this repo has no description
Sync with monorepo
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doc/add_example.mld
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doc/add_example.mld
···
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{0 Tensor Addition}
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@x-ocaml.universe ./universe
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@x-ocaml.worker ./universe/worker.js
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This notebook demonstrates basic ONNX Runtime inference in OCaml:
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creating tensors, loading a model, and running addition.
···
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Load [onnxrt], [Note] (FRP), and the widget library:
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{@ocaml[
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{@ocaml x[
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#require "onnxrt";;
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#require "note";;
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#require "js_top_worker-widget";;
···
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Load the ONNX Runtime JavaScript library into the worker:
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{@ocaml[
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{@ocaml x[
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let () =
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Js_of_ocaml.Js.Unsafe.meth_call
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Js_of_ocaml.Js.Unsafe.global "importScripts"
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doc/sentiment_example.mld
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doc/sentiment_example.mld
···
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{0 Sentiment Analysis}
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@x-ocaml.universe ./universe
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@x-ocaml.worker ./universe/worker.js
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This notebook runs a DistilBERT sentiment analysis model entirely in
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the browser using ONNX Runtime. It includes a vocabulary loader,
···
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Load [onnxrt], [Note] (FRP), and the widget library:
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{@ocaml[
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{@ocaml x[
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#require "onnxrt";;
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#require "note";;
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#require "js_top_worker-widget";;
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]}
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{@ocaml[
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{@ocaml x[
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let () =
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Js_of_ocaml.Js.Unsafe.meth_call
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Js_of_ocaml.Js.Unsafe.global "importScripts"
···
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Create int64 tensors (required by DistilBERT) and compute softmax
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over logits:
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{@ocaml[
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{@ocaml x[
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open Onnxrt
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let make_int64_tensor (data : int array) (dims : int array) : Tensor.t =
···
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the quantized DistilBERT model. A status widget updates as loading
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progresses:
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{@ocaml[
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{@ocaml x[
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let max_length = 128
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let vocab = ref None
···
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Style ("padding", "0.75em 1em");
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Style ("border-radius", "6px");
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Style ("font-family", "monospace");
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Style ("background", "#f0f4f8");
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Style ("border", "1px solid currentColor");
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Style ("opacity", "0.8");
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]; children = [Text msg] }
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let () =
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let open Lwt.Syntax in
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let* s = Session.create "model_quantized.onnx" () in
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session := Some s;
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send_model_status "Ready! Edit the text below and click Analyze.";
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send_model_status "Model ready.";
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Lwt.return_unit)
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]}
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{1 Analyze Sentiment}
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Edit the sample text and click {b Run} to classify it. The result
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widget updates reactively when inference completes:
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Type or edit the text below — the model classifies it reactively
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via [Note] signals whenever you click {b Analyze}.
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{@ocaml exercise[
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{@ocaml x[
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let input_e, send_input = Note.E.create ()
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let input_text = Note.S.hold
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"This movie was absolutely wonderful, I loved every minute of it!"
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input_e
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let result_e, send_result = Note.E.create ()
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let result_s = Note.S.hold "" result_e
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let result_s = Note.S.hold "Type something and click Analyze." result_e
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let result_view msg =
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let open Widget.View in
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if msg = "" then Element { tag = "div"; attrs = []; children = [] }
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else
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Element { tag = "div"; attrs = [
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Style ("padding", "0.75em 1em");
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Style ("border-radius", "6px");
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Style ("font-family", "monospace");
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Style ("font-size", "1.1em");
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Style ("background", "#e8f5e9");
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]; children = [Text msg] }
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let () =
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Widget.display ~id:"sentiment-result" ~handlers:[]
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(result_view "")
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let _logr2 = Note.S.log
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(Note.S.map result_view result_s)
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(Widget.update ~id:"sentiment-result")
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let () = Note.Logr.hold _logr2
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]}
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{@ocaml exercise run-on=click[
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let text = "This movie was absolutely wonderful, I loved every minute of it!"
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let () =
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let analyze text =
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match !vocab, !session with
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| Some v, Some s ->
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send_result "Running inference...";
···
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let label, confidence =
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if probs.(1) > probs.(0) then ("POSITIVE", probs.(1))
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else ("NEGATIVE", probs.(0)) in
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send_result (Printf.sprintf "%s (confidence: %.1f%%)"
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label (confidence *. 100.0));
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let emoji = if label = "POSITIVE" then "👍" else "👎" in
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send_result (Printf.sprintf "%s %s (%.1f%% confident)"
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emoji label (confidence *. 100.0));
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Tensor.dispose input_ids_tensor;
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Tensor.dispose attention_mask_tensor;
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Tensor.dispose logits_tensor;
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Lwt.return_unit)
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| _ ->
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send_result "Model not loaded yet — wait a moment and try again."
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]}
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Edit the [text] variable above, click {b Run}, and the result will
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appear automatically.
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let input_view text =
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let open Widget.View in
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Element { tag = "div"; attrs = [
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Style ("display", "flex");
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Style ("flex-direction", "column");
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Style ("gap", "0.75em");
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]; children = [
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Element { tag = "textarea"; attrs = [
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Property ("rows", "3");
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Style ("width", "100%");
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Style ("padding", "0.75em");
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Style ("border-radius", "6px");
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Style ("border", "1px solid currentColor");
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Style ("font-size", "1em");
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Style ("font-family", "inherit");
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Style ("background", "transparent");
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Style ("color", "inherit");
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Style ("resize", "vertical");
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Style ("opacity", "0.9");
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Handler ("input", "text_changed");
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]; children = [Text text] };
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Element { tag = "button"; attrs = [
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Style ("padding", "0.5em 1.5em");
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Style ("border-radius", "6px");
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Style ("border", "1px solid currentColor");
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Style ("background", "transparent");
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Style ("color", "inherit");
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Style ("font-size", "1em");
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Style ("cursor", "pointer");
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Handler ("click", "analyze");
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]; children = [Text "Analyze"] };
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] }
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let result_view result =
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let open Widget.View in
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Element { tag = "div"; attrs = [
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Style ("font-family", "monospace");
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Style ("padding", "0.75em 1em");
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Style ("border-radius", "6px");
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Style ("border", "1px solid currentColor");
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Style ("opacity", "0.8");
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]; children = [Text result] }
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let () =
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Widget.display ~id:"sentiment-input"
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~handlers:[
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"text_changed", (fun v -> send_input (Option.value ~default:"" v));
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"analyze", (fun _ -> analyze (Note.S.value input_text));
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]
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(input_view (Note.S.value input_text))
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let () =
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Widget.display ~id:"sentiment-result" ~handlers:[]
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(result_view (Note.S.value result_s))
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let _logr_input = Note.S.log input_text (fun _ -> ())
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let () = Note.Logr.hold _logr_input
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let _logr_result = Note.S.log
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(Note.S.map result_view result_s)
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(Widget.update ~id:"sentiment-result")
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let () = Note.Logr.hold _logr_result
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]}