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Offline fix #1484

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Offline fix #1484

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211 changes: 115 additions & 96 deletions wgp.py
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Original file line number Diff line number Diff line change
Expand Up @@ -6845,116 +6845,135 @@ def release_gen():
gen["status"] = "Generating Video"
gen["header_text"] = ""

yield time.time(), time.time()
prompt_no = 0
while len(queue) > 0:
paused_for_edit = False
while gen.get("queue_paused_for_edit", False):
if not paused_for_edit:
gr.Info("Queue Paused until Current Task Edition is Done")
gen["status"] = "Queue paused for editing..."
yield time.time(), time.time()
paused_for_edit = True
time.sleep(0.5)

if paused_for_edit:
gen["status"] = "Resuming queue processing..."
yield time.time(), time.time()
yield time.time(), time.time()

prompt_no += 1
gen["prompt_no"] = prompt_no
com_stream = AsyncStream()
send_cmd = com_stream.output_queue.push

task = None
with lock:
if len(queue) > 0:
task = queue[0]
def queue_worker_func():
prompt_no = 0
try:
while len(queue) > 0:
paused_for_edit = False
while gen.get("queue_paused_for_edit", False):
if not paused_for_edit:
send_cmd("info", "Queue Paused until Current Task Edition is Done")
send_cmd("status", "Queue paused for editing...")
send_cmd("output", None)
paused_for_edit = True
time.sleep(0.5)

if paused_for_edit:
send_cmd("status", "Resuming queue processing...")
send_cmd("output", None)

if task is None:
break
prompt_no += 1
gen["prompt_no"] = prompt_no

task_id = task["id"]
params = task['params']
for key in ["model_filename", "lset_name"]:
params.pop(key, None)
com_stream = AsyncStream()
send_cmd = com_stream.output_queue.push
def generate_video_error_handler():
try:
import inspect
model_type = params.get('model_type')
known_defaults = {
'image_refs_relative_size': 50,
}
task = None
with lock:
if len(queue) > 0:
task = queue[0]

for arg_name, default_value in known_defaults.items():
if arg_name not in params:
print(f"Warning: Missing argument '{arg_name}' in loaded task. Applying default value: {default_value}")
params[arg_name] = default_value
if model_type:
default_settings = get_default_settings(model_type)
expected_args = inspect.signature(generate_video).parameters.keys()
for arg_name in expected_args:
if arg_name not in params and arg_name in default_settings:
params[arg_name] = default_settings[arg_name]
plugin_data = task.pop('plugin_data', {})
generate_video(task, send_cmd, plugin_data=plugin_data, **params)
except Exception as e:
tb = traceback.format_exc().split('\n')[:-1]
print('\n'.join(tb))
send_cmd("error",str(e))
finally:
send_cmd("exit", None)
if task is None:
break

async_run(generate_video_error_handler)
task_id = task["id"]
params = task['params']
for key in ["model_filename", "lset_name"]:
params.pop(key, None)

try:
import inspect
model_type = params.get('model_type')
known_defaults = {
'image_refs_relative_size': 50,
}

for arg_name, default_value in known_defaults.items():
if arg_name not in params:
print(f"Warning: Missing argument '{arg_name}' in loaded task. Applying default value: {default_value}")
params[arg_name] = default_value
if model_type:
default_settings = get_default_settings(model_type)
expected_args = inspect.signature(generate_video).parameters.keys()
for arg_name in expected_args:
if arg_name not in params and arg_name in default_settings:
params[arg_name] = default_settings[arg_name]
plugin_data = task.pop('plugin_data', {})

generate_video(task, send_cmd, plugin_data=plugin_data, **params)

except Exception as e:
tb = traceback.format_exc().split('\n')[:-1]
print('\n'.join(tb))
send_cmd("error", str(e))
return

while True:
cmd, data = com_stream.output_queue.next()
if cmd == "exit":
break
elif cmd == "info":
gr.Info(data)
elif cmd == "error":
queue.clear()
gen["prompts_max"] = 0
gen["prompt"] = ""
gen["status_display"] = False
release_gen()
raise gr.Error(data, print_exception= False, duration = 0)
elif cmd == "status":
gen["status"] = data
elif cmd == "output":
gen["preview"] = None
gen["refresh_tab"] = True
yield time.time() , time.time()
elif cmd == "progress":
gen["progress_args"] = data
elif cmd == "preview":
torch.cuda.current_stream().synchronize()
preview= None if data== None else generate_preview(params["model_type"], data)
gen["preview"] = preview
yield time.time() , gr.Text()
else:
release_gen()
raise Exception(f"unknown command {cmd}")
abort = gen.get("abort", False)
if abort:
gen["abort"] = False
send_cmd("status", "Video Generation Aborted")
send_cmd("output", None)

abort = gen.get("abort", False)
if abort:
gen["abort"] = False
status = "Video Generation Aborted", "Video Generation Aborted"
yield time.time() , time.time()
gen["status"] = status
gen["early_stop"] = False
gen["early_stop_forwarded"] = False

gen["early_stop"] = False
gen["early_stop_forwarded"] = False
with lock:
queue[:] = [item for item in queue if item['id'] != task_id]
update_global_queue_ref(queue)

except Exception as e:
traceback.print_exc()
send_cmd("error", f"Queue worker crashed: {e}")
finally:
send_cmd("worker_exit", None)

with lock:
queue[:] = [item for item in queue if item['id'] != task_id]
update_global_queue_ref(queue)
async_run(queue_worker_func)

while True:
cmd, data = com_stream.output_queue.next()
if cmd == "exit":
pass
elif cmd == "worker_exit":
break
elif cmd == "info":
gr.Info(data)
elif cmd == "error":
queue.clear()
gen["prompts_max"] = 0
gen["prompt"] = ""
gen["status_display"] = False
release_gen()
raise gr.Error(data, print_exception=False, duration=0)
elif cmd == "status":
gen["status"] = data
elif cmd == "output":
gen["preview"] = None
gen["refresh_tab"] = True
yield time.time(), time.time()
elif cmd == "progress":
gen["progress_args"] = data
elif cmd == "preview":
current_model_type = "unknown"
with lock:
if len(queue) > 0:
current_model_type = queue[0]["params"].get("model_type")

try:
torch.cuda.current_stream().synchronize()
preview = None if data is None else generate_preview(current_model_type, data)
gen["preview"] = preview
yield time.time() , gr.Text()
except Exception:
pass
else:
pass

gen["prompts_max"] = 0
gen["prompt"] = ""
end_time = time.time()
if abort:
if gen.get("abort", False):
status = f"Video generation was aborted. Total Generation Time: {format_time(end_time-start_time)}"
else:
status = f"Total Generation Time: {format_time(end_time-start_time)}"
Expand Down