Nn Ops

Summary

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:: DataFormatDimMap	Returns the dimension index in the destination data format given the one in.
tensorflow:: ops:: DataFormatVecPermute	Permute input tensor from src_format to dst_format .
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 the exponential linear function.
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 3D 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	TODO: add doc.
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.