WCNegentropy
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BitTransformerLM

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-<!DOCTYPE html>
-<html lang="en">
-<head>
-    <meta charset="UTF-8">
-    <title>Bit Transformer Dashboard</title>
-    <link rel="stylesheet" href="{{ url_for('static', filename='style.css') }}">
-    <script src="https://cdn.jsdelivr.net/npm/chart.js"></script>
-</head>
-<body>
-    <h1>Bit Transformer Dashboard</h1>
-    <div class="container">
-    <section>
-        <h2>Initialize Model</h2>
-        <form id="initForm">
-            d_model: <input type="number" name="d_model" value="{{ defaults.d_model }}" title="Model width (default {{ defaults.d_model }})"><br>
-            nhead: <input type="number" name="nhead" value="{{ defaults.nhead }}" title="Attention heads (default {{ defaults.nhead }})"><br>
-            num_layers: <input type="number" name="num_layers" value="{{ defaults.num_layers }}" title="Transformer layers (default {{ defaults.num_layers }})"><br>
-            dim_feedforward: <input type="number" name="dim_feedforward" value="{{ defaults.dim_feedforward }}" title="Feedforward dim (default {{ defaults.dim_feedforward }})"><br>
-            max_seq_len: <input type="number" name="max_seq_len" value="{{ defaults.max_seq_len }}" title="Max sequence length (default {{ defaults.max_seq_len }})"><br>
-            chunk_size: <input type="number" name="chunk_size" title="Chunked attention size"><br>
-            overlap: <input type="number" name="overlap" value="{{ defaults.overlap }}" title="Sliding window overlap"><br>
-            Reversible: <input type="checkbox" name="reversible" id="reversible_box" title="Use reversible layers (default {{ defaults.reversible }})"><br>
-            Gradient Checkpointing: <input type="checkbox" name="use_checkpoint" id="checkpoint_box" checked title="Enable gradient checkpointing (default {{ defaults.use_checkpoint }})"><br>
-            act_threshold: <input type="number" step="0.01" name="act_threshold" value="{{ defaults.act_threshold }}" title="ACT halt threshold (default {{ defaults.act_threshold }})"><br>
-            c_floor: <input type="number" step="0.01" name="c_floor" value="{{ c_floor }}" title="Complexity floor"><br>
-            s_floor: <input type="number" step="0.01" name="s_floor" value="{{ s_floor }}" title="Symbiosis floor"><br>
-            <button type="submit">Init</button>
-        </form>
-    </section>
-    <section>
-        <h2>Train Step</h2>
-        <form id="trainForm">
-            Bits (e.g. 0 1 0 1): <input type="text" name="bits" value="0 1 0 1"><br>
-            Upload file: <input type="file" id="train_file"><br>
-            <button type="submit">Train</button>
-        </form>
-        <label>Load sample dataset:
-            <select id="datasetSelect">
-                <option value="">--Select--</option>
-                <option value="wikitext2_train">Wikitext-2 (train)</option>
-                <option value="wikitext2_validation">Wikitext-2 (validation)</option>
-            </select>
-        </label>
-        <p id="trainOut"></p>
-    </section>
-    <section>
-        <h2>Scale Up</h2>
-        Width Mult: <input type="number" step="0.1" id="width_mult" value="1.0"><br>
-        <button id="scaleBtn">Scale Model</button>
-    </section>
-    <section>
-        <h2>Collapse Submodel</h2>
-        <form id="collapseForm">
-            Cluster Bits (JSON array of arrays):<br>
-            <textarea name="clusters" rows="3" cols="40">[[0,1,0,1],[1,1,0,0]]</textarea><br>
-            Target Params (JSON):<br>
-            <textarea name="params" rows="3" cols="40">{"d_model":32,"nhead":4,"num_layers":1,"dim_feedforward":64,"max_seq_len":16}</textarea><br>
