def repeat_rows(x, num_reps):
"""Each row of tensor `x` is repeated `num_reps` times along leading dimension."""
if not utils.is_positive_int(num_reps):
raise TypeError("Number of repetitions must be a positive integer.")
shape = x.shape
x = x.unsqueeze(1)
x = x.expand(shape[0], num_reps, *shape[1:])
return merge_leading_dims(x, num_dims=2)
def tile(x, n):
if not utils.is_positive_int(n):
raise TypeError("Argument `n` must be a positive integer.")
x_ = x.reshape(-1)
x_ = x_.repeat(n)
x_ = x_.reshape(n, -1)
x_ = x_.transpose(1, 0)
x_ = x_.reshape(-1)
return x_
def merge_leading_dims(x, num_dims):
"""Reshapes the tensor `x` such that the first `num_dims` dimensions are merged to one."""
if not utils.is_positive_int(num_dims):
raise TypeError("Number of leading dims must be a positive integer.")
if num_dims > x.dim():
raise ValueError(
"Number of leading dims can't be greater than total number of dims."
)
new_shape = torch.Size([-1]) + x.shape[num_dims:]
return torch.reshape(x, new_shape)
