---
title: TensorFlow 1.15 API支持列表
description: "本章节列出AI处理器对TensorFlow 1.15版本Python API的支持情况。"
url: https://www.hiascend.com/document/detail/zh/TensorFlowCommercial/latest/migration/tfmigr1/tfmigr1_tfadapi_0131.html
sourcePath: /source/zh/TensorFlowCommercial/900/migration/tfmigr1/tfmigr1_tfadapi_0131.html
indexId: 9dc0902eb875804347b3617bc530e1c645d033b8f266c88a5e356b8f665fda8b79
---
# TensorFlow 1.15 API支持列表

本章节列出AI处理器对TensorFlow 1.15版本Python API的支持情况。

#### 支持的Python API

以下列表是支持的TensorFlow Python API集合列表，但此列表并不详尽。

| 模块 | 支持的Python API |
| --- | --- |
| tf | tf.abs |
| tf | tf.accumulate\_n |
| tf | tf.acos |
| tf | tf.acosh |
| tf | tf.add |
| tf | tf.add\_check\_numerics\_ops |
| tf | tf.add\_n |
| tf | tf.add\_to\_collection |
| tf | tf.add\_to\_collections |
| tf | tf.all\_variables |
| tf | tf.angle |
| tf | tf.arg\_max |
| tf | tf.arg\_min |
| tf | tf.argmax |
| tf | tf.argmin |
| tf | tf.argsort |
| tf | tf.as\_dtype |
| tf | tf.as\_string |
| tf | tf.asin |
| tf | tf.asinh |
| tf | tf.Assert |
| tf | tf.assert\_equal |
| tf | tf.assert\_greater |
| tf | tf.assert\_greater\_equal |
| tf | tf.assert\_integer |
| tf | tf.assert\_less |
| tf | tf.assert\_less\_equal |
| tf | tf.assert\_near |
| tf | tf.assert\_negative |
| tf | tf.assert\_non\_negative |
| tf | tf.assert\_non\_positive |
| tf | tf.assert\_none\_equal |
| tf | tf.assert\_positive |
| tf | tf.assert\_proper\_iterable |
| tf | tf.assert\_rank |
| tf | tf.assert\_rank\_at\_least |
| tf | tf.assert\_rank\_in |
| tf | tf.assert\_same\_float\_dtype |
| tf | tf.assert\_scalar |
| tf | tf.assert\_type |
| tf | tf.assert\_variables\_initialized |
| tf | tf.assign |
| tf | tf.assign\_add |
| tf | tf.assign\_sub |
| tf | tf.atan |
| tf | tf.atan2 |
| tf | tf.atanh |
| tf | tf.AttrValue |
| tf | tf.AttrValue.ListValue |
| tf | tf.batch\_gather |
| tf | tf.batch\_scatter\_update |
| tf | tf.batch\_to\_space |
| tf | tf.batch\_to\_space\_nd |
| tf | tf.betainc |
| tf | tf.bincount |
| tf | tf.bitcast |
| tf | tf.boolean\_mask |
| tf | tf.broadcast\_dynamic\_shape |
| tf | tf.broadcast\_static\_shape |
| tf | tf.broadcast\_to |
| tf | tf.case |
| tf | tf.cast |
| tf | tf.ceil |
| tf | tf.check\_numerics |
| tf | tf.cholesky |
| tf | tf.cholesky\_solve |
| tf | tf.clip\_by\_average\_norm |
| tf | tf.clip\_by\_global\_norm |
| tf | tf.clip\_by\_norm |
| tf | tf.clip\_by\_value |
| tf | tf.complex |
| tf | tf.concat |
| tf | tf.cond |
| tf | tf.ConditionalAccumulator |
| tf | tf.ConfigProto |
| tf | tf.confusion\_matrix |
| tf | tf.conj |
| tf | tf.constant |
| tf | tf.constant\_initializer |
| tf | tf.container |
| tf | tf.control\_dependencies |
| tf | tf.control\_flow\_v2\_enabled |
| tf | tf.convert\_to\_tensor |
| tf | tf.cos |
| tf | tf.cosh |
| tf | tf.count\_nonzero |
| tf | tf.count\_up\_to |
| tf | tf.create\_partitioned\_variables |
| tf | tf.cross |
| tf | tf.cumprod |
| tf | tf.cumsum |
| tf | tf.custom\_gradient |
| tf | tf.decode\_csv |
| tf | tf.decode\_raw |
| tf | tf.delete\_session\_tensor |
| tf | tf.depth\_to\_space |
| tf | tf.device |
| tf | tf.DeviceSpec |
| tf | tf.diag |
| tf | tf.diag\_part |
| tf | tf.digamma |
| tf | tf.Dimension |
| tf | tf.dimension\_value |
| tf | tf.disable\_control\_flow\_v2 |
| tf | tf.disable\_eager\_execution |
| tf | tf.disable\_resource\_variables |
| tf | tf.disable\_tensor\_equality |
| tf | tf.disable\_v2\_behavior |
| tf | tf.disable\_v2\_tensorshape |
| tf | tf.div |
| tf | tf.div\_no\_nan |
| tf | tf.divide |
| tf | tf.DType |
| tf | tf.dynamic\_partition |
| tf | tf.dynamic\_stitch |
| tf | tf.edit\_distance |
| tf | tf.einsum |
| tf | tf.enable\_control\_flow\_v2 |
| tf | tf.enable\_resource\_variables |
| tf | tf.ensure\_shape |
| tf | tf.equal |
| tf | tf.erf |
| tf | tf.erfc |
| tf | tf.exp |
| tf | tf.expand\_dims |
| tf | tf.expm1 |
| tf | tf.extract\_image\_patches |
| tf | tf.extract\_volume\_patches |
| tf | tf.eye |
| tf | tf.fake\_quant\_with\_min\_max\_args |
| tf | tf.fake\_quant\_with\_min\_max\_args\_gradient |
| tf | tf.fft |
| tf | tf.fft2d |
| tf | tf.fft3d |
| tf | tf.FIFOQueue |
| tf | tf.fill |
| tf | tf.fingerprint |
| tf | tf.fixed\_size\_partitioner |
| tf | tf.FixedLenFeature |
| tf | tf.FixedLengthRecordReader |
| tf | tf.floor |
| tf | tf.floor\_div |
| tf | tf.floordiv |
| tf | tf.floormod |
| tf | tf.foldl |
| tf | tf.foldr |
| tf | tf.function |
| tf | tf.gather |
| tf | tf.gather\_nd |
| tf | tf.get\_collection |
| tf | tf.get\_collection\_ref |
| tf | tf.get\_default\_graph |
| tf | tf.get\_default\_session |
| tf | tf.get\_local\_variable |
| tf | tf.get\_logger |
| tf | tf.get\_seed |
| tf | tf.get\_session\_handle |
| tf | tf.get\_session\_tensor |
| tf | tf.get\_static\_value |
| tf | tf.get\_variable |
| tf | tf.get\_variable\_scope |
| tf | tf.global\_norm |
| tf | tf.global\_variables |
| tf | tf.global\_variables\_initializer |
| tf | tf.glorot\_normal\_initializer |
| tf | tf.glorot\_uniform\_initializer |
| tf | tf.GPUOptions |
| tf | tf.grad\_pass\_through |
| tf | tf.gradients |
| tf | tf.GradientTape |
| tf | tf.Graph |
| tf | tf.GraphDef |
| tf | tf.GraphKeys |
| tf | tf.greater |
| tf | tf.greater\_equal |
| tf | tf.group |
| tf | tf.guarantee\_const |
| tf | tf.hessians |
| tf | tf.histogram\_fixed\_width |
| tf | tf.histogram\_fixed\_width\_bins |
| tf | tf.identity |
| tf | tf.identity\_n |
| tf | tf.ifft |
| tf | tf.ifft2d |
| tf | tf.ifft3d |
| tf | tf.igamma |
| tf | tf.igammac |
| tf | tf.imag |
| tf | tf.image.ResizeMethod |
| tf | tf.import\_graph\_def |
| tf | tf.IndexedSlices |
| tf | tf.init\_scope |
| tf | tf.initialize\_all\_tables |
| tf | tf.initialize\_all\_variables |
| tf | tf.initialize\_local\_variables |
| tf | tf.initialize\_variables |
| tf | tf.InteractiveSession |
| tf | tf.invert\_permutation |
| tf | tf.is\_non\_decreasing |
| tf | tf.is\_numeric\_tensor |
| tf | tf.is\_strictly\_increasing |
| tf | tf.is\_tensor |
| tf | tf.is\_variable\_initialized |
| tf | tf.lbeta |
| tf | tf.less |
| tf | tf.less\_equal |
| tf | tf.lgamma |
| tf | tf.lin\_space |
| tf | tf.linspace |
| tf | tf.load\_file\_system\_library |
| tf | tf.load\_library |
| tf | tf.load\_op\_library |
| tf | tf.local\_variables |
| tf | tf.local\_variables\_initializer |
| tf | tf.log |
| tf | tf.log\_sigmoid |
| tf | tf.log1p |
| tf | tf.logical\_and |
| tf | tf.logical\_not |
| tf | tf.logical\_or |
| tf | tf.logical\_xor |
| tf | tf.LogMessage |
| tf | tf.make\_ndarray |
| tf | tf.make\_template |
| tf | tf.make\_tensor\_proto |
| tf | tf.map\_fn |
| tf | tf.matmul |
| tf | tf.matrix\_band\_part |
| tf | tf.matrix\_determinant |
| tf | tf.matrix\_diag |
| tf | tf.matrix\_diag\_part |
| tf | tf.matrix\_inverse |
| tf | tf.matrix\_set\_diag |
| tf | tf.matrix\_solve |
| tf | tf.matrix\_solve\_ls |
| tf | tf.matrix\_square\_root |
| tf | tf.matrix\_transpose |
| tf | tf.matrix\_triangular\_solve |
| tf | tf.maximum |
| tf | tf.meshgrid |
| tf | tf.min\_max\_variable\_partitioner |
| tf | tf.minimum |
| tf | tf.mod |
| tf | tf.model\_variables |
| tf | tf.Module |
| tf | tf.moving\_average\_variables |
| tf | tf.multinomial |
| tf | tf.multiply |
| tf | tf.name\_scope |
| tf | tf.negative |
| tf | tf.no\_op |
| tf | tf.norm |
| tf | tf.not\_equal |
| tf | tf.numpy\_function |
| tf | tf.one\_hot |
| tf | tf.ones |
| tf | tf.ones\_initializer |
| tf | tf.ones\_like |
| tf | tf.op\_scope |
| tf | tf.Operation |
| tf | tf.OptimizerOptions |
| tf | tf.orthogonal\_initializer |
| tf | tf.pad |
| tf | tf.PaddingFIFOQueue |
| tf | tf.parallel\_stack |
| tf | tf.parse\_single\_example |
| tf | tf.placeholder |
| tf | tf.placeholder\_with\_default |
| tf | tf.polygamma |
| tf | tf.pow |
| tf | tf.Print |
| tf | tf.print |
| tf | tf.PriorityQueue |
| tf | tf.py\_func |
| tf | tf.py\_function |
| tf | tf.qr |
| tf | tf.quantize\_v2 |
| tf | tf.RaggedTensor |
| tf | tf.RaggedTensorSpec |
| tf | tf.RandomShuffleQueue |
| tf | tf.range |
| tf | tf.rank |
| tf | tf.read\_file |
| tf | tf.ReaderBase |
| tf | tf.real |
| tf | tf.realdiv |
| tf | tf.reciprocal |
| tf | tf.recompute\_grad |
| tf | tf.reduce\_all |
| tf | tf.reduce\_any |
| tf | tf.reduce\_join |
| tf | tf.reduce\_logsumexp |
| tf | tf.reduce\_max |
| tf | tf.reduce\_mean |
| tf | tf.reduce\_min |
| tf | tf.reduce\_prod |
| tf | tf.reduce\_sum |
| tf | tf.regex\_replace |
| tf | tf.register\_tensor\_conversion\_function |
| tf | tf.RegisterGradient |
| tf | tf.repeat |
| tf | tf.report\_uninitialized\_variables |
| tf | tf.required\_space\_to\_batch\_paddings |
| tf | tf.reset\_default\_graph |
| tf | tf.reshape |
| tf | tf.reverse |
| tf | tf.reverse\_sequence |
| tf | tf.reverse\_v2 |
| tf | tf.rint |
| tf | tf.roll |
| tf | tf.round |
| tf | tf.rsqrt |
| tf | tf.RunMetadata |
| tf | tf.RunOptions |
| tf | tf.saturate\_cast |
| tf | tf.scalar\_mul |
| tf | tf.scan |
| tf | tf.scatter\_add |
| tf | tf.scatter\_div |
| tf | tf.scatter\_max |
| tf | tf.scatter\_min |
| tf | tf.scatter\_mul |
| tf | tf.scatter\_nd |
| tf | tf.scatter\_nd\_add |
| tf | tf.scatter\_nd\_sub |
| tf | tf.scatter\_nd\_update |
| tf | tf.scatter\_sub |
| tf | tf.scatter\_update |
| tf | tf.searchsorted |
| tf | tf.segment\_max |
| tf | tf.segment\_mean |
| tf | tf.segment\_min |
| tf | tf.segment\_prod |
| tf | tf.segment\_sum |
| tf | tf.self\_adjoint\_eig |
| tf | tf.self\_adjoint\_eigvals |
| tf | tf.sequence\_mask |
| tf | tf.Session |
| tf | tf.set\_random\_seed |
| tf | tf.setdiff1d |
| tf | tf.shape |
| tf | tf.shape\_n |
| tf | tf.sigmoid |
| tf | tf.sign |
| tf | tf.sin |
| tf | tf.sinh |
| tf | tf.size |
| tf | tf.slice |
| tf | tf.sort |
| tf | tf.space\_to\_batch |
| tf | tf.space\_to\_batch\_nd |
| tf | tf.space\_to\_depth |
| tf | tf.sparse\_add |
| tf | tf.sparse\_concat |
| tf | tf.sparse\_fill\_empty\_rows |
| tf | tf.sparse\_mask |
| tf | tf.sparse\_matmul |
| tf | tf.sparse\_maximum |
| tf | tf.sparse\_merge |
| tf | tf.sparse\_minimum |
| tf | tf.sparse\_placeholder |
| tf | tf.sparse\_reduce\_max |
| tf | tf.sparse\_reduce\_max\_sparse |
| tf | tf.sparse\_reduce\_sum |
| tf | tf.sparse\_reduce\_sum\_sparse |
| tf | tf.sparse\_reorder |
| tf | tf.sparse\_reset\_shape |
| tf | tf.sparse\_reshape |
| tf | tf.sparse\_retain |
| tf | tf.sparse\_segment\_mean |
| tf | tf.sparse\_segment\_sqrt\_n |
| tf | tf.sparse\_segment\_sum |
| tf | tf.sparse\_slice |
| tf | tf.sparse\_softmax |
| tf | tf.sparse\_split |
| tf | tf.sparse\_tensor\_dense\_matmul |
| tf | tf.sparse\_tensor\_to\_dense |
| tf | tf.sparse\_to\_dense |
| tf | tf.sparse\_to\_indicator |
| tf | tf.sparse\_transpose |
| tf | tf.SparseConditionalAccumulator |
| tf | tf.SparseTensor |
