import torch class Rotary(torch.nn.Module): def __init__(self, dim, base=10_000): super().__init__() inv_freq = 1.0 / (base ** (torch.arange(0, dim, 2).float() / dim)) self.register_buffer("inv_freq", inv_freq) self.seq_len_cached = None self.cos_cached = None self.sin_cached = None def forward(self, x, seq_dim=1): seq_len = x.shape[seq_dim] if seq_len != self.seq_len_cached: self.seq_len_cached = seq_len t = torch.arange(x.shape[seq_dim], device=x.device).type_as(self.inv_freq) freqs = torch.einsum("i,j->ij", t, self.inv_freq.clone()) emb = torch.cat((freqs, freqs), dim=-1).to(x.device) # dims are: batch, seq_len, qkv, head, dim self.cos_cached = emb.cos()[None, :, None, None, :].repeat(1, 1, 3, 1, 1) self.sin_cached = emb.sin()[None, :, None, None, :].repeat(1, 1, 3, 1, 1) # This makes the transformation on v an identity. self.cos_cached[:, :, 2, :, :].fill_(1.0) self.sin_cached[:, :, 2, :, :].fill_(0.0) return self.cos_cached, self.sin_cached def rotate_half(x): x1, x2 = x[..., : x.shape[-1] // 2], x[..., x.shape[-1] // 2 :] return torch.cat((-x2, x1), dim=-1) def _apply_rotary_pos_emb_native(qkv, cos, sin): """Native PyTorch implementation without JIT compilation""" return (qkv * cos) + (rotate_half(qkv) * sin) @torch.jit.script def _apply_rotary_pos_emb_torchscript(qkv, cos, sin): return (qkv * cos) + (rotate_half(qkv) * sin) def apply_rotary_pos_emb(qkv, cos, sin): try: import flash_attn.layers.rotary cos_flash = cos[0, :, 0, 0, : cos.shape[-1] // 2] sin_flash = sin[0, :, 0, 0, : sin.shape[-1] // 2] return flash_attn.layers.rotary.apply_rotary_emb_qkv_(qkv, cos_flash, sin_flash) except (ImportError, AttributeError, RuntimeError): # Use native implementation without TorchScript due to compatibility issues return _apply_rotary_pos_emb_native(qkv, cos, sin)