vm.torch.nn.functional¶
Functions¶
adaptive_avg_pool1d(…) : Apply the 1d adaptive average pooling to input.
adaptive_avg_pool2d(…) : Apply the 2d adaptive average pooling to input.
adaptive_avg_pool3d(…) : Apply the 3d adaptive average pooling to input.
adaptive_max_pool1d(…) : Apply the 1d adaptive max pooling to input.
adaptive_max_pool2d(…) : Apply the 2d adaptive max pooling to input.
adaptive_max_pool3d(…) : Apply the 3d adaptive max pooling to input.
affine(…) : Apply the affine transformation to input.
avg_pool1d(…) : Apply the 1d average pooling to input.
avg_pool2d(…) : Apply the 2d average pooling to input.
avg_pool3d(…) : Apply the 3d average pooling to input.
batch_norm(…) : Apply the batch normalization to input. [Ioffe & Szegedy, 2015].
binary_cross_entropy_with_logits(…) : Compute the sigmoid cross entropy with contiguous target.
channel_norm(…) : Apply the normalization to each channel of input.
channel_shuffle(…) : Apply the group shuffle to each channel of input. [Zhang et.al, 2017].
conv1d(…) : Apply the 1d convolution to input.
conv2d(…) : Apply the 2d convolution to input.
conv3d(…) : Apply the 3d convolution to input.
conv_transpose1d(…) : Apply the 1d deconvolution to input.
conv_transpose2d(…) : Apply the 2d deconvolution to input.
conv_transpose3d(…) : Apply the 3d deconvolution to input.
cosine_similarity(…) : Compute the cosine similarity between inputs.
cross_entropy(…) : Compute the softmax cross entropy.
ctc_loss(…) : Compute the ctc loss. [Graves & Gomez, 2006].
depthwise_conv2d(…) : Apply the 2d depthwise convolution to input. [Chollet, 2016].
drop_block2d(…) : Set the blocks over input to zero randomly. [Ghiasi et.al, 2018].
drop_path(…) : Set the examples over input to zero randomly. [Larsson et.al, 2016].
dropout(…) : Set the elements of input to zero randomly. [Srivastava et.al, 2014].
elu(…) : Apply the exponential linear unit to input. [Clevert et.al, 2015].
gelu(…) : Apply the gaussian error linear unit to input. [Hendrycks & Gimpel, 2016].
group_norm(…) : Apply the group normalization to input. [Wu & He, 2018].
hardsigmoid(…) : Apply the hard sigmoid function to input.
hardswish(…) : Apply the hard swish function to input. [Howard et.al, 2019].
kl_div(…) : Compute the Kullback-Leibler divergence.
l1_loss(…) : Compute the element-wise absolute value difference.
layer_norm(…) : Apply the layer normalization to input. [Ba et.al, 2016]
leaky_relu(…) : Apply the leaky rectified linear unit to input.
linear(…) : Apply the linear transformation to input.
local_response_norm(…) : Apply the local response normalization to input. [Krizhevsky et.al, 2012].
log_softmax(…) : Apply the composite of logarithm and softmax to input.
interpolate(…) : Resize input via interpolating neighborhoods.
max_pool1d(…) : Apply the 1d max pooling to input.
max_pool2d(…) : Apply the 2d max pooling to input.
max_pool3d(…) : Apply the 3d max pooling to input.
mse_loss(…) : Compute the element-wise squared error.
multi_head_attention_forward(…) : Apply the multihead attention to input. [Vaswani et.al, 2017].
nll_loss(…) : Compute the negative likelihood loss.
normalize(…) : Apply the \(L_{p}\) normalization to the input.
one_hot(…) : Return the one-hot representation of input.
pad(…) : Pad the input according to the given sizes.
pixel_shuffle(…) : Rearrange depth elements of input into pixels.
pixel_unshuffle(…) : Rearrange pixels of input into depth elements.
prelu(…) : Apply the parametric rectified linear unit to input. [He et.al, 2015].
relu(…) : Apply rectified linear unit to input. [Nair & Hinton, 2010].
relu6(…) : Apply the clipped-6 rectified linear unit to input. [Krizhevsky, 2010].
selu(…) : Compute the sigmoid focal loss. [Lin et.al, 2017].
sigmoid(…) : Apply the sigmoid function to input.
sigmoid_focal_loss(…) : Compute the sigmoid focal loss. [Lin et.al, 2017].
silu(…) : Apply the sigmoid linear unit to input. [Hendrycks & Gimpel, 2016].
smooth_l1_loss(…) : Compute the element-wise error transited from L1 and L2. [Girshick, 2015].
softmax(…) : Apply the softmax function to input.
sync_batch_norm(…) : Apply the sync batch normalization to input. [Ioffe & Szegedy, 2015].
tanh(…) : Apply the tanh function to input.
unfold(…) : Extract the sliding blocks from input.
upsample(…) : Upsample input via interpolating neighborhoods.
upsample_bilinear(…) : Upsample input via bilinear interpolating.
upsample_nearest(…) : Upsample input via nearest interpolating.