create

README.md

@@ -1,2 +1,33 @@
-# sd-extension-system-info
+# Info Tab extensions for SD Automatic WebUI
-System Info Extension for SD WebUI
+
+Creates a top-level **Info** tab in Automatic WebUI with 
+
+State & memory info are auto-updated every second if tab is visible (no updates are performed when tab is not visible)  
+All other information is updated once upon WebUI load and can be force refreshed if required  
+
+## Current information:
+- Version
+- Current Model & VAE
+- Current State
+- Current Memory statistics
+
+## System data:
+- Platform details
+- Torch & CUDA details
+- Active CMD flags such as `low-vram` or `med-vram`
+- Versions of critical libraries
+- Versions of dependent repositories
+
+  ![screenshot](system-info.jpg)
+
+## Models
+- Models
+- Hypernetworks
+- Embeddings
+
+  ![screenshot](system-info-models.jpg)
+
+## Info Object
+- System object is available as JSON for quick passing of information
+
+  ![screenshot](system-info-json.jpg)

install.py

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+import launch

javascript/system-info.js

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+// this would not be needed if automatic run gradio with loop enabled
+
+let loaded = false;
+let interval;
+
+function refresh() {
+  const btn = gradioApp().getElementById('system_info_tab_refresh_btn') // we could cache this dom element
+  if (!btn) return // but ui may get destroyed
+  btn.click() // actual refresh is done from python code we just trigger it but simulating button click
+}
+
+function onHidden() { // stop refresh interval when tab is not visible
+  if (!interval) return
+  clearInterval(interval);
+  interval = undefined;
+}
+
+function onVisible() { // start refresh interval tab is when visible
+  if (interval) return // interval already started so dont start it again
+  interval = setInterval(refresh, 1000);
+}
+
+function initLoading() { // triggered on gradio change to monitor when ui gets sufficiently constructed
+  if (loaded) return
+  const block = gradioApp().getElementById('system_info_tab');
+  if (!block) return
+  intersectionObserver = new IntersectionObserver((entries) => {
+    if (entries[0].intersectionRatio <= 0) onHidden();
+    if (entries[0].intersectionRatio > 0) onVisible();
+  });
+  intersectionObserver.observe(block); // monitor visibility of tab
+}
+
+function initInitial() { // just setup monitor for gradio events
+  const mutationObserver = new MutationObserver(initLoading)
+  mutationObserver.observe(gradioApp(), { childList: true, subtree: true }); // monitor changes to gradio
+}
+
+document.addEventListener('DOMContentLoaded', initInitial);

preload.py

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+def preload(parser):
+  pass

