rpc | Perform batches of RPC requests. |
Rpc.Options | Optional attributes for Rpc |
RPCOptions | Protobuf type tensorflow.RPCOptions |
RPCOptions.Builder | Protobuf type tensorflow.RPCOptions |
RPCOptionsOrBuilder | |
Rsqrt <T extends TType > | Computes reciprocal of square root of x element-wise. |
RsqrtGrad <T extends TType > | Computes the gradient for the rsqrt of `x` wrt its input. |
RunConfiguration | Run-specific items such as arguments to the test / benchmark. |
RunConfiguration.Builder | Run-specific items such as arguments to the test / benchmark. |
RunConfigurationOrBuilder | |
RunMetadata | Metadata output (i.e., non-Tensor) for a single Run() call. |
RunMetadata.Builder | Metadata output (i.e., non-Tensor) for a single Run() call. |
RunMetadata.FunctionGraphs | Protobuf type tensorflow.RunMetadata.FunctionGraphs |
RunMetadata.FunctionGraphs.Builder | Protobuf type tensorflow.RunMetadata.FunctionGraphs |
RunMetadata.FunctionGraphsOrBuilder | |
RunMetadataOrBuilder | |
RunOptions | Options for a single Run() call. |
RunOptions.Builder | Options for a single Run() call. |
RunOptions.Experimental | Everything inside Experimental is subject to change and is not subject to API stability guarantees in https://www.tensorflow.org/guide/version_compat. |
RunOptions.Experimental.Builder | Everything inside Experimental is subject to change and is not subject to API stability guarantees in https://www.tensorflow.org/guide/version_compat. |
RunOptions.Experimental.RunHandlerPoolOptions | Options for run handler thread pool. |
RunOptions.Experimental.RunHandlerPoolOptions.Builder | Options for run handler thread pool. |
RunOptions.Experimental.RunHandlerPoolOptionsOrBuilder | |
RunOptions.ExperimentalOrBuilder | |
RunOptions.TraceLevel | TODO(pbar) Turn this into a TraceOptions proto which allows tracing to be controlled in a more orthogonal manner?Protobuf enum tensorflow.RunOptions.TraceLevel |
RunOptionsOrBuilder |
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SampleDistortedBoundingBox <T extends TNumber > | Generate a single randomly distorted bounding box for an image. |
SampleDistortedBoundingBox.Options | Optional attributes for SampleDistortedBoundingBox |
SamplingDataset | Creates a dataset that takes a Bernoulli sample of the contents of another dataset. |
يحفظ | Saves tensors in V2 checkpoint format. |
SaveableObject | Protobuf type tensorflow.SaveableObject |
SaveableObject.Builder | Protobuf type tensorflow.SaveableObject |
SaveableObjectOrBuilder | |
SavedAsset | A SavedAsset points to an asset in the MetaGraph. |
SavedAsset.Builder | A SavedAsset points to an asset in the MetaGraph. |
SavedAssetOrBuilder | |
SavedBareConcreteFunction | Protobuf type tensorflow.SavedBareConcreteFunction |
SavedBareConcreteFunction.Builder | Protobuf type tensorflow.SavedBareConcreteFunction |
SavedBareConcreteFunctionOrBuilder | |
SavedConcreteFunction | Stores low-level information about a concrete function. |
SavedConcreteFunction.Builder | Stores low-level information about a concrete function. |
SavedConcreteFunctionOrBuilder | |
SavedConstant | Protobuf type tensorflow.SavedConstant |
SavedConstant.Builder | Protobuf type tensorflow.SavedConstant |
SavedConstantOrBuilder | |
SavedFunction | A function with multiple signatures, possibly with non-Tensor arguments. |
SavedFunction.Builder | A function with multiple signatures, possibly with non-Tensor arguments. |
SavedFunctionOrBuilder | |
SavedModel | SavedModel is the high level serialization format for TensorFlow Models. |
SavedModel.Builder | SavedModel is the high level serialization format for TensorFlow Models. |
SavedModelBundle | SavedModelBundle represents a model loaded from storage. |
SavedModelBundle.Exporter | Options for exporting a SavedModel. |
SavedModelBundle.Loader | Options for loading a SavedModel. |
SavedModelOrBuilder | |
SavedModelProtos | |
SavedObject | Protobuf type tensorflow.SavedObject |
SavedObject.Builder | Protobuf type tensorflow.SavedObject |
SavedObject.KindCase | |
SavedObjectGraph | Protobuf type tensorflow.SavedObjectGraph |
SavedObjectGraph.Builder | Protobuf type tensorflow.SavedObjectGraph |
SavedObjectGraphOrBuilder | |
SavedObjectGraphProtos | |
SavedObjectOrBuilder | |
SavedResource | A SavedResource represents a TF object that holds state during its lifetime. |
SavedResource.Builder | A SavedResource represents a TF object that holds state during its lifetime. |
SavedResourceOrBuilder | |
SavedSlice | Saved tensor slice: it stores the name of the tensors, the slice, and the raw data. |
SavedSlice.Builder | Saved tensor slice: it stores the name of the tensors, the slice, and the raw data. |
SavedSliceMeta | Metadata describing the set of slices of the same tensor saved in a checkpoint file. |
SavedSliceMeta.Builder | Metadata describing the set of slices of the same tensor saved in a checkpoint file. |
SavedSliceMetaOrBuilder | |
SavedSliceOrBuilder | |
SavedTensorSliceMeta | Metadata describing the set of tensor slices saved in a checkpoint file. |
SavedTensorSliceMeta.Builder | Metadata describing the set of tensor slices saved in a checkpoint file. |
SavedTensorSliceMetaOrBuilder | |
SavedTensorSliceProtos | |
SavedTensorSlices | Each record in a v3 checkpoint file is a serialized SavedTensorSlices message. |
SavedTensorSlices.Builder | Each record in a v3 checkpoint file is a serialized SavedTensorSlices message. |
SavedTensorSlicesOrBuilder | |
SavedUserObject | A SavedUserObject is an object (in the object-oriented language of the TensorFlow program) of some user- or framework-defined class other than those handled specifically by the other kinds of SavedObjects. |
SavedUserObject.Builder | A SavedUserObject is an object (in the object-oriented language of the TensorFlow program) of some user- or framework-defined class other than those handled specifically by the other kinds of SavedObjects. |
SavedUserObjectOrBuilder | |
SavedVariable | Represents a Variable that is initialized by loading the contents from the checkpoint. |
SavedVariable.Builder | Represents a Variable that is initialized by loading the contents from the checkpoint. |
SavedVariableOrBuilder | |
SaverDef | Protocol buffer representing the configuration of a Saver. |
SaverDef.Builder | Protocol buffer representing the configuration of a Saver. |
SaverDef.CheckpointFormatVersion | A version number that identifies a different on-disk checkpoint format. |
SaverDefOrBuilder | |
SaverProtos | |
SaveSliceInfoDef | Protobuf type tensorflow.SaveSliceInfoDef |
SaveSliceInfoDef.Builder | Protobuf type tensorflow.SaveSliceInfoDef |
SaveSliceInfoDefOrBuilder | |
SaveSlices | Saves input tensors slices to disk. |
ScalarSummary | Outputs a `Summary` protocol buffer with scalar values. |
ScaleAndTranslate | |
ScaleAndTranslate.Options | Optional attributes for ScaleAndTranslate |
ScaleAndTranslateGrad <T extends TNumber > | |
ScaleAndTranslateGrad.Options | Optional attributes for ScaleAndTranslateGrad |
ScatterAdd <T extends TType > | Adds sparse updates to a variable reference. |
ScatterAdd.Options | Optional attributes for ScatterAdd |
ScatterDiv <T extends TType > | Divides a variable reference by sparse updates. |
ScatterDiv.Options | Optional attributes for ScatterDiv |
ScatterMax <T extends TNumber > | Reduces sparse updates into a variable reference using the `max` operation. |
ScatterMax.Options | Optional attributes for ScatterMax |
ScatterMin <T extends TNumber > | Reduces sparse updates into a variable reference using the `min` operation. |
ScatterMin.Options | Optional attributes for ScatterMin |
ScatterMul <T extends TType > | Multiplies sparse updates into a variable reference. |
ScatterMul.Options | Optional attributes for ScatterMul |
ScatterNd <U extends TType > | Scatter `updates` into a new tensor according to `indices`. |
ScatterNdAdd <T extends TType > | Applies sparse addition to individual values or slices in a Variable. |
ScatterNdAdd.Options | Optional attributes for ScatterNdAdd |
ScatterNdMax <T extends TType > | Computes element-wise maximum. |
ScatterNdMax.Options | Optional attributes for ScatterNdMax |
ScatterNdMin <T extends TType > | Computes element-wise minimum. |