-            Width Scale: <input type="number" step="0.1" id="width_scale" value="1.0"><br>
-            <button type="submit">Collapse</button>
-        </form>
-    </section>
-    <section>
-        <h2>Inference</h2>
-        <form id="inferForm">
-            Bits: <input type="text" name="bits" value="0 1 0 1"><br>
-            Upload file: <input type="file" id="infer_file"><br>
-            <button type="submit">Infer</button>
-        </form>
-        <pre id="inferOut"></pre>
-    </section>
-    <section>
-        <h2>Long Inference</h2>
-        <form id="inferLongForm">
-            Bits: <input type="text" name="bits" value="0 1 0 1"><br>
-            ctx_bits: <input type="number" name="ctx_bits" value="4096"><br>
-            overlap: <input type="number" name="overlap" value="256"><br>
-            <button type="submit">Infer Long</button>
-        </form>
-        <pre id="inferLongOut"></pre>
-    </section>
-    <section>
-        <h2>Text Inference</h2>
-        <form id="textInferForm">
-            Text: <input type="text" name="text" value="hello"><br>
-            <button type="submit">Infer Text</button>
-        </form>
-        <pre id="textInferOut"></pre>
-    </section>
-    <section>
-        <h2>&lambda; Weights</h2>
-        <form id="lambdaForm">
-            &lambda;<sub>K</sub>: <input type="range" min="0" max="2" step="0.1" id="lambda_K" oninput="lambda_K_val.innerText=value"><span id="lambda_K_val"></span><br>
-            &lambda;<sub>C</sub>: <input type="range" min="0" max="2" step="0.1" id="lambda_C" oninput="lambda_C_val.innerText=value"><span id="lambda_C_val"></span><br>
-            &lambda;<sub>S</sub>: <input type="range" min="0" max="2" step="0.1" id="lambda_S" oninput="lambda_S_val.innerText=value"><span id="lambda_S_val"></span><br>
-            <button type="submit">Update</button>
-        </form>
-    </section>
-    <section>
-        <h2>Diffusion LM</h2>
-        <label><input type="checkbox" id="diffusion_box"> Enable Diffusion Mode</label>
-    </section>
-    <section>
-        <h2>GPU Acceleration</h2>
-        <label><input type="checkbox" id="gpu_box"> Enable FSDP &amp; CUDA</label>
-    </section>
-    <section>
-        <h2>Enable Compression</h2>
-        <label><input type="checkbox" id="compression_box"> Compress I/O</label>
-        <p>Ratio: <span id="comp_ratio">1.0</span></p>
-    </section>
-    <section>
-        <h2>Quantization Aware Training</h2>
-        <label><input type="checkbox" id="qat_box"> Enable 4-bit QAT</label>
-    </section>
-    <section>
-        <h2>Model Status</h2>
-        <pre id="statusOut"></pre>
-    </section>
-    <section>
-        <h2>Telemetry</h2>
-        <canvas id="metricChart" width="600" height="300"></canvas>
-    </section>
-    <section>
-        <h2>Hugging Face Checkpoints</h2>
-        Repo ID: <input type="text" id="hf_repo"><br>
-        Token: <input type="password" id="hf_token" placeholder="optional"><br>
-        <button id="uploadBtn">Upload weights</button>
-        <button id="downloadBtn">Download weights</button>
-        <p id="hfStatus"></p>
-    </section>
-<script>
-async function postJSON(url, data){
-    const resp = await fetch(url, {method:'POST', headers:{'Content-Type':'application/json'}, body:JSON.stringify(data)});
-    return resp.json();
-}
-async function pollJob(id){
-    while(true){
-        const job = await fetch(`/job/${id}`).then(r=>r.json());
-        if(job.status === 'completed') return job.result;
-        if(job.status === 'error') throw job.error || 'Job failed';
-        await new Promise(r=>setTimeout(r, 1000));
-    }
-}
-function loadInitParams(){
-    const saved = JSON.parse(localStorage.getItem('init_params')||'{}');
