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author | Gustaf Rydholm <gustaf.rydholm@gmail.com> | 2023-09-11 22:11:29 +0200 |
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committer | Gustaf Rydholm <gustaf.rydholm@gmail.com> | 2023-09-11 22:11:29 +0200 |
commit | 3a9ca4a230b59e9025216383664da8ef1780a3a0 (patch) | |
tree | 7805b4c3f67f6b1e4dc71cec6272b38df8fc3a38 /text_recognizer/network/transformer/embedding | |
parent | 72ce2361f97676fc50ebc6b68b9083a402fa30c5 (diff) |
Add rotary embedding
Diffstat (limited to 'text_recognizer/network/transformer/embedding')
-rw-r--r-- | text_recognizer/network/transformer/embedding/rotary.py | 25 |
1 files changed, 25 insertions, 0 deletions
diff --git a/text_recognizer/network/transformer/embedding/rotary.py b/text_recognizer/network/transformer/embedding/rotary.py new file mode 100644 index 0000000..2254f81 --- /dev/null +++ b/text_recognizer/network/transformer/embedding/rotary.py @@ -0,0 +1,25 @@ +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()) |