ScatterNdMin.Options | Optional attributes for ScatterNdMin |
ScatterNdNonAliasingAdd <T extends TType > | Applies sparse addition to `input` using individual values or slices from `updates` according to indices `indices`. |
ScatterNdSub <T extends TType > | Applies sparse subtraction to individual values or slices in a Variable. |
ScatterNdSub.Options | Optional attributes for ScatterNdSub |
ScatterNdUpdate <T extends TType > | Applies sparse `updates` to individual values or slices within a given variable according to `indices`. |
ScatterNdUpdate.Options | Optional attributes for ScatterNdUpdate |
ScatterSub <T extends TType > | Subtracts sparse updates to a variable reference. |
ScatterSub.Options | Optional attributes for ScatterSub |
ScatterUpdate <T extends TType > | Applies sparse updates to a variable reference. |
ScatterUpdate.Options | Optional attributes for ScatterUpdate |
نِطَاق | Manages groups of related properties when creating Tensorflow Operations, such as a common name prefix. |
ScopedAllocatorOptions | Protobuf type tensorflow.ScopedAllocatorOptions |
ScopedAllocatorOptions.Builder | Protobuf type tensorflow.ScopedAllocatorOptions |
ScopedAllocatorOptionsOrBuilder | |
SdcaFprint | Computes fingerprints of the input strings. |
SdcaOptimizer | Distributed version of Stochastic Dual Coordinate Ascent (SDCA) optimizer for linear models with L1 + L2 regularization. |
SdcaOptimizer.Options | Optional attributes for SdcaOptimizer |
SdcaShrinkL1 | Applies L1 regularization shrink step on the parameters. |
SegmentMax <T extends TNumber > | Computes the maximum along segments of a tensor. |
SegmentMean <T extends TType > | Computes the mean along segments of a tensor. |
SegmentMin <T extends TNumber > | Computes the minimum along segments of a tensor. |
SegmentProd <T extends TType > | Computes the product along segments of a tensor. |
SegmentSum <T extends TType > | Computes the sum along segments of a tensor. |
Select <T extends TType > | |
SelfAdjointEig <T extends TType > | Computes the eigen decomposition of one or more square self-adjoint matrices. |
SelfAdjointEig <T extends TType > | Computes the eigen decomposition of a batch of self-adjoint matrices (Note: Only real inputs are supported). |
SelfAdjointEig.Options | Optional attributes for SelfAdjointEig |
Selu <T extends TNumber > | Computes scaled exponential linear: `scale * alpha * (exp(features) - 1)` if < 0, `scale * features` otherwise. |
SELU <T extends TFloating > | Scaled Exponential Linear Unit (SELU). |
SeluGrad <T extends TNumber > | Computes gradients for the scaled exponential linear (Selu) operation. |
يرسل | Sends the named tensor from send_device to recv_device. |
يرسل | Sends the named tensor to another XLA computation. |
Send.Options | Optional attributes for Send |
SendTPUEmbeddingGradients | Performs gradient updates of embedding tables. |
SequenceExample | Protobuf type tensorflow.SequenceExample |
SequenceExample.Builder | Protobuf type tensorflow.SequenceExample |
SequenceExampleOrBuilder | |
SerializeIterator | Converts the given `resource_handle` representing an iterator to a variant tensor. |
SerializeIterator.Options | Optional attributes for SerializeIterator |
SerializeManySparse <U extends TType > | Serialize an `N`-minibatch `SparseTensor` into an `[N, 3]` `Tensor` object. |
SerializeSparse <U extends TType > | Serialize a `SparseTensor` into a `[3]` `Tensor` object. |
SerializeTensor | Transforms a Tensor into a serialized TensorProto proto. |
الخادم | An in-process TensorFlow server, for use in distributed training. |
ServerDef | Defines the configuration of a single TensorFlow server. |
ServerDef.Builder | Defines the configuration of a single TensorFlow server. |
ServerDefOrBuilder | |
ServerProtos | |
ServiceConfig | |
ServiceConfig.DispatcherConfig | Configuration for a tf.data service DispatchServer. |
ServiceConfig.DispatcherConfig.Builder | Configuration for a tf.data service DispatchServer. |
ServiceConfig.DispatcherConfigOrBuilder | |
ServiceConfig.WorkerConfig | Configuration for a tf.data service WorkerServer. |
ServiceConfig.WorkerConfig.Builder | Configuration for a tf.data service WorkerServer. |
ServiceConfig.WorkerConfigOrBuilder | |
حصة | Driver for Graph execution. |
Session.Run | Output tensors and metadata obtained when executing a session. |
Session.Runner | Run Operation s and evaluate Tensors . |
SessionLog | Protocol buffer used for logging session state. |
SessionLog.Builder | Protocol buffer used for logging session state. |
SessionLog.SessionStatus | Protobuf enum tensorflow.SessionLog.SessionStatus |
SessionLogOrBuilder | |
SessionMetadata | Metadata about the session. |
SessionMetadata.Builder | Metadata about the session. |
SessionMetadataOrBuilder | |
SetDiff1d <T extends TType , U extends TNumber > | Computes the difference between two lists of numbers or strings. |
SetSize | Number of unique elements along last dimension of input `set`. |
SetSize.Options | Optional attributes for SetSize |
SetsOps | Implementation of set operations |
SetsOps.Operation | Enumeration containing the string operation values to be passed to the TensorFlow Sparse Ops function ERROR(/SparseOps#denseToDenseSetOperation) |
SetStatsAggregatorDataset | |
SetStatsAggregatorDataset | |
شكل | The shape of a Tensor or NdArray . |
Shape <U extends TNumber > | Returns the shape of a tensor. |
Shape_inference_func_TF_ShapeInferenceContext_TF_Status | |
على شكل | Any data container with a given Shape . |
ShapeN <U extends TNumber > | Returns shape of tensors. |
الأشكال | An operator providing methods on org.tensorflow.op.core.Shape tensors and 1d operands that represent the dimensions of a shape. |
ShapeUtils | Various methods for processing with Shapes and Operands |
ShardDataset | Creates a `Dataset` that includes only 1/`num_shards` of this dataset. |
ShardDataset.Options | Optional attributes for ShardDataset |
ShardedFilename | Generate a sharded filename. |
ShardedFilespec | Generate a glob pattern matching all sharded file names. |
Sharding <T extends TType > | An op which shards the input based on the given sharding attribute. |
ShortDataBuffer | A DataBuffer of shorts. |
ShortDataLayout <S extends DataBuffer <?>> | A DataLayout that converts data stored in a buffer to shorts. |
ShortDenseNdArray | |
ShortNdArray | An NdArray of shorts. |
ShuffleAndRepeatDataset | |
ShuffleAndRepeatDataset.Options | Optional attributes for ShuffleAndRepeatDataset |
ShuffleDataset | |
ShuffleDataset.Options | Optional attributes for ShuffleDataset |
ShutdownDistributedTPU | Shuts down a running distributed TPU system. |
Sigmoid <T extends TFloating > | Sigmoid activation. |
Sigmoid <T extends TType > | Computes sigmoid of `x` element-wise. |
SigmoidCrossEntropyWithLogits | |
SigmoidGrad <T extends TType > | Computes the gradient of the sigmoid of `x` wrt its input. |
Sign <T extends TType > | Returns an element-wise indication of the sign of a number. |
إمضاء | Describe the inputs and outputs of an executable entity, such as a ConcreteFunction , among other useful metadata. |
Signature.Builder | Builds a new function signature. |
Signature.TensorDescription | |
SignatureDef | SignatureDef defines the signature of a computation supported by a TensorFlow graph. |
SignatureDef.Builder | SignatureDef defines the signature of a computation supported by a TensorFlow graph. |
SignatureDefOrBuilder | |
Sin <T extends TType > | Computes sine of x element-wise. |
SingleElementSequence <T, U extends NdArray <T>> | A sequence of one single element |
Sinh <T extends TType > | Computes hyperbolic sine of x element-wise. |
Size <U extends TNumber > | Returns the size of a tensor. |
SkipDataset | |
SkipDataset | Creates a dataset that skips `count` elements from the `input_dataset`. |
Skipgram | Parses a text file and creates a batch of examples. |
Skipgram.Options | Optional attributes for Skipgram |
SleepDataset | |
SleepDataset | |
Slice <T extends TType > | Return a slice from 'input'. |
SlicingElementSequence <T, U extends NdArray <T>> | A sequence creating a new NdArray instance (slice) for each element of an iteration |
