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7 changes: 6 additions & 1 deletion ggml/src/ggml-sycl/ggml-sycl.cpp
Original file line number Diff line number Diff line change
Expand Up @@ -372,9 +372,14 @@ static void ggml_backend_sycl_buffer_set_tensor(ggml_backend_buffer_t buffer,
auto stream = &(dpct::dev_mgr::instance().get_device(ctx->device).default_queue());
SYCL_CHECK(
CHECK_TRY_ERROR(dpct::dev_mgr::instance().get_device(ctx->device).queues_wait_and_throw()));
// Note: Use host buffer to save the data from mmap(), then copy to device. It's workaround for mmap() issue on PVC GPU.
// This function will be called during load model from disk. Use memory buffer replace dynamic won't save more time and brings potential memory leak risk here.
char* host_buf = (char*)malloc(size);
memcpy(host_buf, data, size);
SYCL_CHECK(
CHECK_TRY_ERROR((*stream).memcpy((char *)tensor->data + offset, data, size)
CHECK_TRY_ERROR((*stream).memcpy((char *)tensor->data + offset, host_buf, size)
.wait()));
free(host_buf);
}
catch (sycl::exception const &exc) {
std::cerr << exc.what() << "Exception caught at file:" << __FILE__
Expand Down
10 changes: 10 additions & 0 deletions gguf-py/gguf/lazy.py
Original file line number Diff line number Diff line change
Expand Up @@ -139,6 +139,16 @@ def wrapped_fn(*args, **kwargs):

if isinstance(res, cls._tensor_type):
return cls(meta=cls.eager_to_meta(res), args=args, kwargs=kwargs, func=fn)
elif isinstance(res, tuple) and all(isinstance(t, cls._tensor_type) for t in res):
# share the evaluation between lazy tuple elements
shared_args: list = [args, None]

def eager_tuple_element(a: list[Any], i: int = 0, /, **kw) -> LazyBase:
assert len(a) == 2
if a[1] is None:
a[1] = fn(*a[0], **kw)
return a[1][i]
return tuple(cls(meta=cls.eager_to_meta(res[i]), args=(shared_args, i), kwargs=kwargs, func=eager_tuple_element) for i in range(len(res)))
else:
del res # not needed
# non-tensor return likely relies on the contents of the args
Expand Down
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