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Scope split-mode graph mmap to the tensor being loaded. Prevents memory leak #2126

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Scope split-mode graph mmap to the tensor being loaded. Prevents memory leak #2126

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32 changes: 2 additions & 30 deletions src/llama-model-loader.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -1078,10 +1078,6 @@ bool llama_model_loader::load_all_data(
std::vector<void*> host_ptrs;
std::vector<ggml_backend_event_t> events;

#if !defined(_WIN32)
std::vector<std::unique_ptr<llama_mmap>> split_mappings(files.size());
#endif

ggml_backend_t cuda_backend = nullptr;
if (!use_mmap && !check_tensors) {
// When not using mmaped io use async uploads from pinned memory to GPU memory.
Expand Down Expand Up @@ -1201,37 +1197,13 @@ bool llama_model_loader::load_all_data(
const char * buffer_name = ggml_backend_buffer_name(cur->buffer);
const bool is_probably_split_mode_graph = std::strncmp(buffer_name, GGML_CUDA_NAME, strlen(GGML_CUDA_NAME)) == 0;
if (is_probably_split_mode_graph) {
#if !defined(_WIN32)
llama_mmap * mapping;
{
std::lock_guard<std::mutex> lock(load_mutex);
auto & m = split_mappings[weight->idx];
if (!m) {
m.reset(new llama_mmap(files.at(weight->idx).get(), 0, ggml_is_numa()));
}
mapping = m.get();
}
uint8_t * data = (uint8_t *) mapping->addr() + weight->offs;
llama_mmap mapping(file.get(), 0);
uint8_t * data = (uint8_t *) mapping.addr() + weight->offs;
ggml_backend_tensor_set(cur, data, 0, n_size);
if (check_tensors && !ggml_validate_row_data(cur->type, data, n_size)) {
throw std::runtime_error(format("tensor '%s' has invalid data", ggml_get_name(cur)));
}
mapping->dontneed_fragment(weight->offs, weight->offs + n_size);
return n_size;
#else
auto & read_buf = read_bufs[thread_idx];
if (read_buf.capacity() > n_size) {
read_buf = std::vector<no_init<uint8_t>>();
}
read_buf.resize(n_size);
file->seek(weight->offs, SEEK_SET);
file->read_raw(read_buf.data(), n_size);
ggml_backend_tensor_set(cur, read_buf.data(), 0, n_size);
if (check_tensors && !ggml_validate_row_data(cur->type, read_buf.data(), n_size)) {
throw std::runtime_error(format("tensor '%s' has invalid data", ggml_get_name(cur)));
}
return n_size;
#endif
}
#endif
// rest. Serialized.
Expand Down