SlidingWindowDataset | Creates a dataset that passes a sliding window over `input_dataset`. |
SlidingWindowDataset | Creates a dataset that passes a sliding window over `input_dataset`. |
Snapshot <T extends TType > | Returns a copy of the input tensor. |
SnapShot | Protobuf type tensorflow.SnapShot |
SnapShot.Builder | Protobuf type tensorflow.SnapShot |
SnapshotMetadataRecord | This stores the metadata information present in each snapshot record. |
SnapshotMetadataRecord.Builder | This stores the metadata information present in each snapshot record. |
SnapshotMetadataRecordOrBuilder | |
SnapShotOrBuilder | |
SnapshotProtos | |
SnapshotRecord | Each SnapshotRecord represents one batch of pre-processed input data. |
SnapshotRecord.Builder | Each SnapshotRecord represents one batch of pre-processed input data. |
SnapshotRecordOrBuilder | |
SnapshotTensorMetadata | Metadata for all the tensors in a Snapshot Record. |
SnapshotTensorMetadata.Builder | Metadata for all the tensors in a Snapshot Record. |
SnapshotTensorMetadataOrBuilder | |
SobolSample <T extends TNumber > | Generates points from the Sobol sequence. |
Softmax <T extends TFloating > | Softmax converts a real vector to a vector of categorical probabilities. |
Softmax <T extends TNumber > | Computes softmax activations. |
SoftmaxCrossEntropyWithLogits | |
SoftmaxCrossEntropyWithLogits <T extends TNumber > | Computes softmax cross entropy cost and gradients to backpropagate. |
Softplus <T extends TFloating > | Softplus activation function, softplus(x) = log(exp(x) + 1) . |
Softplus <T extends TNumber > | Computes softplus: `log(exp(features) + 1)`. |
SoftplusGrad <T extends TNumber > | Computes softplus gradients for a softplus operation. |
Softsign <T extends TFloating > | Softsign activation function, softsign(x) = x / (abs(x) + 1) . |
Softsign <T extends TNumber > | Computes softsign: `features / (abs(features) + 1)`. |
SoftsignGrad <T extends TNumber > | Computes softsign gradients for a softsign operation. |
Solve <T extends TType > | Solves systems of linear equations. |
Solve.Options | Optional attributes for Solve |
Sort <T extends TType > | Wraps the XLA Sort operator, documented at https://www.tensorflow.org/performance/xla/operation_semantics#sort . |
SourceFile | Content of a source file involved in the execution of the debugged TensorFlow program. |
SourceFile.Builder | Content of a source file involved in the execution of the debugged TensorFlow program. |
SourceFileOrBuilder | |
SpaceToBatch <T extends TType > | SpaceToBatch for 4-D tensors of type T. |
SpaceToBatchNd <T extends TType > | SpaceToBatch for ND tensors of type T. |
SpaceToDepth <T extends TType > | SpaceToDepth for tensors of type T. |
SpaceToDepth.Options | Optional attributes for SpaceToDepth |
SparseAccumulatorApplyGradient | Applies a sparse gradient to a given accumulator. |
SparseAccumulatorTakeGradient <T extends TType > | Extracts the average sparse gradient in a SparseConditionalAccumulator. |
SparseAdd <T extends TType > | Adds two `SparseTensor` objects to produce another `SparseTensor`. |
SparseAddGrad <T extends TType > | The gradient operator for the SparseAdd op. |
SparseApplyAdadelta <T extends TType > | var: Should be from a Variable(). |
SparseApplyAdadelta.Options | Optional attributes for SparseApplyAdadelta |
SparseApplyAdagrad <T extends TType > | Update relevant entries in '*var' and '*accum' according to the adagrad scheme. |
SparseApplyAdagrad.Options | Optional attributes for SparseApplyAdagrad |
SparseApplyAdagradDa <T extends TType > | Update entries in '*var' and '*accum' according to the proximal adagrad scheme. |
SparseApplyAdagradDa.Options | Optional attributes for SparseApplyAdagradDa |
SparseApplyCenteredRmsProp <T extends TType > | Update '*var' according to the centered RMSProp algorithm. |
SparseApplyCenteredRmsProp.Options | Optional attributes for SparseApplyCenteredRmsProp |
SparseApplyFtrl <T extends TType > | Update relevant entries in '*var' according to the Ftrl-proximal scheme. |
SparseApplyFtrl.Options | Optional attributes for SparseApplyFtrl |
SparseApplyMomentum <T extends TType > | Update relevant entries in '*var' and '*accum' according to the momentum scheme. |
SparseApplyMomentum.Options | Optional attributes for SparseApplyMomentum |
SparseApplyProximalAdagrad <T extends TType > | Sparse update entries in '*var' and '*accum' according to FOBOS algorithm. |
SparseApplyProximalAdagrad.Options | Optional attributes for SparseApplyProximalAdagrad |
SparseApplyProximalGradientDescent <T extends TType > | Sparse update '*var' as FOBOS algorithm with fixed learning rate. |
SparseApplyProximalGradientDescent.Options | Optional attributes for SparseApplyProximalGradientDescent |
SparseApplyRmsProp <T extends TType > | Update '*var' according to the RMSProp algorithm. |
SparseApplyRmsProp.Options | Optional attributes for SparseApplyRmsProp |
SparseBincount <U extends TNumber > | Counts the number of occurrences of each value in an integer array. |
SparseBincount.Options | Optional attributes for SparseBincount |
SparseCategoricalCrossentropy | Computes the crossentropy loss between labels and predictions. |
SparseCategoricalCrossentropy <T extends TNumber > | A metric that computes the sparse categorical cross-entropy loss between true labels and predicted labels. |
SparseConcat <T extends TType > | Concatenates a list of `SparseTensor` along the specified dimension. |
SparseConditionalAccumulator | A conditional accumulator for aggregating sparse gradients. |
SparseConditionalAccumulator.Options | Optional attributes for SparseConditionalAccumulator |
SparseCountSparseOutput <U extends TNumber > | Performs sparse-output bin counting for a sparse tensor input. |
SparseCountSparseOutput.Options | Optional attributes for SparseCountSparseOutput |
SparseCross | Generates sparse cross from a list of sparse and dense tensors. |
SparseCrossHashed | Generates sparse cross from a list of sparse and dense tensors. |
SparseDenseCwiseAdd <T extends TType > | Adds up a SparseTensor and a dense Tensor, using these special rules: (1) Broadcasts the dense side to have the same shape as the sparse side, if eligible; (2) Then, only the dense values pointed to by the indices of the SparseTensor participate in the cwise addition. |
SparseDenseCwiseDiv <T extends TType > | Component-wise divides a SparseTensor by a dense Tensor. |
SparseDenseCwiseMul <T extends TType > | Component-wise multiplies a SparseTensor by a dense Tensor. |
SparseFillEmptyRows <T extends TType > | Fills empty rows in the input 2-D `SparseTensor` with a default value. |
SparseFillEmptyRowsGrad <T extends TType > | The gradient of SparseFillEmptyRows. |
SparseMatMul | Multiply matrix "a" by matrix "b". |
SparseMatMul.Options | Optional attributes for SparseMatMul |
SparseMatrixAdd | Sparse addition of two CSR matrices, C = alpha * A + beta * B. |
SparseMatrixMatMul <T extends TType > | Matrix-multiplies a sparse matrix with a dense matrix. |
SparseMatrixMatMul.Options | Optional attributes for SparseMatrixMatMul |
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`. |
SparseMatrixSparseMatMul.Options | Optional attributes for SparseMatrixSparseMatMul |
SparseMatrixTranspose | Transposes the inner (matrix) dimensions of a CSRSparseMatrix. |
SparseMatrixTranspose.Options | Optional attributes for SparseMatrixTranspose |
SparseMatrixZeros | Creates an all-zeros CSRSparseMatrix with shape `dense_shape`. |
SparseReduceMax <T extends TNumber > | Computes the max of elements across dimensions of a SparseTensor. |
SparseReduceMax.Options | Optional attributes for SparseReduceMax |
SparseReduceMaxSparse <T extends TNumber > | Computes the max of elements across dimensions of a SparseTensor. |
SparseReduceMaxSparse.Options | Optional attributes for SparseReduceMaxSparse |
SparseReduceSum <T extends TType > | Computes the sum of elements across dimensions of a SparseTensor. |
SparseReduceSum.Options | Optional attributes for SparseReduceSum |
SparseReduceSumSparse <T extends TType > | Computes the sum of elements across dimensions of a SparseTensor. |
SparseReduceSumSparse.Options | Optional attributes for SparseReduceSumSparse |
