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Update llama.py

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This commit is contained in:
Daniel Han 2025-02-20 07:40:45 -08:00
commit 1505235f0f
1 changed files with 8 additions and 6 deletions
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14
unsloth/models/llama.py
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@ -247,7 +247,7 @@ def LlamaAttention_fast_forward_inference(
# Grouped query attention
_, _, cached_len, _ = Knn.shape
if True:
if bsz == 1 or not SDPA_HAS_GQA and n_groups != 1:
Knn = Knn[:, :, None, :, :].expand(bsz, n_kv_heads, n_groups, cached_len, head_dim)
Vnn = Vnn[:, :, None, :, :].expand(bsz, n_kv_heads, n_groups, cached_len, head_dim)
Knn = Knn.reshape(bsz, n_heads, cached_len, head_dim)
@ -266,7 +266,10 @@ def LlamaAttention_fast_forward_inference(
A[:] = torch_nn_functional_softmax(A, dim = -1, dtype = torch.float32)#.to(A.dtype)
A = torch_matmul(A, Vnn, out = Qn)
else:
A = scaled_dot_product_attention(Qn, Knn, Vnn, attn_mask = attention_mask, is_causal = False)
if SDPA_HAS_GQA:
A = scaled_dot_product_attention(Qn, Knn, Vnn, attn_mask = attention_mask, is_causal = False, enable_gqa = True)
else:
A = scaled_dot_product_attention(Qn, Knn, Vnn, attn_mask = attention_mask, is_causal = False)
pass
A = A.transpose(1, 2)
A = A.reshape(bsz, 1, attention_size)
@ -448,10 +451,9 @@ def LlamaAttention_fast_forward(
if SDPA_HAS_GQA:
# Needs (batch_size, n_heads, seq_len, head_dim)
# is_casual and attention_mask must not be both set!
Q, K, V = Q.contiguous(), K.contiguous(), V.contiguous()
A = scaled_dot_product_attention(Q, K, V, attn_mask = attention_mask, is_causal = False, enable_gqa = n_groups != 1)
# Go back to (batch_size, seq_len, n_heads, head_dim)
A = A.transpose(1, 2).contiguous()
A = A.transpose(1, 2)#.contiguous()
else:
if n_groups != 1:
K = K[:, :, None, :, :].expand(bsz, n_kv_heads, n_groups, kv_seq_len, head_dim)
@ -723,8 +725,8 @@ def LlamaModel_fast_forward(
past_key_values_length,
sliding_window = getattr(self.config, "sliding_window", None),
)
if attention_mask is not None:
attention_mask = attention_mask.to(torch.bool)
# if attention_mask is not None:
# attention_mask = attention_mask.to(torch.bool)
pass
hidden_states = inputs_embeds