TensorFlow 1 version
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Public API for tf.raw_ops namespace.
Functions
Abort(...): Raise a exception to abort the process when called.
Abs(...): Computes the absolute value of a tensor.
AccumulateNV2(...): Returns the element-wise sum of a list of tensors.
AccumulatorApplyGradient(...): Applies a gradient to a given accumulator.
AccumulatorNumAccumulated(...): Returns the number of gradients aggregated in the given accumulators.
AccumulatorSetGlobalStep(...): Updates the accumulator with a new value for global_step.
AccumulatorTakeGradient(...): Extracts the average gradient in the given ConditionalAccumulator.
Acos(...): Computes acos of x element-wise.
Acosh(...): Computes inverse hyperbolic cosine of x element-wise.
Add(...): Returns x + y element-wise.
AddManySparseToTensorsMap(...): Add an N-minibatch SparseTensor to a SparseTensorsMap, return N handles.
AddN(...): Add all input tensors element wise.
AddSparseToTensorsMap(...): Add a SparseTensor to a SparseTensorsMap return its handle.
AddV2(...): Returns x + y element-wise.
AdjustContrast(...): Deprecated. Disallowed in GraphDef version >= 2.
AdjustContrastv2(...): Adjust the contrast of one or more images.
AdjustHue(...): Adjust the hue of one or more images.
AdjustSaturation(...): Adjust the saturation of one or more images.
All(...): Computes the "logical and" of elements across dimensions of a tensor.
AllCandidateSampler(...): Generates labels for candidate sampling with a learned unigram distribution.
AllToAll(...): An Op to exchange data across TPU replicas.
Angle(...): Returns the argument of a complex number.
AnonymousIterator(...): A container for an iterator resource.
AnonymousIteratorV2(...): A container for an iterator resource.
AnonymousMultiDeviceIterator(...): A container for a multi device iterator resource.
AnonymousRandomSeedGenerator(...)
Any(...): Computes the "logical or" of elements across dimensions of a tensor.
ApplyAdaMax(...): Update '*var' according to the AdaMax algorithm.
ApplyAdadelta(...): Update '*var' according to the adadelta scheme.
ApplyAdagrad(...): Update '*var' according to the adagrad scheme.
ApplyAdagradDA(...): Update '*var' according to the proximal adagrad scheme.
ApplyAdagradV2(...): Update '*var' according to the adagrad scheme.
ApplyAdam(...): Update '*var' according to the Adam algorithm.
ApplyAddSign(...): Update '*var' according to the AddSign update.
ApplyCenteredRMSProp(...): Update '*var' according to the centered RMSProp algorithm.
ApplyFtrl(...): Update '*var' according to the Ftrl-proximal scheme.
ApplyFtrlV2(...): Update '*var' according to the Ftrl-proximal scheme.
ApplyGradientDescent(...): Update '*var' by subtracting 'alpha' * 'delta' from it.
ApplyMomentum(...): Update '*var' according to the momentum scheme.
ApplyPowerSign(...): Update '*var' according to the AddSign update.
ApplyProximalAdagrad(...): Update 'var' and 'accum' according to FOBOS with Adagrad learning rate.
ApplyProximalGradientDescent(...): Update '*var' as FOBOS algorithm with fixed learning rate.
ApplyRMSProp(...): Update '*var' according to the RMSProp algorithm.
ApproximateEqual(...): Returns the truth value of abs(x-y) < tolerance element-wise.
ArgMax(...): Returns the index with the largest value across dimensions of a tensor.
ArgMin(...): Returns the index with the smallest value across dimensions of a tensor.
AsString(...): Converts each entry in the given tensor to strings.
Asin(...): Computes the trignometric inverse sine of x element-wise.
Asinh(...): Computes inverse hyperbolic sine of x element-wise.
Assert(...): Asserts that the given condition is true.
AssertNextDataset(...): A transformation that asserts which transformations happen next.
Assign(...): Update 'ref' by assigning 'value' to it.
AssignAdd(...): Update 'ref' by adding 'value' to it.
AssignAddVariableOp(...): Adds a value to the current value of a variable.
AssignSub(...): Update 'ref' by subtracting 'value' from it.
AssignSubVariableOp(...): Subtracts a value from the current value of a variable.
AssignVariableOp(...): Assigns a new value to a variable.
Atan(...): Computes the trignometric inverse tangent of x element-wise.
Atan2(...): Computes arctangent of y/x element-wise, respecting signs of the arguments.
Atanh(...): Computes inverse hyperbolic tangent of x element-wise.
AudioSpectrogram(...): Produces a visualization of audio data over time.
AudioSummary(...): Outputs a Summary protocol buffer with audio.
AudioSummaryV2(...): Outputs a Summary protocol buffer with audio.
AutoShardDataset(...): Creates a dataset that shards the input dataset.
AvgPool(...): Performs average pooling on the input.
AvgPool3D(...): Performs 3D average pooling on the input.
AvgPool3DGrad(...): Computes gradients of average pooling function.
AvgPoolGrad(...): Computes gradients of the average pooling function.
Barrier(...): Defines a barrier that persists across different graph executions.
BarrierClose(...): Closes the given barrier.
BarrierIncompleteSize(...): Computes the number of incomplete elements in the given barrier.
BarrierInsertMany(...): For each key, assigns the respective value to the specified component.
BarrierReadySize(...): Computes the number of complete elements in the given barrier.
BarrierTakeMany(...): Takes the given number of completed elements from a barrier.
Batch(...): Batches all input tensors nondeterministically.
BatchDataset(...): Creates a dataset that batches batch_size elements from input_dataset.
BatchDatasetV2(...): Creates a dataset that batches batch_size elements from input_dataset.
BatchFunction(...): Batches all the inputs tensors to the computation done by the function.
BatchMatMul(...): Multiplies slices of two tensors in batches.
BatchMatMulV2(...): Multiplies slices of two tensors in batches.
BatchMatrixTriangularSolve(...)
BatchNormWithGlobalNormalization(...): Batch normalization.
BatchNormWithGlobalNormalizationGrad(...): Gradients for batch normalization.
BatchToSpace(...): BatchToSpace for 4-D tensors of type T.
BatchToSpaceND(...): BatchToSpace for N-D tensors of type T.