Update llama.py

This commit is contained in:
Daniel Han-Chen 2024-02-02 15:56:56 +11:00
commit 40e8848c4e

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@ -259,19 +259,19 @@ def LlamaAttention_fast_forward_inference(
Kn *= cos; Kn.addcmul_(RH_K, sin);
# New KV cache
Kn = torch.cat([K1, Kn], dim = 2)
Vn = torch.cat([V1, Vn], dim = 2)
# Kn = torch.cat([K1, Kn], dim = 2)
# Vn = torch.cat([V1, Vn], dim = 2)
if not hasattr(self, "paged_attention"):
self.paged_attention = torch.empty((2048, 2, bsz, n_kv_heads, head_dim), dtype = dtype, device = "cuda")
self.paged_attention = torch.zeros((2048, 2, bsz, n_kv_heads, head_dim), dtype = dtype, device = "cuda")
self.paged_attention_K = self.paged_attention[:,0]
self.paged_attention_V = self.paged_attention[:,1]
self.paged_attention_K[:seq_len] = K1.permute(2, 0, 1, 3)
self.paged_attention_K[:seq_len] = V1.permute(2, 0, 1, 3)
self.paged_attention_V[:seq_len] = V1.permute(2, 0, 1, 3)
pass
self.paged_attention_K[seq_len] = Kn.permute(2, 0, 1, 3)
self.paged_attention_V[seq_len] = Vn.permute(2, 0, 1, 3)
Kn = self.paged_attention_K.permute(1, 2, 0, 3)
Vn = self.paged_attention_V.permute(1, 2, 0, 3)
Kn = self.paged_attention_K[:kv_seq_len].permute(1, 2, 0, 3)
Vn = self.paged_attention_V[:kv_seq_len].permute(1, 2, 0, 3)
# Grouped query attention
if n_groups != 1: