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* remove splitwise_role and engine_worker_queue_port * fix xpu * fix xpu * fix xpu * fix unittest * resolve conflct
117 lines
3.9 KiB
Python
117 lines
3.9 KiB
Python
import unittest
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from unittest.mock import Mock
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from fastdeploy import envs
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from fastdeploy.config import (
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CacheConfig,
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FDConfig,
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GraphOptimizationConfig,
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LoadConfig,
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ParallelConfig,
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SchedulerConfig,
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)
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class TestConfig(unittest.TestCase):
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def test_fdconfig_nnode(self):
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parallel_config = ParallelConfig({"tensor_parallel_size": 16, "expert_parallel_size": 1})
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graph_opt_config = GraphOptimizationConfig({})
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cache_config = CacheConfig({})
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load_config = LoadConfig({})
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scheduler_config = SchedulerConfig({})
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model_config = Mock()
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fd_config = FDConfig(
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parallel_config=parallel_config,
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graph_opt_config=graph_opt_config,
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load_config=load_config,
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cache_config=cache_config,
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scheduler_config=scheduler_config,
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model_config=model_config,
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ips=["1.1.1.1", "0.0.0.0"],
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test_mode=True,
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)
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assert fd_config.nnode == 2
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assert fd_config.is_master is False
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def test_fdconfig_ips(self):
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parallel_config = ParallelConfig({})
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graph_opt_config = GraphOptimizationConfig({})
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cache_config = CacheConfig({})
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load_config = LoadConfig({})
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scheduler_config = SchedulerConfig({})
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model_config = Mock()
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fd_config = FDConfig(
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parallel_config=parallel_config,
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graph_opt_config=graph_opt_config,
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load_config=load_config,
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cache_config=cache_config,
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scheduler_config=scheduler_config,
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model_config=model_config,
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ips="0.0.0.0",
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test_mode=True,
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)
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assert fd_config.master_ip == "0.0.0.0"
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def test_fdconfig_max_num_tokens(self):
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parallel_config = ParallelConfig({})
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graph_opt_config = GraphOptimizationConfig({})
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cache_config = CacheConfig({})
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load_config = LoadConfig({})
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cache_config.enable_chunked_prefill = True
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scheduler_config = SchedulerConfig({})
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model_config = model_config = Mock()
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fd_config = FDConfig(
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parallel_config=parallel_config,
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graph_opt_config=graph_opt_config,
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cache_config=cache_config,
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load_config=load_config,
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scheduler_config=scheduler_config,
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model_config=model_config,
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ips="0.0.0.0",
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test_mode=True,
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)
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if not envs.ENABLE_V1_KVCACHE_SCHEDULER:
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assert fd_config.scheduler_config.max_num_batched_tokens == 2048
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cache_config.enable_chunked_prefill = False
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fd_config = FDConfig(
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parallel_config=parallel_config,
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graph_opt_config=graph_opt_config,
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cache_config=cache_config,
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load_config=load_config,
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scheduler_config=scheduler_config,
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model_config=model_config,
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ips="0.0.0.0",
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test_mode=True,
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)
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if not envs.ENABLE_V1_KVCACHE_SCHEDULER:
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assert fd_config.scheduler_config.max_num_batched_tokens == 8192
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def test_fdconfig_init_cache(self):
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parallel_config = ParallelConfig({})
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graph_opt_config = GraphOptimizationConfig({})
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cache_config = CacheConfig({})
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cache_config.cache_transfer_protocol = "rdma,ipc"
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cache_config.pd_comm_port = "2334"
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load_config = LoadConfig({})
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scheduler_config = SchedulerConfig({})
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scheduler_config.splitwise_role = "prefill"
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model_config = model_config = Mock()
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fd_config = FDConfig(
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parallel_config=parallel_config,
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graph_opt_config=graph_opt_config,
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cache_config=cache_config,
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load_config=load_config,
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scheduler_config=scheduler_config,
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model_config=model_config,
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test_mode=True,
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)
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fd_config.init_cache_info()
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assert fd_config.disaggregate_info["role"] == "prefill"
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if __name__ == "__main__":
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unittest.main()
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