}
// Set data on mask tensors
- // Since this must be backend agnostic, we get tensor data with
- // ggml_backend_tensor_get, copy our desired values and send it back
- // to backend with ggml_backend_tensor_set
+ // Since this must be backend agnostic, we write our desired values on mask_data,
+ // and send it to backend with ggml_backend_tensor_set.
+ // Each mask in N_HEADS*N_ALIGNMENT_HEADS, one per text layer containing alignment
+ // heads. Each row of the mask "marks" one alignment head. E.g. if some text layer
+ // has a total of 10 heads and of those, heads 0,5,6 are alignment heads, the mask
+ // should read:
+ // 1 0 0 0 0 0 0 0 0 0
+ // 0 0 0 0 0 1 0 0 0 0
+ // 0 0 0 0 0 0 1 0 0 0
std::vector<float> mask_data;
for (int64_t il = 0; il < n_text_layer; ++il) {
if (aheads_masks.m[il] != nullptr) {
auto aheads = get_alignment_heads_by_layer(cparams, il, n_text_layer, n_head);
- size_t data_size = aheads_masks.m[il]->ne[0] * aheads_masks.m[il]->ne[1] * sizeof(float);
+ size_t data_size = aheads_masks.m[il]->ne[0] * aheads_masks.m[il]->ne[1];
+ size_t data_size_bytes = data_size * sizeof(float);
mask_data.resize(data_size);
- ggml_backend_tensor_get(aheads_masks.m[il], mask_data.data(), 0, data_size);
- memset(mask_data.data(), 0, data_size);
+ std::fill(mask_data.begin(), mask_data.end(), 0);
for (size_t ih = 0; ih < aheads.size(); ++ih) {
- size_t pos = (aheads[ih] + (ih * aheads_masks.m[il]->ne[0] * aheads[ih]));
- float v = 1.0f;
- memcpy(mask_data.data() + pos, &v, sizeof(float));
+ size_t pos = (aheads[ih] + (ih * aheads_masks.m[il]->ne[0]));
+ mask_data[pos] = 1.0f;
}
- ggml_backend_tensor_set(aheads_masks.m[il], mask_data.data(), 0, data_size);
+ ggml_backend_tensor_set(aheads_masks.m[il], mask_data.data(), 0, data_size_bytes);
}
}