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-rw-r--r--examples/train-text-from-scratch/train-text-from-scratch.cpp14
1 files changed, 5 insertions, 9 deletions
diff --git a/examples/train-text-from-scratch/train-text-from-scratch.cpp b/examples/train-text-from-scratch/train-text-from-scratch.cpp
index f7ed6336..4a9a2340 100644
--- a/examples/train-text-from-scratch/train-text-from-scratch.cpp
+++ b/examples/train-text-from-scratch/train-text-from-scratch.cpp
@@ -369,10 +369,7 @@ static struct ggml_tensor * llama_build_train_graphs(
checkpoints.push_back(t00);
checkpoints.push_back(t01);
- struct ggml_tensor * kv_scale = NULL;
- if (!enable_flash_attn) {
- kv_scale = ggml_new_f32(ctx, 1.0f/sqrtf(float(n_embd)/n_head));
- }
+ const float kv_scale = 1.0f/sqrtf(float(n_embd)/n_head);
for (int il = 0; il < n_layer; ++il) {
struct my_llama_layer & layer = model->layers[il];
@@ -444,14 +441,13 @@ static struct ggml_tensor * llama_build_train_graphs(
// make sure some tensors are not reallocated by inserting new temporary nodes depending on them
int n_leafs_before = gb->n_leafs;
int n_nodes_before = gb->n_nodes;
- struct ggml_tensor * one = ggml_new_f32(ctx, 1.0f);
// output tensors
- ggml_build_forward_expand(gb, ggml_scale_inplace(ctx, t35, one));
- ggml_build_forward_expand(gb, ggml_scale_inplace(ctx, t36, one));
+ ggml_build_forward_expand(gb, ggml_scale_inplace(ctx, t35, 1.0f));
+ ggml_build_forward_expand(gb, ggml_scale_inplace(ctx, t36, 1.0f));
// input gradient
- ggml_build_forward_expand(gb, ggml_scale_inplace(ctx, t36->grad, one));
+ ggml_build_forward_expand(gb, ggml_scale_inplace(ctx, t36->grad, 1.0f));
// KQ_pos
- ggml_build_forward_expand(gb, ggml_scale_inplace(ctx, KQ_pos, one));
+ ggml_build_forward_expand(gb, ggml_scale_inplace(ctx, KQ_pos, 1.0f));
GGML_ASSERT(t36->grad->data == NULL && t36->grad->view_src == NULL);
ggml_allocr_alloc(alloc, t36->grad);