TensorFlow C ++リファレンス
array_ops
Candidate_sampling_ops
メンバー | |
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tensorflow :: ops :: AllCandidateSampler | 学習したユニグラム分布を使用して、候補サンプリングのラベルを生成します。 |
tensorflow :: ops :: ComputeAccidentalHits | true_labelsに一致するsampled_candidatesの位置のIDを計算します。 |
tensorflow :: ops :: FixedUnigramCandidateSampler | 学習したユニグラム分布を使用して、候補サンプリングのラベルを生成します。 |
tensorflow :: ops :: LearnedUnigramCandidateSampler | 学習したユニグラム分布を使用して、候補サンプリングのラベルを生成します。 |
tensorflow :: ops :: LogUniformCandidateSampler | 対数均一分布の候補サンプリング用のラベルを生成します。 |
tensorflow :: ops :: UniformCandidateSampler | 一様分布の候補サンプリング用のラベルを生成します。 |
control_flow_ops
メンバー | |
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tensorflow :: ops :: Abort | 呼び出されたときにプロセスを中止するには、例外を発生させます。 |
tensorflow :: ops :: ControlTrigger | 何もしません。 |
tensorflow :: ops :: LoopCond | 入力を出力に転送します。 |
tensorflow :: ops :: Merge | 利用可能なテンソルの値をinputs からoutput inputs しoutput 。 |
tensorflow :: ops :: NextIteration | その入力を次の反復で使用できるようにします。 |
tensorflow :: ops :: RefNextIteration | その入力を次の反復で使用できるようにします。 |
tensorflow :: ops :: RefSelect | inputs index 番目の要素をoutput にinputs しoutput 。 |
tensorflow :: ops :: RefSwitch | pred によって決定された出力ポートに参照テンソルdata をdata します。 |
tensorflow :: ops :: Switch | pred によって決定された出力ポートにdata をdata します。 |
芯
メンバー | |
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tensorflow :: ClientSession | ClientSession オブジェクトを使用すると、呼び出し元はC ++ APIで作成されたTensorFlowグラフの評価を実行できます。 |
tensorflow :: Input | オペランドとして使用することができるテンソル値表す動作。 |
tensorflow :: InputList | テンソルのリストを必要とするopsへの入力を表すためのタイプ。 |
tensorflow :: Operation | 計算グラフのノードを表します。 |
tensorflow :: Output | 操作によって生成されたテンソル値を表します。 |
tensorflow :: Scope | Scope オブジェクトは、共通名のプレフィックスなど、同じプロパティを持つ関連するTensorFlow操作のセットを表します。 |
tensorflow :: Status | Tensorflowでの呼び出しの成功または失敗を示します。 |
tensorflow :: TensorBuffer |
data_flow_ops
image_ops
io_ops
logging_ops
メンバー | |
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tensorflow :: ops :: Assert | 指定された条件が真であることを表明します。 |
tensorflow :: ops :: HistogramSummary | ヒストグラム付きのSummary プロトコルバッファを出力します。 |
tensorflow :: ops :: MergeSummary | 要約をマージします。 |
tensorflow :: ops :: Print | テンソルのリストを出力します。 |
tensorflow :: ops :: PrintV2 | 文字列スカラーを出力します。 |
tensorflow :: ops :: ScalarSummary | スカラー値を含むSummary プロトコルバッファを出力します。 |
tensorflow :: ops :: TensorSummary | テンソルを使用してSummary プロトコルバッファを出力します。 |
tensorflow :: ops :: TensorSummaryV2 | テンソルとプラグインごとのデータを含むSummary プロトコルバッファを出力します。 |
tensorflow :: ops :: Timestamp | エポックからの時間を秒単位で提供します。 |
math_ops
nn_ops
メンバー | |
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tensorflow :: ops :: AvgPool | 入力に対して平均プーリングを実行します。 |
tensorflow :: ops :: AvgPool3D | 入力に対して3D平均プーリングを実行します。 |
tensorflow :: ops :: AvgPool3DGrad | 平均プーリング関数の勾配を計算します。 |
tensorflow :: ops :: biasAdd | value bias を追加しvalue 。 |
tensorflow :: ops :: biasAddGrad | 「bias」テンソルでの「BiasAdd」の逆方向操作。 |
tensorflow :: ops :: Conv2D | 4D input およびfilter テンソルが与えられた場合の2D畳み込みを計算します。 |
tensorflow :: ops :: Conv2DBackpropFilter | フィルタに関する畳み込みの勾配を計算します。 |
tensorflow :: ops :: Conv2DBackpropInput | 入力に関する畳み込みの勾配を計算します。 |
tensorflow :: ops :: Conv3D | 5D input およびfilter テンソルが与えられた場合の3D畳み込みを計算します。 |
tensorflow :: ops :: Conv3DBackpropFilterV2 | フィルタに関する3D畳み込みの勾配を計算します。 |
tensorflow :: ops :: Conv3DBackpropInputV2 | 入力に関する3D畳み込みの勾配を計算します。 |
tensorflow :: ops :: DataFormatDimMap | で指定された宛先データ形式でディメンションインデックスを返します。 |
tensorflow :: ops :: DataFormatVecPermute | 指定された宛先データ形式で並べ替えられたベクトル/テンソルを返します。 |
tensorflow :: ops :: DeepthwiseConv2dNative | 4D input テンソルとfilter テンソルを指定して、2次元の深さ方向の畳み込みを計算します。 |
tensorflow :: ops :: DeepthwiseConv2dNativeBackpropFilter | フィルタに関する深さ方向の畳み込みの勾配を計算します。 |
tensorflow :: ops :: DeepthwiseConv2dNativeBackpropInput | 入力に関する深さ方向の畳み込みの勾配を計算します。 |
tensorflow :: ops :: Dilation2D | 4D input と3D filter テンソルのグレースケール膨張を計算します。 |