SparseReorder <T extends TType > | Reorders a SparseTensor into the canonical, row-major ordering. |
SparseReshape | Reshapes a SparseTensor to represent values in a new dense shape. |
SparseSegmentMean <T extends TNumber > | Computes the mean along sparse segments of a tensor. |
SparseSegmentMeanGrad <T extends TNumber > | Computes gradients for SparseSegmentMean. |
SparseSegmentMeanWithNumSegments <T extends TNumber > | Computes the mean along sparse segments of a tensor. |
SparseSegmentSqrtN <T extends TNumber > | Computes the sum along sparse segments of a tensor divided by the sqrt of N. |
SparseSegmentSqrtNGrad <T extends TNumber > | Computes gradients for SparseSegmentSqrtN. |
SparseSegmentSqrtNWithNumSegments <T extends TNumber > | Computes the sum along sparse segments of a tensor divided by the sqrt of N. |
SparseSegmentSum <T extends TNumber > | Computes the sum along sparse segments of a tensor. |
SparseSegmentSumWithNumSegments <T extends TNumber > | Computes the sum along sparse segments of a tensor. |
SparseSlice <T extends TType > | Slice a `SparseTensor` based on the `start` and `size`. |
SparseSliceGrad <T extends TType > | The gradient operator for the SparseSlice op. |
SparseSoftmax <T extends TNumber > | Applies softmax to a batched ND `SparseTensor`. |
SparseSoftmaxCrossEntropyWithLogits | |
SparseSoftmaxCrossEntropyWithLogits <T extends TNumber > | Computes softmax cross entropy cost and gradients to backpropagate. |
SparseSparseMaximum <T extends TNumber > | Returns the element-wise max of two SparseTensors. |
SparseSparseMinimum <T extends TType > | Returns the element-wise min of two SparseTensors. |
SparseSplit <T extends TType > | Split a `SparseTensor` into `num_split` tensors along one dimension. |
SparseTensorDenseAdd <U extends TType > | Adds up a `SparseTensor` and a dense `Tensor`, producing a dense `Tensor`. |
SparseTensorDenseMatMul <U extends TType > | Multiply SparseTensor (of rank 2) "A" by dense matrix "B". |
SparseTensorDenseMatMul.Options | Optional attributes for SparseTensorDenseMatMul |
SparseTensorSliceDataset | Creates a dataset that splits a SparseTensor into elements row-wise. |
SparseTensorToCSRSparseMatrix | Converts a SparseTensor to a (possibly batched) CSRSparseMatrix. |
SparseToDense <U extends TType > | Converts a sparse representation into a dense tensor. |
SparseToDense.Options | Optional attributes for SparseToDense |
SparseToSparseSetOperation <T extends TType > | Applies set operation along last dimension of 2 `SparseTensor` inputs. |
SparseToSparseSetOperation.Options | Optional attributes for SparseToSparseSetOperation |
SpecializedType | For identifying the underlying type of a variant. |
Spence <T extends TNumber > | |
Split <T extends TType > | Splits a tensor into `num_split` tensors along one dimension. |
SplitV <T extends TType > | Splits a tensor into `num_split` tensors along one dimension. |
SqlDataset | Creates a dataset that executes a SQL query and emits rows of the result set. |
SqlDataset | Creates a dataset that executes a SQL query and emits rows of the result set. |
Sqrt <T extends TType > | Computes square root of x element-wise. |
SqrtGrad <T extends TType > | Computes the gradient for the sqrt of `x` wrt its input. |
Sqrtm <T extends TType > | Computes the matrix square root of one or more square matrices: matmul(sqrtm(A), sqrtm(A)) = A The input matrix should be invertible. |
Square <T extends TType > | Computes square of x element-wise. |
SquaredDifference <T extends TType > | Returns conj(x - y)(x - y) element-wise. |
SquaredHinge | Computes the squared hinge loss between labels and predictions. |
SquaredHinge <T extends TNumber > | A metric that computes the squared hinge loss metric between labels and predictions. |
Squeeze <T extends TType > | Removes dimensions of size 1 from the shape of a tensor. |
Squeeze.Options | Optional attributes for Squeeze |
Stack <T extends TType > | Packs a list of `N` rank-`R` tensors into one rank-`(R+1)` tensor. |
Stack.Options | Optional attributes for Stack |
StackFrameWithId | A stack frame with ID. |
StackFrameWithId.Builder | A stack frame with ID. |
StackFrameWithIdOrBuilder | |
منصة | Stage values similar to a lightweight Enqueue. |
Stage.Options | Optional attributes for Stage |
StageClear | Op removes all elements in the underlying container. |
StageClear.Options | Optional attributes for StageClear |
StagePeek | Op peeks at the values at the specified index. |
StagePeek.Options | Optional attributes for StagePeek |
StageSize | Op returns the number of elements in the underlying container. |
StageSize.Options | Optional attributes for StageSize |
StatefulRandomBinomial <V extends TNumber > | |
StatefulStandardNormal <U extends TType > | Outputs random values from a normal distribution. |
StatefulTruncatedNormal <U extends TType > | Outputs random values from a truncated normal distribution. |
StatefulUniform <U extends TType > | Outputs random values from a uniform distribution. |
StatefulUniformFullInt <U extends TType > | Outputs random integers from a uniform distribution. |
StatefulUniformInt <U extends TType > | Outputs random integers from a uniform distribution. |
StatelessMultinomial <V extends TNumber > | Draws samples from a multinomial distribution. |
StatelessParameterizedTruncatedNormal <V extends TNumber > | |
StatelessRandomBinomial <W extends TNumber > | Outputs deterministic pseudorandom random numbers from a binomial distribution. |
StatelessRandomGamma <V extends TNumber > | Outputs deterministic pseudorandom random numbers from a gamma distribution. |
StatelessRandomGetKeyCounterAlg | Picks the best algorithm based on device, and scrambles seed into key and counter. |
StatelessRandomNormal <V extends TNumber > | Outputs deterministic pseudorandom values from a normal distribution. |
StatelessRandomNormalV2 <U extends TNumber > | Outputs deterministic pseudorandom values from a normal distribution. |
StatelessRandomPoisson <W extends TNumber > | Outputs deterministic pseudorandom random numbers from a Poisson distribution. |
StatelessRandomUniform <V extends TNumber > | Outputs deterministic pseudorandom random values from a uniform distribution. |
StatelessRandomUniformFullInt <V extends TNumber > | Outputs deterministic pseudorandom random integers from a uniform distribution. |
StatelessRandomUniformFullIntV2 <U extends TNumber > | Outputs deterministic pseudorandom random integers from a uniform distribution. |
StatelessRandomUniformInt <V extends TNumber > | Outputs deterministic pseudorandom random integers from a uniform distribution. |
StatelessRandomUniformIntV2 <U extends TNumber > | Outputs deterministic pseudorandom random integers from a uniform distribution. |
StatelessRandomUniformV2 <U extends TNumber > | Outputs deterministic pseudorandom random values from a uniform distribution. |
StatelessSampleDistortedBoundingBox <T extends TNumber > | Generate a randomly distorted bounding box for an image deterministically. |
StatelessSampleDistortedBoundingBox.Options | Optional attributes for StatelessSampleDistortedBoundingBox |
StatelessTruncatedNormal <V extends TNumber > | Outputs deterministic pseudorandom values from a truncated normal distribution. |
StatelessTruncatedNormalV2 <U extends TNumber > | Outputs deterministic pseudorandom values from a truncated normal distribution. |
StaticRegexFullMatch | Check if the input matches the regex pattern. |
StaticRegexReplace | Replaces the match of pattern in input with rewrite. |
StaticRegexReplace.Options | Optional attributes for StaticRegexReplace |
StatsAggregatorHandle | Creates a statistics manager resource. |
StatsAggregatorHandle | |
StatsAggregatorHandle.Options | Optional attributes for StatsAggregatorHandle |
StatsAggregatorHandle.Options | Optional attributes for StatsAggregatorHandle |
StatsAggregatorSetSummaryWriter | Set a summary_writer_interface to record statistics using given stats_aggregator. |
StatsAggregatorSummary | Produces a summary of any statistics recorded by the given statistics manager. |
StatsAggregatorSummary | Produces a summary of any statistics recorded by the given statistics manager. |