scripts/system-info.py

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+import datetime
+import os
+import platform
+import subprocess
+import time
+
+import accelerate
+import gradio as gr
+import psutil
+import pytorch_lightning
+import safetensors
+import torch
+import transformers
+from modules import paths, script_callbacks, sd_hijack, sd_models, sd_samplers, shared
+
+data = {}
+
+def get_cuda():
+    if not torch.cuda.is_available():
+        return {}
+    else:
+        try:
+            return {
+                'version': torch.version.cuda,
+                'devices': torch.cuda.device_count(),
+                'current': torch.cuda.get_device_name(torch.cuda.current_device()),
+                'arch': torch.cuda.get_arch_list()[-1],
+                'capability': torch.cuda.get_device_capability(shared.device),
+            }
+        except Exception as e:
+            return { 'error': e }
+
+def get_uptime():
+    s = vars(shared.state)
+    return time.strftime('%c', time.localtime(s.get('server_start', time.time())))
+
+def get_state():
+    s = vars(shared.state)
+    flags = 'skipped ' if s.get('skipped', False) else ''
+    flags += 'interrupted ' if s.get('interrupted', False) else ''
+    flags += 'needs restart' if s.get('need_restart', False) else ''
+    return {
+        'started': time.strftime('%c', time.localtime(s.get('time_start', time.time()))),
+        'step': f'{s.get("sampling_step", 0)} / {s.get("sampling_steps", 0)}',
+        'jobs': f'{s.get("job_no", 0)} / {s.get("job_count", 0)}', # pylint: disable=consider-using-f-string
+        'flags': flags,
+        'job': s.get('job', ''),
+        'text': s.get('textinfo', ''),
+    }
+
+def get_memory():
+    def gb(val: float):
+        return round(val / 1024 / 1024 / 1024, 2)
+    mem = {}
+    try:
+        process = psutil.Process(os.getpid())
+        res = process.memory_info()
+        ram_total = 100 * res.rss / process.memory_percent()
+        ram = { 'free': gb(ram_total - res.rss), 'used': gb(res.rss), 'total': gb(ram_total) }
+        mem.update({ 'ram': ram })
+    except Exception as e:
+        mem.update({ 'ram': e })
+    try:
+        if torch.cuda.is_available():
+            s = torch.cuda.mem_get_info()
+            gpu = { 'free': gb(s[0]), 'used': gb(s[1] - s[0]), 'total': gb(s[1]) }
+            s = dict(torch.cuda.memory_stats(shared.device))
+            allocated = { 'current': gb(s['allocated_bytes.all.current']), 'peak': gb(s['allocated_bytes.all.peak']) }
+            reserved = { 'current': gb(s['reserved_bytes.all.current']), 'peak': gb(s['reserved_bytes.all.peak']) }
+            active = { 'current': gb(s['active_bytes.all.current']), 'peak': gb(s['active_bytes.all.peak']) }
+            inactive = { 'current': gb(s['inactive_split_bytes.all.current']), 'peak': gb(s['inactive_split_bytes.all.peak']) }
+            warnings = { 'retries': s['num_alloc_retries'], 'oom': s['num_ooms'] }
+            mem.update({
+                'gpu': gpu,
+                'gpu-active': active,
+                'gpu-allocated': allocated,
+                'gpu-reserved': reserved,
+                'gpu-inactive': inactive,
+                'events': warnings,
+            })
+    except:
+        pass
+    return mem
+
+def get_optimizations():
+    ram = []
+    if shared.cmd_opts.medvram:
+        ram.append('medvram')
+    if shared.cmd_opts.lowvram:
+        ram.append('lowvram')
+    if shared.cmd_opts.lowram:
+        ram.append('lowram')
+    if len(ram) == 0:
+        ram.append('none')
+    return ram
+
+def get_libs():
+    return {
+        'xformers': shared.xformers_available,
+        'accelerate': accelerate.__version__,
+        'transformers': transformers.__version__,
+        'safetensors': safetensors.__version__,
+        'lightning': pytorch_lightning.__version__,
+    }
+
+def get_repos():
+    repos = {}
+    for key, val in paths.paths.items():
+        try:
+            cmd = f'git -C {val} log --pretty=format:"%h %ad" -1 --date=short'
+            res = subprocess.run(f'{cmd} {val}', stdout = subprocess.PIPE, stderr = subprocess.PIPE, shell=True, check=True)
+            stdout = res.stdout.decode(encoding = 'utf8', errors='ignore') if len(res.stdout) > 0 else ''
+            words = stdout.split(' ')
+            repos[key] = f'[{words[0]}] {words[1]}'
+        except:
+            repos[key] = '(unknown)'
+    return repos
+
+def get_model():
+    try:
+        return {
+            'configured': shared.opts.data['sd_model_checkpoint'],
+            'current': shared.sd_model.sd_checkpoint_info.title,
+            'configuration': os.path.basename(sd_models.find_checkpoint_config(shared.sd_model.sd_checkpoint_info)),
+        }
+    except:
+        return { 'error': 'no model config found' }
+
+def get_vae():
+    try:
+        return {
+            'configured': shared.opts.sd_vae,
+            'current': os.path.basename(shared.sd_vae.loaded_vae_file),
+        }
+    except:
+        return { 'error': 'no vae config found' }
+
+def get_platform():
+    try:
+        return {
+            'host': platform.node(),
+            'arch': platform.machine(),
+            'cpu': platform.processor(),
+            'system': platform.system(),
+            'platform': platform.platform(aliased = True, terse = False),
+            'release': platform.release(),
+            'version': platform.version(),
+            'python': platform.python_version(),
+        }
+    except Exception as e:
+        return { 'error': e }
+
+def get_torch():
+    return {
+        'version': torch.__version__,
+        'precision': shared.cmd_opts.precision + (' fp32' if shared.cmd_opts.no_half else ' fp16'),
+    }
+
+def get_version():
+    try:
+        res = subprocess.run('git log --pretty=format:"%h %ad" -1 --date=short', stdout = subprocess.PIPE, stderr = subprocess.PIPE, shell=True, check=True)
+        ver = res.stdout.decode(encoding = 'utf8', errors='ignore') if len(res.stdout) > 0 else ''
+        githash, updated = ver.split(' ')
+        res = subprocess.run('git remote get-url origin', stdout = subprocess.PIPE, stderr = subprocess.PIPE, shell=True, check=True)
+        origin = res.stdout.decode(encoding = 'utf8', errors='ignore') if len(res.stdout) > 0 else ''
+        res = subprocess.run('git branch --show-current', stdout = subprocess.PIPE, stderr = subprocess.PIPE, shell=True, check=True)
+        branch = res.stdout.decode(encoding = 'utf8', errors='ignore') if len(res.stdout) > 0 else ''
+        return {
+            'updated': updated,
+            'hash': githash,
+            'origin': origin.replace('\n', ''),
+            'branch': branch.replace('\n', ''),
+        }
+    except:
+        return {}
+
+def get_embeddings():
+    return [f'{v} ({sd_hijack.model_hijack.embedding_db.word_embeddings[v].vectors})' for i, v in enumerate(sd_hijack.model_hijack.embedding_db.word_embeddings)]
+
+def get_skipped():
+    return [k for k in sd_hijack.model_hijack.embedding_db.skipped_embeddings.keys()]
+
+def get_crossattention():
+    try:
+        return sd_hijack.model_hijack.optimization_method
+    except:
+        return 'unknown'
+
+def get_models():
+    return [x.title for x in sd_models.checkpoints_list.values()]
+
+def get_samplers():
+    return [sampler[0] for sampler in sd_samplers.all_samplers]
+
+def get_full_data():
+    global data # pylint: disable=global-statement
+    data = {
+        'date': datetime.datetime.now().strftime('%c'),
+        'timestamp': datetime.datetime.now().strftime('%X'),
+        'uptime': get_uptime(),
+        'version': get_version(),
+        'model': get_model(),
+        'vae': get_vae(),
+        'torch': get_torch(),
+        'cuda': get_cuda(),
+        'state': get_state(),
+        'memory': get_memory(),
+        'optimizations': get_optimizations(),
+        'libs': get_libs(),
+        'repos': get_repos(),
+        'models': get_models(),
+        'hypernetworks': [name for name in shared.hypernetworks],
+        'embeddings': get_embeddings(),
+        'skipped': get_skipped(),
+        'schedulers': get_samplers(),
+        'platform': get_platform(),
+        'crossattention': get_crossattention(),
+        'api': shared.cmd_opts.api,
+        'webui': not shared.cmd_opts.nowebui,
+    }
+    return data
+
+def get_quick_data():
+    data['timestamp'] = datetime.datetime.now().strftime('%X')
+    data['state'] = get_state()
+    data['memory'] = get_memory()
+
+def list2text(lst: list):
+    return '\n'.join(lst)
+
+def dict2str(d: dict):
+    arr = [f'{name}: {d[name]}' for i, name in enumerate(d)]
+    return ' '.join(arr)
+
+def dict2text(d: dict):
+    arr = ['{name}: {val}'.format(name = name, val = d[name] if not type(d[name]) is dict else dict2str(d[name])) for i, name in enumerate(d)] # pylint: disable=consider-using-f-string
+    return list2text(arr)
+
+def refresh_info_quick():
+    get_quick_data()
+    return dict2text(data['state']), dict2text(data['memory']), data['timestamp'], data
+
+def refresh_info_full():
+    get_full_data()
+    return dict2text(data['state']), dict2text(data['memory']), data['models'], data['hypernetworks'], data['embeddings'], data['skipped'], dict2text(data['model']), dict2text(data['vae']), data['timestamp'], data