tensorflow :: ops :: Dilation2DBackpropFilter | Computes the gradient of morphological 2-D dilation with respect to the filter. |
tensorflow::ops::Dilation2DBackpropInput | Computes the gradient of morphological 2-D dilation with respect to the input. |
tensorflow::ops::Elu | Computes exponential linear: exp(features) - 1 if < 0, features otherwise. |
tensorflow::ops::FractionalAvgPool | Performs fractional average pooling on the input. |
tensorflow::ops::FractionalMaxPool | Performs fractional max pooling on the input. |
tensorflow::ops::FusedBatchNorm | Batch normalization. |
tensorflow::ops::FusedBatchNormGrad | Gradient for batch normalization. |
tensorflow::ops::FusedBatchNormGradV2 | Gradient for batch normalization. |
tensorflow::ops::FusedBatchNormGradV3 | Gradient for batch normalization. |
tensorflow::ops::FusedBatchNormV2 | Batch normalization. |
tensorflow::ops::FusedBatchNormV3 | Batch normalization. |
tensorflow::ops::FusedPadConv2D | Performs a padding as a preprocess during a convolution. |
tensorflow::ops::FusedResizeAndPadConv2D | Performs a resize and padding as a preprocess during a convolution. |
tensorflow::ops::InTopK | Says whether the targets are in the top K predictions. |
tensorflow::ops::InTopKV2 | Says whether the targets are in the top K predictions. |
tensorflow::ops::L2Loss | L2 Loss. |
tensorflow::ops::LRN | Local Response Normalization. |
tensorflow::ops::LogSoftmax | Computes log softmax activations. |
tensorflow::ops::MaxPool | Performs max pooling on the input. |
tensorflow::ops::MaxPool3D | Performs 3D max pooling on the input. |
tensorflow::ops::MaxPool3DGrad | Computes gradients of max pooling function. |
tensorflow::ops::MaxPool3DGradGrad | Computes second-order gradients of the maxpooling function. |
tensorflow::ops::MaxPoolGradGrad | Computes second-order gradients of the maxpooling function. |
tensorflow::ops::MaxPoolGradGradV2 | Computes second-order gradients of the maxpooling function. |
tensorflow::ops::MaxPoolGradGradWithArgmax | Computes second-order gradients of the maxpooling function. |
tensorflow::ops::MaxPoolGradV2 | Computes gradients of the maxpooling function. |
tensorflow::ops::MaxPoolV2 | Performs max pooling on the input. |
tensorflow::ops::MaxPoolWithArgmax | Performs max pooling on the input and outputs both max values and indices. |
tensorflow::ops::NthElement | Finds values of the n -th order statistic for the last dimension. |
tensorflow::ops::QuantizedAvgPool | Produces the average pool of the input tensor for quantized types. |
tensorflow::ops::QuantizedBatchNormWithGlobalNormalization | Quantized Batch normalization. |
tensorflow::ops::QuantizedBiasAdd | Adds Tensor 'bias' to Tensor 'input' for Quantized types. |
tensorflow::ops::QuantizedConv2D | Computes a 2D convolution given quantized 4D input and filter tensors. |
tensorflow::ops::QuantizedMaxPool | Produces the max pool of the input tensor for quantized types. |
tensorflow::ops::QuantizedRelu | Computes Quantized Rectified Linear: max(features, 0) |
tensorflow::ops::QuantizedRelu6 | Computes Quantized Rectified Linear 6: min(max(features, 0), 6) |
tensorflow::ops::QuantizedReluX | Computes Quantized Rectified Linear X: min(max(features, 0), max_value) |
tensorflow::ops::Relu | Computes rectified linear: max(features, 0) . |
tensorflow::ops::Relu6 | Computes rectified linear 6: min(max(features, 0), 6) . |
tensorflow::ops::Selu | Computes scaled exponential linear: scale * alpha * (exp(features) - 1) |
tensorflow::ops::Softmax | Computes softmax activations. |
tensorflow::ops::SoftmaxCrossEntropyWithLogits | Computes softmax cross entropy cost and gradients to backpropagate. |
tensorflow::ops::Softplus | Computes softplus: log(exp(features) + 1) . |
tensorflow::ops::Softsign | Computes softsign: features / (abs(features) + 1) . |
