#include <algorithm>
#include <cassert>
-#include <cmath>
#include <cfloat>
#include <cstring>
#include <cmath>
llama_mlocks mlock_mmaps;
// contexts where the model tensors metadata is stored as well ass the corresponding buffers:
- std::vector<std::pair<ggml_context_ptr, ggml_backend_buffer_ptr>> ctxs_bufs;
+ std::vector<std::pair<ggml_context_ptr, std::vector<ggml_backend_buffer_ptr>>> ctxs_bufs;
buft_list_t cpu_buft_list;
std::map<ggml_backend_dev_t, buft_list_t> gpu_buft_list;
bool buffer_from_host_ptr_supported = props.caps.buffer_from_host_ptr;
bool is_default_buft = buft == ggml_backend_dev_buffer_type(dev);
- ggml_backend_buffer_t buf = nullptr;
+ std::vector<ggml_backend_buffer_ptr> bufs;
if (ml.use_mmap && use_mmap_buffer && buffer_from_host_ptr_supported && is_default_buft) {
for (uint32_t idx = 0; idx < ml.files.size(); idx++) {
// only the mmap region containing the tensors in the model is mapped to the backend buffer
continue;
}
const size_t max_size = ggml_get_max_tensor_size(ctx);
- buf = ggml_backend_dev_buffer_from_host_ptr(dev, (char *) addr + first, last - first, max_size);
+ ggml_backend_buffer_t buf = ggml_backend_dev_buffer_from_host_ptr(dev, (char *) addr + first, last - first, max_size);
if (buf == nullptr) {
throw std::runtime_error(format("unable to allocate %s buffer", ggml_backend_buft_name(buft)));
}
+ bufs.emplace_back(buf);
buf_map.emplace(idx, buf);
}
}
else {
- buf = ggml_backend_alloc_ctx_tensors_from_buft(ctx, buft);
+ ggml_backend_buffer_t buf = ggml_backend_alloc_ctx_tensors_from_buft(ctx, buft);
if (buf == nullptr) {
throw std::runtime_error(format("unable to allocate %s buffer", ggml_backend_buft_name(buft)));
}
mlock_buf->init (ggml_backend_buffer_get_base(buf));
mlock_buf->grow_to(ggml_backend_buffer_get_size(buf));
}
+ bufs.emplace_back(buf);
for (uint32_t idx = 0; idx < ml.files.size(); idx++) {
buf_map.emplace(idx, buf);
}
}
- pimpl->ctxs_bufs.emplace_back(std::move(ctx_ptr), buf);
+ pimpl->ctxs_bufs.emplace_back(std::move(ctx_ptr), std::move(bufs));
for (auto & buf : buf_map) {
// indicate that this buffer contains weights
}
// print memory requirements per buffer type
- for (auto & [_, buf] : pimpl->ctxs_bufs) {
- LLAMA_LOG_INFO("%s: %12s model buffer size = %8.2f MiB\n", __func__, ggml_backend_buffer_name(buf.get()), ggml_backend_buffer_get_size(buf.get()) / 1024.0 / 1024.0);
+ for (auto & [_, bufs] : pimpl->ctxs_bufs) {
+ for (auto & buf: bufs) {
+ LLAMA_LOG_INFO("%s: %12s model buffer size = %8.2f MiB\n",
+ __func__, ggml_backend_buffer_name(buf.get()), ggml_backend_buffer_get_size(buf.get()) / 1024.0 / 1024.0);
+ }
}
// populate tensors_by_name
std::map<ggml_backend_buffer_type_t, size_t> llama_model::memory_breakdown() const {
std::map<ggml_backend_buffer_type_t, size_t> ret;
- for (const auto & [_, buf] : pimpl->ctxs_bufs) {
- ret[ggml_backend_buffer_get_type(buf.get())] += ggml_backend_buffer_get_size(buf.get());
+ for (const auto & [_, bufs] : pimpl->ctxs_bufs) {
+ for (const auto & buf : bufs) {
+ ret[ggml_backend_buffer_get_type(buf.get())] += ggml_backend_buffer_get_size(buf.get());
+ }
}
return ret;
}