| tf | tf.SparseTensorSpec |
| tf | tf.SparseTensorValue |
| tf | tf.split |
| tf | tf.sqrt |
| tf | tf.square |
| tf | tf.squared\_difference |
| tf | tf.squeeze |
| tf | tf.stack |
| tf | tf.stop\_gradient |
| tf | tf.strided\_slice |
| tf | tf.string\_join |
| tf | tf.string\_split |
| tf | tf.string\_strip |
| tf | tf.string\_to\_hash\_bucket |
| tf | tf.string\_to\_hash\_bucket\_fast |
| tf | tf.string\_to\_hash\_bucket\_strong |
| tf | tf.string\_to\_number |
| tf | tf.substr |
| tf | tf.subtract |
| tf | tf.Summary |
| tf | tf.Summary.Value |
| tf | tf.svd |
| tf | tf.switch\_case |
| tf | tf.tables\_initializer |
| tf | tf.tan |
| tf | tf.tanh |
| tf | tf.Tensor |
| tf | tf.tensor\_scatter\_add |
| tf | tf.tensor\_scatter\_nd\_add |
| tf | tf.tensor\_scatter\_nd\_sub |
| tf | tf.tensor\_scatter\_nd\_update |
| tf | tf.tensor\_scatter\_sub |
| tf | tf.tensor\_scatter\_update |
| tf | tf.TensorArray |
| tf | tf.tensordot |
| tf | tf.TensorShape |
| tf | tf.TensorSpec |
| tf | tf.TextLineReader |
| tf | tf.TFRecordReader |
| tf | tf.tile |
| tf | tf.timestamp |
| tf | tf.to\_bfloat16 |
| tf | tf.to\_complex128 |
| tf | tf.to\_complex64 |
| tf | tf.to\_double |
| tf | tf.to\_float |
| tf | tf.to\_int32 |
| tf | tf.to\_int64 |
| tf | tf.trace |
| tf | tf.transpose |
| tf | tf.truediv |
| tf | tf.truncated\_normal |
| tf | tf.truncated\_normal\_initializer |
| tf | tf.truncatediv |
| tf | tf.truncatemod |
| tf | tf.tuple |
| tf | tf.TypeSpec |
| tf | tf.uniform\_unit\_scaling\_initializer |
| tf | tf.unique |
| tf | tf.unique\_with\_counts |
| tf | tf.unravel\_index |
| tf | tf.unsorted\_segment\_max |
| tf | tf.unsorted\_segment\_mean |
| tf | tf.unsorted\_segment\_min |
| tf | tf.unsorted\_segment\_prod |
| tf | tf.unsorted\_segment\_sqrt\_n |
| tf | tf.unsorted\_segment\_sum |
| tf | tf.unstack |
| tf | tf.Variable |
| tf | tf.Variable.SaveSliceInfo |
| tf | tf.variable\_axis\_size\_partitioner |
| tf | tf.variable\_scope |
| tf | tf.variables\_initializer |
| tf | tf.variance\_scaling\_initializer |
| tf | tf.VarLenFeature |
| tf | tf.vectorized\_map |
| tf | tf.verify\_tensor\_all\_finite |
| tf | tf.where |
| tf | tf.where\_v2 |
| tf | tf.while\_loop |
| tf | tf.zeros |
| tf | tf.zeros\_initializer |
| tf | tf.zeros\_like |
| tf | tf.zeta |
| tf.app | tf.app.run |
| tf.audio | tf.audio.decode\_wav |
| tf.audio | tf.audio.encode\_wav |
| tf.autograph | tf.autograph.experimental.do\_not\_convert |
| tf.autograph | tf.autograph.experimental.Feature |
| tf.autograph | tf.autograph.set\_verbosity |
| tf.autograph | tf.autograph.to\_code |
| tf.autograph | tf.autograph.to\_graph |
| tf.autograph | tf.autograph.trace |
| tf.bitwise | tf.bitwise.bitwise\_and |
| tf.bitwise | tf.bitwise.bitwise\_or |
| tf.bitwise | tf.bitwise.bitwise\_xor |
| tf.bitwise | tf.bitwise.invert |
| tf.bitwise | tf.bitwise.left\_shift |
| tf.bitwise | tf.bitwise.right\_shift |
| tf.compat | tf.compat.as\_bytes |
| tf.compat | tf.compat.as\_str |
| tf.compat | tf.compat.as\_str\_any |
| tf.compat | tf.compat.as\_text |
| tf.compat | tf.compat.dimension\_at\_index |
| tf.compat | tf.compat.dimension\_value |
| tf.compat | tf.compat.forward\_compatibility\_horizon |
| tf.compat | tf.compat.forward\_compatible |
| tf.compat | tf.compat.path\_to\_str |
| tf.contrib | tf.contrib.data.map\_and\_batch |
| tf.contrib | tf.contrib.data.parallel\_interleave |
| tf.contrib | tf.contrib.graph\_editor.add\_control\_inputs |
| tf.contrib | tf.contrib.graph\_editor.copy\_with\_input\_replacements |
| tf.contrib | tf.contrib.graph\_editor.filter\_ts |
| tf.contrib | tf.contrib.graph\_editor.filter\_ts\_from\_regex |
| tf.contrib | tf.contrib.graph\_editor.get\_backward\_walk\_ops |
| tf.contrib | tf.contrib.graph\_editor.reroute\_ts |
| tf.contrib | tf.contrib.tpu.TPUEstimator |
| tf.contrib | tf.contrib.tpu.TPUEstimatorSpec |
| tf.data | tf.data.Dataset |
| tf.data | tf.data.experimental.cardinality |
| tf.data | tf.data.experimental.group\_by\_window |
| tf.data | tf.data.experimental.map\_and\_batch |
| tf.data | tf.data.experimental.parallel\_interleave |
| tf.data | tf.data.experimental.prefetch\_to\_device |
| tf.data | tf.data.experimental.sample\_from\_datasets |
| tf.data | tf.data.experimental.shuffle\_and\_repeat |
| tf.data | tf.data.FixedLengthRecordDataset |
| tf.data | tf.data.Iterator |
| tf.data | tf.data.make\_initializable\_iterator |
| tf.data | tf.data.make\_one\_shot\_iterator |
| tf.data | tf.data.Options |
| tf.data | tf.data.TextLineDataset |
| tf.data | tf.data.TFRecordDataset |
| tf.debugging | tf.debugging.Assert |
| tf.debugging | tf.debugging.assert\_all\_finite |
| tf.debugging | tf.debugging.assert\_equal |
| tf.debugging | tf.debugging.assert\_greater |
| tf.debugging | tf.debugging.assert\_greater\_equal |
| tf.debugging | tf.debugging.assert\_integer |
| tf.debugging | tf.debugging.assert\_less |
| tf.debugging | tf.debugging.assert\_less\_equal |
| tf.debugging | tf.debugging.assert\_near |
| tf.debugging | tf.debugging.assert\_negative |
| tf.debugging | tf.debugging.assert\_non\_negative |
| tf.debugging | tf.debugging.assert\_non\_positive |
| tf.debugging | tf.debugging.assert\_none\_equal |
| tf.debugging | tf.debugging.assert\_positive |
| tf.debugging | tf.debugging.assert\_proper\_iterable |
| tf.debugging | tf.debugging.assert\_rank |
| tf.debugging | tf.debugging.assert\_rank\_at\_least |
| tf.debugging | tf.debugging.assert\_rank\_in |
| tf.debugging | tf.debugging.assert\_same\_float\_dtype |
| tf.debugging | tf.debugging.assert\_scalar |
| tf.debugging | tf.debugging.assert\_shapes |
| tf.debugging | tf.debugging.assert\_type |
| tf.debugging | tf.debugging.check\_numerics |
| tf.debugging | tf.debugging.get\_log\_device\_placement |
| tf.debugging | tf.debugging.is\_finite |
| tf.debugging | tf.debugging.is\_inf |
| tf.debugging | tf.debugging.is\_nan |
| tf.debugging | tf.debugging.is\_non\_decreasing |
| tf.debugging | tf.debugging.is\_numeric\_tensor |
| tf.debugging | tf.debugging.is\_strictly\_increasing |
| tf.debugging | tf.debugging.set\_log\_device\_placement |
| tf.distribute | tf.distribute.CrossDeviceOps |
| tf.distribute | tf.distribute.experimental.CollectiveCommunication |
| tf.distribute | tf.distribute.HierarchicalCopyAllReduce |
| tf.distribute | tf.distribute.InputContext |
| tf.distribute | tf.distribute.NcclAllReduce |
| tf.distribute | tf.distribute.OneDeviceStrategy |
| tf.distribute | tf.distribute.Strategy |
| tf.distributions | tf.distributions.Bernoulli |
| tf.distributions | tf.distributions.Beta |
| tf.distributions | tf.distributions.Categorical |
| tf.distributions | tf.distributions.Dirichlet |
| tf.distributions | tf.distributions.DirichletMultinomial |
| tf.distributions | tf.distributions.Exponential |
| tf.distributions | tf.distributions.Gamma |
| tf.distributions | tf.distributions.Laplace |
| tf.distributions | tf.distributions.Multinomial |
| tf.distributions | tf.distributions.Normal |
| tf.distributions | tf.distributions.RegisterKL |
| tf.distributions | tf.distributions.StudentT |
| tf.distributions | tf.distributions.Uniform |
| tf.dtypes | tf.dtypes.as\_dtype |
| tf.dtypes | tf.dtypes.as\_string |
| tf.dtypes | tf.dtypes.cast |
| tf.dtypes | tf.dtypes.complex |
| tf.dtypes | tf.dtypes.DType |
| tf.dtypes | tf.dtypes.saturate\_cast |
| tf.errors | tf.errors.InvalidArgumentError |
| tf.errors | tf.errors.NotFoundError |
| tf.errors | tf.errors.OutOfRangeError |
| tf.errors | tf.errors.ResourceExhaustedError |
| tf.estimator | tf.estimator.add\_metrics |
| tf.estimator | tf.estimator.BaselineClassifier |
| tf.estimator | tf.estimator.BaselineEstimator |
| tf.estimator | tf.estimator.BaselineRegressor |
| tf.estimator | tf.estimator.BestExporter |
| tf.estimator | tf.estimator.BinaryClassHead |
| tf.estimator | tf.estimator.BoostedTreesClassifier |
| tf.estimator | tf.estimator.BoostedTreesEstimator |
| tf.estimator | tf.estimator.BoostedTreesRegressor |
| tf.estimator | tf.estimator.CheckpointSaverHook |
| tf.estimator | tf.estimator.CheckpointSaverListener |
| tf.estimator | tf.estimator.DNNClassifier |
| tf.estimator | tf.estimator.DNNEstimator |
| tf.estimator | tf.estimator.DNNLinearCombinedClassifier |
| tf.estimator | tf.estimator.DNNLinearCombinedEstimator |
| tf.estimator | tf.estimator.DNNLinearCombinedRegressor |
| tf.estimator | tf.estimator.DNNRegressor |
| tf.estimator | tf.estimator.Estimator |
| tf.estimator | tf.estimator.EstimatorSpec |
| tf.estimator | tf.estimator.EvalSpec |
| tf.estimator | tf.estimator.FeedFnHook |
| tf.estimator | tf.estimator.FinalOpsHook |
| tf.estimator | tf.estimator.GlobalStepWaiterHook |
| tf.estimator | tf.estimator.inputs.numpy\_input\_fn |
| tf.estimator | tf.estimator.LinearClassifier |
| tf.estimator | tf.estimator.LinearEstimator |
| tf.estimator | tf.estimator.LinearRegressor |
| tf.estimator | tf.estimator.LoggingTensorHook |
| tf.estimator | tf.estimator.ModeKeys |
| tf.estimator | tf.estimator.ProfilerHook |
| tf.estimator | tf.estimator.RunConfig |
| tf.estimator | tf.estimator.SecondOrStepTimer |
| tf.estimator | tf.estimator.SessionRunArgs |
| tf.estimator | tf.estimator.SessionRunContext |
| tf.estimator | tf.estimator.SessionRunHook |
| tf.estimator | tf.estimator.SessionRunValues |
| tf.estimator | tf.estimator.StepCounterHook |
| tf.estimator | tf.estimator.StopAtStepHook |
| tf.estimator | tf.estimator.SummarySaverHook |
| tf.estimator | tf.estimator.tpu.RunConfig |
| tf.estimator | tf.estimator.tpu.TPUEstimator |
| tf.estimator | tf.estimator.train\_and\_evaluate |
| tf.estimator | tf.estimator.TrainSpec |
| tf.estimator | tf.estimator.VocabInfo |
| tf.feature\_column | tf.feature\_column.bucketized\_column |
| tf.feature\_column | tf.feature\_column.categorical\_column\_with\_hash\_bucket |
| tf.feature\_column | tf.feature\_column.categorical\_column\_with\_identity |
| tf.feature\_column | tf.feature\_column.categorical\_column\_with\_vocabulary\_file |
| tf.feature\_column | tf.feature\_column.categorical\_column\_with\_vocabulary\_list |
| tf.feature\_column | tf.feature\_column.crossed\_column |
| tf.feature\_column | tf.feature\_column.embedding\_column |
| tf.feature\_column | tf.feature\_column.indicator\_column |
| tf.feature\_column | tf.feature\_column.input\_layer |
| tf.feature\_column | tf.feature\_column.linear\_model |
| tf.feature\_column | tf.feature\_column.make\_parse\_example\_spec |
| tf.feature\_column | tf.feature\_column.numeric\_column |
| tf.feature\_column | tf.feature\_column.sequence\_categorical\_column\_with\_hash\_bucket |
| tf.feature\_column | tf.feature\_column.sequence\_categorical\_column\_with\_identity |