tensorflow::ops::SparseSoftmaxCrossEntropyWithLogits | Computes softmax cross entropy cost and gradients to backpropagate. |
tensorflow::ops::TopK | Finds values and indices of the k largest elements for the last dimension. |
no_op
Members | |
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tensorflow::ops::NoOp | Does nothing. |
parsing_ops
Members | |
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tensorflow::ops::DecodeCSV | Convert CSV records to tensors. |
tensorflow::ops::DecodeCompressed | Decompress strings. |
tensorflow::ops::DecodeJSONExample | Convert JSON-encoded Example records to binary protocol buffer strings. |
tensorflow::ops::DecodePaddedRaw | Reinterpret the bytes of a string as a vector of numbers. |
tensorflow::ops::DecodeRaw | Reinterpret the bytes of a string as a vector of numbers. |
tensorflow::ops::ParseExample | Transforms a vector of brain.Example protos (as strings) into typed tensors. |
tensorflow::ops::ParseSequenceExample | Transforms a vector of brain.SequenceExample protos (as strings) into typed tensors. |
tensorflow::ops::ParseSingleExample | Transforms a tf.Example proto (as a string) into typed tensors. |
tensorflow::ops::ParseSingleSequenceExample | Transforms a scalar brain.SequenceExample proto (as strings) into typed tensors. |
tensorflow::ops::ParseTensor | Transforms a serialized tensorflow.TensorProto proto into a Tensor . |
tensorflow::ops::SerializeTensor | Transforms a Tensor into a serialized TensorProto proto. |
tensorflow::ops::StringToNumber | Converts each string in the input Tensor to the specified numeric type. |
random_ops
Members | |
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tensorflow::ops::Multinomial | Draws samples from a multinomial distribution. |
tensorflow::ops::ParameterizedTruncatedNormal | Outputs random values from a normal distribution. |
tensorflow::ops::RandomGamma | Outputs random values from the Gamma distribution(s) described by alpha. |
tensorflow::ops::RandomNormal | Outputs random values from a normal distribution. |
tensorflow::ops::RandomPoissonV2 | Outputs random values from the Poisson distribution(s) described by rate. |
tensorflow::ops::RandomShuffle | Randomly shuffles a tensor along its first dimension. |
tensorflow::ops::RandomUniform | Outputs random values from a uniform distribution. |
tensorflow::ops::RandomUniformInt | Outputs random integers from a uniform distribution. |
tensorflow::ops::TruncatedNormal | Outputs random values from a truncated normal distribution. |
sparse_ops
Members | |
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tensorflow::ops::AddManySparseToTensorsMap | Add an N -minibatch SparseTensor to a SparseTensorsMap , return N handles. |
tensorflow::ops::AddSparseToTensorsMap | Add a SparseTensor to a SparseTensorsMap return its handle. |
tensorflow::ops::DeserializeManySparse | Deserialize and concatenate SparseTensors from a serialized minibatch. |
tensorflow::ops::DeserializeSparse | Deserialize SparseTensor objects. |
tensorflow::ops::SerializeManySparse | Serialize an N -minibatch SparseTensor into an [N, 3] Tensor object. |
tensorflow::ops::SerializeSparse | Serialize a SparseTensor into a [3] Tensor object. |
tensorflow::ops::SparseAdd | Adds two SparseTensor objects to produce another SparseTensor . |
tensorflow::ops::SparseAddGrad | The gradient operator for the SparseAdd op. |
tensorflow::ops::SparseConcat | Concatenates a list of SparseTensor along the specified dimension. |
tensorflow::ops::SparseCross | Generates sparse cross from a list of sparse and dense tensors. |
tensorflow::ops::SparseDenseCwiseAdd | Adds up a SparseTensor and a dense Tensor , using these special rules: |
tensorflow::ops::SparseDenseCwiseDiv | Component-wise divides a SparseTensor by a dense Tensor . |