StdArrays | Utility class for working with NdArray instances mixed with standard Java arrays. |
StepStats | Protobuf type tensorflow.StepStats |
StepStats.Builder | Protobuf type tensorflow.StepStats |
StepStatsOrBuilder | |
StepStatsProtos | |
StopGradient <T extends TType > | Stops gradient computation. |
StridedSlice <T extends TType > | Return a strided slice from `input`. |
StridedSlice.Options | Optional attributes for StridedSlice |
StridedSliceAssign <T extends TType > | Assign `value` to the sliced l-value reference of `ref`. |
StridedSliceAssign.Options | Optional attributes for StridedSliceAssign |
StridedSliceGrad <U extends TType > | Returns the gradient of `StridedSlice`. |
StridedSliceGrad.Options | Optional attributes for StridedSliceGrad |
StridedSliceHelper | Helper endpoint methods for Python like indexing. |
StringFormat | Formats a string template using a list of tensors. |
StringFormat.Options | Optional attributes for StringFormat |
StringLayout | Data layout that converts a String to/from a sequence of bytes applying a given charset. |
StringLength | String lengths of `input`. |
StringLength.Options | Optional attributes for StringLength |
StringNGrams <T extends TNumber > | Creates ngrams from ragged string data. |
StringSplit | Split elements of `source` based on `sep` into a `SparseTensor`. |
StringSplit.Options | Optional attributes for StringSplit |
يجرد | Strip leading and trailing whitespaces from the Tensor. |
StructProtos | |
StructuredValue | `StructuredValue` represents a dynamically typed value representing various data structures that are inspired by Python data structures typically used in TensorFlow functions as inputs and outputs. |
StructuredValue.Builder | `StructuredValue` represents a dynamically typed value representing various data structures that are inspired by Python data structures typically used in TensorFlow functions as inputs and outputs. |
StructuredValue.KindCase | |
StructuredValueOrBuilder | |
Sub <T extends TType > | Returns x - y element-wise. |
شارع فرعي | Return substrings from `Tensor` of strings. |
Substr.Options | Optional attributes for Substr |
Sum <T extends TType > | Computes the sum of elements across dimensions of a tensor. |
Sum.Options | Optional attributes for Sum |
ملخص | A Summary is a set of named values to be displayed by the visualizer. |
Summary.Audio | Protobuf type tensorflow.Summary.Audio |
Summary.Audio.Builder | Protobuf type tensorflow.Summary.Audio |
Summary.AudioOrBuilder | |
Summary.Builder | A Summary is a set of named values to be displayed by the visualizer. |
Summary.Image | Protobuf type tensorflow.Summary.Image |
Summary.Image.Builder | Protobuf type tensorflow.Summary.Image |
Summary.ImageOrBuilder | |
Summary.Value | Protobuf type tensorflow.Summary.Value |
Summary.Value.Builder | Protobuf type tensorflow.Summary.Value |
Summary.Value.ValueCase | |
Summary.ValueOrBuilder | |
SummaryDescription | Metadata associated with a series of Summary dataProtobuf type tensorflow.SummaryDescription |
SummaryDescription.Builder | Metadata associated with a series of Summary dataProtobuf type tensorflow.SummaryDescription |
SummaryDescriptionOrBuilder | |
SummaryMetadata | A SummaryMetadata encapsulates information on which plugins are able to make use of a certain summary value. |
SummaryMetadata.Builder | A SummaryMetadata encapsulates information on which plugins are able to make use of a certain summary value. |
SummaryMetadata.PluginData | Protobuf type tensorflow.SummaryMetadata.PluginData |
SummaryMetadata.PluginData.Builder | Protobuf type tensorflow.SummaryMetadata.PluginData |
SummaryMetadata.PluginDataOrBuilder | |
SummaryMetadataOrBuilder | |
SummaryOrBuilder | |
SummaryProtos | |
SummaryWriter | |
SummaryWriter.Options | Optional attributes for SummaryWriter |
Svd <T extends TType > | Computes the singular value decompositions of one or more matrices. |
Svd <T extends TType > | Computes the eigen decomposition of a batch of self-adjoint matrices (Note: Only real inputs are supported). |
Svd.Options | Optional attributes for Svd |
Swish <T extends TFloating > | Swish activation function. |
SwitchCond <T extends TType > | Forwards `data` to the output port determined by `pred`. |
ت
TaggedRunMetadata | For logging the metadata output for a single session.run() call. |
TaggedRunMetadata.Builder | For logging the metadata output for a single session.run() call. |
TaggedRunMetadataOrBuilder | |
TakeDataset | |
TakeDataset | Creates a dataset that contains `count` elements from the `input_dataset`. |
TakeManySparseFromTensorsMap <T extends TType > | Read `SparseTensors` from a `SparseTensorsMap` and concatenate them. |
TakeManySparseFromTensorsMap.Options | Optional attributes for TakeManySparseFromTensorsMap |
Tan <T extends TType > | Computes tan of x element-wise. |
Tanh <T extends TFloating > | Hyperbolic tangent activation function. |
Tanh <T extends TType > | Computes hyperbolic tangent of `x` element-wise. |
TanhGrad <T extends TType > | Computes the gradient for the tanh of `x` wrt its input. |
TaskDeviceFilters | Defines the device filters for a remote task. |
TaskDeviceFilters.Builder | Defines the device filters for a remote task. |
TaskDeviceFiltersOrBuilder | |
TBfloat16 | Brain 16-bit float tensor type. |
TBfloat16Mapper | Maps memory of DT_BFLOAT16 tensors to a n-dimensional data space. |
TBool | Boolean tensor type. |
TBoolMapper | Maps memory of DT_BOOL tensors to a n-dimensional data space. |
TemporaryVariable <T extends TType > | Returns a tensor that may be mutated, but only persists within a single step. |
TemporaryVariable.Options | Optional attributes for TemporaryVariable |
Tensor | A statically typed multi-dimensional array. |
Tensor | |
TensorArray | An array of Tensors of given size. |
TensorArray.Options | Optional attributes for TensorArray |
TensorArrayClose | Delete the TensorArray from its resource container. |
TensorArrayConcat <T extends TType > | Concat the elements from the TensorArray into value `value`. |
TensorArrayConcat.Options | Optional attributes for TensorArrayConcat |
TensorArrayGather <T extends TType > | Gather specific elements from the TensorArray into output `value`. |
TensorArrayGather.Options | Optional attributes for TensorArrayGather |
TensorArrayGrad | Creates a TensorArray for storing the gradients of values in the given handle. |
TensorArrayGradWithShape | Creates a TensorArray for storing multiple gradients of values in the given handle. |
TensorArrayPack <T extends TType > | |
TensorArrayPack.Options | Optional attributes for TensorArrayPack |
TensorArrayRead <T extends TType > | Read an element from the TensorArray into output `value`. |
TensorArrayScatter | Scatter the data from the input value into specific TensorArray elements. |
TensorArraySize | Get the current size of the TensorArray. |
TensorArraySplit | Split the data from the input value into TensorArray elements. |
TensorArrayUnpack | |
TensorArrayWrite | Push an element onto the tensor_array. |
TensorBuffers | Maps native tensor memory into DataBuffers , allowing I/O operations from the JVM. |
TensorBundleProtos | |
TensorConnection | Defines a connection between two tensors in a `GraphDef`. |
TensorConnection.Builder | Defines a connection between two tensors in a `GraphDef`. |
TensorConnectionOrBuilder | |
TensorDataset | Creates a dataset that emits `components` as a tuple of tensors once. |
TensorDebugMode | Available modes for extracting debugging information from a Tensor. |
TensorDescription | Protobuf type tensorflow.TensorDescription |
TensorDescription.Builder | Protobuf type tensorflow.TensorDescription |
TensorDescriptionOrBuilder | |
TensorDescriptionProtos | |
TensorDiag <T extends TType > | Returns a diagonal tensor with a given diagonal values. |
TensorDiagPart <T extends TType > | Returns the diagonal part of the tensor. |
TensorFlow | Static utility methods describing the TensorFlow runtime. |
com.tensorflow | |
com.tensorflow | |
TensorFlowException | Unchecked exception thrown by TensorFlow core classes |
TensorForestCreateTreeVariable | Creates a tree resource and returns a handle to it. |
