vbatts/llama.cpp
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remove trailing whitespace

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xaedes 2023-08-29 19:30:42 +02:00
parent 5813ac832f
commit a6165dafcd
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3 changed files with 5 additions and 5 deletions
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2
examples/finetune/convert-finetune-checkpoint-to-gguf.py
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@ -131,7 +131,7 @@ class OptimizationContext:
def load(self, data, offset): def load(self, data, offset):
self.version = struct.unpack('<I', bytes(data[offset:offset + 4]))[0] self.version = struct.unpack('<I', bytes(data[offset:offset + 4]))[0]
offset += 4 offset += 4
if self.version != 1: if self.version != 1:
raise ValueError('Invalid version of optimization context in checkpoint file') raise ValueError('Invalid version of optimization context in checkpoint file')

6
examples/finetune/finetune.cpp
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@ -1468,7 +1468,7 @@ void save_opt_context_gguf(struct gguf_context * fctx, struct ggml_opt_context *
void load_llama_lora_gguf(struct gguf_context * fctx, struct ggml_context * f_ggml_ctx, struct my_llama_model * model, struct my_llama_lora * lora) { void load_llama_lora_gguf(struct gguf_context * fctx, struct ggml_context * f_ggml_ctx, struct my_llama_model * model, struct my_llama_lora * lora) {
// NOTE: gguf_context must be initialized with f_ggml_ctx and no_alloc=false, otherwise tensor data can not be read // NOTE: gguf_context must be initialized with f_ggml_ctx and no_alloc=false, otherwise tensor data can not be read
std::string arch; std::string arch;
std::vector<char> keybuf; std::vector<char> keybuf;
@ -1525,7 +1525,7 @@ void load_llama_lora_gguf(struct gguf_context * fctx, struct ggml_context * f_gg
read_tensor_by_name(lora->norm_b, f_ggml_ctx, ggml_get_name(lora->norm_b)); read_tensor_by_name(lora->norm_b, f_ggml_ctx, ggml_get_name(lora->norm_b));
read_tensor_by_name(lora->output_a, f_ggml_ctx, ggml_get_name(lora->output_a)); read_tensor_by_name(lora->output_a, f_ggml_ctx, ggml_get_name(lora->output_a));
read_tensor_by_name(lora->output_b, f_ggml_ctx, ggml_get_name(lora->output_b)); read_tensor_by_name(lora->output_b, f_ggml_ctx, ggml_get_name(lora->output_b));
for (uint32_t i = 0; i < lora->layers.size(); ++i) { for (uint32_t i = 0; i < lora->layers.size(); ++i) {
auto & layer = lora->layers[i]; auto & layer = lora->layers[i];
read_tensor_by_name(layer.attention_norm_a, f_ggml_ctx, ggml_get_name(layer.attention_norm_a)); read_tensor_by_name(layer.attention_norm_a, f_ggml_ctx, ggml_get_name(layer.attention_norm_a));
@ -1565,7 +1565,7 @@ void save_llama_lora_gguf(struct gguf_context * fctx, struct my_llama_model * mo
gguf_set_val_u32(fctx, kv(LLM_KV_CONTEXT_LENGTH), model->hparams.n_ctx); gguf_set_val_u32(fctx, kv(LLM_KV_CONTEXT_LENGTH), model->hparams.n_ctx);
gguf_set_val_u32(fctx, kv(LLM_KV_EMBEDDING_LENGTH), model->hparams.n_embd); gguf_set_val_u32(fctx, kv(LLM_KV_EMBEDDING_LENGTH), model->hparams.n_embd);
gguf_set_val_u32(fctx, kv(LLM_KV_FEED_FORWARD_LENGTH), model->hparams.n_ff); gguf_set_val_u32(fctx, kv(LLM_KV_FEED_FORWARD_LENGTH), model->hparams.n_ff);
gguf_set_val_u32(fctx, kv(LLM_KV_ATTENTION_HEAD_COUNT), model->hparams.n_head); gguf_set_val_u32(fctx, kv(LLM_KV_ATTENTION_HEAD_COUNT), model->hparams.n_head);
gguf_set_val_u32(fctx, kv(LLM_KV_BLOCK_COUNT), model->hparams.n_layer); gguf_set_val_u32(fctx, kv(LLM_KV_BLOCK_COUNT), model->hparams.n_layer);
gguf_set_val_u32(fctx, kv(LLM_KV_ROPE_DIMENSION_COUNT), model->hparams.n_rot); gguf_set_val_u32(fctx, kv(LLM_KV_ROPE_DIMENSION_COUNT), model->hparams.n_rot);

2
ggml.c
View file

@ -16497,7 +16497,7 @@ static void ggml_compute_backward(struct ggml_context * ctx, struct ggml_tensor
if (src0->grad) { if (src0->grad) {
src0->grad = src0->grad =
ggml_add_or_set(ctx, src0->grad, ggml_add_or_set(ctx, src0->grad,
// last ggml_get_rows_back argument src0->grad is only // last ggml_get_rows_back argument src0->grad is only
// necessary to setup correct output shape // necessary to setup correct output shape
ggml_get_rows_back(ctx, tensor->grad, src1, src0->grad), ggml_get_rows_back(ctx, tensor->grad, src1, src0->grad),
zero_table); zero_table);