tensorflow::ops::SparseDenseCwiseMul | Component-wise multiplies a SparseTensor by a dense Tensor . |
tensorflow::ops::SparseFillEmptyRows | Fills empty rows in the input 2-D SparseTensor with a default value. |
tensorflow::ops::SparseFillEmptyRowsGrad | The gradient of SparseFillEmptyRows . |
tensorflow::ops::SparseReduceMax | Computes the max of elements across dimensions of a SparseTensor. |
tensorflow::ops::SparseReduceMaxSparse | Computes the max of elements across dimensions of a SparseTensor. |
tensorflow::ops::SparseReduceSum | Computes the sum of elements across dimensions of a SparseTensor. |
tensorflow::ops::SparseReduceSumSparse | Computes the sum of elements across dimensions of a SparseTensor. |
tensorflow::ops::SparseReorder | Reorders a SparseTensor into the canonical, row-major ordering. |
tensorflow::ops::SparseReshape | Reshapes a SparseTensor to represent values in a new dense shape. |
tensorflow::ops::SparseSlice | Slice a SparseTensor based on the start and size . |
tensorflow::ops::SparseSliceGrad | The gradient operator for the SparseSlice op. |
tensorflow::ops::SparseSoftmax | Applies softmax to a batched ND SparseTensor . |
tensorflow::ops::SparseSparseMaximum | Returns the element-wise max of two SparseTensors. |
tensorflow::ops::SparseSparseMinimum | Returns the element-wise min of two SparseTensors. |
tensorflow::ops::SparseSplit | Split a SparseTensor into num_split tensors along one dimension. |
tensorflow::ops::SparseTensorDenseAdd | Adds up a SparseTensor and a dense Tensor , producing a dense Tensor . |
tensorflow::ops::SparseTensorDenseMatMul | Multiply SparseTensor (of rank 2) "A" by dense matrix "B". |
tensorflow::ops::TakeManySparseFromTensorsMap | Converts a sparse representation into a dense tensor. |
state_ops
Members | |
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tensorflow::ops::Assign | Update 'ref' by assigning 'value' to it. |
tensorflow::ops::AssignAdd | Update 'ref' by adding 'value' to it. |
tensorflow::ops::AssignSub | Update 'ref' by subtracting 'value' from it. |
tensorflow::ops::CountUpTo | Increments 'ref' until it reaches 'limit'. |
tensorflow::ops::DestroyTemporaryVariable | Destroys the temporary variable and returns its final value. |
tensorflow::ops::IsVariableInitialized | Checks whether a tensor has been initialized. |
tensorflow::ops::ResourceCountUpTo | Increments variable pointed to by 'resource' until it reaches 'limit'. |
tensorflow::ops::ResourceScatterNdAdd | Applies sparse addition to individual values or slices in a Variable . |
tensorflow::ops::ResourceScatterNdSub | Applies sparse subtraction to individual values or slices in a Variable . |
tensorflow::ops::ResourceScatterNdUpdate | Applies sparse updates to individual values or slices within a given. |
tensorflow::ops::ScatterAdd | Adds sparse updates to a variable reference. |
tensorflow::ops::ScatterDiv | Divides a variable reference by sparse updates. |
tensorflow::ops::ScatterMax | Reduces sparse updates into a variable reference using the max operation. |
tensorflow::ops::ScatterMin | Reduces sparse updates into a variable reference using the min operation. |
tensorflow::ops::ScatterMul | Multiplies sparse updates into a variable reference. |
tensorflow::ops::ScatterNdAdd | Applies sparse addition to individual values or slices in a Variable . |
tensorflow::ops::ScatterNdSub | Applies sparse subtraction to individual values or slices in a Variable . |
tensorflow::ops::ScatterNdUpdate | Applies sparse updates to individual values or slices within a given. |
tensorflow::ops::ScatterSub | Subtracts sparse updates to a variable reference. |
tensorflow::ops::ScatterUpdate | Applies sparse updates to a variable reference. |
tensorflow::ops::TemporaryVariable | Returns a tensor that may be mutated, but only persists within a single step. |
tensorflow::ops::Variable | Holds state in the form of a tensor that persists across steps. |
string_ops
Members | |
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tensorflow::ops::AsString | Converts each entry in the given tensor to strings. |
tensorflow::ops::DecodeBase64 | Decode web-safe base64-encoded strings. |
tensorflow::ops::EncodeBase64 | Encode strings into web-safe base64 format. |
tensorflow::ops::ReduceJoin | Joins a string Tensor across the given dimensions. |
tensorflow::ops::RegexFullMatch | Check if the input matches the regex pattern. |
tensorflow::ops::RegexReplace | Replaces matches of the pattern regular expression in input with the replacement string provided in rewrite . |
tensorflow::ops::StringFormat | Formats a string template using a list of tensors. |
tensorflow::ops::StringJoin | Joins the strings in the given list of string tensors into one tensor;. |
tensorflow::ops::StringLength | String lengths of input . |
tensorflow::ops::StringLower | TODO: add doc. |
tensorflow::ops::StringNGrams | Creates ngrams from ragged string data. |
tensorflow::ops::StringSplit | Split elements of input based on delimiter into a SparseTensor . |
tensorflow::ops::StringSplitV2 | Split elements of source based on sep into a SparseTensor . |
tensorflow::ops::StringStrip | Strip leading and trailing whitespaces from the Tensor . |
tensorflow::ops::StringToHashBucket | Converts each string in the input Tensor to its hash mod by a number of buckets. |
tensorflow::ops::StringToHashBucketFast | Converts each string in the input Tensor to its hash mod by a number of buckets. |
tensorflow::ops::StringToHashBucketStrong | Converts each string in the input Tensor to its hash mod by a number of buckets. |
tensorflow::ops::StringUpper | TODO: add doc. |
tensorflow::ops::Substr | Return substrings from Tensor of strings. |
tensorflow::ops::UnicodeScript | Determine the script codes of a given tensor of Unicode integer code points. |
tensorflow::ops::UnicodeTranscode | Transcode the input text from a source encoding to a destination encoding. |
tensorflow::ops::UnsortedSegmentJoin | Joins the elements of inputs based on segment_ids . |
training_ops
Members | |
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tensorflow::ops::ApplyAdadelta | Update '*var' according to the adadelta scheme. |
tensorflow::ops::ApplyAdagrad | Update '*var' according to the adagrad scheme. |
tensorflow::ops::ApplyAdagradDA | Update '*var' according to the proximal adagrad scheme. |
tensorflow::ops::ApplyAdam | Update '*var' according to the Adam algorithm. |
tensorflow::ops::ApplyAddSign | Update '*var' according to the AddSign update. |
tensorflow::ops::ApplyCenteredRMSProp | Update '*var' according to the centered RMSProp algorithm. |
tensorflow::ops::ApplyFtrl | Update '*var' according to the Ftrl-proximal scheme. |
tensorflow::ops::ApplyFtrlV2 | Update '*var' according to the Ftrl-proximal scheme. |
tensorflow::ops::ApplyGradientDescent | Update '*var' by subtracting 'alpha' * 'delta' from it. |
tensorflow::ops::ApplyMomentum | Update '*var' according to the momentum scheme. |
tensorflow::ops::ApplyPowerSign | Update '*var' according to the AddSign update. |
tensorflow::ops::ApplyProximalAdagrad | Update '*var' and '*accum' according to FOBOS with Adagrad learning rate. |
tensorflow::ops::ApplyProximalGradientDescent | Update '*var' as FOBOS algorithm with fixed learning rate. |
tensorflow::ops::ApplyRMSProp | Update '*var' according to the RMSProp algorithm. |
tensorflow::ops::ResourceApplyAdadelta | Update '*var' according to the adadelta scheme. |
tensorflow::ops::ResourceApplyAdagrad | Update '*var' according to the adagrad scheme. |
tensorflow::ops::ResourceApplyAdagradDA | Update '*var' according to the proximal adagrad scheme. |