TensorForestTreeDeserialize | Deserializes a proto into the tree handle |
TensorForestTreeIsInitializedOp | Checks whether a tree has been initialized. |
TensorForestTreePredict | Output the logits for the given input data |
TensorForestTreeResourceHandleOp | Creates a handle to a TensorForestTreeResource |
TensorForestTreeResourceHandleOp.Options | Optional attributes for TensorForestTreeResourceHandleOp |
TensorForestTreeSerialize | Serializes the tree handle to a proto |
TensorForestTreeSize | Get the number of nodes in a tree |
TensorInfo | Information about a Tensor necessary for feeding or retrieval. |
TensorInfo.Builder | Information about a Tensor necessary for feeding or retrieval. |
TensorInfo.CompositeTensor | Generic encoding for composite tensors. |
TensorInfo.CompositeTensor.Builder | Generic encoding for composite tensors. |
TensorInfo.CompositeTensorOrBuilder | |
TensorInfo.CooSparse | For sparse tensors, The COO encoding stores a triple of values, indices, and shape. |
TensorInfo.CooSparse.Builder | For sparse tensors, The COO encoding stores a triple of values, indices, and shape. |
TensorInfo.CooSparseOrBuilder | |
TensorInfo.EncodingCase | |
TensorInfoOrBuilder | |
TensorListConcat <U extends TType > | Concats all tensors in the list along the 0th dimension. |
TensorListConcatLists | |
TensorListElementShape <T extends TNumber > | The shape of the elements of the given list, as a tensor. |
TensorListFromTensor | Creates a TensorList which, when stacked, has the value of `tensor`. |
TensorListGather <T extends TType > | Creates a Tensor by indexing into the TensorList. |
TensorListGetItem <T extends TType > | |
TensorListLength | Returns the number of tensors in the input tensor list. |
TensorListPopBack <T extends TType > | Returns the last element of the input list as well as a list with all but that element. |
TensorListPushBack | Returns a list which has the passed-in `Tensor` as last element and the other elements of the given list in `input_handle`. |
TensorListPushBackBatch | |
TensorListReserve | List of the given size with empty elements. |
TensorListResize | Resizes the list. |
TensorListScatter | Creates a TensorList by indexing into a Tensor. |
TensorListScatterIntoExistingList | Scatters tensor at indices in an input list. |
TensorListSetItem | |
TensorListSplit | Splits a tensor into a list. |
TensorListStack <T extends TType > | Stacks all tensors in the list. |
TensorListStack.Options | Optional attributes for TensorListStack |
TensorMapErase | Returns a tensor map with item from given key erased. |
TensorMapHasKey | Returns whether the given key exists in the map. |
TensorMapInsert | Returns a map that is the 'input_handle' with the given key-value pair inserted. |
TensorMapLookup <U extends TType > | Returns the value from a given key in a tensor map. |
TensorMapper <T extends TType > | Maps the native memory of a RawTensor to a n-dimensional typed data space accessible from the JVM. |
TensorMapSize | Returns the number of tensors in the input tensor map. |
TensorMapStackKeys <T extends TType > | Returns a Tensor stack of all keys in a tensor map. |
TensorMetadata | Metadata for a single tensor in the Snapshot Record. |
TensorMetadata.Builder | Metadata for a single tensor in the Snapshot Record. |
TensorMetadataOrBuilder | |
TensorProto | Protocol buffer representing a tensor. |
TensorProto.Builder | Protocol buffer representing a tensor. |
TensorProtoOrBuilder | |
TensorProtos | |
TensorScatterNdAdd <T extends TType > | Adds sparse `updates` to an existing tensor according to `indices`. |
TensorScatterNdMax <T extends TType > | |
TensorScatterNdMin <T extends TType > | |
TensorScatterNdSub <T extends TType > | Subtracts sparse `updates` from an existing tensor according to `indices`. |
TensorScatterNdUpdate <T extends TType > | Scatter `updates` into an existing tensor according to `indices`. |
TensorShapeProto | Dimensions of a tensor. |
TensorShapeProto.Builder | Dimensions of a tensor. |
TensorShapeProto.Dim | One dimension of the tensor. |
TensorShapeProto.Dim.Builder | One dimension of the tensor. |
TensorShapeProto.DimOrBuilder | |
TensorShapeProtoOrBuilder | |
TensorShapeProtos | |
TensorSliceDataset | |
TensorSliceDataset | Creates a dataset that emits each dim-0 slice of `components` once. |
TensorSliceProto | Can only be interpreted if you know the corresponding TensorShape. |
TensorSliceProto.Builder | Can only be interpreted if you know the corresponding TensorShape. |
TensorSliceProto.Extent | Extent of the slice in one dimension. |
TensorSliceProto.Extent.Builder | Extent of the slice in one dimension. |
TensorSliceProto.Extent.HasLengthCase | |
TensorSliceProto.ExtentOrBuilder | |
TensorSliceProtoOrBuilder | |
TensorSliceProtos | |
TensorSpecProto | A protobuf to represent tf.TensorSpec. |
TensorSpecProto.Builder | A protobuf to represent tf.TensorSpec. |
TensorSpecProtoOrBuilder | |
TensorStridedSliceUpdate <T extends TType > | Assign `value` to the sliced l-value reference of `input`. |
TensorStridedSliceUpdate.Options | Optional attributes for TensorStridedSliceUpdate |
TensorSummary | Outputs a `Summary` protocol buffer with a tensor and per-plugin data. |
TensorType | Annotation for all tensor types. |
TensorTypeInfo <T extends TType > | Registered information about a tensor type. |
TensorTypeRegistry | Repository of all registered tensor types. |
TestLogProtos | |
TestResults | The output of one benchmark / test run. |
TestResults.BenchmarkType | The type of benchmark. |
TestResults.Builder | The output of one benchmark / test run. |
TestResultsOrBuilder | |
TextLineDataset | |
TextLineDataset | Creates a dataset that emits the lines of one or more text files. |
TextLineReader | A Reader that outputs the lines of a file delimited by '\n'. |
TextLineReader.Options | Optional attributes for TextLineReader |
TF_AllocatorAttributes | |
TF_ApiDefMap | |
TF_AttrMetadata | |
TF_Buffer | |
TF_Buffer.Data_deallocator_Pointer_long | |
TF_DeprecatedSession | |
TF_DeviceList | |
TF_DimensionHandle | |
TF_Function | |
TF_FunctionOptions | |
TF_Graph | |
TF_ImportGraphDefOptions | |
TF_ImportGraphDefResults | |
TF_Input | |
TF_KernelBuilder | |
TF_Library | |
TF_OpDefinitionBuilder | |
TF_Operation | |
TF_OperationDescription | |
TF_OpKernelConstruction | |
TF_OpKernelContext | |
TF_Output | |
TF_Server | |
TF_Session | |
TF_SessionOptions | |
TF_ShapeHandle | |
TF_ShapeInferenceContext | |
TF_Status | |
TF_StringView | |
TF_Tensor | |
TF_TString | |
TF_TString_Large | |
TF_TString_Offset | |
TF_TString_Raw | |
TF_TString_Small | |
TF_TString_Union | |
TF_TString_View | |
TF_WhileParams | |
TFE_Context | |
TFE_ContextOptions | |
TFE_Op | |
TFE_TensorDebugInfo | |
TFE_TensorHandle | |
TFFailedPreconditionException | |
TFInvalidArgumentException | |
TFloat16 | IEEE-754 half-precision 16-bit float tensor type. |
TFloat16Mapper | Maps memory of DT_HALF tensors to a n-dimensional data space. |
TFloat32 | IEEE-754 single-precision 32-bit float tensor type. |
TFloat32Mapper | Maps memory of DT_FLOAT tensors to a n-dimensional data space. |
TFloat64 | IEEE-754 double-precision 64-bit float tensor type. |
TFloat64Mapper | Maps memory of DT_DOUBLE tensors to a n-dimensional data space. |
TFloating | Common interface for all floating point tensors. |
TFOutOfRangeException | |
TFPermissionDeniedException | |
TfRecordDataset | Creates a dataset that emits the records from one or more TFRecord files. |
TFRecordDataset | |
TfRecordReader | A Reader that outputs the records from a TensorFlow Records file. |
TfRecordReader.Options | Optional attributes for TfRecordReader |
TFResourceExhaustedException | |
TFUnauthenticatedException | |
TFUnimplementedException | |
ThreadPoolDataset | Creates a dataset that uses a custom thread pool to compute `input_dataset`. |
ThreadPoolDataset | Creates a dataset that uses a custom thread pool to compute `input_dataset`. |
ThreadPoolHandle | Creates a dataset that uses a custom thread pool to compute `input_dataset`. |
ThreadPoolHandle | Creates a dataset that uses a custom thread pool to compute `input_dataset`. |
ThreadPoolHandle.Options | Optional attributes for ThreadPoolHandle |
