mirror of
https://github.com/ggerganov/llama.cpp.git
synced 2024-12-25 10:54:36 +00:00
mpt : implement backwards compatiblity with duped output tensor (#6139)
This commit is contained in:
parent
104f5e0fc1
commit
d199ca79f2
17
llama.cpp
17
llama.cpp
@ -540,6 +540,7 @@ static const std::map<llm_arch, std::map<llm_tensor, std::string>> LLM_TENSOR_NA
|
|||||||
{
|
{
|
||||||
{ LLM_TENSOR_TOKEN_EMBD, "token_embd" },
|
{ LLM_TENSOR_TOKEN_EMBD, "token_embd" },
|
||||||
{ LLM_TENSOR_OUTPUT_NORM, "output_norm" },
|
{ LLM_TENSOR_OUTPUT_NORM, "output_norm" },
|
||||||
|
{ LLM_TENSOR_OUTPUT, "output"},
|
||||||
{ LLM_TENSOR_ATTN_NORM, "blk.%d.attn_norm" },
|
{ LLM_TENSOR_ATTN_NORM, "blk.%d.attn_norm" },
|
||||||
{ LLM_TENSOR_FFN_NORM, "blk.%d.ffn_norm" },
|
{ LLM_TENSOR_FFN_NORM, "blk.%d.ffn_norm" },
|
||||||
{ LLM_TENSOR_ATTN_QKV, "blk.%d.attn_qkv" },
|
{ LLM_TENSOR_ATTN_QKV, "blk.%d.attn_qkv" },
|
||||||
@ -4300,9 +4301,9 @@ static bool llm_load_tensors(
|
|||||||
{
|
{
|
||||||
model.output_norm = ml.create_tensor(ctx_output, tn(LLM_TENSOR_OUTPUT_NORM, "weight"), {n_embd});
|
model.output_norm = ml.create_tensor(ctx_output, tn(LLM_TENSOR_OUTPUT_NORM, "weight"), {n_embd});
|
||||||
model.output_norm_b = ml.create_tensor(ctx_output, tn(LLM_TENSOR_OUTPUT_NORM, "bias"), {n_embd});
|
model.output_norm_b = ml.create_tensor(ctx_output, tn(LLM_TENSOR_OUTPUT_NORM, "bias"), {n_embd});
|
||||||
if (gguf_find_tensor(ml.ctx_gguf, tn(LLM_TENSOR_OUTPUT, "weight").c_str()) >= 0) {
|
|
||||||
model.output = ml.create_tensor(ctx_output_split, tn(LLM_TENSOR_OUTPUT, "weight"), {n_embd, n_vocab});
|
model.output = ml.create_tensor(ctx_output_split, tn(LLM_TENSOR_OUTPUT, "weight"), {n_embd, n_vocab}, false);
|
||||||
} else {
|
if (!model.output) {
|
||||||
model.output = ml.create_tensor(ctx_output_split, tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab}); // needs to be on GPU
|
model.output = ml.create_tensor(ctx_output_split, tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab}); // needs to be on GPU
|
||||||
ml.n_created--; // artificial tensor
|
ml.n_created--; // artificial tensor
|
||||||
ml.size_data += ggml_nbytes(model.output);
|
ml.size_data += ggml_nbytes(model.output);
|
||||||
@ -4507,10 +4508,12 @@ static bool llm_load_tensors(
|
|||||||
model.output_norm = ml.create_tensor(ctx_output, tn(LLM_TENSOR_OUTPUT_NORM, "weight"), {n_embd});
|
model.output_norm = ml.create_tensor(ctx_output, tn(LLM_TENSOR_OUTPUT_NORM, "weight"), {n_embd});
|
||||||
model.output_norm_b = ml.create_tensor(ctx_output, tn(LLM_TENSOR_OUTPUT_NORM, "bias"), {n_embd}, false);
|
model.output_norm_b = ml.create_tensor(ctx_output, tn(LLM_TENSOR_OUTPUT_NORM, "bias"), {n_embd}, false);
|
||||||
|
|
||||||
// same as tok_embd, duplicated to allow offloading
|
model.output = ml.create_tensor(ctx_output_split, tn(LLM_TENSOR_OUTPUT, "weight"), {n_embd, n_vocab}, false);
|
||||||
model.output = ml.create_tensor(ctx_output_split, tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab});
|
if (!model.output) {
|
||||||
ml.n_created--; // artificial tensor
|
model.output = ml.create_tensor(ctx_output_split, tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab}); // needs to be on GPU
|
||||||
ml.size_data += ggml_nbytes(model.output);
|
ml.n_created--; // artificial tensor
|
||||||
|
ml.size_data += ggml_nbytes(model.output);
|
||||||
|
}
|
||||||
}
|
}
|
||||||
|
|
||||||
for (int i = 0; i < n_layer; ++i) {
|
for (int i = 0; i < n_layer; ++i) {
|
||||||
|
Loading…
Reference in New Issue
Block a user