tensorflow::ops::ResourceApplyAdam | Update '*var' according to the Adam algorithm. |
tensorflow::ops::ResourceApplyAdamWithAmsgrad | Update '*var' according to the Adam algorithm. |
tensorflow::ops::ResourceApplyAddSign | Update '*var' according to the AddSign update. |
tensorflow::ops::ResourceApplyCenteredRMSProp | Update '*var' according to the centered RMSProp algorithm. |
tensorflow::ops::ResourceApplyFtrl | Update '*var' according to the Ftrl-proximal scheme. |
tensorflow::ops::ResourceApplyFtrlV2 | Update '*var' according to the Ftrl-proximal scheme. |
tensorflow::ops::ResourceApplyGradientDescent | Update '*var' by subtracting 'alpha' * 'delta' from it. |
tensorflow::ops::ResourceApplyKerasMomentum | Update '*var' according to the momentum scheme. |
tensorflow::ops::ResourceApplyMomentum | Update '*var' according to the momentum scheme. |
tensorflow::ops::ResourceApplyPowerSign | Update '*var' according to the AddSign update. |
tensorflow::ops::ResourceApplyProximalAdagrad | Update '*var' and '*accum' according to FOBOS with Adagrad learning rate. |
tensorflow::ops::ResourceApplyProximalGradientDescent | Update '*var' as FOBOS algorithm with fixed learning rate. |
tensorflow::ops::ResourceApplyRMSProp | Update '*var' according to the RMSProp algorithm. |
tensorflow::ops::ResourceSparseApplyAdadelta | var: Should be from a Variable(). |
tensorflow::ops::ResourceSparseApplyAdagrad | Update relevant entries in '*var' and '*accum' according to the adagrad scheme. |
tensorflow::ops::ResourceSparseApplyAdagradDA | Update entries in '*var' and '*accum' according to the proximal adagrad scheme. |
tensorflow::ops::ResourceSparseApplyCenteredRMSProp | Update '*var' according to the centered RMSProp algorithm. |
tensorflow::ops::ResourceSparseApplyFtrl | Update relevant entries in '*var' according to the Ftrl-proximal scheme. |
tensorflow::ops::ResourceSparseApplyFtrlV2 | Update relevant entries in '*var' according to the Ftrl-proximal scheme. |
tensorflow::ops::ResourceSparseApplyKerasMomentum | Update relevant entries in '*var' and '*accum' according to the momentum scheme. |
tensorflow::ops::ResourceSparseApplyMomentum | Update relevant entries in '*var' and '*accum' according to the momentum scheme. |
tensorflow::ops::ResourceSparseApplyProximalAdagrad | Sparse update entries in '*var' and '*accum' according to FOBOS algorithm. |
tensorflow::ops::ResourceSparseApplyProximalGradientDescent | Sparse update '*var' as FOBOS algorithm with fixed learning rate. |
tensorflow::ops::ResourceSparseApplyRMSProp | Update '*var' according to the RMSProp algorithm. |
tensorflow::ops::SparseApplyAdadelta | var: Should be from a Variable(). |
tensorflow::ops::SparseApplyAdagrad | Update relevant entries in '*var' and '*accum' according to the adagrad scheme. |
tensorflow::ops::SparseApplyAdagradDA | Update entries in '*var' and '*accum' according to the proximal adagrad scheme. |
tensorflow::ops::SparseApplyCenteredRMSProp | Update '*var' according to the centered RMSProp algorithm. |
tensorflow::ops::SparseApplyFtrl | Update relevant entries in '*var' according to the Ftrl-proximal scheme. |
tensorflow::ops::SparseApplyFtrlV2 | Update relevant entries in '*var' according to the Ftrl-proximal scheme. |
tensorflow::ops::SparseApplyMomentum | Update relevant entries in '*var' and '*accum' according to the momentum scheme. |
tensorflow::ops::SparseApplyProximalAdagrad | Sparse update entries in '*var' and '*accum' according to FOBOS algorithm. |
tensorflow::ops::SparseApplyProximalGradientDescent | Sparse update '*var' as FOBOS algorithm with fixed learning rate. |
tensorflow::ops::SparseApplyRMSProp | Update '*var' according to the RMSProp algorithm. |
user_ops
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tensorflow::ops::Fact | Output a fact about factorials. |