ThreadPoolHandle.Options | Optional attributes for ThreadPoolHandle |
ThreadPoolOptionProto | Protobuf type tensorflow.ThreadPoolOptionProto |
ThreadPoolOptionProto.Builder | Protobuf type tensorflow.ThreadPoolOptionProto |
ThreadPoolOptionProtoOrBuilder | |
Tile <T extends TType > | Constructs a tensor by tiling a given tensor. |
TileGrad <T extends TType > | Returns the gradient of `Tile`. |
الطابع الزمني | Provides the time since epoch in seconds. |
TInt32 | 32-bit signed integer tensor type. |
TInt32Mapper | Maps memory of DT_INT32 tensors to a n-dimensional data space. |
TInt64 | 64-bit signed integer tensor type. |
TInt64Mapper | Maps memory of DT_INT64 tensors to a n-dimensional data space. |
TIntegral | Common interface for all integral numeric tensors. |
TNumber | Common interface for all numeric tensors. |
ToBool | Converts a tensor to a scalar predicate. |
ToHashBucket | Converts each string in the input Tensor to its hash mod by a number of buckets. |
ToHashBucketFast | Converts each string in the input Tensor to its hash mod by a number of buckets. |
ToHashBucketStrong | Converts each string in the input Tensor to its hash mod by a number of buckets. |
ToNumber <T extends TNumber > | Converts each string in the input Tensor to the specified numeric type. |
TopK <T extends TNumber > | Finds values and indices of the `k` largest elements for the last dimension. |
TopK.Options | Optional attributes for TopK |
TopKUnique | Returns the TopK unique values in the array in sorted order. |
TopKWithUnique | Returns the TopK values in the array in sorted order. |
TPUCompilationResult | Returns the result of a TPU compilation. |
TPUEmbeddingActivations | An op enabling differentiation of TPU Embeddings. |
TPUReplicatedInput <T extends TType > | Connects N inputs to an N-way replicated TPU computation. |
TPUReplicatedInput.Options | Optional attributes for TPUReplicatedInput |
TPUReplicatedOutput <T extends TType > | Connects N outputs from an N-way replicated TPU computation. |
TPUReplicateMetadata | Metadata indicating how the TPU computation should be replicated. |
TPUReplicateMetadata.Options | Optional attributes for TPUReplicateMetadata |
TrackableObjectGraph | Protobuf type tensorflow.TrackableObjectGraph |
TrackableObjectGraph.Builder | Protobuf type tensorflow.TrackableObjectGraph |
TrackableObjectGraph.TrackableObject | Protobuf type tensorflow.TrackableObjectGraph.TrackableObject |
TrackableObjectGraph.TrackableObject.Builder | Protobuf type tensorflow.TrackableObjectGraph.TrackableObject |
TrackableObjectGraph.TrackableObject.ObjectReference | Protobuf type tensorflow.TrackableObjectGraph.TrackableObject.ObjectReference |
TrackableObjectGraph.TrackableObject.ObjectReference.Builder | Protobuf type tensorflow.TrackableObjectGraph.TrackableObject.ObjectReference |
TrackableObjectGraph.TrackableObject.ObjectReferenceOrBuilder | |
TrackableObjectGraph.TrackableObject.SerializedTensor | Protobuf type tensorflow.TrackableObjectGraph.TrackableObject.SerializedTensor |
TrackableObjectGraph.TrackableObject.SerializedTensor.Builder | Protobuf type tensorflow.TrackableObjectGraph.TrackableObject.SerializedTensor |
TrackableObjectGraph.TrackableObject.SerializedTensorOrBuilder | |
TrackableObjectGraph.TrackableObject.SlotVariableReference | Protobuf type tensorflow.TrackableObjectGraph.TrackableObject.SlotVariableReference |
TrackableObjectGraph.TrackableObject.SlotVariableReference.Builder | Protobuf type tensorflow.TrackableObjectGraph.TrackableObject.SlotVariableReference |
TrackableObjectGraph.TrackableObject.SlotVariableReferenceOrBuilder | |
TrackableObjectGraph.TrackableObjectOrBuilder | |
TrackableObjectGraphOrBuilder | |
TrackableObjectGraphProtos | |
TransportOptions | |
TransportOptions.RecvBufRespExtra | Extra data needed on a non-RDMA RecvBufResponse. |
TransportOptions.RecvBufRespExtra.Builder | Extra data needed on a non-RDMA RecvBufResponse. |
TransportOptions.RecvBufRespExtraOrBuilder | |
Transpose <T extends TType > | Shuffle dimensions of x according to a permutation. |
TriangularSolve <T extends TType > | Solves systems of linear equations with upper or lower triangular matrices by backsubstitution. |
TriangularSolve.Options | Optional attributes for TriangularSolve |
TridiagonalMatMul <T extends TType > | Calculate product with tridiagonal matrix. |
TridiagonalSolve <T extends TType > | Solves tridiagonal systems of equations. |
TridiagonalSolve.Options | Optional attributes for TridiagonalSolve |
TruncateDiv <T extends TType > | Returns x / y element-wise for integer types. |
TruncatedNormal <T extends TFloating > | Initializer that generates a truncated normal distribution. |
TruncatedNormal <U extends TNumber > | Outputs random values from a truncated normal distribution. |
TruncatedNormal.Options | Optional attributes for TruncatedNormal |
TruncateMod <T extends TNumber > | Returns element-wise remainder of division. |
TryRpc | Perform batches of RPC requests. |
TryRpc.Options | Optional attributes for TryRpc |
TString | String type. |
TStringInitializer <T> | Helper class for initializing a TString tensor. |
TStringMapper | Maps memory of DT_STRING tensors to a n-dimensional data space. |
TType | Common interface for all typed tensors. |
TUint8 | 8-bit unsigned integer tensor type. |
TUint8Mapper | Maps memory of DT_UINT8 tensors to a n-dimensional data space. |
TupleValue | Represents a Python tuple. |
TupleValue.Builder | Represents a Python tuple. |
TupleValueOrBuilder | |
TypeSpecProto | Represents a tf.TypeSpecProtobuf type tensorflow.TypeSpecProto |
TypeSpecProto.Builder | Represents a tf.TypeSpecProtobuf type tensorflow.TypeSpecProto |
TypeSpecProto.TypeSpecClass | Protobuf enum tensorflow.TypeSpecProto.TypeSpecClass |
TypeSpecProtoOrBuilder | |
TypesProtos |
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Unbatch <T extends TType > | Reverses the operation of Batch for a single output Tensor. |
Unbatch.Options | Optional attributes for Unbatch |
UnbatchDataset | A dataset that splits the elements of its input into multiple elements. |
UnbatchDataset | A dataset that splits the elements of its input into multiple elements. |
UnbatchGrad <T extends TType > | Gradient of Unbatch. |
UnbatchGrad.Options | Optional attributes for UnbatchGrad |
UncompressElement | Uncompresses a compressed dataset element. |
UnicodeDecode <T extends TNumber > | Decodes each string in `input` into a sequence of Unicode code points. |
UnicodeDecode.Options | Optional attributes for UnicodeDecode |
UnicodeDecodeWithOffsets <T extends TNumber > | Decodes each string in `input` into a sequence of Unicode code points. |
UnicodeDecodeWithOffsets.Options | Optional attributes for UnicodeDecodeWithOffsets |
UnicodeEncode | Encode a tensor of ints into unicode strings. |
UnicodeEncode.Options | Optional attributes for UnicodeEncode |
UnicodeScript | Determine the script codes of a given tensor of Unicode integer code points. |
UnicodeTranscode | Transcode the input text from a source encoding to a destination encoding. |
UnicodeTranscode.Options | Optional attributes for UnicodeTranscode |
UniformCandidateSampler | Generates labels for candidate sampling with a uniform distribution. |
UniformCandidateSampler.Options | Optional attributes for UniformCandidateSampler |
Unique <T extends TType , V extends TNumber > | Finds unique elements along an axis of a tensor. |
UniqueDataset | Creates a dataset that contains the unique elements of `input_dataset`. |
UniqueDataset | Creates a dataset that contains the unique elements of `input_dataset`. |
UniqueWithCounts <T extends TType , V extends TNumber > | Finds unique elements along an axis of a tensor. |
UnitNorm | Constrains the weights to have unit norm. |
UnravelIndex <T extends TNumber > | Converts an array of flat indices into a tuple of coordinate arrays. |
UnsortedSegmentJoin | Joins the elements of `inputs` based on `segment_ids`. |
UnsortedSegmentJoin.Options | Optional attributes for UnsortedSegmentJoin |
UnsortedSegmentMax <T extends TNumber > | Computes the maximum along segments of a tensor. |
UnsortedSegmentMin <T extends TNumber > | Computes the minimum along segments of a tensor. |
