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import torch
from torch import nn, einsum
from einops import rearrange
class RotaryEmbedding(nn.Module):
def __init__(self, dim):
super().__init__()
inv_freq = 1.0 / (10000 ** (torch.arange(0, dim, 2).float() / dim))
self.register_buffer("inv_freq", inv_freq)
def forward(self, max_seq_len, *, device):
seq = torch.arange(max_seq_len, device=device, dtype=self.inv_freq.dtype)
freqs = einsum("i , j -> i j", seq, self.inv_freq)
return torch.cat((freqs, freqs), dim=-1)
def rotate_half(x):
x = rearrange(x, "... (j d) -> ... j d", j=2)
x1, x2 = x.unbind(dim=-2)
return torch.cat((-x2, x1), dim=-1)
def apply_rotary_pos_emb(pos, t):
return (t * pos.cos()) + (rotate_half(t) * pos.sin())
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