Upload MainTest.py

Was_node_suite/MainTest.py

@@ -0,0 +1,295 @@
+import atexit, requests, subprocess, time, re, os
+from random import randint
+from threading import Timer
+from queue import Queue
+def cloudflared(port, metrics_port, output_queue):
+    atexit.register(lambda p: p.terminate(), subprocess.Popen(['/workspace/ComfyUI/cloudflared-linux-amd64', 'tunnel', '--url', f'http://127.0.0.1:{port}', '--metrics', f'127.0.0.1:{metrics_port}'], stdout=subprocess.DEVNULL, stderr=subprocess.STDOUT))
+    attempts, tunnel_url = 0, None
+    while attempts < 10 and not tunnel_url:
+        attempts += 1
+        time.sleep(3)
+        try:
+            tunnel_url = re.search("(?P<url>https?:\/\/[^\s]+.trycloudflare.com)", requests.get(f'http://127.0.0.1:{metrics_port}/metrics').text).group("url")
+        except:
+            pass
+    if not tunnel_url:
+        raise Exception("Can't connect to Cloudflare Edge")
+    output_queue.put(tunnel_url)
+output_queue, metrics_port = Queue(), randint(8100, 9000)
+thread = Timer(2, cloudflared, args=(8188, metrics_port, output_queue))
+thread.start()
+thread.join()
+tunnel_url = output_queue.get()
+os.environ['webui_url'] = tunnel_url
+print(tunnel_url)
+
+import comfy.options
+comfy.options.enable_args_parsing()
+
+import os
+import importlib.util
+import folder_paths
+import time
+from comfy.cli_args import args
+
+
+def execute_prestartup_script():
+    def execute_script(script_path):
+        module_name = os.path.splitext(script_path)[0]
+        try:
+            spec = importlib.util.spec_from_file_location(module_name, script_path)
+            module = importlib.util.module_from_spec(spec)
+            spec.loader.exec_module(module)
+            return True
+        except Exception as e:
+            print(f"Failed to execute startup-script: {script_path} / {e}")
+        return False
+
+    if args.disable_all_custom_nodes:
+        return
+
+    node_paths = folder_paths.get_folder_paths("custom_nodes")
+    for custom_node_path in node_paths:
+        possible_modules = os.listdir(custom_node_path)
+        node_prestartup_times = []
+
+        for possible_module in possible_modules:
+            module_path = os.path.join(custom_node_path, possible_module)
+            if os.path.isfile(module_path) or module_path.endswith(".disabled") or module_path == "__pycache__":
+                continue
+
+            script_path = os.path.join(module_path, "prestartup_script.py")
+            if os.path.exists(script_path):
+                time_before = time.perf_counter()
+                success = execute_script(script_path)
+                node_prestartup_times.append((time.perf_counter() - time_before, module_path, success))
+    if len(node_prestartup_times) > 0:
+        print("\nPrestartup times for custom nodes:")
+        for n in sorted(node_prestartup_times):
+            if n[2]:
+                import_message = ""
+            else:
+                import_message = " (PRESTARTUP FAILED)"
+            print("{:6.1f} seconds{}:".format(n[0], import_message), n[1])
+        print()
+
+execute_prestartup_script()
+
+
+# Main code
+import asyncio
+import itertools
+import shutil
+import threading
+import gc
+
+import logging
+
+if os.name == "nt":
+    logging.getLogger("xformers").addFilter(lambda record: 'A matching Triton is not available' not in record.getMessage())
+
+if __name__ == "__main__":
+    if args.cuda_device is not None:
+        os.environ['CUDA_VISIBLE_DEVICES'] = str(args.cuda_device)
+        logging.info("Set cuda device to: {}".format(args.cuda_device))
+
+    if args.deterministic:
+        if 'CUBLAS_WORKSPACE_CONFIG' not in os.environ:
+            os.environ['CUBLAS_WORKSPACE_CONFIG'] = ":4096:8"
+
+    import cuda_malloc
+
+if args.windows_standalone_build:
+    try:
+        import fix_torch
+    except:
+        pass
+
+import comfy.utils
+import yaml
+
+import execution
+import server
+from server import BinaryEventTypes
+import nodes
+import comfy.model_management
+
+def cuda_malloc_warning():
+    device = comfy.model_management.get_torch_device()
+    device_name = comfy.model_management.get_torch_device_name(device)
+    cuda_malloc_warning = False
+    if "cudaMallocAsync" in device_name:
+        for b in cuda_malloc.blacklist:
+            if b in device_name:
+                cuda_malloc_warning = True
+        if cuda_malloc_warning:
+            logging.warning("\nWARNING: this card most likely does not support cuda-malloc, if you get \"CUDA error\" please run ComfyUI with: --disable-cuda-malloc\n")
+
+def prompt_worker(q, server):
+    e = execution.PromptExecutor(server, lru_size=args.cache_lru)
+    last_gc_collect = 0
+    need_gc = False
+    gc_collect_interval = 10.0
+
+    while True:
+        timeout = 1000.0
+        if need_gc:
+            timeout = max(gc_collect_interval - (current_time - last_gc_collect), 0.0)
+
+        queue_item = q.get(timeout=timeout)
+        if queue_item is not None:
+            item, item_id = queue_item
+            execution_start_time = time.perf_counter()
+            prompt_id = item[1]
+            server.last_prompt_id = prompt_id
+
+            e.execute(item[2], prompt_id, item[3], item[4])
+            need_gc = True
+            q.task_done(item_id,
+                        e.history_result,
+                        status=execution.PromptQueue.ExecutionStatus(
+                            status_str='success' if e.success else 'error',
+                            completed=e.success,
+                            messages=e.status_messages))
+            if server.client_id is not None:
+                server.send_sync("executing", { "node": None, "prompt_id": prompt_id }, server.client_id)
+
+            current_time = time.perf_counter()
+            execution_time = current_time - execution_start_time
+            logging.info("Prompt executed in {:.2f} seconds".format(execution_time))
+
+        flags = q.get_flags()
+        free_memory = flags.get("free_memory", False)
+
+        if flags.get("unload_models", free_memory):
+            comfy.model_management.unload_all_models()
+            need_gc = True
+            last_gc_collect = 0
+
+        if free_memory:
+            e.reset()
+            need_gc = True
+            last_gc_collect = 0
+
+        if need_gc:
+            current_time = time.perf_counter()
+            if (current_time - last_gc_collect) > gc_collect_interval:
+                comfy.model_management.cleanup_models()
+                gc.collect()
+                comfy.model_management.soft_empty_cache()
+                last_gc_collect = current_time
+                need_gc = False
+
+async def run(server, address='', port=8188, verbose=True, call_on_start=None):
+    await asyncio.gather(server.start(address, port, verbose, call_on_start), server.publish_loop())
+
+
+def hijack_progress(server):
+    def hook(value, total, preview_image):
+        comfy.model_management.throw_exception_if_processing_interrupted()
+        progress = {"value": value, "max": total, "prompt_id": server.last_prompt_id, "node": server.last_node_id}
+
+        server.send_sync("progress", progress, server.client_id)
+        if preview_image is not None:
+            server.send_sync(BinaryEventTypes.UNENCODED_PREVIEW_IMAGE, preview_image, server.client_id)
+    comfy.utils.set_progress_bar_global_hook(hook)
+
+
+def cleanup_temp():
+    temp_dir = folder_paths.get_temp_directory()
+    if os.path.exists(temp_dir):
+        shutil.rmtree(temp_dir, ignore_errors=True)
+
+
+def load_extra_path_config(yaml_path):
+    with open(yaml_path, 'r') as stream:
+        config = yaml.safe_load(stream)
+    for c in config:
+        conf = config[c]
+        if conf is None:
+            continue
+        base_path = None
+        if "base_path" in conf:
+            base_path = conf.pop("base_path")
+        for x in conf:
+            for y in conf[x].split("\n"):
+                if len(y) == 0:
+                    continue
+                full_path = y
+                if base_path is not None:
+                    full_path = os.path.join(base_path, full_path)
+                logging.info("Adding extra search path {} {}".format(x, full_path))
+                folder_paths.add_model_folder_path(x, full_path)
+
+
+if __name__ == "__main__":
+    if args.temp_directory:
+        temp_dir = os.path.join(os.path.abspath(args.temp_directory), "temp")
+        logging.info(f"Setting temp directory to: {temp_dir}")
+        folder_paths.set_temp_directory(temp_dir)
+    cleanup_temp()
+
+    if args.windows_standalone_build:
+        try:
+            import new_updater
+            new_updater.update_windows_updater()
+        except:
+            pass
+
+    loop = asyncio.new_event_loop()
+    asyncio.set_event_loop(loop)
+    server = server.PromptServer(loop)
+    q = execution.PromptQueue(server)
+
+    extra_model_paths_config_path = os.path.join(os.path.dirname(os.path.realpath(__file__)), "extra_model_paths.yaml")
+    if os.path.isfile(extra_model_paths_config_path):
+        load_extra_path_config(extra_model_paths_config_path)
+
+    if args.extra_model_paths_config:
+        for config_path in itertools.chain(*args.extra_model_paths_config):
+            load_extra_path_config(config_path)
+
+    nodes.init_extra_nodes(init_custom_nodes=not args.disable_all_custom_nodes)
+
+    cuda_malloc_warning()
+
+    server.add_routes()
+    hijack_progress(server)
+
+    threading.Thread(target=prompt_worker, daemon=True, args=(q, server,)).start()
+
+    if args.output_directory:
+        output_dir = os.path.abspath(args.output_directory)
+        logging.info(f"Setting output directory to: {output_dir}")
+        folder_paths.set_output_directory(output_dir)
+
+    #These are the default folders that checkpoints, clip and vae models will be saved to when using CheckpointSave, etc.. nodes
+    folder_paths.add_model_folder_path("checkpoints", os.path.join(folder_paths.get_output_directory(), "checkpoints"))
+    folder_paths.add_model_folder_path("clip", os.path.join(folder_paths.get_output_directory(), "clip"))
+    folder_paths.add_model_folder_path("vae", os.path.join(folder_paths.get_output_directory(), "vae"))
+    folder_paths.add_model_folder_path("diffusion_models", os.path.join(folder_paths.get_output_directory(), "diffusion_models"))
+
+    if args.input_directory:
+        input_dir = os.path.abspath(args.input_directory)
+        logging.info(f"Setting input directory to: {input_dir}")
+        folder_paths.set_input_directory(input_dir)
+
+    if args.quick_test_for_ci:
+        exit(0)
+
+    call_on_start = None
+    if args.auto_launch:
+        def startup_server(scheme, address, port):
+            import webbrowser
+            if os.name == 'nt' and address == '0.0.0.0':
+                address = '127.0.0.1'
+            webbrowser.open(f"{scheme}://{address}:{port}")
+        call_on_start = startup_server
+
+    try:
+        loop.run_until_complete(server.setup())
+        loop.run_until_complete(run(server, address=args.listen, port=args.port, verbose=not args.dont_print_server, call_on_start=call_on_start))
+    except KeyboardInterrupt:
+        logging.info("\nStopped server")
+
+    cleanup_temp()