| tf.feature\_column | tf.feature\_column.sequence\_categorical\_column\_with\_vocabulary\_file |
| tf.feature\_column | tf.feature\_column.sequence\_categorical\_column\_with\_vocabulary\_list |
| tf.feature\_column | tf.feature\_column.sequence\_numeric\_column |
| tf.feature\_column | tf.feature\_column.shared\_embedding\_columns |
| tf.feature\_column | tf.feature\_column.weighted\_categorical\_column |
| tf.gfile | tf.gfile.Copy |
| tf.gfile | tf.gfile.DeleteRecursively |
| tf.gfile | tf.gfile.Exists |
| tf.gfile | tf.gfile.FastGFile |
| tf.gfile | tf.gfile.GFile |
| tf.gfile | tf.gfile.Glob |
| tf.gfile | tf.gfile.IsDirectory |
| tf.gfile | tf.gfile.ListDirectory |
| tf.gfile | tf.gfile.MakeDirs |
| tf.gfile | tf.gfile.MkDir |
| tf.gfile | tf.gfile.Open |
| tf.gfile | tf.gfile.Remove |
| tf.gfile | tf.gfile.Rename |
| tf.gfile | tf.gfile.Stat |
| tf.gfile | tf.gfile.Walk |
| tf.graph\_util | tf.graph\_util.convert\_variables\_to\_constants |
| tf.graph\_util | tf.graph\_util.extract\_sub\_graph |
| tf.graph\_util | tf.graph\_util.import\_graph\_def |
| tf.graph\_util | tf.graph\_util.remove\_training\_nodes |
| tf.image | tf.image.combined\_non\_max\_suppression |
| tf.image | tf.image.convert\_image\_dtype |
| tf.image | tf.image.crop\_and\_resize |
| tf.image | tf.image.decode\_image |
| tf.image | tf.image.decode\_jpeg |
| tf.image | tf.image.decode\_png |
| tf.image | tf.image.draw\_bounding\_boxes |
| tf.image | tf.image.encode\_jpeg |
| tf.image | tf.image.extract\_image\_patches |
| tf.image | tf.image.is\_jpeg |
| tf.image | tf.image.non\_max\_suppression |
| tf.image | tf.image.pad\_to\_bounding\_box |
| tf.image | tf.image.psnr |
| tf.image | tf.image.random\_crop |
| tf.image | tf.image.random\_flip\_left\_right |
| tf.image | tf.image.resize |
| tf.image | tf.image.resize\_bilinear |
| tf.image | tf.image.resize\_image\_with\_crop\_or\_pad |
| tf.image | tf.image.resize\_image\_with\_pad |
| tf.image | tf.image.resize\_images |
| tf.image | tf.image.resize\_nearest\_neighbor |
| tf.image | tf.image.sample\_distorted\_bounding\_box |
| tf.image | tf.image.ssim |
| tf.initializers | tf.initializers.constant |
| tf.initializers | tf.initializers.global\_variables |
| tf.initializers | tf.initializers.glorot\_normal |
| tf.initializers | tf.initializers.glorot\_uniform |
| tf.initializers | tf.initializers.he\_normal |
| tf.initializers | tf.initializers.he\_uniform |
| tf.initializers | tf.initializers.identity |
| tf.initializers | tf.initializers.lecun\_normal |
| tf.initializers | tf.initializers.lecun\_uniform |
| tf.initializers | tf.initializers.local\_variables |
| tf.initializers | tf.initializers.ones |
| tf.initializers | tf.initializers.orthogonal |
| tf.initializers | tf.initializers.random\_normal |
| tf.initializers | tf.initializers.random\_uniform |
| tf.initializers | tf.initializers.tables\_initializer |
| tf.initializers | tf.initializers.truncated\_normal |
| tf.initializers | tf.initializers.uniform\_unit\_scaling |
| tf.initializers | tf.initializers.variables |
| tf.initializers | tf.initializers.variance\_scaling |
| tf.initializers | tf.initializers.zeros |
| tf.io | tf.io.decode\_csv |
| tf.io | tf.io.decode\_raw |
| tf.io | tf.io.FixedLenFeature |
| tf.io | tf.io.gfile.exists |
| tf.io | tf.io.gfile.GFile |
| tf.io | tf.io.gfile.glob |
| tf.io | tf.io.gfile.listdir |
| tf.io | tf.io.gfile.makedirs |
| tf.io | tf.io.PaddingFIFOQueue |
| tf.io | tf.io.parse\_single\_example |
| tf.io | tf.io.PriorityQueue |
| tf.io | tf.io.RandomShuffleQueue |
| tf.io | tf.io.read\_file |
| tf.io | tf.io.VarLenFeature |
| tf.io | tf.io.write\_graph |
| tf.keras | tf.keras.activations.deserialize |
| tf.keras | tf.keras.activations.elu |
| tf.keras | tf.keras.activations.exponential |
| tf.keras | tf.keras.activations.get |
| tf.keras | tf.keras.activations.hard\_sigmoid |
| tf.keras | tf.keras.activations.linear |
| tf.keras | tf.keras.activations.relu |
| tf.keras | tf.keras.activations.selu |
| tf.keras | tf.keras.activations.serialize |
| tf.keras | tf.keras.activations.sigmoid |
| tf.keras | tf.keras.activations.softmax |
| tf.keras | tf.keras.activations.softplus |
| tf.keras | tf.keras.activations.softsign |
| tf.keras | tf.keras.activations.tanh |
| tf.keras | tf.keras.applications.densenet |
| tf.keras | tf.keras.applications.densenet.decode\_predictions |
| tf.keras | tf.keras.applications.densenet.DenseNet121 |
| tf.keras | tf.keras.applications.densenet.DenseNet169 |
| tf.keras | tf.keras.applications.densenet.DenseNet201 |
| tf.keras | tf.keras.applications.densenet.preprocess\_input |
| tf.keras | tf.keras.applications.DenseNet121 |
| tf.keras | tf.keras.applications.DenseNet169 |
| tf.keras | tf.keras.applications.DenseNet201 |
| tf.keras | tf.keras.applications.imagenet\_utils |
| tf.keras | tf.keras.applications.imagenet\_utils.decode\_predictions |
| tf.keras | tf.keras.applications.imagenet\_utils.preprocess\_input |
| tf.keras | tf.keras.applications.inception\_resnet\_v2 |
| tf.keras | tf.keras.applications.inception\_resnet\_v2.decode\_predictions |
| tf.keras | tf.keras.applications.inception\_resnet\_v2.InceptionResNetV2 |
| tf.keras | tf.keras.applications.inception\_resnet\_v2.preprocess\_input |
| tf.keras | tf.keras.applications.inception\_v3 |
| tf.keras | tf.keras.applications.inception\_v3.decode\_predictions |
| tf.keras | tf.keras.applications.inception\_v3.InceptionV3 |
| tf.keras | tf.keras.applications.inception\_v3.preprocess\_input |
| tf.keras | tf.keras.applications.InceptionResNetV2 |
| tf.keras | tf.keras.applications.InceptionV3 |
| tf.keras | tf.keras.applications.MobileNet |
| tf.keras | tf.keras.applications.mobilenet |
| tf.keras | tf.keras.applications.mobilenet.decode\_predictions |
| tf.keras | tf.keras.applications.mobilenet.MobileNet |
| tf.keras | tf.keras.applications.mobilenet.preprocess\_input |
| tf.keras | tf.keras.applications.mobilenet\_v2 |
| tf.keras | tf.keras.applications.mobilenet\_v2.decode\_predictions |
| tf.keras | tf.keras.applications.mobilenet\_v2.MobileNetV2 |
| tf.keras | tf.keras.applications.mobilenet\_v2.preprocess\_input |
| tf.keras | tf.keras.applications.MobileNetV2 |
| tf.keras | tf.keras.applications.nasnet |
| tf.keras | tf.keras.applications.nasnet.preprocess\_input |
| tf.keras | tf.keras.applications.NASNetLarge |
| tf.keras | tf.keras.applications.NASNetMobile |
| tf.keras | tf.keras.applications.resnet |
| tf.keras | tf.keras.applications.resnet.decode\_predictions |
| tf.keras | tf.keras.applications.resnet.preprocess\_input |
| tf.keras | tf.keras.applications.resnet.ResNet101 |
| tf.keras | tf.keras.applications.resnet.ResNet152 |
| tf.keras | tf.keras.applications.resnet.ResNet50 |
| tf.keras | tf.keras.applications.resnet\_v2 |
| tf.keras | tf.keras.applications.resnet\_v2.decode\_predictions |
| tf.keras | tf.keras.applications.resnet\_v2.preprocess\_input |
| tf.keras | tf.keras.applications.resnet\_v2.ResNet101V2 |
| tf.keras | tf.keras.applications.resnet\_v2.ResNet152V2 |
| tf.keras | tf.keras.applications.resnet\_v2.ResNet50V2 |
| tf.keras | tf.keras.applications.ResNet101 |
| tf.keras | tf.keras.applications.ResNet101V2 |
| tf.keras | tf.keras.applications.ResNet152 |
| tf.keras | tf.keras.applications.ResNet152V2 |
| tf.keras | tf.keras.applications.ResNet50 |
| tf.keras | tf.keras.applications.resnet50 |
| tf.keras | tf.keras.applications.resnet50.decode\_predictions |
| tf.keras | tf.keras.applications.resnet50.preprocess\_input |
| tf.keras | tf.keras.applications.resnet50.ResNet50 |
| tf.keras | tf.keras.applications.ResNet50V2 |
| tf.keras | tf.keras.applications.VGG16 |
| tf.keras | tf.keras.applications.vgg16 |
| tf.keras | tf.keras.applications.vgg16.decode\_predictions |
| tf.keras | tf.keras.applications.vgg16.preprocess\_input |
| tf.keras | tf.keras.applications.vgg16.VGG16 |
| tf.keras | tf.keras.applications.VGG19 |
| tf.keras | tf.keras.applications.vgg19 |
| tf.keras | tf.keras.applications.vgg19.decode\_predictions |
| tf.keras | tf.keras.applications.vgg19.preprocess\_input |
| tf.keras | tf.keras.applications.vgg19.VGG19 |
| tf.keras | tf.keras.applications.Xception |
| tf.keras | tf.keras.applications.xception |
| tf.keras | tf.keras.applications.xception.decode\_predictions |
| tf.keras | tf.keras.applications.xception.preprocess\_input |
| tf.keras | tf.keras.applications.xception.Xception |
| tf.keras | tf.keras.backend.abs |
| tf.keras | tf.keras.backend.all |
| tf.keras | tf.keras.backend.any |
| tf.keras | tf.keras.backend.arange |
| tf.keras | tf.keras.backend.argmax |
| tf.keras | tf.keras.backend.argmin |
| tf.keras | tf.keras.backend.backend |
| tf.keras | tf.keras.backend.batch\_dot |
| tf.keras | tf.keras.backend.batch\_flatten |
| tf.keras | tf.keras.backend.batch\_get\_value |
| tf.keras | tf.keras.backend.batch\_normalization |
| tf.keras | tf.keras.backend.batch\_set\_value |
| tf.keras | tf.keras.backend.bias\_add |
| tf.keras | tf.keras.backend.binary\_crossentropy |
| tf.keras | tf.keras.backend.cast |
| tf.keras | tf.keras.backend.cast\_to\_floatx |
| tf.keras | tf.keras.backend.categorical\_crossentropy |
| tf.keras | tf.keras.backend.clear\_session |
| tf.keras | tf.keras.backend.clip |
| tf.keras | tf.keras.backend.concatenate |
| tf.keras | tf.keras.backend.constant |
| tf.keras | tf.keras.backend.conv1d |
| tf.keras | tf.keras.backend.conv2d |
| tf.keras | tf.keras.backend.conv2d\_transpose |
| tf.keras | tf.keras.backend.conv3d |
| tf.keras | tf.keras.backend.cos |
| tf.keras | tf.keras.backend.count\_params |
| tf.keras | tf.keras.backend.ctc\_batch\_cost |
| tf.keras | tf.keras.backend.ctc\_decode |
| tf.keras | tf.keras.backend.ctc\_label\_dense\_to\_sparse |
| tf.keras | tf.keras.backend.cumprod |
| tf.keras | tf.keras.backend.cumsum |
| tf.keras | tf.keras.backend.dot |
| tf.keras | tf.keras.backend.dropout |
| tf.keras | tf.keras.backend.dtype |
| tf.keras | tf.keras.backend.elu |
| tf.keras | tf.keras.backend.epsilon |
| tf.keras | tf.keras.backend.equal |
| tf.keras | tf.keras.backend.eval |
| tf.keras | tf.keras.backend.exp |
| tf.keras | tf.keras.backend.expand\_dims |
| tf.keras | tf.keras.backend.eye |
| tf.keras | tf.keras.backend.flatten |
| tf.keras | tf.keras.backend.floatx |
| tf.keras | tf.keras.backend.foldl |
| tf.keras | tf.keras.backend.foldr |
| tf.keras | tf.keras.backend.function |
| tf.keras | tf.keras.backend.gather |
| tf.keras | tf.keras.backend.get\_session |
| tf.keras | tf.keras.backend.get\_uid |
| tf.keras | tf.keras.backend.get\_value |
| tf.keras | tf.keras.backend.gradients |
