utils

Helper functions for PyTorch forecasting

Functions

autocorrelation(input[, dim])	Computes the autocorrelation of samples at dimension dim.
get_embedding_size(n)
groupby_apply(keys, values[, bins, …])	Groupby apply for torch tensors
integer_histogram(data[, min, max])	Create histogram of integers in predefined range
next_fast_len(size)	Returns the next largest number n >= size whose prime factors are all 2, 3, or 5.
padded_stack(tensors[, side, mode, value])	Stack tensors along first dimension and pad them along last dimension to ensure their size is equal.
profile(function, profile_fname[, filter, …])	Profile a given function with vmprof.
unpack_sequence(sequence)	Unpack RNN sequence.

Ranger pytorch_forecasting.utils.autocorrelation