Update llama.py

This commit is contained in:
Daniel Han-Chen 2024-02-03 22:42:11 +11:00
commit 381b991c45

View file

@ -147,9 +147,9 @@ def LlamaAttention_fast_forward_inference(
RH_Q = torch.empty((bsz, n_heads, 1, head_dim), dtype = dtype, device = "cuda")
pass
Qn = fast_linear_forward(self.q_proj, Xn, out = self.temp_QA[0])
Kn = fast_linear_forward(self.k_proj, Xn, out = self.temp_KV[0])
Vn = fast_linear_forward(self.v_proj, Xn, out = self.temp_KV[1])
Qn = fast_linear_forward(self.q_proj, Xn, out = temp_QA[0])
Kn = fast_linear_forward(self.k_proj, Xn, out = temp_KV[0])
Vn = fast_linear_forward(self.v_proj, Xn, out = temp_KV[1])
Qn = Qn.view(bsz, 1, n_heads, head_dim).transpose(1, 2)
Kn = Kn.view(bsz, 1, n_kv_heads, head_dim).transpose(1, 2)
Vn = Vn.view(bsz, 1, n_kv_heads, head_dim).transpose(1, 2)
@ -193,7 +193,7 @@ def LlamaAttention_fast_forward_inference(
A = torch.matmul(A, Vnn, out = Qn)
A = A.transpose(1, 2)
A = A.reshape(bsz, 1, self.hidden_size)
A = fast_linear_forward(self.o_proj, A, out = self.temp_QA[1])
A = fast_linear_forward(self.o_proj, A, out = temp_QA[1])
return A, (Kn, Vn)
pass