| tf.keras | tf.keras.backend.greater |
| tf.keras | tf.keras.backend.greater\_equal |
| tf.keras | tf.keras.backend.hard\_sigmoid |
| tf.keras | tf.keras.backend.image\_data\_format |
| tf.keras | tf.keras.backend.in\_test\_phase |
| tf.keras | tf.keras.backend.in\_top\_k |
| tf.keras | tf.keras.backend.in\_train\_phase |
| tf.keras | tf.keras.backend.int\_shape |
| tf.keras | tf.keras.backend.is\_sparse |
| tf.keras | tf.keras.backend.l2\_normalize |
| tf.keras | tf.keras.backend.learning\_phase |
| tf.keras | tf.keras.backend.learning\_phase\_scope |
| tf.keras | tf.keras.backend.less |
| tf.keras | tf.keras.backend.less\_equal |
| tf.keras | tf.keras.backend.local\_conv1d |
| tf.keras | tf.keras.backend.local\_conv2d |
| tf.keras | tf.keras.backend.log |
| tf.keras | tf.keras.backend.manual\_variable\_initialization |
| tf.keras | tf.keras.backend.map\_fn |
| tf.keras | tf.keras.backend.max |
| tf.keras | tf.keras.backend.maximum |
| tf.keras | tf.keras.backend.mean |
| tf.keras | tf.keras.backend.min |
| tf.keras | tf.keras.backend.minimum |
| tf.keras | tf.keras.backend.moving\_average\_update |
| tf.keras | tf.keras.backend.name\_scope |
| tf.keras | tf.keras.backend.ndim |
| tf.keras | tf.keras.backend.normalize\_batch\_in\_training |
| tf.keras | tf.keras.backend.not\_equal |
| tf.keras | tf.keras.backend.one\_hot |
| tf.keras | tf.keras.backend.ones |
| tf.keras | tf.keras.backend.ones\_like |
| tf.keras | tf.keras.backend.permute\_dimensions |
| tf.keras | tf.keras.backend.placeholder |
| tf.keras | tf.keras.backend.pool2d |
| tf.keras | tf.keras.backend.pool3d |
| tf.keras | tf.keras.backend.pow |
| tf.keras | tf.keras.backend.print\_tensor |
| tf.keras | tf.keras.backend.prod |
| tf.keras | tf.keras.backend.random\_binomial |
| tf.keras | tf.keras.backend.random\_normal |
| tf.keras | tf.keras.backend.random\_normal\_variable |
| tf.keras | tf.keras.backend.random\_uniform |
| tf.keras | tf.keras.backend.random\_uniform\_variable |
| tf.keras | tf.keras.backend.relu |
| tf.keras | tf.keras.backend.repeat |
| tf.keras | tf.keras.backend.repeat\_elements |
| tf.keras | tf.keras.backend.reset\_uids |
| tf.keras | tf.keras.backend.reshape |
| tf.keras | tf.keras.backend.resize\_images |
| tf.keras | tf.keras.backend.resize\_volumes |
| tf.keras | tf.keras.backend.reverse |
| tf.keras | tf.keras.backend.rnn |
| tf.keras | tf.keras.backend.round |
| tf.keras | tf.keras.backend.separable\_conv2d |
| tf.keras | tf.keras.backend.set\_epsilon |
| tf.keras | tf.keras.backend.set\_floatx |
| tf.keras | tf.keras.backend.set\_image\_data\_format |
| tf.keras | tf.keras.backend.set\_learning\_phase |
| tf.keras | tf.keras.backend.set\_session |
| tf.keras | tf.keras.backend.set\_value |
| tf.keras | tf.keras.backend.shape |
| tf.keras | tf.keras.backend.sigmoid |
| tf.keras | tf.keras.backend.sign |
| tf.keras | tf.keras.backend.sin |
| tf.keras | tf.keras.backend.softmax |
| tf.keras | tf.keras.backend.softplus |
| tf.keras | tf.keras.backend.softsign |
| tf.keras | tf.keras.backend.sparse\_categorical\_crossentropy |
| tf.keras | tf.keras.backend.spatial\_2d\_padding |
| tf.keras | tf.keras.backend.spatial\_3d\_padding |
| tf.keras | tf.keras.backend.sqrt |
| tf.keras | tf.keras.backend.square |
| tf.keras | tf.keras.backend.squeeze |
| tf.keras | tf.keras.backend.stack |
| tf.keras | tf.keras.backend.std |
| tf.keras | tf.keras.backend.stop\_gradient |
| tf.keras | tf.keras.backend.sum |
| tf.keras | tf.keras.backend.switch |
| tf.keras | tf.keras.backend.tanh |
| tf.keras | tf.keras.backend.temporal\_padding |
| tf.keras | tf.keras.backend.tile |
| tf.keras | tf.keras.backend.to\_dense |
| tf.keras | tf.keras.backend.transpose |
| tf.keras | tf.keras.backend.truncated\_normal |
| tf.keras | tf.keras.backend.update |
| tf.keras | tf.keras.backend.update\_add |
| tf.keras | tf.keras.backend.update\_sub |
| tf.keras | tf.keras.backend.var |
| tf.keras | tf.keras.backend.variable |
| tf.keras | tf.keras.backend.zeros |
| tf.keras | tf.keras.backend.zeros\_like |
| tf.keras | tf.keras.callbacks.BaseLogger |
| tf.keras | tf.keras.callbacks.Callback |
| tf.keras | tf.keras.callbacks.CSVLogger |
| tf.keras | tf.keras.callbacks.EarlyStopping |
| tf.keras | tf.keras.callbacks.History |
| tf.keras | tf.keras.callbacks.LambdaCallback |
| tf.keras | tf.keras.callbacks.LearningRateScheduler |
| tf.keras | tf.keras.callbacks.ModelCheckpoint |
| tf.keras | tf.keras.callbacks.ProgbarLogger |
| tf.keras | tf.keras.callbacks.ReduceLROnPlateau |
| tf.keras | tf.keras.callbacks.TensorBoard |
| tf.keras | tf.keras.constraints |
| tf.keras | tf.keras.constraints.deserialize |
| tf.keras | tf.keras.constraints.get |
| tf.keras | tf.keras.constraints.max\_norm |
| tf.keras | tf.keras.constraints.MaxNorm |
| tf.keras | tf.keras.constraints.min\_max\_norm |
| tf.keras | tf.keras.constraints.MinMaxNorm |
| tf.keras | tf.keras.constraints.non\_neg |
| tf.keras | tf.keras.constraints.NonNeg |
| tf.keras | tf.keras.constraints.radial\_constraint |
| tf.keras | tf.keras.constraints.serialize |
| tf.keras | tf.keras.constraints.unit\_norm |
| tf.keras | tf.keras.constraints.UnitNorm |
| tf.keras | tf.keras.datasets |
| tf.keras | tf.keras.datasets.boston\_housing.load\_data |
| tf.keras | tf.keras.datasets.cifar10 |
| tf.keras | tf.keras.datasets.cifar10.load\_data |
| tf.keras | tf.keras.datasets.cifar100.load\_data |
| tf.keras | tf.keras.datasets.fashion\_mnist |
| tf.keras | tf.keras.datasets.fashion\_mnist.load\_data |
| tf.keras | tf.keras.datasets.imdb |
| tf.keras | tf.keras.datasets.imdb.get\_word\_index |
| tf.keras | tf.keras.datasets.imdb.load\_data |
| tf.keras | tf.keras.datasets.mnist |
| tf.keras | tf.keras.datasets.mnist.load\_data |
| tf.keras | tf.keras.datasets.reuters |
| tf.keras | tf.keras.datasets.reuters.get\_word\_index |
| tf.keras | tf.keras.datasets.reuters.load\_data |
| tf.keras | tf.keras.experimental.CosineDecay |
| tf.keras | tf.keras.experimental.CosineDecayRestarts |
| tf.keras | tf.keras.experimental.LinearCosineDecay |
| tf.keras | tf.keras.experimental.NoisyLinearCosineDecay |
| tf.keras | tf.keras.experimental.WideDeepModel |
| tf.keras | tf.keras.initializers |
| tf.keras | tf.keras.initializers.Constant |
| tf.keras | tf.keras.initializers.constant |
| tf.keras | tf.keras.initializers.deserialize |
| tf.keras | tf.keras.initializers.get |
| tf.keras | tf.keras.initializers.glorot\_normal |
| tf.keras | tf.keras.initializers.glorot\_uniform |
| tf.keras | tf.keras.initializers.he\_normal |
| tf.keras | tf.keras.initializers.he\_uniform |
| tf.keras | tf.keras.initializers.Identity |
| tf.keras | tf.keras.initializers.identity |
| tf.keras | tf.keras.initializers.lecun\_normal |
| tf.keras | tf.keras.initializers.lecun\_uniform |
| tf.keras | tf.keras.initializers.normal |
| tf.keras | tf.keras.initializers.Ones |
| tf.keras | tf.keras.initializers.ones |
| tf.keras | tf.keras.initializers.Orthogonal |
| tf.keras | tf.keras.initializers.orthogonal |
| tf.keras | tf.keras.initializers.random\_normal |
| tf.keras | tf.keras.initializers.random\_uniform |
| tf.keras | tf.keras.initializers.RandomNormal |
| tf.keras | tf.keras.initializers.RandomUniform |
| tf.keras | tf.keras.initializers.serialize |
| tf.keras | tf.keras.initializers.truncated\_normal |
| tf.keras | tf.keras.initializers.TruncatedNormal |
| tf.keras | tf.keras.initializers.uniform |
| tf.keras | tf.keras.initializers.VarianceScaling |
| tf.keras | tf.keras.initializers.Zeros |
| tf.keras | tf.keras.initializers.zeros |
| tf.keras | tf.keras.Input |
| tf.keras | tf.keras.layers |
| tf.keras | tf.keras.layers.AbstractRNNCell |
| tf.keras | tf.keras.layers.Activation |
| tf.keras | tf.keras.layers.ActivityRegularization |
| tf.keras | tf.keras.layers.Add |
| tf.keras | tf.keras.layers.add |
| tf.keras | tf.keras.layers.AdditiveAttention |
| tf.keras | tf.keras.layers.AlphaDropout |
| tf.keras | tf.keras.layers.Attention |
| tf.keras | tf.keras.layers.Average |
| tf.keras | tf.keras.layers.average |
| tf.keras | tf.keras.layers.AveragePooling1D |
| tf.keras | tf.keras.layers.AveragePooling2D |
| tf.keras | tf.keras.layers.AveragePooling3D |
| tf.keras | tf.keras.layers.AvgPool1D |
| tf.keras | tf.keras.layers.AvgPool2D |
| tf.keras | tf.keras.layers.AvgPool3D |
| tf.keras | tf.keras.layers.BatchNormalization |
| tf.keras | tf.keras.layers.Bidirectional |
| tf.keras | tf.keras.layers.Concatenate |
| tf.keras | tf.keras.layers.concatenate |
| tf.keras | tf.keras.layers.Conv1D |
| tf.keras | tf.keras.layers.Conv2D |
| tf.keras | tf.keras.layers.Conv2DTranspose |
| tf.keras | tf.keras.layers.Conv3D |
| tf.keras | tf.keras.layers.Conv3DTranspose |
| tf.keras | tf.keras.layers.ConvLSTM2D |
| tf.keras | tf.keras.layers.Convolution1D |
| tf.keras | tf.keras.layers.Convolution2D |
| tf.keras | tf.keras.layers.Convolution2DTranspose |
| tf.keras | tf.keras.layers.Convolution3D |
| tf.keras | tf.keras.layers.Convolution3DTranspose |
| tf.keras | tf.keras.layers.Cropping1D |
| tf.keras | tf.keras.layers.Cropping2D |
| tf.keras | tf.keras.layers.Cropping3D |
| tf.keras | tf.keras.layers.CuDNNGRU |
| tf.keras | tf.keras.layers.CuDNNLSTM |
| tf.keras | tf.keras.layers.Dense |
| tf.keras | tf.keras.layers.DenseFeatures |
| tf.keras | tf.keras.layers.DepthwiseConv2D |
| tf.keras | tf.keras.layers.deserialize |
| tf.keras | tf.keras.layers.Dot |
| tf.keras | tf.keras.layers.dot |
| tf.keras | tf.keras.layers.Dropout |
| tf.keras | tf.keras.layers.ELU |
| tf.keras | tf.keras.layers.Embedding |
| tf.keras | tf.keras.layers.Flatten |
| tf.keras | tf.keras.layers.GaussianDropout |
| tf.keras | tf.keras.layers.GaussianNoise |
| tf.keras | tf.keras.layers.GlobalAveragePooling1D |
| tf.keras | tf.keras.layers.GlobalAveragePooling2D |
| tf.keras | tf.keras.layers.GlobalAveragePooling3D |
| tf.keras | tf.keras.layers.GlobalAvgPool1D |
| tf.keras | tf.keras.layers.GlobalAvgPool2D |
| tf.keras | tf.keras.layers.GlobalAvgPool3D |
| tf.keras | tf.keras.layers.GlobalMaxPool1D |
| tf.keras | tf.keras.layers.GlobalMaxPool2D |
| tf.keras | tf.keras.layers.GlobalMaxPool3D |
| tf.keras | tf.keras.layers.GlobalMaxPooling1D |
| tf.keras | tf.keras.layers.GlobalMaxPooling2D |
| tf.keras | tf.keras.layers.GlobalMaxPooling3D |
| tf.keras | tf.keras.layers.GRU |
| tf.keras | tf.keras.layers.GRUCell |
| tf.keras | tf.keras.layers.Input |
| tf.keras | tf.keras.layers.InputLayer |
| tf.keras | tf.keras.layers.InputSpec |
| tf.keras | tf.keras.layers.Lambda |
| tf.keras | tf.keras.layers.Layer |
| tf.keras | tf.keras.layers.LayerNormalization |
| tf.keras | tf.keras.layers.LeakyReLU |
| tf.keras | tf.keras.layers.LocallyConnected1D |
| tf.keras | tf.keras.layers.LocallyConnected2D |
| tf.keras | tf.keras.layers.LSTM |
| tf.keras | tf.keras.layers.LSTMCell |
| tf.keras | tf.keras.layers.Masking |
| tf.keras | tf.keras.layers.Maximum |
| tf.keras | tf.keras.layers.maximum |
| tf.keras | tf.keras.layers.MaxPool1D |
| tf.keras | tf.keras.layers.MaxPool2D |
| tf.keras | tf.keras.layers.MaxPool3D |
| tf.keras | tf.keras.layers.MaxPooling1D |
| tf.keras | tf.keras.layers.MaxPooling2D |
| tf.keras | tf.keras.layers.MaxPooling3D |
| tf.keras | tf.keras.layers.Minimum |
| tf.keras | tf.keras.layers.minimum |
| tf.keras | tf.keras.layers.Multiply |
| tf.keras | tf.keras.layers.multiply |
| tf.keras | tf.keras.layers.Permute |
| tf.keras | tf.keras.layers.PReLU |
| tf.keras | tf.keras.layers.ReLU |
| tf.keras | tf.keras.layers.RepeatVector |
| tf.keras | tf.keras.layers.Reshape |
| tf.keras | tf.keras.layers.RNN |
| tf.keras | tf.keras.layers.SeparableConv1D |
| tf.keras | tf.keras.layers.SeparableConv2D |
| tf.keras | tf.keras.layers.SeparableConvolution1D |
| tf.keras | tf.keras.layers.SeparableConvolution2D |
| tf.keras | tf.keras.layers.serialize |
| tf.keras | tf.keras.layers.SimpleRNN |
| tf.keras | tf.keras.layers.SimpleRNNCell |
| tf.keras | tf.keras.layers.Softmax |
| tf.keras | tf.keras.layers.SpatialDropout1D |
| tf.keras | tf.keras.layers.SpatialDropout2D |
| tf.keras | tf.keras.layers.SpatialDropout3D |
| tf.keras | tf.keras.layers.StackedRNNCells |
| tf.keras | tf.keras.layers.Subtract |
| tf.keras | tf.keras.layers.subtract |
| tf.keras | tf.keras.layers.ThresholdedReLU |
| tf.keras | tf.keras.layers.TimeDistributed |
| tf.keras | tf.keras.layers.UpSampling1D |
| tf.keras | tf.keras.layers.UpSampling2D |
| tf.keras | tf.keras.layers.UpSampling3D |
| tf.keras | tf.keras.layers.Wrapper |
| tf.keras | tf.keras.layers.ZeroPadding1D |
| tf.keras | tf.keras.layers.ZeroPadding2D |
| tf.keras | tf.keras.layers.ZeroPadding3D |
| tf.keras | tf.keras.losses.binary\_crossentropy |
| tf.keras | tf.keras.losses.BinaryCrossentropy |
| tf.keras | tf.keras.losses.categorical\_crossentropy |
| tf.keras | tf.keras.losses.categorical\_hinge |
| tf.keras | tf.keras.losses.CategoricalCrossentropy |
| tf.keras | tf.keras.losses.CategoricalHinge |
| tf.keras | tf.keras.losses.cosine |
| tf.keras | tf.keras.losses.cosine\_proximity |
| tf.keras | tf.keras.losses.cosine\_similarity |
| tf.keras | tf.keras.losses.CosineSimilarity |
| tf.keras | tf.keras.losses.deserialize |
| tf.keras | tf.keras.losses.get |
| tf.keras | tf.keras.losses.Hinge |
| tf.keras | tf.keras.losses.hinge |
| tf.keras | tf.keras.losses.Huber |
| tf.keras | tf.keras.losses.KLD |
| tf.keras | tf.keras.losses.kld |
| tf.keras | tf.keras.losses.KLDivergence |
| tf.keras | tf.keras.losses.kullback\_leibler\_divergence |
| tf.keras | tf.keras.losses.LogCosh |
| tf.keras | tf.keras.losses.logcosh |
| tf.keras | tf.keras.losses.Loss |
| tf.keras | tf.keras.losses.MAE |
| tf.keras | tf.keras.losses.mae |
| tf.keras | tf.keras.losses.MAPE |
| tf.keras | tf.keras.losses.mape |
| tf.keras | tf.keras.losses.mean\_absolute\_error |
| tf.keras | tf.keras.losses.mean\_absolute\_percentage\_error |
| tf.keras | tf.keras.losses.mean\_squared\_error |
| tf.keras | tf.keras.losses.mean\_squared\_logarithmic\_error |
| tf.keras | tf.keras.losses.MeanAbsoluteError |
| tf.keras | tf.keras.losses.MeanAbsolutePercentageError |
| tf.keras | tf.keras.losses.MeanSquaredError |
| tf.keras | tf.keras.losses.MeanSquaredLogarithmicError |
| tf.keras | tf.keras.losses.MSE |
| tf.keras | tf.keras.losses.mse |
| tf.keras | tf.keras.losses.MSLE |
| tf.keras | tf.keras.losses.msle |
| tf.keras | tf.keras.losses.Poisson |
| tf.keras | tf.keras.losses.poisson |
| tf.keras | tf.keras.losses.serialize |
| tf.keras | tf.keras.losses.sparse\_categorical\_crossentropy |
| tf.keras | tf.keras.losses.SparseCategoricalCrossentropy |
| tf.keras | tf.keras.losses.squared\_hinge |
| tf.keras | tf.keras.losses.SquaredHinge |
| tf.keras | tf.keras.metrics.Accuracy |
| tf.keras | tf.keras.metrics.AUC |
| tf.keras | tf.keras.metrics.binary\_accuracy |
| tf.keras | tf.keras.metrics.binary\_crossentropy |
| tf.keras | tf.keras.metrics.BinaryAccuracy |
| tf.keras | tf.keras.metrics.BinaryCrossentropy |
| tf.keras | tf.keras.metrics.categorical\_accuracy |
| tf.keras | tf.keras.metrics.categorical\_crossentropy |
| tf.keras | tf.keras.metrics.CategoricalAccuracy |
| tf.keras | tf.keras.metrics.CategoricalCrossentropy |
| tf.keras | tf.keras.metrics.CategoricalHinge |
| tf.keras | tf.keras.metrics.cosine |
| tf.keras | tf.keras.metrics.cosine\_proximity |
| tf.keras | tf.keras.metrics.CosineSimilarity |
| tf.keras | tf.keras.metrics.deserialize |
| tf.keras | tf.keras.metrics.FalseNegatives |
| tf.keras | tf.keras.metrics.FalsePositives |
| tf.keras | tf.keras.metrics.get |
| tf.keras | tf.keras.metrics.Hinge |
| tf.keras | tf.keras.metrics.hinge |
| tf.keras | tf.keras.metrics.KLD |
| tf.keras | tf.keras.metrics.kld |
| tf.keras | tf.keras.metrics.KLDivergence |
| tf.keras | tf.keras.metrics.kullback\_leibler\_divergence |
| tf.keras | tf.keras.metrics.LogCoshError |
| tf.keras | tf.keras.metrics.MAE |
| tf.keras | tf.keras.metrics.mae |
| tf.keras | tf.keras.metrics.MAPE |
| tf.keras | tf.keras.metrics.mape |
| tf.keras | tf.keras.metrics.Mean |
| tf.keras | tf.keras.metrics.mean\_absolute\_error |
| tf.keras | tf.keras.metrics.mean\_absolute\_percentage\_error |
| tf.keras | tf.keras.metrics.mean\_squared\_error |
| tf.keras | tf.keras.metrics.mean\_squared\_logarithmic\_error |
| tf.keras | tf.keras.metrics.MeanAbsoluteError |
| tf.keras | tf.keras.metrics.MeanAbsolutePercentageError |
| tf.keras | tf.keras.metrics.MeanIoU |
| tf.keras | tf.keras.metrics.MeanRelativeError |
| tf.keras | tf.keras.metrics.MeanSquaredError |
| tf.keras | tf.keras.metrics.MeanSquaredLogarithmicError |
| tf.keras | tf.keras.metrics.MeanTensor |
| tf.keras | tf.keras.metrics.Metric |
| tf.keras | tf.keras.metrics.MSE |
| tf.keras | tf.keras.metrics.mse |
| tf.keras | tf.keras.metrics.MSLE |
| tf.keras | tf.keras.metrics.msle |
| tf.keras | tf.keras.metrics.Poisson |
| tf.keras | tf.keras.metrics.poisson |
| tf.keras | tf.keras.metrics.Precision |
| tf.keras | tf.keras.metrics.Recall |
| tf.keras | tf.keras.metrics.RootMeanSquaredError |
| tf.keras | tf.keras.metrics.SensitivityAtSpecificity |
| tf.keras | tf.keras.metrics.serialize |
| tf.keras | tf.keras.metrics.sparse\_categorical\_crossentropy |
| tf.keras | tf.keras.metrics.sparse\_top\_k\_categorical\_accuracy |
| tf.keras | tf.keras.metrics.SparseCategoricalAccuracy |
| tf.keras | tf.keras.metrics.SparseCategoricalCrossentropy |
| tf.keras | tf.keras.metrics.SparseTopKCategoricalAccuracy |
| tf.keras | tf.keras.metrics.SpecificityAtSensitivity |
| tf.keras | tf.keras.metrics.squared\_hinge |
| tf.keras | tf.keras.metrics.SquaredHinge |
| tf.keras | tf.keras.metrics.Sum |
| tf.keras | tf.keras.metrics.top\_k\_categorical\_accuracy |
| tf.keras | tf.keras.metrics.TopKCategoricalAccuracy |
| tf.keras | tf.keras.metrics.TrueNegatives |
| tf.keras | tf.keras.metrics.TruePositives |
| tf.keras | tf.keras.mixed\_precision.experimental.global\_policy |
| tf.keras | tf.keras.mixed\_precision.experimental.LossScaleOptimizer |
| tf.keras | tf.keras.mixed\_precision.experimental.Policy |
| tf.keras | tf.keras.mixed\_precision.experimental.set\_policy |
| tf.keras | tf.keras.Model |
| tf.keras | tf.keras.models.clone\_model |
| tf.keras | tf.keras.models.load\_model |
| tf.keras | tf.keras.models.Model |
| tf.keras | tf.keras.models.model\_from\_config |
| tf.keras | tf.keras.models.model\_from\_json |
| tf.keras | tf.keras.models.model\_from\_yaml |
| tf.keras | tf.keras.models.save\_model |
| tf.keras | tf.keras.models.Sequential |
| tf.keras | tf.keras.optimizers.Adadelta |
| tf.keras | tf.keras.optimizers.Adagrad |
| tf.keras | tf.keras.optimizers.Adam |
| tf.keras | tf.keras.optimizers.Adamax |
| tf.keras | tf.keras.optimizers.deserialize |
| tf.keras | tf.keras.optimizers.Ftrl |
| tf.keras | tf.keras.optimizers.get |
| tf.keras | tf.keras.optimizers.Nadam |
| tf.keras | tf.keras.optimizers.Optimizer |
| tf.keras | tf.keras.optimizers.RMSprop |
| tf.keras | tf.keras.optimizers.schedules.deserialize |
| tf.keras | tf.keras.optimizers.schedules.ExponentialDecay |
| tf.keras | tf.keras.optimizers.schedules.InverseTimeDecay |
| tf.keras | tf.keras.optimizers.schedules.PiecewiseConstantDecay |
| tf.keras | tf.keras.optimizers.schedules.PolynomialDecay |
| tf.keras | tf.keras.optimizers.schedules.serialize |
| tf.keras | tf.keras.optimizers.serialize |
| tf.keras | tf.keras.optimizers.SGD |
| tf.keras | tf.keras.preprocessing.image.apply\_affine\_transform |
| tf.keras | tf.keras.preprocessing.image.apply\_channel\_shift |
| tf.keras | tf.keras.preprocessing.image.array\_to\_img |
| tf.keras | tf.keras.preprocessing.image.DirectoryIterator |
| tf.keras | tf.keras.preprocessing.image.ImageDataGenerator |
| tf.keras | tf.keras.preprocessing.image.img\_to\_array |
| tf.keras | tf.keras.preprocessing.image.Iterator |
| tf.keras | tf.keras.preprocessing.image.load\_img |
| tf.keras | tf.keras.preprocessing.image.random\_channel\_shift |
| tf.keras | tf.keras.preprocessing.image.random\_rotation |
| tf.keras | tf.keras.preprocessing.image.random\_shear |
| tf.keras | tf.keras.preprocessing.image.random\_shift |
| tf.keras | tf.keras.preprocessing.image.random\_zoom |
| tf.keras | tf.keras.preprocessing.image.save\_img |
| tf.keras | tf.keras.preprocessing.sequence.make\_sampling\_table |
| tf.keras | tf.keras.preprocessing.sequence.pad\_sequences |
| tf.keras | tf.keras.preprocessing.sequence.skipgrams |
| tf.keras | tf.keras.preprocessing.sequence.TimeseriesGenerator |
| tf.keras | tf.keras.preprocessing.text.hashing\_trick |
| tf.keras | tf.keras.preprocessing.text.one\_hot |
| tf.keras | tf.keras.preprocessing.text.text\_to\_word\_sequence |
| tf.keras | tf.keras.preprocessing.text.Tokenizer |
| tf.keras | tf.keras.regularizers.deserialize |
| tf.keras | tf.keras.regularizers.get |
| tf.keras | tf.keras.regularizers.l1 |
| tf.keras | tf.keras.regularizers.l1\_l2 |
| tf.keras | tf.keras.regularizers.L1L2 |
| tf.keras | tf.keras.regularizers.l2 |
| tf.keras | tf.keras.regularizers.Regularizer |
| tf.keras | tf.keras.regularizers.serialize |
| tf.keras | tf.keras.Sequential |
| tf.keras | tf.keras.utils.custom\_object\_scope |
| tf.keras | tf.keras.utils.CustomObjectScope |
| tf.keras | tf.keras.utils.deserialize\_keras\_object |
| tf.keras | tf.keras.utils.GeneratorEnqueuer |
| tf.keras | tf.keras.utils.get\_custom\_objects |
