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training logic tested and working

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drunkplato 2024-11-29 20:41:09 +00:00 committed by Ubuntu
parent a22b1a7895
commit 6ea9f911d3
1 changed files with 52 additions and 10 deletions
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62
memedeck.py
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@ -16,6 +16,8 @@ load_dotenv()
amqp_addr = os.getenv('AMQP_ADDR') or 'amqp://api:gacdownatravKekmy9@51.8.120.154:5672/dev'
logging.getLogger().setLevel(logging.INFO)
from enum import Enum
class QueueProgressKind(Enum):
@ -83,8 +85,8 @@ class MemedeckWorker:
# Start the process_job_queue task **after** prompt_queue is set
self.loop.create_task(self.process_job_queue())
parameters = pika.URLParameters(self.amqp_url)
logging.getLogger('pika').setLevel(logging.WARNING) # suppress all logs from pika
self.connection = pika.SelectConnection(parameters, on_open_callback=self.on_connection_open)
@ -113,7 +115,11 @@ class MemedeckWorker:
# Only consume one message at a time
self.channel.basic_qos(prefetch_size=0, prefetch_count=1)
# Declare the queue and set the callback
self.channel.queue_declare(queue=self.queue_name, durable=True, callback=self.on_queue_declared)
self.channel.queue_declare(
queue=self.queue_name,
durable=True,
callback=self.on_queue_declared
)
def on_queue_declared(self, frame):
self.channel.basic_consume(queue=self.queue_name, on_message_callback=self.on_message_received)
@ -151,13 +157,31 @@ class MemedeckWorker:
"outputs_to_execute": outputs_to_execute,
"client_id": "memedeck-1",
"is_memedeck": True,
"end_node_id": None,
"end_node_id": "130" if self.training_only else None,
"ws_id": payload["source_ws_id"],
"context": payload["req_ctx"] if "req_ctx" in payload else {},
"current_node": None,
"current_progress": 0,
"delivery_tag": method.delivery_tag,
"task_status": "waiting",
# based on workflow:flux_training_v1
"training_loop": {
"4": 0.1, # loop 1 start
"9": 0.25, # loop 1 end
"44": 0.25, # loop 2 start
"46": 0.5, # loop 2 end
"59": 0.5, # loop 3 start
"61": 0.75, # loop 3 end
"60": 0.75, # loop 4 start
"62": 1.0, # loop 4 end
},
"training_status": {
"4": "loop-1",
"44": "loop-2",
"59": "loop-3",
"60": "loop-4",
},
"training_filename": payload['filename'] if 'filename' in payload else None
}
# Find the end_node_id
@ -165,9 +189,6 @@ class MemedeckWorker:
if isinstance(prompt[node], dict) and prompt[node].get("class_type") == "SaveImageWebsocket":
task_info['end_node_id'] = node
break
if self.training_only and isinstance(prompt[node], dict) and prompt[node].get("class_type") == "FluxTrainEnd":
task_info['end_node_id'] = node
break
if valid[0]:
# Enqueue the task into the internal job queue
@ -256,7 +277,7 @@ class MemedeckWorker:
return
if task['workflow'] == 'training':
return self.handle_training_send(event, task, sid)
return await self.handle_training_send(event=event, task=task, sid=sid, data=data)
# this logic is for generation and faceswap (todo move to separate function)
@ -315,12 +336,33 @@ class MemedeckWorker:
# Update the task in tasks_by_ws_id
self.tasks_by_ws_id[sid] = task
def handle_training_send(self, event, task, sid):
async def handle_training_send(self, event, task, sid, data):
# if event == "progress":
# self.logger.info(f"[memedeck]: training progress: {data}")
if event == "executing":
training_progress = task['training_loop'][data['node']] if data['node'] in task['training_loop'] else None
status = task['training_status'][data['node']] if data['node'] in task['training_status'] else None
if training_progress is not None:
await self.send_to_api({
"ws_id": sid,
"prompt_id": data['prompt_id'],
"progress": training_progress,
"status": status
})
if event == "executed":
if task['current_node'] == task['end_node_id']:
self.logger.info(f"[memedeck]: training completed for {sid}")
if data['node'] == task['end_node_id']:
await self.send_to_api({
"ws_id": sid,
"progress": 1.0,
"status": "completed",
"filename": task['training_filename']
})
# training task is done
del self.tasks_by_ws_id[sid]
async def send_preview(self, image_data, sid=None, progress=None, context=None, workflow=None):
if sid is None: