vm.tensorflow.nn¶

Functions¶

avg_pool(…) : Apply the n-dimension average pooling.

avg_pool1d(…) : Apply the 1d average pooling.

avg_pool2d(…) : Apply the 2d average pooling.

avg_pool3d(…) : Apply the 3d average pooling.

bias_add(…) : Add the bias across channels to input.

conv1d(…) : Apply the 1d convolution.

conv1d_transpose(…) : Apply the 1d deconvolution.

conv2d(…) : Apply the 2d convolution.

conv2d_transpose(…) : Apply the 2d deconvolution.

conv3d(…) : Apply the 3d convolution.

conv3d_transpose(…) : Apply the 3d deconvolution.

convolution(…) : Apply the n-dimension convolution.

conv_transpose(…) : Apply the n-dimension deconvolution.

depthwise_conv2d(…) : Apply the 2d depthwise convolution. [Chollet, 2016].

depth_to_space(…) : Rearrange depth data into spatial blocks.

dropout(…) : Set the elements of input to zero randomly. [Srivastava et.al, 2014].

elu(…) : Apply the exponential exponential linear unit to input. [Clevert et.al, 2015].

fused_batch_norm(…) : Apply the batch normalization. [Ioffe & Szegedy, 2015].

gelu(…) : Apply the gaussian error linear unit. [Hendrycks & Gimpel, 2016].

l2_loss(…) : Compute the loss of element-wise squared error.

leaky_relu(…) : Apply the leaky rectified linear unit.

local_response_normalization(…) : Apply the local response normalization. [Krizhevsky et.al, 2012].

log_softmax(…) : Apply the composite of logarithm and softmax.

max_pool(…) : Apply the n-dimension max pooling.

max_pool1d(…) : Apply the 1d max pooling.

max_pool2d(…) : Apply the 2d max pooling.

max_pool3d(…) : Apply the 3d max pooling.

moments(…) : Compute the mean and variance of input along the given axes.

relu(…) : Apply the rectified linear unit. [Nair & Hinton, 2010].

relu6(…) : Apply the clipped-6 rectified linear unit. [Krizhevsky, 2010].

selu(…) : Apply the scaled exponential linear unit. [Klambauer et.al, 2017].

sigmoid_cross_entropy_with_logits(…) : Compute the loss of sigmoid cross entropy.

silu(…) : Apply the sigmoid linear unit. [Hendrycks & Gimpel, 2016].

softmax(…) : Apply the softmax function.

softmax_cross_entropy_with_logits(…) : Compute the loss of softmax cross entropy.

space_to_depth(…) : Rearrange blocks of spatial data into depth.

sparse_softmax_cross_entropy_with_logits(…) : Compute the loss of softmax cross entropy with sparse labels.