-    const form = document.getElementById('initForm');
-    for(const [k,v] of Object.entries(saved)){
-        const el = form.elements[k];
-        if(!el) continue;
-        if(el.type === 'checkbox') el.checked = v; else el.value = v;
-    }
-}
-loadInitParams();
-function byteArrayToBits(arr){
-    const bits=[];
-    for(const b of arr){
-        for(let i=7;i>=0;i--) bits.push((b>>i)&1);
-    }
-    return bits;
-}
-let trainFileBits=null, inferFileBits=null, datasetBits=null;
-async function fileToBits(file){
-    if(file.type.startsWith('text')){
-        const text = await file.text();
-        const res = await postJSON('/text_to_bits', {text});
-        return res.bits;
-    }
-    const buf = await file.arrayBuffer();
-    return byteArrayToBits(new Uint8Array(buf));
-}
-let metricChart;
-async function initChart(){
-    const data = await fetch('/metrics').then(r=>r.json());
-    const labels = data.negentropy.map((_,i)=>i);
-    const ctx = document.getElementById('metricChart').getContext('2d');
-    metricChart = new Chart(ctx, {
-        type:'line',
-        data:{
-            labels:labels,
-            datasets:[
-                {label:'Negentropy', data:data.negentropy, borderColor:'blue', fill:false},
-                {label:'LZ Complexity', data:data.lz_complexity, borderColor:'orange', fill:false},
-                {label:'Symbiosis', data:data.symbiosis, borderColor:'green', fill:false}
-            ]
-        },
-        options:{responsive:false, interaction:{mode:'index', intersect:false}}
-    });
-}
-async function updateChart(){
-    const data = await fetch('/metrics').then(r=>r.json());
-    const labels = data.negentropy.map((_,i)=>i);
-    metricChart.data.labels = labels;
-    metricChart.data.datasets[0].data = data.negentropy;
-    metricChart.data.datasets[1].data = data.lz_complexity;
-    metricChart.data.datasets[2].data = data.symbiosis;
-    metricChart.update();
-}
-initChart();
-setInterval(updateChart, 2000);
-async function refreshStatus(){
-    const [s, c] = await Promise.all([fetch('/status'), fetch('/model_config')]);
-    const status = await s.json();
-    const config = await c.json();
-    document.getElementById('statusOut').innerText = JSON.stringify({...status, ...config}, null, 2);
-}
-document.getElementById('initForm').addEventListener('submit', async (e)=>{
-    e.preventDefault();
-    const fd = new FormData(e.target);
-    const obj = Object.fromEntries(fd.entries());
-    const ints = ['d_model','nhead','num_layers','dim_feedforward','max_seq_len','chunk_size','overlap'];
-    ints.forEach(k=>{ if(obj[k]===''){ delete obj[k]; } else obj[k]=parseInt(obj[k]); });
-    obj.reversible = document.getElementById('reversible_box').checked;
-    obj.use_checkpoint = document.getElementById('checkpoint_box').checked;
-    obj.act_threshold = parseFloat(obj.act_threshold);
-    const floors = {c_floor: parseFloat(obj.c_floor), s_floor: parseFloat(obj.s_floor)};
-    delete obj.c_floor; delete obj.s_floor;
-    await postJSON('/init', obj);
-    await postJSON('/config/telemetry', floors);
-    localStorage.setItem('init_params', JSON.stringify({...obj, ...floors}));
-    refreshStatus();
-    updateChart();
-});
-document.getElementById('trainForm').addEventListener('submit', async (e)=>{
-    e.preventDefault();
-    const form = e.target;
-    let payload;
-    if(trainFileBits){
-        payload = trainFileBits;
-    } else if(datasetBits){
-        payload = datasetBits;
-    } else {
-        payload = [form.bits.value.trim().split(/\s+/).map(Number)];
-    }
-    for(const el of form.elements) el.disabled = true;
-    const out = document.getElementById('trainOut');
-    out.innerText = '⏳';
-    try{
-        const job = await postJSON('/train', {bits: payload});
