TensorFlow C ++ 참조
array_ops
후보 _ 샘플링 _ 작업
회원 | |
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tensorflow :: ops :: AllCandidateSampler | 학습 된 유니 그램 분포를 사용하여 후보 샘플링에 대한 레이블을 생성합니다. |
tensorflow :: ops :: ComputeAccidentalHits | true_labels와 일치하는 sampled_candidates 위치의 ID를 계산합니다. |
tensorflow :: ops :: FixedUnigramCandidateSampler | 학습 된 유니 그램 분포를 사용하여 후보 샘플링에 대한 레이블을 생성합니다. |
tensorflow :: ops :: LearnedUnigramCandidateSampler | 학습 된 유니 그램 분포를 사용하여 후보 샘플링에 대한 레이블을 생성합니다. |
tensorflow :: ops :: LogUniformCandidateSampler | 로그 균일 분포를 사용하여 후보 샘플링에 대한 레이블을 생성합니다. |
tensorflow :: ops :: UniformCandidateSampler | 균등 분포로 후보 샘플링에 대한 레이블을 생성합니다. |
control_flow_ops
회원 | |
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tensorflow :: ops :: Abort | 호출시 프로세스를 중단하려면 예외를 발생시킵니다. |
tensorflow :: ops :: ControlTrigger | 아무것도하지 않습니다. |
tensorflow :: ops :: LoopCond | 입력을 출력으로 전달합니다. |
tensorflow :: ops :: Merge | 사용 가능한 텐서 값을 inputs 에서 output 전달합니다. |
tensorflow :: ops :: NextIteration | 다음 반복에서 입력을 사용할 수 있도록합니다. |
tensorflow :: ops :: RefNextIteration | 다음 반복에서 입력을 사용할 수 있도록합니다. |
tensorflow :: ops :: RefSelect | inputs 의 index 번째 요소를 output 전달합니다. |
tensorflow :: ops :: RefSwitch | 참조 텐서 data 를 pred 의해 결정된 출력 포트로 전달합니다. |
tensorflow :: ops :: Switch | pred 의해 결정된 출력 포트로 data 를 전달 data . |
핵심
회원 | |
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tensorflow :: ClientSession | ClientSession 객체를 사용하면 호출자가 C ++ API로 구성된 TensorFlow 그래프의 평가를 유도 할 수 있습니다. |
tensorflow :: 입력 | Operation에 대한 피연산자로 사용할 수있는 텐서 값을 나타냅니다. |
tensorflow :: InputList | 텐서 목록이 필요한 연산에 대한 입력을 나타내는 유형입니다. |
tensorflow :: 연산 | 계산 그래프의 노드를 나타냅니다. |
tensorflow :: 출력 | Operation에 의해 생성 된 텐서 값을 나타냅니다. |
tensorflow :: 범위 | Scope 개체는 공통 이름 접두사와 같은 동일한 속성을 가진 관련 TensorFlow 작업 집합을 나타냅니다. |
tensorflow :: 상태 | Tensorflow에서 호출의 성공 또는 실패를 나타냅니다. |
tensorflow :: TensorBuffer |
data_flow_ops
image_ops
io_ops
logging_ops
회원 | |
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tensorflow :: ops :: Assert | 주어진 조건이 참임을 주장합니다. |
tensorflow :: ops :: HistogramSummary | 히스토그램과 함께 Summary 프로토콜 버퍼를 출력합니다. |
tensorflow :: ops :: MergeSummary | 요약을 병합합니다. |
tensorflow :: ops :: Print | 텐서 목록을 인쇄합니다. |
tensorflow :: ops :: PrintV2 | 문자열 스칼라를 인쇄합니다. |
tensorflow :: ops :: ScalarSummary | 스칼라 값이있는 Summary 프로토콜 버퍼를 출력합니다. |
tensorflow :: ops :: TensorSummary | 텐서가있는 Summary 프로토콜 버퍼를 출력합니다. |
tensorflow :: ops :: TensorSummaryV2 | 텐서 및 플러그인 별 데이터가있는 Summary 프로토콜 버퍼를 출력합니다. |
tensorflow :: ops :: Timestamp | Epoch 이후의 시간을 초 단위로 제공합니다. |
math_ops
nn_ops
회원 | |
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tensorflow :: ops :: AvgPool | 입력에 대해 평균 풀링을 수행합니다. |
tensorflow :: ops :: AvgPool3D | 입력에 대해 3D 평균 풀링을 수행합니다. |
tensorflow :: ops :: AvgPool3DGrad | 평균 풀링 함수의 기울기를 계산합니다. |
tensorflow :: ops :: BiasAdd | value bias 을 추가합니다. |
tensorflow :: ops :: BiasAddGrad | "bias"텐서의 "BiasAdd"에 대한 역방향 연산입니다. |
tensorflow :: ops :: Conv2D | 4 차원 input 및 filter 텐서가 주어지면 2 차원 컨볼 루션을 계산합니다. |
tensorflow :: ops :: Conv2DBackpropFilter | 필터에 대한 컨볼 루션의 기울기를 계산합니다. |
tensorflow :: ops :: Conv2DBackpropInput | 입력에 대한 컨볼 루션의 기울기를 계산합니다. |
tensorflow :: ops :: Conv3D | 5D input 및 filter 텐서가 주어지면 3D 컨볼 루션을 계산합니다. |
tensorflow :: ops :: Conv3DBackpropFilterV2 | 필터를 기준으로 3 차원 컨볼 루션의 기울기를 계산합니다. |
tensorflow :: ops :: Conv3DBackpropInputV2 | 입력 값을 기준으로 3 차원 컨벌루션의 기울기를 계산합니다. |
tensorflow :: ops :: DataFormatDimMap | 주어진 대상 데이터 형식의 차원 인덱스를 반환합니다. |
tensorflow :: ops :: DataFormatVecPermute | 주어진 대상 데이터 형식으로 순열 된 벡터 / 텐서를 반환합니다. |
tensorflow :: ops :: DepthwiseConv2dNative | 4 차원 input 및 filter 텐서가 주어진 경우 2 차원 깊이 별 컨볼 루션을 계산합니다. |
tensorflow :: ops :: DepthwiseConv2dNativeBackpropFilter | 필터를 기준으로 깊이 별 컨볼 루션의 기울기를 계산합니다. |
tensorflow :: ops :: DepthwiseConv2dNativeBackpropInput | 입력에 대한 깊이 별 컨볼 루션의 기울기를 계산합니다. |
tensorflow :: ops :: Dilation2D | 4 차원 input 및 3 차원 filter 텐서의 회색조 확장을 계산합니다. |
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::ParseExampleV2 | Transforms a vector of tf.Example protos (as strings) into typed tensors. |
tensorflow::ops::ParseSequenceExample | Transforms a vector of brain.SequenceExample protos (as strings) into typed tensors. |
tensorflow::ops::ParseSequenceExampleV2 | Transforms a vector of tf.io.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
Members | |
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tensorflow::ops::Fact | Output a fact about factorials. |