+
+def on_ui_tabs():
+    get_full_data()
+    with gr.Blocks(analytics_enabled = False) as system_info_tab:
+        with gr.Row(elem_id = 'system_info_tab'):
+            with gr.Column(scale = 9):
+                with gr.Box():
+                    with gr.Row():
+                        with gr.Column():
+                            gr.Textbox(data['uptime'], label = 'Server start time', lines = 1)
+                            gr.Textbox(dict2text(data['version']), label = 'Version', lines = len(data['version']))
+                        with gr.Column():
+                            model = gr.Textbox(dict2text(data['model']), label = 'Model', lines = len(data['model']))
+                            vae = gr.Textbox(dict2text(data['vae']), label = 'VAE', lines = len(data['vae']))
+                        with gr.Column():
+                            state = gr.Textbox(dict2text(data['state']), label = 'State', lines = len(data['state']))
+                        with gr.Column():
+                            memory = gr.Textbox(dict2text(data['memory']), label = 'Memory', lines = len(data['memory']))
+                with gr.Box():
+                    with gr.Accordion('System data', open = True, visible = True):
+                        with gr.Row():
+                            with gr.Column():
+                                gr.Textbox(dict2text(data['platform']), label = 'Platform', lines = len(data['platform']))
+                            with gr.Column():
+                                gr.Textbox(dict2text(data['torch']), label = 'Torch', lines = len(data['torch']))
+                                gr.Textbox(dict2text(data['cuda']), label = 'CUDA', lines = len(data['cuda']))
+                                with gr.Row():
+                                    gr.Textbox(list2text(data['optimizations']), label = 'Memory optimization')
+                                    gr.Textbox(data['crossattention'], label = 'Cross-attention')
+                                    gr.Textbox((data['api']), label = 'API')
+                            with gr.Column():
+                                gr.Textbox(dict2text(data['libs']), label = 'Libs', lines = len(data['libs']))
+                                gr.Textbox(dict2text(data['repos']), label = 'Repos', lines = len(data['repos']))
+                with gr.Box():
+                    with gr.Accordion('Models...', open = False, visible = True):
+                        with gr.Row():
+                            with gr.Column():
+                                models = gr.JSON(data['models'], label = 'Models', lines = len(data['models']))
+                                hypernetworks = gr.JSON(data['hypernetworks'], label = 'Hypernetworks', lines = len(data['hypernetworks']))
+                            with gr.Column():
+                                embeddings = gr.JSON(data['embeddings'], label = 'Embeddings: loaded', lines = len(data['embeddings']))
+                                skipped = gr.JSON(data['skipped'], label = 'Embeddings: skipped', lines = len(data['embeddings']))
+                with gr.Box():
+                    with gr.Accordion('Info object', open = False, visible = True):
+                        # reduce json data to avoid private info
+                        data.pop('models', None)
+                        data.pop('embeddings', None)
+                        data.pop('skipped', None)
+                        data.pop('hypernetworks', None)
+                        data.pop('schedulers', None)
+                        json = gr.JSON(data)
+            with gr.Column(scale = 1, min_width = 120):
+                timestamp = gr.Text(data['timestamp'], label = '', elem_id = 'system_info_tab_last_update')
+                refresh_quick = gr.Button('Refresh state', elem_id = 'system_info_tab_refresh_btn', visible = False).style(full_width = False) # quick refresh is used from js interval
+                refresh_quick.click(refresh_info_quick, inputs = [], outputs = [state, memory, timestamp, json])
+                refresh_full = gr.Button('Refresh data', elem_id = 'system_info_tab_refresh_full_btn').style(full_width = False)
+                refresh_full.click(refresh_info_full, inputs = [], outputs = [state, memory, models, hypernetworks, embeddings, skipped, model, vae, timestamp, json])
+                interrupt = gr.Button('Send interrupt', elem_id = 'system_info_tab_interrupt_btn')
+                interrupt.click(shared.state.interrupt, inputs = [], outputs = [])
+    return (system_info_tab, 'System Info', 'system_info_tab'),
+
+script_callbacks.on_ui_tabs(on_ui_tabs)