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au_whisper_web/patches/@huggingface%[email protected]
T

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diff --git a/dist/transformers.web.js b/dist/transformers.web.js
index bb7b32717a42475a5f66411a33d5e5964dfda3e2..799cb402e98d8d0d58bf59629c4c2992407477e0 100644
--- a/dist/transformers.web.js
+++ b/dist/transformers.web.js
@@ -18558,22 +18558,28 @@ async function getSession(pretrained_model_name_or_path, fileName, options, cach
return { buffer_or_path, session_options, session_config };
}
async function constructSessions(pretrained_model_name_or_path, names, options, cache_sessions = void 0) {
- return Object.fromEntries(
- await Promise.all(
- Object.keys(names).map(async (name) => {
- const cache_config = cache_sessions?.[name] ?? false;
- const { buffer_or_path, session_options, session_config } = await getSession(
- pretrained_model_name_or_path,
- names[name],
- options,
- cache_config,
- name
- );
- const session = await createInferenceSession(buffer_or_path, session_options, session_config);
- return [name, session];
- })
- )
- );
+ // Patched (au_whisper_web): load sub-model sessions one at a time instead of
+ // Promise.all-ing them. Each entry briefly holds a full-size decoded model
+ // buffer in JS-heap memory (on top of onnxruntime-web's own WASM-heap copy
+ // during session creation); loading Whisper's encoder and decoder
+ // concurrently keeps both buffers alive at once and roughly doubles the
+ // load-time memory peak, which is enough to OOM-crash mobile browsers on
+ // larger models (e.g. medium, ~460 MB combined). Sequential loading lets the
+ // previous entry's buffer become garbage before the next one is fetched.
+ const entries = [];
+ for (const name of Object.keys(names)) {
+ const cache_config = cache_sessions?.[name] ?? false;
+ const { buffer_or_path, session_options, session_config } = await getSession(
+ pretrained_model_name_or_path,
+ names[name],
+ options,
+ cache_config,
+ name
+ );
+ const session = await createInferenceSession(buffer_or_path, session_options, session_config);
+ entries.push([name, session]);
+ }
+ return Object.fromEntries(entries);
}
function replaceTensors(obj) {
for (let prop in obj) {