-        const res = await pollJob(job.job_id);
-        out.innerText = 'Loss: '+res.loss.toFixed(4);
-        if(res.ratio !== undefined){
-            document.getElementById('comp_ratio').innerText = res.ratio.toFixed(2);
-        }
-    } catch(err){
-        out.innerText = 'Error';
-        alert(err);
-    } finally {
-        for(const el of form.elements) el.disabled = false;
-        refreshStatus();
-        updateChart();
-    }
-});
-document.getElementById('train_file').addEventListener('change', async (e)=>{
-    const f = e.target.files[0];
-    if(!f) return;
-    const bits = await fileToBits(f);
-    trainFileBits = [bits];
-    datasetBits = null;
-    document.querySelector('#trainForm input[name="bits"]').value = bits.slice(0,64).join(' ');
-});
-document.querySelector('#trainForm input[name="bits"]').addEventListener('input', ()=>{
-    trainFileBits = null;
-    datasetBits = null;
-});
-document.getElementById('scaleBtn').addEventListener('click', async ()=>{
-    const btn = document.getElementById('scaleBtn');
-    const input = document.getElementById('width_mult');
-    const mult = parseFloat(input.value);
-    btn.disabled = true; input.disabled = true;
-    const original = btn.innerText; btn.innerText = '⏳';
-    try{
-        const job = await postJSON('/scale_up', {width_mult: mult});
-        await pollJob(job.job_id);
-    } catch(err){
-        alert(err);
-    } finally {
-        btn.innerText = original;
-        btn.disabled = false; input.disabled = false;
-        refreshStatus();
-        updateChart();
-    }
-});
-document.getElementById('collapseForm').addEventListener('submit', async (e)=>{
-    e.preventDefault();
-    const form = e.target;
-    const btn = form.querySelector('button');
-    for(const el of form.elements) el.disabled = true;
-    const clusters = JSON.parse(form.clusters.value);
-    const params = JSON.parse(form.params.value);
-    const w = parseFloat(document.getElementById('width_scale').value);
-    const original = btn.innerText; btn.innerText = '⏳';
-    try{
-        const job = await postJSON('/collapse', {clusters: clusters, params: params, width_scale: w});
-        await pollJob(job.job_id);
-    } catch(err){
-        alert(err);
-    } finally {
-        btn.innerText = original;
-        for(const el of form.elements) el.disabled = false;
-        refreshStatus();
-        updateChart();
-    }
-});
-document.getElementById('inferForm').addEventListener('submit', async (e)=>{
-    e.preventDefault();
-    let bits;
-    if(inferFileBits){
-        bits = inferFileBits;
-    } else if(datasetBits){
-        bits = [datasetBits[0]];
-    } else {
-        bits = [e.target.bits.value.trim().split(/\s+/).map(Number)];
-    }
-    const res = await postJSON('/infer', {bits});
-    if(res.error){
-        alert(res.error + '\n' + (res.suggestion||''));
-    } else {
-        document.getElementById('inferOut').innerText = JSON.stringify(res, null, 2);
-        if(res.ratio !== undefined){
-            document.getElementById('comp_ratio').innerText = res.ratio.toFixed(2);
-        }
-    }
-    refreshStatus();
-    updateChart();
-});
-document.getElementById('infer_file').addEventListener('change', async (e)=>{
-    const f = e.target.files[0];
-    if(!f) return;
-    const bits = await fileToBits(f);
-    inferFileBits = [bits];
-    datasetBits = null;
-    document.querySelector('#inferForm input[name="bits"]').value = bits.slice(0,64).join(' ');
-});
-document.querySelector('#inferForm input[name="bits"]').addEventListener('input', ()=>{
-    inferFileBits = null;
-    datasetBits = null;
-});
-document.getElementById('datasetSelect').addEventListener('change', async (e)=>{
-    const val = e.target.value;
-    trainFileBits = null;
-    inferFileBits = null;
-    if(!val){ datasetBits = null; return; }
-    const [name, split] = val.split('_');
-    const resp = await fetch(`/dataset?name=${name}&split=${split}&size=4&seq_len=64`);
-    const data = await resp.json();
-    datasetBits = data.bits;
-    const preview = data.bits[0].slice(0,64).join(' ');
-    document.querySelector('#trainForm input[name="bits"]').value = preview;
-    document.querySelector('#inferForm input[name="bits"]').value = preview;
-});
-document.getElementById('inferLongForm').addEventListener('submit', async (e)=>{
-    e.preventDefault();
-    const bits = e.target.bits.value.trim().split(/\s+/).map(Number);
-    const ctx = parseInt(e.target.ctx_bits.value);
-    const ov = parseInt(e.target.overlap.value);
-    const res = await postJSON('/infer_long', {bits: bits, ctx_bits: ctx, overlap: ov});
-    document.getElementById('inferLongOut').innerText = JSON.stringify(res, null, 2);
-    refreshStatus();
-    updateChart();
-});
-document.getElementById('textInferForm').addEventListener('submit', async (e)=>{
-    e.preventDefault();
-    const text = e.target.text.value;
-    const res = await postJSON('/infer_text', {text:text});
-    document.getElementById('textInferOut').innerText = JSON.stringify(res, null, 2);
-    refreshStatus();
-    updateChart();
-});
-async function loadLambdas(){
-    const resp = await fetch('/lambdas');
-    const vals = await resp.json();
-    for(const k of ['lambda_K','lambda_C','lambda_S']){
-        document.getElementById(k).value = vals[k];
-        document.getElementById(k+"_val").innerText = vals[k];
-    }
-}
-document.getElementById('lambdaForm').addEventListener('submit', async (e)=>{
-    e.preventDefault();
-    const data = {
-        lambda_K: parseFloat(document.getElementById('lambda_K').value),
-        lambda_C: parseFloat(document.getElementById('lambda_C').value),
-        lambda_S: parseFloat(document.getElementById('lambda_S').value),
-    };
-    await postJSON('/lambdas', data);
-    for(const k in data){
-        document.getElementById(k+"_val").innerText = data[k];
-    }
-    refreshStatus();
-});
-loadLambdas();
-function restoreToggle(id,key,endpoint,field){
-    const box = document.getElementById(id);
-    const saved = localStorage.getItem(key);
-    if(saved !== null){ box.checked = saved === 'true'; postJSON(endpoint,{[field]: box.checked}); }
-    box.addEventListener('change', async (e)=>{
-        await postJSON(endpoint, {[field]: e.target.checked});
-        localStorage.setItem(key, e.target.checked);
-        refreshStatus();
-    });
-}
-restoreToggle('diffusion_box','diffusion','/diffusion','diffusion');
-restoreToggle('gpu_box','use_gpu','/gpu','use_gpu');
-restoreToggle('compression_box','compression','/compression','compression');
-restoreToggle('qat_box','qat','/qat','qat');
-document.getElementById('uploadBtn').addEventListener('click', async ()=>{
-    const repo = document.getElementById('hf_repo').value;
-    const token = document.getElementById('hf_token').value;
-    const res = await postJSON('/save_checkpoint', {repo_id: repo, token: token||undefined});
-    document.getElementById('hfStatus').innerText = res.status || res.error;
-});
-document.getElementById('downloadBtn').addEventListener('click', async ()=>{
-    const repo = document.getElementById('hf_repo').value;
-    const token = document.getElementById('hf_token').value;
-    const res = await postJSON('/download_checkpoint', {repo_id: repo, token: token||undefined});
-    document.getElementById('hfStatus').innerText = res.status || res.error;
-    refreshStatus();
-    updateChart();
-});
-refreshStatus();
-</script>
-    </div>
-</body>
-</html>