Files
robertvoy-ComfyUI-Distributed/upscale/worker_comms.py
T

272 lines
12 KiB
Python

import asyncio, io, json, time
import aiohttp
from PIL import Image
from ..utils.logging import debug_log, log
from ..utils.network import get_client_session
from ..utils.constants import TILE_SEND_TIMEOUT
from ..utils.usdu_managment import MAX_PAYLOAD_SIZE, _send_heartbeat_to_master
from ..utils.image import tensor_to_pil
class WorkerCommsMixin:
async def send_tiles_batch_to_master(self, processed_tiles, multi_job_id, master_url,
padding, worker_id):
"""Send all processed tiles to master, chunked if large."""
if not processed_tiles:
return # Early exit if empty
total_tiles = len(processed_tiles)
debug_log(f"Worker[{worker_id[:8]}] - Preparing to send {total_tiles} tiles (size-aware chunks)")
# Prepare encoded images and sizes to enable size-aware chunking
encoded = []
for idx, tile_data in enumerate(processed_tiles):
img = tensor_to_pil(tile_data['tile'], 0)
bio = io.BytesIO()
# Keep compression low to balance speed and size; adjust if needed
img.save(bio, format='PNG', compress_level=0)
raw = bio.getvalue()
encoded.append({
'bytes': raw,
'meta': {
'tile_idx': tile_data['tile_idx'],
'x': tile_data['x'],
'y': tile_data['y'],
'extracted_width': tile_data['extracted_width'],
'extracted_height': tile_data['extracted_height'],
**({'batch_idx': tile_data['batch_idx']} if 'batch_idx' in tile_data else {}),
**({'global_idx': tile_data['global_idx']} if 'global_idx' in tile_data else {}),
}
})
# Size-aware chunking
max_bytes = int(MAX_PAYLOAD_SIZE) - (1024 * 1024) # 1MB headroom
i = 0
chunk_index = 0
while i < total_tiles:
data = aiohttp.FormData()
data.add_field('multi_job_id', multi_job_id)
data.add_field('worker_id', str(worker_id))
data.add_field('padding', str(padding))
metadata = []
used = 0
j = i
while j < total_tiles:
img_bytes = encoded[j]['bytes']
meta = encoded[j]['meta']
# Rough overhead for fields + JSON
overhead = 1024
if used + len(img_bytes) + overhead > max_bytes and j > i:
break
# Accept this tile in this chunk
metadata.append(meta)
data.add_field(f'tile_{j - i}', io.BytesIO(img_bytes), filename=f'tile_{j}.png', content_type='image/png')
used += len(img_bytes) + overhead
j += 1
# Ensure at least one tile per chunk
if j == i:
# Single oversized tile, send anyway
meta = encoded[j]['meta']
metadata.append(meta)
data.add_field('tile_0', io.BytesIO(encoded[j]['bytes']), filename=f'tile_{j}.png', content_type='image/png')
j += 1
chunk_size = j - i
is_chunk_last = (j >= total_tiles)
data.add_field('is_last', str(is_chunk_last))
data.add_field('batch_size', str(chunk_size))
data.add_field('tiles_metadata', json.dumps(metadata), content_type='application/json')
# Retry logic with exponential backoff
max_retries = 5
retry_delay = 0.5
for attempt in range(max_retries):
try:
session = await get_client_session()
url = f"{master_url}/distributed/submit_tiles"
async with session.post(url, data=data) as response:
response.raise_for_status()
break
except Exception as e:
if attempt < max_retries - 1:
await asyncio.sleep(retry_delay)
retry_delay = min(retry_delay * 2, 5.0)
else:
log(f"UltimateSDUpscale Worker - Failed to send chunk {chunk_index} after {max_retries} attempts: {e}")
raise
debug_log(f"Worker[{worker_id[:8]}] - Sent chunk {chunk_index} ({chunk_size} tiles, ~{used/1e6:.2f} MB)")
chunk_index += 1
i = j
async def _request_image_from_master(self, multi_job_id, master_url, worker_id):
"""Request an image index to process from master in dynamic mode."""