| tf.keras | tf.keras.utils.get\_file |
| tf.keras | tf.keras.utils.get\_source\_inputs |
| tf.keras | tf.keras.utils.HDF5Matrix |
| tf.keras | tf.keras.utils.model\_to\_dot |
| tf.keras | tf.keras.utils.normalize |
| tf.keras | tf.keras.utils.OrderedEnqueuer |
| tf.keras | tf.keras.utils.plot\_model |
| tf.keras | tf.keras.utils.Progbar |
| tf.keras | tf.keras.utils.serialize\_keras\_object |
| tf.keras | tf.keras.utils.to\_categorical |
| tf.keras | tf.keras.wrappers.scikit\_learn |
| tf.keras | tf.keras.wrappers.scikit\_learn.KerasClassifier |
| tf.keras | tf.keras.wrappers.scikit\_learn.KerasRegressor |
| tf.layers | tf.layers.average\_pooling2d |
| tf.layers | tf.layers.AveragePooling1D |
| tf.layers | tf.layers.AveragePooling2D |
| tf.layers | tf.layers.AveragePooling3D |
| tf.layers | tf.layers.batch\_normalization |
| tf.layers | tf.layers.BatchNormalization |
| tf.layers | tf.layers.Conv1D |
| tf.layers | tf.layers.conv1d |
| tf.layers | tf.layers.Conv2D |
| tf.layers | tf.layers.conv2d |
| tf.layers | tf.layers.conv2d\_transpose |
| tf.layers | tf.layers.Conv2DTranspose |
| tf.layers | tf.layers.Conv3D |
| tf.layers | tf.layers.Conv3DTranspose |
| tf.layers | tf.layers.Dense |
| tf.layers | tf.layers.dense |
| tf.layers | tf.layers.Dropout |
| tf.layers | tf.layers.dropout |
| tf.layers | tf.layers.Flatten |
| tf.layers | tf.layers.flatten |
| tf.layers | tf.layers.InputSpec |
| tf.layers | tf.layers.Layer |
| tf.layers | tf.layers.max\_pooling1d |
| tf.layers | tf.layers.max\_pooling2d |
| tf.layers | tf.layers.MaxPooling1D |
| tf.layers | tf.layers.MaxPooling2D |
| tf.layers | tf.layers.MaxPooling3D |
| tf.layers | tf.layers.separable\_conv1d |
| tf.layers | tf.layers.separable\_conv2d |
| tf.layers | tf.layers.SeparableConv1D |
| tf.layers | tf.layers.SeparableConv2D |
| tf.linalg | tf.linalg.adjoint |
| tf.linalg | tf.linalg.band\_part |
| tf.linalg | tf.linalg.cholesky |
| tf.linalg | tf.linalg.cholesky\_solve |
| tf.linalg | tf.linalg.cross |
| tf.linalg | tf.linalg.det |
| tf.linalg | tf.linalg.diag |
| tf.linalg | tf.linalg.diag\_part |
| tf.linalg | tf.linalg.eigh |
| tf.linalg | tf.linalg.eigvalsh |
| tf.linalg | tf.linalg.einsum |
| tf.linalg | tf.linalg.expm |
| tf.linalg | tf.linalg.eye |
| tf.linalg | tf.linalg.global\_norm |
| tf.linalg | tf.linalg.inv |
| tf.linalg | tf.linalg.l2\_normalize |
| tf.linalg | tf.linalg.LinearOperator |
| tf.linalg | tf.linalg.LinearOperatorAdjoint |
| tf.linalg | tf.linalg.LinearOperatorBlockDiag |
| tf.linalg | tf.linalg.LinearOperatorCirculant |
| tf.linalg | tf.linalg.LinearOperatorCirculant2D |
| tf.linalg | tf.linalg.LinearOperatorCirculant3D |
| tf.linalg | tf.linalg.LinearOperatorComposition |
| tf.linalg | tf.linalg.LinearOperatorDiag |
| tf.linalg | tf.linalg.LinearOperatorFullMatrix |
| tf.linalg | tf.linalg.LinearOperatorHouseholder |
| tf.linalg | tf.linalg.LinearOperatorIdentity |
| tf.linalg | tf.linalg.LinearOperatorInversion |
| tf.linalg | tf.linalg.LinearOperatorKronecker |
| tf.linalg | tf.linalg.LinearOperatorLowerTriangular |
| tf.linalg | tf.linalg.LinearOperatorLowRankUpdate |
| tf.linalg | tf.linalg.LinearOperatorScaledIdentity |
| tf.linalg | tf.linalg.LinearOperatorToeplitz |
| tf.linalg | tf.linalg.LinearOperatorZeros |
| tf.linalg | tf.linalg.logdet |
| tf.linalg | tf.linalg.logm |
| tf.linalg | tf.linalg.lstsq |
| tf.linalg | tf.linalg.lu |
| tf.linalg | tf.linalg.matmul |
| tf.linalg | tf.linalg.matrix\_rank |
| tf.linalg | tf.linalg.matrix\_transpose |
| tf.linalg | tf.linalg.matvec |
| tf.linalg | tf.linalg.norm |
| tf.linalg | tf.linalg.normalize |
| tf.linalg | tf.linalg.pinv |
| tf.linalg | tf.linalg.qr |
| tf.linalg | tf.linalg.set\_diag |
| tf.linalg | tf.linalg.slogdet |
| tf.linalg | tf.linalg.solve |
| tf.linalg | tf.linalg.sqrtm |
| tf.linalg | tf.linalg.svd |
| tf.linalg | tf.linalg.tensor\_diag |
| tf.linalg | tf.linalg.tensor\_diag\_part |
| tf.linalg | tf.linalg.tensordot |
| tf.linalg | tf.linalg.trace |
| tf.linalg | tf.linalg.transpose |
| tf.linalg | tf.linalg.triangular\_solve |
| tf.linalg | tf.linalg.tridiagonal\_matmul |
| tf.linalg | tf.linalg.tridiagonal\_solve |
| tf.lite | tf.lite.constants |
| tf.lite | tf.lite.Interpreter |
| tf.lite | tf.lite.OpHint |
| tf.lite | tf.lite.OpHint.OpHintArgumentTracker |
| tf.lite | tf.lite.OpsSet |
| tf.lite | tf.lite.Optimize |
| tf.lite | tf.lite.RepresentativeDataset |
| tf.lite | tf.lite.TargetSpec |
| tf.lite | tf.lite.TFLiteConverter |
| tf.lite | tf.lite.TocoConverter |
| tf.logging | tf.logging.debug |
| tf.logging | tf.logging.error |
| tf.logging | tf.logging.fatal |
| tf.logging | tf.logging.flush |
| tf.logging | tf.logging.get\_verbosity |
| tf.logging | tf.logging.info |
| tf.logging | tf.logging.log |
| tf.logging | tf.logging.log\_every\_n |
| tf.logging | tf.logging.log\_first\_n |
| tf.logging | tf.logging.log\_if |
| tf.logging | tf.logging.set\_verbosity |
| tf.logging | tf.logging.TaskLevelStatusMessage |
| tf.logging | tf.logging.vlog |
| tf.logging | tf.logging.warn |
| tf.logging | tf.logging.warning |
| tf.lookup | tf.lookup.experimental.DenseHashTable |
| tf.lookup | tf.lookup.KeyValueTensorInitializer |
| tf.lookup | tf.lookup.StaticHashTable |
| tf.lookup | tf.lookup.StaticVocabularyTable |
| tf.lookup | tf.lookup.TextFileIndex |
| tf.lookup | tf.lookup.TextFileInitializer |
| tf.losses | tf.losses.absolute\_difference |
| tf.losses | tf.losses.add\_loss |
| tf.losses | tf.losses.compute\_weighted\_loss |
| tf.losses | tf.losses.cosine\_distance |
| tf.losses | tf.losses.get\_losses |
| tf.losses | tf.losses.get\_regularization\_loss |
| tf.losses | tf.losses.get\_regularization\_losses |
| tf.losses | tf.losses.get\_total\_loss |
| tf.losses | tf.losses.hinge\_loss |
| tf.losses | tf.losses.huber\_loss |
| tf.losses | tf.losses.log\_loss |
| tf.losses | tf.losses.mean\_pairwise\_squared\_error |
| tf.losses | tf.losses.mean\_squared\_error |
| tf.losses | tf.losses.Reduction |
| tf.losses | tf.losses.sigmoid\_cross\_entropy |
| tf.losses | tf.losses.softmax\_cross\_entropy |
| tf.losses | tf.losses.sparse\_softmax\_cross\_entropy |
| tf.manip | tf.manip.batch\_to\_space\_nd |
| tf.manip | tf.manip.gather\_nd |
| tf.manip | tf.manip.reshape |
| tf.manip | tf.manip.reverse |
| tf.manip | tf.manip.roll |
| tf.manip | tf.manip.scatter\_nd |
| tf.manip | tf.manip.space\_to\_batch\_nd |
| tf.manip | tf.manip.tile |
| tf.math | tf.math.abs |
| tf.math | tf.math.accumulate\_n |
| tf.math | tf.math.acos |
| tf.math | tf.math.acosh |
| tf.math | tf.math.add |
| tf.math | tf.math.add\_n |
| tf.math | tf.math.angle |
| tf.math | tf.math.argmax |
| tf.math | tf.math.argmin |
| tf.math | tf.math.asin |
| tf.math | tf.math.asinh |
| tf.math | tf.math.atan |
| tf.math | tf.math.atan2 |
| tf.math | tf.math.atanh |
| tf.math | tf.math.bessel\_i0 |
| tf.math | tf.math.bessel\_i0e |
| tf.math | tf.math.bessel\_i1 |
| tf.math | tf.math.bessel\_i1e |
| tf.math | tf.math.betainc |
| tf.math | tf.math.bincount |
| tf.math | tf.math.ceil |
| tf.math | tf.math.confusion\_matrix |
| tf.math | tf.math.conj |
| tf.math | tf.math.cos |
| tf.math | tf.math.cosh |
| tf.math | tf.math.count\_nonzero |
| tf.math | tf.math.cumprod |
| tf.math | tf.math.cumsum |
| tf.math | tf.math.cumulative\_logsumexp |
| tf.math | tf.math.digamma |
| tf.math | tf.math.divide |
| tf.math | tf.math.divide\_no\_nan |
| tf.math | tf.math.equal |
| tf.math | tf.math.erf |
| tf.math | tf.math.erfc |
| tf.math | tf.math.exp |
| tf.math | tf.math.expm1 |
| tf.math | tf.math.floor |
| tf.math | tf.math.floordiv |
| tf.math | tf.math.floormod |
| tf.math | tf.math.greater |
| tf.math | tf.math.greater\_equal |
| tf.math | tf.math.igamma |
| tf.math | tf.math.igammac |
| tf.math | tf.math.imag |
| tf.math | tf.math.in\_top\_k |
| tf.math | tf.math.invert\_permutation |
| tf.math | tf.math.is\_finite |
| tf.math | tf.math.is\_inf |
| tf.math | tf.math.is\_nan |
| tf.math | tf.math.is\_non\_decreasing |
| tf.math | tf.math.is\_strictly\_increasing |
| tf.math | tf.math.l2\_normalize |
| tf.math | tf.math.lbeta |
| tf.math | tf.math.less |
| tf.math | tf.math.less\_equal |
| tf.math | tf.math.lgamma |
| tf.math | tf.math.log |
| tf.math | tf.math.log\_sigmoid |
| tf.math | tf.math.log\_softmax |
| tf.math | tf.math.log1p |
| tf.math | tf.math.logical\_and |
| tf.math | tf.math.logical\_not |
| tf.math | tf.math.logical\_or |
| tf.math | tf.math.logical\_xor |
| tf.math | tf.math.maximum |
| tf.math | tf.math.minimum |
| tf.math | tf.math.mod |
| tf.math | tf.math.multiply |
| tf.math | tf.math.multiply\_no\_nan |
| tf.math | tf.math.negative |
| tf.math | tf.math.nextafter |
| tf.math | tf.math.not\_equal |
| tf.math | tf.math.polygamma |
| tf.math | tf.math.polyval |
| tf.math | tf.math.pow |
| tf.math | tf.math.real |
| tf.math | tf.math.reciprocal |
| tf.math | tf.math.reciprocal\_no\_nan |
| tf.math | tf.math.reduce\_all |
| tf.math | tf.math.reduce\_any |
| tf.math | tf.math.reduce\_euclidean\_norm |
| tf.math | tf.math.reduce\_logsumexp |
| tf.math | tf.math.reduce\_max |
| tf.math | tf.math.reduce\_mean |
| tf.math | tf.math.reduce\_min |
| tf.math | tf.math.reduce\_prod |
| tf.math | tf.math.reduce\_std |
| tf.math | tf.math.reduce\_sum |
| tf.math | tf.math.reduce\_variance |
| tf.math | tf.math.rint |
| tf.math | tf.math.round |
| tf.math | tf.math.rsqrt |
| tf.math | tf.math.scalar\_mul |
| tf.math | tf.math.segment\_max |
| tf.math | tf.math.segment\_mean |
| tf.math | tf.math.segment\_min |
| tf.math | tf.math.segment\_prod |
| tf.math | tf.math.segment\_sum |
| tf.math | tf.math.sigmoid |
| tf.math | tf.math.sign |
| tf.math | tf.math.sin |
| tf.math | tf.math.sinh |
| tf.math | tf.math.softmax |
| tf.math | tf.math.softplus |
| tf.math | tf.math.softsign |
| tf.math | tf.math.sqrt |
| tf.math | tf.math.square |
| tf.math | tf.math.squared\_difference |
| tf.math | tf.math.subtract |
| tf.math | tf.math.tan |
| tf.math | tf.math.tanh |
| tf.math | tf.math.top\_k |
| tf.math | tf.math.truediv |
| tf.math | tf.math.unsorted\_segment\_max |
| tf.math | tf.math.unsorted\_segment\_mean |
| tf.math | tf.math.unsorted\_segment\_min |
| tf.math | tf.math.unsorted\_segment\_prod |
| tf.math | tf.math.unsorted\_segment\_sqrt\_n |
| tf.math | tf.math.unsorted\_segment\_sum |
| tf.math | tf.math.xdivy |
| tf.math | tf.math.xlogy |
| tf.math | tf.math.zero\_fraction |
| tf.math | tf.math.zeta |
| tf.metrics | tf.metrics.accuracy |
| tf.metrics | tf.metrics.auc |
| tf.metrics | tf.metrics.average\_precision\_at\_k |
| tf.metrics | tf.metrics.false\_negatives |
| tf.metrics | tf.metrics.false\_negatives\_at\_thresholds |
| tf.metrics | tf.metrics.false\_positives |
| tf.metrics | tf.metrics.false\_positives\_at\_thresholds |
| tf.metrics | tf.metrics.mean |
| tf.metrics | tf.metrics.mean\_absolute\_error |
| tf.metrics | tf.metrics.mean\_cosine\_distance |
| tf.metrics | tf.metrics.mean\_iou |
| tf.metrics | tf.metrics.mean\_per\_class\_accuracy |
| tf.metrics | tf.metrics.mean\_relative\_error |
| tf.metrics | tf.metrics.mean\_squared\_error |
| tf.metrics | tf.metrics.mean\_tensor |
| tf.metrics | tf.metrics.percentage\_below |
| tf.metrics | tf.metrics.precision |
| tf.metrics | tf.metrics.precision\_at\_k |
| tf.metrics | tf.metrics.precision\_at\_thresholds |
| tf.metrics | tf.metrics.precision\_at\_top\_k |
| tf.metrics | tf.metrics.recall |
| tf.metrics | tf.metrics.recall\_at\_k |
| tf.metrics | tf.metrics.recall\_at\_thresholds |
| tf.metrics | tf.metrics.recall\_at\_top\_k |
| tf.metrics | tf.metrics.root\_mean\_squared\_error |
| tf.metrics | tf.metrics.sensitivity\_at\_specificity |
| tf.metrics | tf.metrics.sparse\_average\_precision\_at\_k |
| tf.metrics | tf.metrics.sparse\_precision\_at\_k |
| tf.metrics | tf.metrics.specificity\_at\_sensitivity |
| tf.metrics | tf.metrics.true\_negatives |
| tf.metrics | tf.metrics.true\_negatives\_at\_thresholds |
| tf.metrics | tf.metrics.true\_positives |
| tf.metrics | tf.metrics.true\_positives\_at\_thresholds |
| tf.nest | tf.nest.assert\_same\_structure |
| tf.nest | tf.nest.flatten |
| tf.nest | tf.nest.is\_nested |
| tf.nest | tf.nest.map\_structure |
| tf.nest | tf.nest.pack\_sequence\_as |
| tf.nn | tf.nn.all\_candidate\_sampler |
| tf.nn | tf.nn.atrous\_conv2d |
| tf.nn | tf.nn.atrous\_conv2d\_transpose |
| tf.nn | tf.nn.avg\_pool |
| tf.nn | tf.nn.avg\_pool\_v2 |
| tf.nn | tf.nn.avg\_pool1d |
| tf.nn | tf.nn.avg\_pool2d |
| tf.nn | tf.nn.avg\_pool3d |
| tf.nn | tf.nn.batch\_norm\_with\_global\_normalization |
| tf.nn | tf.nn.batch\_normalization |
| tf.nn | tf.nn.bias\_add |
| tf.nn | tf.nn.bidirectional\_dynamic\_rnn |
| tf.nn | tf.nn.collapse\_repeated |
| tf.nn | tf.nn.compute\_accidental\_hits |
| tf.nn | tf.nn.compute\_average\_loss |
| tf.nn | tf.nn.conv\_transpose |
| tf.nn | tf.nn.conv1d |
| tf.nn | tf.nn.conv1d\_transpose |
| tf.nn | tf.nn.conv2d |
| tf.nn | tf.nn.conv2d\_backprop\_filter |
| tf.nn | tf.nn.conv2d\_backprop\_input |
| tf.nn | tf.nn.conv2d\_transpose |
| tf.nn | tf.nn.conv3d |
| tf.nn | tf.nn.conv3d\_backprop\_filter |
| tf.nn | tf.nn.conv3d\_backprop\_filter\_v2 |
| tf.nn | tf.nn.conv3d\_transpose |
| tf.nn | tf.nn.convolution |
| tf.nn | tf.nn.crelu |
| tf.nn | tf.nn.ctc\_beam\_search\_decoder |
| tf.nn | tf.nn.ctc\_greedy\_decoder |
| tf.nn | tf.nn.ctc\_loss |
| tf.nn | tf.nn.ctc\_loss\_v2 |
| tf.nn | tf.nn.ctc\_unique\_labels |
| tf.nn | tf.nn.depth\_to\_space |
| tf.nn | tf.nn.depthwise\_conv2d |
| tf.nn | tf.nn.depthwise\_conv2d\_backprop\_filter |
| tf.nn | tf.nn.depthwise\_conv2d\_backprop\_input |
| tf.nn | tf.nn.depthwise\_conv2d\_native |
| tf.nn | tf.nn.depthwise\_conv2d\_native\_backprop\_filter |
| tf.nn | tf.nn.depthwise\_conv2d\_native\_backprop\_input |
| tf.nn | tf.nn.dilation2d |
| tf.nn | tf.nn.dropout |
| tf.nn | tf.nn.dynamic\_rnn |
| tf.nn | tf.nn.elu |
| tf.nn | tf.nn.embedding\_lookup |
| tf.nn | tf.nn.embedding\_lookup\_sparse |
| tf.nn | tf.nn.erosion2d |
| tf.nn | tf.nn.fixed\_unigram\_candidate\_sampler |
| tf.nn | tf.nn.fractional\_avg\_pool |
| tf.nn | tf.nn.fractional\_max\_pool |
| tf.nn | tf.nn.fused\_batch\_norm |
| tf.nn | tf.nn.in\_top\_k |
| tf.nn | tf.nn.l2\_loss |
| tf.nn | tf.nn.l2\_normalize |
| tf.nn | tf.nn.leaky\_relu |
| tf.nn | tf.nn.learned\_unigram\_candidate\_sampler |
| tf.nn | tf.nn.local\_response\_normalization |
| tf.nn | tf.nn.log\_poisson\_loss |
| tf.nn | tf.nn.log\_softmax |
| tf.nn | tf.nn.log\_uniform\_candidate\_sampler |
| tf.nn | tf.nn.lrn |
| tf.nn | tf.nn.max\_pool |
| tf.nn | tf.nn.max\_pool\_v2 |
| tf.nn | tf.nn.max\_pool\_with\_argmax |
| tf.nn | tf.nn.max\_pool1d |
| tf.nn | tf.nn.max\_pool2d |
| tf.nn | tf.nn.max\_pool3d |
| tf.nn | tf.nn.moments |
| tf.nn | tf.nn.nce\_loss |
| tf.nn | tf.nn.normalize\_moments |
| tf.nn | tf.nn.pool |
| tf.nn | tf.nn.quantized\_conv2d |
| tf.nn | tf.nn.raw\_rnn |
| tf.nn | tf.nn.relu |
| tf.nn | tf.nn.relu\_layer |
| tf.nn | tf.nn.relu6 |
| tf.nn | tf.nn.rnn\_cell.BasicLSTMCell |
| tf.nn | tf.nn.rnn\_cell.BasicRNNCell |
| tf.nn | tf.nn.rnn\_cell.DeviceWrapper |
| tf.nn | tf.nn.rnn\_cell.GRUCell |
| tf.nn | tf.nn.rnn\_cell.LSTMCell |
| tf.nn | tf.nn.rnn\_cell.LSTMStateTuple |
| tf.nn | tf.nn.rnn\_cell.MultiRNNCell |
| tf.nn | tf.nn.rnn\_cell.ResidualWrapper |
| tf.nn | tf.nn.rnn\_cell.RNNCell |
| tf.nn | tf.nn.safe\_embedding\_lookup\_sparse |
| tf.nn | tf.nn.sampled\_softmax\_loss |
| tf.nn | tf.nn.scale\_regularization\_loss |
| tf.nn | tf.nn.selu |
| tf.nn | tf.nn.separable\_conv2d |
| tf.nn | tf.nn.sigmoid |
| tf.nn | tf.nn.sigmoid\_cross\_entropy\_with\_logits |
| tf.nn | tf.nn.softmax |
| tf.nn | tf.nn.softmax\_cross\_entropy\_with\_logits |
| tf.nn | tf.nn.softmax\_cross\_entropy\_with\_logits\_v2 |
| tf.nn | tf.nn.softplus |
| tf.nn | tf.nn.softsign |
| tf.nn | tf.nn.space\_to\_batch |
| tf.nn | tf.nn.space\_to\_depth |
| tf.nn | tf.nn.sparse\_softmax\_cross\_entropy\_with\_logits |
| tf.nn | tf.nn.static\_bidirectional\_rnn |
| tf.nn | tf.nn.static\_rnn |
| tf.nn | tf.nn.sufficient\_statistics |
| tf.nn | tf.nn.swish |
| tf.nn | tf.nn.tanh |
| tf.nn | tf.nn.top\_k |
| tf.nn | tf.nn.uniform\_candidate\_sampler |
| tf.nn | tf.nn.weighted\_cross\_entropy\_with\_logits |
| tf.nn | tf.nn.weighted\_moments |
| tf.nn | tf.nn.with\_space\_to\_batch |
| tf.nn | tf.nn.xw\_plus\_b |
| tf.nn | tf.nn.zero\_fraction |
| tf.python\_io | tf.python\_io.tf\_record\_iterator |
| tf.python\_io | tf.python\_io.TFRecordWriter |
| tf.quantization | tf.quantization.fake\_quant\_with\_min\_max\_args |
| tf.quantization | tf.quantization.fake\_quant\_with\_min\_max\_args\_gradient |
| tf.queue | tf.queue.FIFOQueue |
| tf.queue | tf.queue.PaddingFIFOQueue |
| tf.queue | tf.queue.PriorityQueue |
| tf.queue | tf.queue.QueueBase |
| tf.queue | tf.queue.RandomShuffleQueue |
| tf.ragged | tf.ragged.boolean\_mask |
| tf.ragged | tf.ragged.constant |
| tf.ragged | tf.ragged.constant\_value |
| tf.ragged | tf.ragged.map\_flat\_values |
| tf.ragged | tf.ragged.placeholder |
| tf.ragged | tf.ragged.RaggedTensorValue |
| tf.ragged | tf.ragged.range |
| tf.ragged | tf.ragged.row\_splits\_to\_segment\_ids |
| tf.ragged | tf.ragged.segment\_ids\_to\_row\_splits |
| tf.ragged | tf.ragged.stack |
| tf.ragged | tf.ragged.stack\_dynamic\_partitions |
| tf.random | tf.random.all\_candidate\_sampler |
| tf.random | tf.random.categorical |
| tf.random | tf.random.fixed\_unigram\_candidate\_sampler |
| tf.random | tf.random.gamma |
| tf.random | tf.random.get\_seed |
| tf.random | tf.random.learned\_unigram\_candidate\_sampler |
| tf.random | tf.random.log\_uniform\_candidate\_sampler |
| tf.random | tf.random.multinomial |
| tf.random | tf.random.normal |
| tf.random | tf.random.poisson |
| tf.random | tf.random.set\_random\_seed |
| tf.random | tf.random.shuffle |
| tf.random | tf.random.stateless\_categorical |
| tf.random | tf.random.stateless\_normal |
| tf.random | tf.random.stateless\_truncated\_normal |
| tf.random | tf.random.stateless\_uniform |
| tf.random | tf.random.truncated\_normal |
| tf.random | tf.random.uniform |
| tf.random | tf.random.uniform\_candidate\_sampler |
| tf.random | tf.random\_crop |
| tf.random | tf.random\_gamma |
| tf.random | tf.random\_normal |
| tf.random | tf.random\_normal\_initializer |
| tf.random | tf.random\_poisson |
| tf.random | tf.random\_shuffle |
| tf.random | tf.random\_uniform |
| tf.random | tf.random\_uniform\_initializer |
| tf.resource\_loader | tf.resource\_loader.get\_data\_files\_path |
| tf.saved\_model | tf.saved\_model.build\_signature\_def |
| tf.saved\_model | tf.saved\_model.build\_tensor\_info |
| tf.saved\_model | tf.saved\_model.builder.SavedModelBuilder |
| tf.saved\_model | tf.saved\_model.contains\_saved\_model |
| tf.saved\_model | tf.saved\_model.load |
| tf.saved\_model | tf.saved\_model.load\_v2 |
| tf.saved\_model | tf.saved\_model.loader.load |
| tf.saved\_model | tf.saved\_model.loader.maybe\_saved\_model\_directory |
| tf.saved\_model | tf.saved\_model.maybe\_saved\_model\_directory |
| tf.saved\_model | tf.saved\_model.predict\_signature\_def |
| tf.saved\_model | tf.saved\_model.save |
| tf.saved\_model | tf.saved\_model.signature\_def\_utils.build\_signature\_def |
| tf.saved\_model | tf.saved\_model.signature\_def\_utils.predict\_signature\_def |
| tf.saved\_model | tf.saved\_model.tag\_constants |
| tf.saved\_model | tf.saved\_model.utils.build\_tensor\_info |
| tf.sets | tf.sets.difference |
| tf.sets | tf.sets.intersection |
| tf.sets | tf.sets.set\_intersection |
| tf.sets | tf.sets.union |
| tf.signal | tf.signal.dct |
| tf.signal | tf.signal.fft |
| tf.signal | tf.signal.fft2d |
| tf.signal | tf.signal.fft3d |
| tf.signal | tf.signal.fftshift |
| tf.signal | tf.signal.frame |
| tf.signal | tf.signal.hamming\_window |
| tf.signal | tf.signal.hann\_window |
| tf.signal | tf.signal.idct |
| tf.signal | tf.signal.ifft |
| tf.signal | tf.signal.ifft2d |
| tf.signal | tf.signal.ifft3d |
| tf.signal | tf.signal.ifftshift |
| tf.signal | tf.signal.inverse\_stft |
| tf.signal | tf.signal.inverse\_stft\_window\_fn |
| tf.signal | tf.signal.irfft |
| tf.signal | tf.signal.irfft2d |
| tf.signal | tf.signal.irfft3d |
| tf.signal | tf.signal.linear\_to\_mel\_weight\_matrix |
| tf.signal | tf.signal.mfccs\_from\_log\_mel\_spectrograms |
| tf.signal | tf.signal.overlap\_and\_add |
| tf.signal | tf.signal.rfft |
| tf.signal | tf.signal.rfft2d |
| tf.signal | tf.signal.rfft3d |
| tf.signal | tf.signal.stft |
| tf.sparse | tf.sparse.add |
| tf.sparse | tf.sparse.concat |
| tf.sparse | tf.sparse.cross |
| tf.sparse | tf.sparse.cross\_hashed |
| tf.sparse | tf.sparse.expand\_dims |
| tf.sparse | tf.sparse.eye |
| tf.sparse | tf.sparse.fill\_empty\_rows |
| tf.sparse | tf.sparse.from\_dense |
| tf.sparse | tf.sparse.mask |
| tf.sparse | tf.sparse.matmul |
| tf.sparse | tf.sparse.maximum |
| tf.sparse | tf.sparse.minimum |
| tf.sparse | tf.sparse.placeholder |
| tf.sparse | tf.sparse.reduce\_max |
| tf.sparse | tf.sparse.reduce\_max\_sparse |
| tf.sparse | tf.sparse.reduce\_sum |
| tf.sparse | tf.sparse.reduce\_sum\_sparse |
| tf.sparse | tf.sparse.reorder |
| tf.sparse | tf.sparse.reset\_shape |
| tf.sparse | tf.sparse.reshape |
| tf.sparse | tf.sparse.retain |
| tf.sparse | tf.sparse.segment\_mean |
