Eta

Docs

std.torch

← Stdlib Reference · Language Guide · Detailed reference

libtorch bindings: tensors, neural-network modules, optimizers, and device management.

Build flag: Available only when Eta is built with -DETA_BUILD_TORCH=ON.

(import std.torch)

Tensor construction

SymbolDescription
(tensor data shape)Build a tensor from nested data.
(ones shape)Tensor of ones.
(zeros shape)Tensor of zeros.
(randn shape)Standard-normal samples.
(arange start end [step])1-D range tensor.
(linspace start end n)Linearly spaced 1-D tensor.
(from-list xs)Build a tensor from a flat list.
(manual-seed n)Set the global RNG seed.
(tensor? x)True when x is a tensor.

Element-wise arithmetic

SymbolDescription
(t+ a b)Addition.
(t- a b)Subtraction.
(t* a b)Hadamard product.
(t/ a b)Element-wise division.
(neg a)Negation.
(tabs a)Absolute value.
(texp a)Exponential.
(tlog a)Natural log.
(tsqrt a)Square root.

Linear algebra

SymbolDescription
(matmul a b)Matrix multiplication.
(dot a b)Dot product.
(cholesky a)Cholesky factor.
(matrix-exp a)Matrix exponential.
(mvnormal mean cov n)Sample multivariate normals.
(column-l2-norm m)L2 norm per column.

Activations

SymbolDescription
(relu x)ReLU.
(sigmoid x)Sigmoid.
(ttanh x)Hyperbolic tangent.
(softmax x dim)Softmax along dimension dim.

Shape

SymbolDescription
(shape t)Shape as a list.
(reshape t shape)Reshape (no copy when possible).
(transpose t dim0 dim1)Swap two dimensions.
(squeeze t [dim])Drop unit dimensions.
(unsqueeze t dim)Insert a unit dimension.
(cat tensors dim)Concatenate along dim.
(fact-table->tensor table cols)Build a tensor from selected columns.

Reductions

SymbolDescription
(tsum t [dim])Sum (full or per dim).
(mean t [dim])Mean.
(tmax t [dim])Max.
(tmin t [dim])Min.
(argmax t [dim])Index of maximum.
(argmin t [dim])Index of minimum.
(item t)Scalar value of a 0-d tensor.
(to-list t)Convert tensor to nested lists.
(numel t)Number of elements.

Autograd

SymbolDescription
(requires-grad! t flag)Toggle gradient tracking.
(requires-grad? t)Read the flag.
(detach t)Detach from the autograd graph.
(backward loss)Backpropagate from a scalar loss.
(grad t)Gradient tensor accumulated on t.
(zero-grad! t)Clear gradient.

Modules

SymbolDescription
(linear in-features out-features)Linear layer.
(sequential layers)Chain modules.
(relu-layer)ReLU as a module.
(sigmoid-layer)Sigmoid as a module.
(dropout p)Dropout layer.
(forward module input)Run the forward pass.
(parameters module)List of trainable parameters.
(train! module)Set training mode.
(eval! module)Set eval mode.
(module? x)True when x is a module.

Losses

SymbolDescription
(mse-loss pred target)Mean-squared error.
(l1-loss pred target)Mean absolute error.
(cross-entropy-loss logits targets)Cross-entropy.

Optimizers

SymbolDescription
(sgd params lr . opts)Build an SGD optimizer.
(adam params lr . opts)Build an Adam optimizer.
(step! optimizer)Apply one optimizer step.
(optim-zero-grad! optimizer)Zero parameter gradients.
(optimizer? x)True when x is an optimizer.
(train-step! optimizer loss-thunk)Convenience: zero, forward+backward, step.

Persistence

SymbolDescription
(tensor-save t path)Save a tensor to a file.
(tensor-load path)Load a tensor from a file.
(tensor-print t)Print a tensor.

Devices

SymbolDescription
(gpu-available?)True when CUDA is available.
(gpu-count)Number of CUDA devices.
(device t)Device that holds t.
(to-device t device)Move tensor to a named device.
(to-gpu t)Move tensor to GPU 0.
(to-cpu t)Move tensor to CPU.
(nn-to-device m device)Move a module to a device.
(nn-to-gpu m)Move a module to GPU 0.
(nn-to-cpu m)Move a module to CPU.

Source: stdlib/std/torch.eta