85 lines
3.1 KiB
Python
85 lines
3.1 KiB
Python
import argparse
|
|
from typing import List
|
|
|
|
from cacheflow.master.frontend import Frontend
|
|
from cacheflow.master.scheduler import Scheduler
|
|
from cacheflow.models import get_memory_analyzer
|
|
from cacheflow.worker.controller import Controller
|
|
|
|
parser = argparse.ArgumentParser(description='CacheFlow server')
|
|
parser.add_argument('--model', type=str, default='facebook/opt-125m', help='model name')
|
|
parser.add_argument('--num-nodes', type=int, default=1, help='number of nodes')
|
|
parser.add_argument('--num-workers', type=int, default=1, help='number of workers per node')
|
|
parser.add_argument('--block-size', type=int, default=8, choices=[8, 16], help='token block size')
|
|
# NOTE(woosuk): If FlashAttention is used, the float data type is not supported.
|
|
parser.add_argument('--dtype', type=str, default='half', choices=['half', 'float'], help='data type')
|
|
# TODO(woosuk): Support fine-grained seeds (e.g., seed per request).
|
|
parser.add_argument('--seed', type=int, default=0, help='random seed')
|
|
parser.add_argument('--max-batch-size', type=int, default=2048, help='maximum number of batched tokens')
|
|
args = parser.parse_args()
|
|
|
|
|
|
def main():
|
|
memory_analyzer = get_memory_analyzer(
|
|
model_name=args.model,
|
|
block_size=args.block_size,
|
|
dtype=args.dtype,
|
|
)
|
|
num_gpu_blocks = memory_analyzer.get_max_num_gpu_blocks(
|
|
max_num_batched_tokens=args.max_batch_size)
|
|
num_cpu_blocks = memory_analyzer.get_max_num_cpu_blocks()
|
|
print(f'# GPU blocks: {num_gpu_blocks}, # CPU blocks: {num_cpu_blocks}')
|
|
|
|
# Create a controller for each node.
|
|
controllers: List[Controller] = []
|
|
for i in range(args.num_nodes):
|
|
controller = Controller(
|
|
node_id=i,
|
|
num_workers=args.num_workers,
|
|
model_name=args.model,
|
|
block_size=args.block_size,
|
|
num_gpu_blocks=num_gpu_blocks,
|
|
num_cpu_blocks=num_cpu_blocks,
|
|
dtype=args.dtype,
|
|
seed=args.seed,
|
|
)
|
|
controllers.append(controller)
|
|
|
|
# Create a frontend.
|
|
frontend = Frontend(
|
|
model_name=args.model,
|
|
block_size=args.block_size,
|
|
)
|
|
|
|
# Create a scheduler.
|
|
scheduler = Scheduler(
|
|
frontend=frontend,
|
|
controllers=controllers,
|
|
block_size=args.block_size,
|
|
num_gpu_blocks=num_gpu_blocks,
|
|
num_cpu_blocks=num_cpu_blocks,
|
|
max_num_batched_tokens=args.max_batch_size,
|
|
)
|
|
# Connect the controllers.
|
|
for i in range(len(controllers) - 1):
|
|
controllers[i].set_next(controllers[i + 1])
|
|
controllers[-1].set_next(scheduler)
|
|
|
|
# Test the following inputs.
|
|
test_inputs = [
|
|
('Ion Stoica is a', {'n': 4, 'use_beam_search': True, 'temperature': 0.0}),
|
|
('UC Berkeley is', {'n': 3, 'temperature': 0.8, 'top_p': 0.99}),
|
|
('The future of cloud computing is', {}), # Use default parameters.
|
|
]
|
|
while True:
|
|
if test_inputs:
|
|
text, sampling_params = test_inputs.pop(0)
|
|
frontend.query(text, **sampling_params)
|
|
scheduler.step()
|
|
if not (scheduler.pending or scheduler.running or test_inputs):
|
|
break
|
|
|
|
|
|
if __name__ == '__main__':
|
|
main()
|