UnsortedSegmentProd <T extends TType > | Computes the product along segments of a tensor. |
UnsortedSegmentSum <T extends TType > | Computes the sum along segments of a tensor. |
Unstack <T extends TType > | Unpacks a given dimension of a rank-`R` tensor into `num` rank-`(R-1)` tensors. |
Unstack.Options | Optional attributes for Unstack |
Unstage | Op is similar to a lightweight Dequeue. |
Unstage.Options | Optional attributes for Unstage |
UnwrapDatasetVariant | |
العلوي | Converts all lowercase characters into their respective uppercase replacements. |
Upper.Options | Optional attributes for Upper |
UpperBound <U extends TNumber > | Applies upper_bound(sorted_search_values, values) along each row. |
V
المدقق | |
المدقق | |
ValuesDef | Protocol buffer representing the values in ControlFlowContext. |
ValuesDef.Builder | Protocol buffer representing the values in ControlFlowContext. |
ValuesDefOrBuilder | |
VarHandleOp | Creates a handle to a Variable resource. |
VarHandleOp.Options | Optional attributes for VarHandleOp |
Variable <T extends TType > | Holds state in the form of a tensor that persists across steps. |
Variable.Options | Optional attributes for Variable |
VariableAggregation | Indicates how a distributed variable will be aggregated. |
VariableDef | Protocol buffer representing a Variable. |
VariableDef.Builder | Protocol buffer representing a Variable. |
VariableDefOrBuilder | |
VariableProtos | |
VariableShape <T extends TNumber > | Returns the shape of the variable pointed to by `resource`. |
VariableSynchronization | Indicates when a distributed variable will be synced. |
VarianceScaling <T extends TFloating > | Initializer capable of adapting its scale to the shape of weights tensors. |
VarianceScaling.Distribution | The random distribution to use when initializing the values. |
VarianceScaling.Mode | The mode to use for calculating the fan values. |
VariantTensorDataProto | Protocol buffer representing the serialization format of DT_VARIANT tensors. |
VariantTensorDataProto.Builder | Protocol buffer representing the serialization format of DT_VARIANT tensors. |
VariantTensorDataProtoOrBuilder | |
VarIsInitializedOp | Checks whether a resource handle-based variable has been initialized. |
VarLenFeatureProto | Protobuf type tensorflow.VarLenFeatureProto |
VarLenFeatureProto.Builder | Protobuf type tensorflow.VarLenFeatureProto |
VarLenFeatureProtoOrBuilder | |
VerifierConfig | The config for graph verifiers. |
VerifierConfig.Builder | The config for graph verifiers. |
VerifierConfig.Toggle | Protobuf enum tensorflow.VerifierConfig.Toggle |
VerifierConfigOrBuilder | |
VerifierConfigProtos | |
VersionDef | Version information for a piece of serialized data There are different types of versions for each type of data (GraphDef, etc.), but they all have the same common shape described here. |
VersionDef.Builder | Version information for a piece of serialized data There are different types of versions for each type of data (GraphDef, etc.), but they all have the same common shape described here. |
VersionDefOrBuilder | |
VersionsProtos |
دبليو
WatchdogConfig | Protobuf type tensorflow.WatchdogConfig |
WatchdogConfig.Builder | Protobuf type tensorflow.WatchdogConfig |
WatchdogConfigOrBuilder | |
WeakPointerScope | A minimalist pointer scope only keeping weak references to its elements. |
أين | Returns locations of nonzero / true values in a tensor. |
WhileContextDef | Protocol buffer representing a WhileContext object. |
WhileContextDef.Builder | Protocol buffer representing a WhileContext object. |
WhileContextDefOrBuilder | |
WholeFileReader | A Reader that outputs the entire contents of a file as a value. |
WholeFileReader.Options | Optional attributes for WholeFileReader |
WindowDataset | Combines (nests of) input elements into a dataset of (nests of) windows. |
WorkerHealth | Current health status of a worker. |
WorkerHeartbeat | Worker heartbeat op. |
WorkerHeartbeatRequest | Protobuf type tensorflow.WorkerHeartbeatRequest |
WorkerHeartbeatRequest.Builder | Protobuf type tensorflow.WorkerHeartbeatRequest |
WorkerHeartbeatRequestOrBuilder | |
WorkerHeartbeatResponse | Protobuf type tensorflow.WorkerHeartbeatResponse |
WorkerHeartbeatResponse.Builder | Protobuf type tensorflow.WorkerHeartbeatResponse |
WorkerHeartbeatResponseOrBuilder | |
WorkerShutdownMode | Indicates the behavior of the worker when an internal error or shutdown signal is received. |
WrapDatasetVariant | |
WriteAudioSummary | Writes an audio summary. |
WriteAudioSummary.Options | Optional attributes for WriteAudioSummary |
WriteFile | Writes contents to the file at input filename. |
WriteGraphSummary | Writes a graph summary. |
WriteHistogramSummary | Writes a histogram summary. |
WriteImageSummary | Writes an image summary. |
WriteImageSummary.Options | Optional attributes for WriteImageSummary |
WriteRawProtoSummary | Writes a serialized proto summary. |
WriteScalarSummary | Writes a scalar summary. |
WriteSummary | Writes a tensor summary. |
X
Xdivy <T extends TType > | Returns 0 if x == 0, and x / y otherwise, elementwise. |
XEvent | An XEvent is a trace event, optionally annotated with XStats. |
XEvent.Builder | An XEvent is a trace event, optionally annotated with XStats. |
XEvent.DataCase | |
XEventMetadata | Metadata for an XEvent, corresponds to an event type and is shared by all XEvents with the same metadata_id. |
XEventMetadata.Builder | Metadata for an XEvent, corresponds to an event type and is shared by all XEvents with the same metadata_id. |
XEventMetadataOrBuilder | |
XEventOrBuilder | |
XlaRecvFromHost <T extends TType > | An op to receive a tensor from the host. |
XlaSendToHost | An op to send a tensor to the host. |
XlaSetBound | Set a bound for the given input value as a hint to Xla compiler, returns the same value. |
XlaSpmdFullToShardShape <T extends TType > | An op used by XLA SPMD partitioner to switch from automatic partitioning to manual partitioning. |
XlaSpmdShardToFullShape <T extends TType > | An op used by XLA SPMD partitioner to switch from manual partitioning to automatic partitioning. |
XLine | An XLine is a timeline of trace events (XEvents). |
XLine.Builder | An XLine is a timeline of trace events (XEvents). |
XLineOrBuilder | |
Xlog1py <T extends TType > | Returns 0 if x == 0, and x * log1p(y) otherwise, elementwise. |
Xlogy <T extends TType > | Returns 0 if x == 0, and x * log(y) otherwise, elementwise. |
XPlane | An XPlane is a container of parallel timelines (XLines), generated by a profiling source or by post-processing one or more XPlanes. |
XPlane.Builder | An XPlane is a container of parallel timelines (XLines), generated by a profiling source or by post-processing one or more XPlanes. |
XPlaneOrBuilder | |
XPlaneProtos | |
XSpace | A container of parallel XPlanes, generated by one or more profiling sources. |
XSpace.Builder | A container of parallel XPlanes, generated by one or more profiling sources. |
XSpaceOrBuilder | |
XStat | An XStat is a named value associated with an XEvent, e.g., a performance counter value, a metric computed by a formula applied over nested XEvents and XStats. |
XStat.Builder | An XStat is a named value associated with an XEvent, e.g., a performance counter value, a metric computed by a formula applied over nested XEvents and XStats. |
XStat.ValueCase | |
XStatMetadata | Metadata for an XStat, corresponds to a stat type and is shared by all XStats with the same metadata_id. |
XStatMetadata.Builder | Metadata for an XStat, corresponds to a stat type and is shared by all XStats with the same metadata_id. |
XStatMetadataOrBuilder | |
XStatOrBuilder |
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Zeros <T extends TType > | Creates an Initializer that sets all values to zero. |
Zeros <T extends TType > | An operator creating a constant initialized with zeros of the shape given by `dims`. |
ZerosLike <T extends TType > | Returns a tensor of zeros with the same shape and type as x. |
Zeta <T extends TNumber > | Compute the Hurwitz zeta function \\(\zeta(x, q)\\). |
ZipDataset | Creates a dataset that zips together `input_datasets`. |