| tf.sparse | tf.sparse.segment\_sqrt\_n |
| tf.sparse | tf.sparse.segment\_sum |
| tf.sparse | tf.sparse.slice |
| tf.sparse | tf.sparse.softmax |
| tf.sparse | tf.sparse.sparse\_dense\_matmul |
| tf.sparse | tf.sparse.SparseConditionalAccumulator |
| tf.sparse | tf.sparse.SparseTensor |
| tf.sparse | tf.sparse.split |
| tf.sparse | tf.sparse.to\_dense |
| tf.sparse | tf.sparse.to\_indicator |
| tf.sparse | tf.sparse.transpose |
| tf.spectral | tf.spectral.dct |
| tf.spectral | tf.spectral.fft |
| tf.spectral | tf.spectral.fft2d |
| tf.spectral | tf.spectral.fft3d |
| tf.spectral | tf.spectral.idct |
| tf.spectral | tf.spectral.ifft |
| tf.spectral | tf.spectral.ifft2d |
| tf.spectral | tf.spectral.ifft3d |
| tf.spectral | tf.spectral.irfft |
| tf.spectral | tf.spectral.irfft2d |
| tf.spectral | tf.spectral.irfft3d |
| tf.spectral | tf.spectral.rfft |
| tf.spectral | tf.spectral.rfft2d |
| tf.spectral | tf.spectral.rfft3d |
| tf.strings | tf.strings.as\_string |
| tf.strings | tf.strings.bytes\_split |
| tf.strings | tf.strings.format |
| tf.strings | tf.strings.join |
| tf.strings | tf.strings.length |
| tf.strings | tf.strings.lower |
| tf.strings | tf.strings.ngrams |
| tf.strings | tf.strings.reduce\_join |
| tf.strings | tf.strings.regex\_full\_match |
| tf.strings | tf.strings.regex\_replace |
| tf.strings | tf.strings.split |
| tf.strings | tf.strings.strip |
| tf.strings | tf.strings.substr |
| tf.strings | tf.strings.to\_hash\_bucket |
| tf.strings | tf.strings.to\_hash\_bucket\_fast |
| tf.strings | tf.strings.to\_hash\_bucket\_strong |
| tf.strings | tf.strings.to\_number |
| tf.strings | tf.strings.unicode\_decode |
| tf.strings | tf.strings.unicode\_decode\_with\_offsets |
| tf.strings | tf.strings.unicode\_encode |
| tf.strings | tf.strings.unicode\_script |
| tf.strings | tf.strings.unicode\_split |
| tf.strings | tf.strings.unicode\_split\_with\_offsets |
| tf.strings | tf.strings.unicode\_transcode |
| tf.strings | tf.strings.unsorted\_segment\_join |
| tf.strings | tf.strings.upper |
| tf.summary | tf.summary.all\_v2\_summary\_ops |
| tf.summary | tf.summary.audio |
| tf.summary | tf.summary.Event |
| tf.summary | tf.summary.FileWriter |
| tf.summary | tf.summary.histogram |
| tf.summary | tf.summary.image |
| tf.summary | tf.summary.merge |
| tf.summary | tf.summary.merge\_all |
| tf.summary | tf.summary.scalar |
| tf.summary | tf.summary.SessionLog |
| tf.summary | tf.summary.Summary |
| tf.summary | tf.summary.Summary.Image |
| tf.summary | tf.summary.Summary.Value |
| tf.summary | tf.summary.tensor\_summary |
| tf.summary | tf.summary.text |
| tf.sysconfig | tf.sysconfig.get\_compile\_flags |
| tf.sysconfig | tf.sysconfig.get\_include |
| tf.test | tf.test.assert\_equal\_graph\_def |
| tf.test | tf.test.Benchmark |
| tf.test | tf.test.benchmark\_config |
| tf.test | tf.test.compute\_gradient |
| tf.test | tf.test.compute\_gradient\_error |
| tf.test | tf.test.create\_local\_cluster |
| tf.test | tf.test.get\_temp\_dir |
| tf.test | tf.test.gpu\_device\_name |
| tf.test | tf.test.is\_built\_with\_cuda |
| tf.test | tf.test.is\_built\_with\_gpu\_support |
| tf.test | tf.test.is\_built\_with\_rocm |
| tf.test | tf.test.is\_gpu\_available |
| tf.test | tf.test.main |
| tf.test | tf.test.StubOutForTesting |
| tf.test | tf.test.test\_src\_dir\_path |
| tf.test | tf.test.TestCase |
| tf.test | tf.test.TestCase.failureException |
| tf.train | tf.train.AdadeltaOptimizer |
| tf.train | tf.train.AdagradDAOptimizer |
| tf.train | tf.train.AdagradOptimizer |
| tf.train | tf.train.AdamOptimizer |
| tf.train | tf.train.assert\_global\_step |
| tf.train | tf.train.basic\_train\_loop |
| tf.train | tf.train.batch |
| tf.train | tf.train.batch\_join |
| tf.train | tf.train.BytesList |
| tf.train | tf.train.Checkpoint |
| tf.train | tf.train.checkpoint\_exists |
| tf.train | tf.train.CheckpointManager |
| tf.train | tf.train.checkpoints\_iterator |
| tf.train | tf.train.CheckpointSaverHook |
| tf.train | tf.train.CheckpointSaverListener |
| tf.train | tf.train.ClusterDef |
| tf.train | tf.train.ClusterSpec |
| tf.train | tf.train.Coordinator |
| tf.train | tf.train.cosine\_decay |
| tf.train | tf.train.cosine\_decay\_restarts |
| tf.train | tf.train.create\_global\_step |
| tf.train | tf.train.Example |
| tf.train | tf.train.experimental.disable\_mixed\_precision\_graph\_rewrite |
| tf.train | tf.train.experimental.DynamicLossScale |
| tf.train | tf.train.experimental.enable\_mixed\_precision\_graph\_rewrite |
| tf.train | tf.train.experimental.FixedLossScale |
| tf.train | tf.train.experimental.LossScale |
| tf.train | tf.train.experimental.MixedPrecisionLossScaleOptimizer |
| tf.train | tf.train.experimental.PythonState |
| tf.train | tf.train.exponential\_decay |
| tf.train | tf.train.ExponentialMovingAverage |
| tf.train | tf.train.export\_meta\_graph |
| tf.train | tf.train.Feature |
| tf.train | tf.train.FeatureList |
| tf.train | tf.train.FeatureLists |
| tf.train | tf.train.Features |
| tf.train | tf.train.FeedFnHook |
| tf.train | tf.train.FinalOpsHook |
| tf.train | tf.train.FloatList |
| tf.train | tf.train.FtrlOptimizer |
| tf.train | tf.train.generate\_checkpoint\_state\_proto |
| tf.train | tf.train.get\_checkpoint\_mtimes |
| tf.train | tf.train.get\_checkpoint\_state |
| tf.train | tf.train.get\_global\_step |
| tf.train | tf.train.get\_or\_create\_global\_step |
| tf.train | tf.train.global\_step |
| tf.train | tf.train.GlobalStepWaiterHook |
| tf.train | tf.train.GradientDescentOptimizer |
| tf.train | tf.train.import\_meta\_graph |
| tf.train | tf.train.init\_from\_checkpoint |
| tf.train | tf.train.Int64List |
| tf.train | tf.train.inverse\_time\_decay |
| tf.train | tf.train.JobDef |
| tf.train | tf.train.JobDef.TasksEntry |
| tf.train | tf.train.latest\_checkpoint |
| tf.train | tf.train.linear\_cosine\_decay |
| tf.train | tf.train.list\_variables |
| tf.train | tf.train.load\_checkpoint |
| tf.train | tf.train.load\_variable |
| tf.train | tf.train.LoggingTensorHook |
| tf.train | tf.train.LooperThread |
| tf.train | tf.train.MomentumOptimizer |
| tf.train | tf.train.MonitoredSession |
| tf.train | tf.train.MonitoredTrainingSession |
| tf.train | tf.train.natural\_exp\_decay |
| tf.train | tf.train.NewCheckpointReader |
| tf.train | tf.train.noisy\_linear\_cosine\_decay |
| tf.train | tf.train.Optimizer |
| tf.train | tf.train.piecewise\_constant |
| tf.train | tf.train.piecewise\_constant\_decay |
| tf.train | tf.train.polynomial\_decay |
| tf.train | tf.train.ProfilerHook |
| tf.train | tf.train.ProximalAdagradOptimizer |
| tf.train | tf.train.ProximalGradientDescentOptimizer |
| tf.train | tf.train.RMSPropOptimizer |
| tf.train | tf.train.Saver |
| tf.train | tf.train.SaverDef |
| tf.train | tf.train.Scaffold |
| tf.train | tf.train.sdca\_fprint |
| tf.train | tf.train.SecondOrStepTimer |
| tf.train | tf.train.SequenceExample |
| tf.train | tf.train.ServerDef |
| tf.train | tf.train.SessionCreator |
| tf.train | tf.train.SessionManager |
| tf.train | tf.train.SessionRunArgs |
| tf.train | tf.train.SessionRunContext |
| tf.train | tf.train.SessionRunHook |
| tf.train | tf.train.SessionRunValues |
| tf.train | tf.train.shuffle\_batch |
| tf.train | tf.train.SingularMonitoredSession |
| tf.train | tf.train.slice\_input\_producer |
| tf.train | tf.train.start\_queue\_runners |
| tf.train | tf.train.StepCounterHook |
| tf.train | tf.train.StopAtStepHook |
| tf.train | tf.train.string\_input\_producer |
| tf.train | tf.train.summary\_iterator |
| tf.train | tf.train.SummarySaverHook |
| tf.train | tf.train.Supervisor |
| tf.train | tf.train.SyncReplicasOptimizer |
| tf.train | tf.train.update\_checkpoint\_state |
| tf.train | tf.train.VocabInfo |
| tf.train | tf.train.warm\_start |
| tf.train | tf.train.WorkerSessionCreator |
| tf.train | tf.train.write\_graph |
| tf.train | tf.trainable\_variables |
| tf.user\_ops | tf.user\_ops.my\_fact |


#### 不支持的Python API

以下列表是不支持的TensorFlow Python API集合列表，但此列表并不详尽。

| 模块 | 不支持的Python API |
| --- | --- |
| tf | tf.CriticalSection |
| tf | tf.enable\_eager\_execution |
| tf | tf.enable\_tensor\_equality |
| tf | tf.enable\_v2\_behavior |
| tf | tf.enable\_v2\_tensorshape |
| tf | tf.executing\_eagerly |
| tf | tf.is\_finite |
| tf | tf.is\_inf |
| tf | tf.is\_nan |
| tf | tf.IdentityReader |
| tf | tf.LMDBReader |
| tf | tf.profiler.Profiler |
| tf | tf.WholeFileReader |
| tf.config | tf.config.experimental.get\_device\_policy |
| tf.config | tf.config.experimental.get\_memory\_growth |
| tf.config | tf.config.experimental.get\_synchronous\_execution |
| tf.config | tf.config.experimental.get\_virtual\_device\_configuration |
| tf.config | tf.config.experimental.get\_visible\_devices |
| tf.config | tf.config.experimental.list\_logical\_devices |
| tf.config | tf.config.experimental.list\_physical\_devices |
| tf.config | tf.config.experimental.set\_device\_policy |
| tf.config | tf.config.experimental.set\_memory\_growth |
| tf.config | tf.config.experimental.set\_synchronous\_execution |
| tf.config | tf.config.experimental.set\_virtual\_device\_configuration |
| tf.config | tf.config.experimental.set\_visible\_devices |
| tf.config | tf.config.experimental.VirtualDeviceConfiguration |
| tf.config | tf.config.experimental\_connect\_to\_cluster |
| tf.config | tf.config.experimental\_connect\_to\_host |
| tf.config | tf.config.experimental\_list\_devices |
| tf.config | tf.config.experimental\_run\_functions\_eagerly |
| tf.config | tf.config.get\_soft\_device\_placement |
| tf.config | tf.config.optimizer.get\_experimental\_options |
| tf.config | tf.config.optimizer.get\_jit |
| tf.config | tf.config.optimizer.set\_experimental\_options |
| tf.config | tf.config.optimizer.set\_jit |
| tf.config | tf.config.set\_soft\_device\_placement |
| tf.config | tf.config.threading.get\_inter\_op\_parallelism\_threads |
| tf.config | tf.config.threading.get\_intra\_op\_parallelism\_threads |
| tf.config | tf.config.threading.set\_inter\_op\_parallelism\_threads |
| tf.config | tf.config.threading.set\_intra\_op\_parallelism\_threads |
| tf.distribute | tf.distribute.experimental.MultiWorkerMirroredStrategy |
| tf.keras | tf.keras.callbacks.TerminateOnNaN |
| tf.keras | tf.keras.utils.multi\_gpu\_model |
| tf.profiler | tf.profiler.advise |
| tf.profiler | tf.profiler.profile |
| tf.profiler | tf.profiler.ProfileOptionBuilder |
| tf.profiler | tf.profiler.write\_op\_log |
| tf.train | tf.train.ChiefSessionCreator |
| tf.train | tf.train.NanTensorHook |
| tf.train | tf.train.replica\_device\_setter |
| tf.xla | tf.xla.experimental.compile |
| tf.xla | tf.xla.experimental.jit\_scope |