# Enhanced retries with 404-specific delay, backoff cap, and total timeout to handle init races
max_retries = 10
retry_delay = 0.5
start_time = time.time()
for attempt in range(max_retries):
# Check total timeout
if time.time() - start_time > 30:
log(f"Total request timeout after 30s for worker {worker_id}")
return None, 0
try:
session = await get_client_session()
url = f"{master_url}/distributed/request_image"
async with session.post(url, json={
'worker_id': str(worker_id),
'multi_job_id': multi_job_id
}) as response:
if response.status == 200:
data = await response.json()
image_idx = data.get('image_idx')
estimated_remaining = data.get('estimated_remaining', 0)
return image_idx, estimated_remaining
elif response.status == 404:
# Special handling for 404 - job not found yet
text = await response.text()
debug_log(f"Job not found (404), will retry: {text}")
await asyncio.sleep(1.0)
else:
text = await response.text()
debug_log(f"Request image failed: {response.status} - {text}")
except Exception as e:
if attempt < max_retries - 1:
debug_log(f"Retry {attempt + 1}/{max_retries} after error: {e}")
await asyncio.sleep(retry_delay)
retry_delay *= 2
retry_delay = min(retry_delay, 5.0) # Cap backoff at 5s
else:
log(f"Failed to request image after {max_retries} attempts: {e}")
raise
return None, 0
async def _request_tile_from_master(self, multi_job_id, master_url, worker_id):
"""Request a tile index to process from master in static mode (reusing dynamic infrastructure)."""
# Reuse the same retry logic as dynamic mode
max_retries = 10
retry_delay = 0.5
start_time = time.time()
for attempt in range(max_retries):
# Check total timeout
if time.time() - start_time > 30:
log(f"Total request timeout after 30s for worker {worker_id}")
return None, 0
try:
session = await get_client_session()
url = f"{master_url}/distributed/request_image" # Same endpoint
async with session.post(url, json={
'worker_id': str(worker_id),
'multi_job_id': multi_job_id
}) as response:
if response.status == 200:
data = await response.json()
tile_idx = data.get('tile_idx')
estimated_remaining = data.get('estimated_remaining', 0)
batched_static = data.get('batched_static', False)
return tile_idx, estimated_remaining, batched_static
elif response.status == 404:
# Special handling for 404 - job not found yet
text = await response.text()
debug_log(f"Job not found (404), will retry: {text}")
await asyncio.sleep(1.0)
else:
text = await response.text()
debug_log(f"Request tile failed: {response.status} - {text}")
except Exception as e:
if attempt < max_retries - 1:
debug_log(f"Retry {attempt + 1}/{max_retries} after error: {e}")
await asyncio.sleep(retry_delay)
retry_delay *= 2
retry_delay = min(retry_delay, 5.0) # Cap backoff at 5s
else:
log(f"Failed to request tile after {max_retries} attempts: {e}")
raise
return None, 0, False
async def _send_full_image_to_master(self, image_pil, image_idx, multi_job_id,
master_url, worker_id, is_last):
"""Send a processed full image back to master in dynamic mode."""
# Serialize image to PNG
byte_io = io.BytesIO()
image_pil.save(byte_io, format='PNG', compress_level=0)
byte_io.seek(0)
# Prepare form data
data = aiohttp.FormData()
data.add_field('multi_job_id', multi_job_id)
data.add_field('worker_id', str(worker_id))
data.add_field('image_idx', str(image_idx))
data.add_field('is_last', str(is_last))
data.add_field('full_image', byte_io, filename=f'image_{image_idx}.png',
content_type='image/png')
# Retry logic
max_retries = 5
retry_delay = 0.5
for attempt in range(max_retries):
try:
session = await get_client_session()
url = f"{master_url}/distributed/submit_image"
async with session.post(url, data=data) as response:
response.raise_for_status()
debug_log(f"Successfully sent image {image_idx} to master")
return
except Exception as e:
if attempt < max_retries - 1:
debug_log(f"Retry {attempt + 1}/{max_retries} after error: {e}")
await asyncio.sleep(retry_delay)
retry_delay *= 2
else:
log(f"Failed to send image {image_idx} after {max_retries} attempts: {e}")
raise
async def _send_worker_complete_signal(self, multi_job_id, master_url, worker_id):
"""Send completion signal to master in dynamic mode."""
# Send a dummy request with is_last=True
data = aiohttp.FormData()
data.add_field('multi_job_id', multi_job_id)
data.add_field('worker_id', str(worker_id))
data.add_field('is_last', 'true')
# No image data - just completion signal
session = await get_client_session()
url = f"{master_url}/distributed/submit_image"
async with session.post(url, data=data) as response:
response.raise_for_status()
debug_log(f"Worker {worker_id} sent completion signal")
async def _check_job_status(self, multi_job_id, master_url):
"""Check if job is ready on the master."""
try:
session = await get_client_session()
url = f"{master_url}/distributed/job_status?multi_job_id={multi_job_id}"
async with session.get(url) as response:
if response.status == 200:
data = await response.json()
return data.get('ready', False)
return False
except Exception as e:
debug_log(f"Job status check failed: {e}")
return False
async def _async_yield(self):
"""Simple async yield to allow event loop processing."""
await asyncio.sleep(0)