Nn Ops

Summary

Typedefs

TopKV2 typedef
TopK

Classes

tensorflow::ops::AvgPool

Performs average pooling on the input.

tensorflow::ops::AvgPool3D

Performs 3D average pooling on the input.

tensorflow::ops::AvgPool3DGrad

Computes gradients of average pooling function.

tensorflow::ops::BiasAdd

Adds bias to value.

tensorflow::ops::BiasAddGrad

The backward operation for "BiasAdd" on the "bias" tensor.

tensorflow::ops::Conv2D

Computes a 2-D convolution given 4-D input and filter tensors.

tensorflow::ops::Conv2DBackpropFilter

Computes the gradients of convolution with respect to the filter.

tensorflow::ops::Conv2DBackpropInput

Computes the gradients of convolution with respect to the input.

tensorflow::ops::Conv3D

Computes a 3-D convolution given 5-D input and filter tensors.

tensorflow::ops::Conv3DBackpropFilterV2

Computes the gradients of 3-D convolution with respect to the filter.

tensorflow::ops::Conv3DBackpropInputV2

Computes the gradients of 3-D convolution with respect to the input.

tensorflow::ops::DepthwiseConv2dNative

Computes a 2-D depthwise convolution given 4-D input and filter tensors.

tensorflow::ops::DepthwiseConv2dNativeBackpropFilter

Computes the gradients of depthwise convolution with respect to the filter.

tensorflow::ops::DepthwiseConv2dNativeBackpropInput

Computes the gradients of depthwise convolution with respect to the input.

tensorflow::ops::Dilation2D

Computes the grayscale dilation of 4-D input and 3-D filter tensors.

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::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::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::MaxPoolWithArgmax

Performs max pooling on the input and outputs both max values and indices.

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::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.

Typedefs

TopKV2

TopK TopKV2