599 lines
18 KiB
Python
599 lines
18 KiB
Python
import os
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import unittest
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from types import SimpleNamespace
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from sglang.srt.environ import envs
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from sglang.test.ci.ci_register import register_cuda_ci
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from sglang.test.run_eval import run_eval
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from sglang.test.server_fixtures.disaggregation_fixture import (
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PDDisaggregationServerBase,
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)
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from sglang.test.test_utils import (
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DEFAULT_HYBRID_GDN_SMALL_MODEL_NAME_FOR_TEST,
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DEFAULT_MODEL_NAME_FOR_TEST,
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DEFAULT_MODEL_NAME_FOR_TEST_MLA,
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DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
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popen_launch_pd_server,
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try_cached_model,
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)
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register_cuda_ci(est_time=375, stage="base-c", runner_config="8-gpu-h20")
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class TestDisaggregationMooncakePrefillLargerTP(PDDisaggregationServerBase):
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@classmethod
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def setUpClass(cls):
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super().setUpClass()
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# Temporarily disable JIT DeepGEMM
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envs.SGLANG_ENABLE_JIT_DEEPGEMM.set(False)
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cls.model = try_cached_model(DEFAULT_MODEL_NAME_FOR_TEST_MLA)
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# Non blocking start servers
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cls.start_prefill()
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cls.start_decode()
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# Block until both
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cls.wait_server_ready(cls.prefill_url + "/health", process=cls.process_prefill)
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cls.wait_server_ready(cls.decode_url + "/health", process=cls.process_decode)
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cls.launch_lb()
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@classmethod
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def start_prefill(cls):
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prefill_args = [
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"--trust-remote-code",
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"--disaggregation-mode",
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"prefill",
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"--disaggregation-bootstrap-port",
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cls.bootstrap_port,
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"--tp",
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"4",
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"--enable-metrics",
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"--enable-request-time-stats-logging",
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]
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prefill_args += cls.transfer_backend + cls.rdma_devices
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cls.process_prefill = popen_launch_pd_server(
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cls.model,
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cls.prefill_url,
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timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
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other_args=prefill_args,
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)
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@classmethod
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def start_decode(cls):
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decode_args = [
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"--trust-remote-code",
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"--disaggregation-mode",
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"decode",
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"--disaggregation-bootstrap-port",
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cls.bootstrap_port,
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"--tp",
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"2",
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"--base-gpu-id",
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"4",
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"--enable-metrics",
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"--enable-request-time-stats-logging",
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]
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decode_args += cls.transfer_backend + cls.rdma_devices
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cls.process_decode = popen_launch_pd_server(
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cls.model,
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cls.decode_url,
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timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
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other_args=decode_args,
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)
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def test_gsm8k(self):
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args = SimpleNamespace(
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base_url=self.base_url,
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model=self.model,
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eval_name="gsm8k",
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api="completion",
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max_tokens=512,
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num_examples=200,
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num_threads=128,
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)
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metrics = run_eval(args)
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print(f"Evaluation metrics: {metrics}")
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self.assertGreater(metrics["score"], 0.60)
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class TestDisaggregationMooncakeDecodeLargerTP(PDDisaggregationServerBase):
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@classmethod
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def setUpClass(cls):
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super().setUpClass()
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# Temporarily disable JIT DeepGEMM
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envs.SGLANG_ENABLE_JIT_DEEPGEMM.set(False)
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cls.model = try_cached_model(DEFAULT_MODEL_NAME_FOR_TEST_MLA)
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# Non blocking start servers
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cls.start_prefill()
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cls.start_decode()
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# Block until both
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cls.wait_server_ready(cls.prefill_url + "/health", process=cls.process_prefill)
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cls.wait_server_ready(cls.decode_url + "/health", process=cls.process_decode)
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cls.launch_lb()
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@classmethod
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def start_prefill(cls):
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prefill_args = [
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"--trust-remote-code",
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"--disaggregation-mode",
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"prefill",
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"--disaggregation-bootstrap-port",
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cls.bootstrap_port,
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"--tp",
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"2",
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"--enable-metrics",
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"--enable-request-time-stats-logging",
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]
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prefill_args += cls.transfer_backend + cls.rdma_devices
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cls.process_prefill = popen_launch_pd_server(
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cls.model,
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cls.prefill_url,
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timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
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other_args=prefill_args,
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)
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@classmethod
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def start_decode(cls):
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decode_args = [
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"--trust-remote-code",
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"--disaggregation-mode",
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"decode",
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"--disaggregation-bootstrap-port",
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cls.bootstrap_port,
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"--tp",
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"4",
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"--base-gpu-id",
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"4",
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"--enable-metrics",
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"--enable-request-time-stats-logging",
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]
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decode_args += cls.transfer_backend + cls.rdma_devices
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cls.process_decode = popen_launch_pd_server(
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cls.model,
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cls.decode_url,
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timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
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other_args=decode_args,
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)
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def test_gsm8k(self):
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args = SimpleNamespace(
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base_url=self.base_url,
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model=self.model,
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eval_name="gsm8k",
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api="completion",
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max_tokens=512,
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num_examples=200,
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num_threads=128,
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)
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metrics = run_eval(args)
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print(f"Evaluation metrics: {metrics}")
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self.assertGreater(metrics["score"], 0.60)
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class TestDisaggregationMooncakeMHAPrefillLargerTP(PDDisaggregationServerBase):
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@classmethod
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def setUpClass(cls):
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super().setUpClass()
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# Temporarily disable JIT DeepGEMM
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envs.SGLANG_ENABLE_JIT_DEEPGEMM.set(False)
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cls.model = try_cached_model(DEFAULT_MODEL_NAME_FOR_TEST)
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# Non blocking start servers
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cls.start_prefill()
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cls.start_decode()
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# Block until both
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cls.wait_server_ready(cls.prefill_url + "/health", process=cls.process_prefill)
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cls.wait_server_ready(cls.decode_url + "/health", process=cls.process_decode)
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cls.launch_lb()
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@classmethod
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def start_prefill(cls):
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prefill_args = [
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"--trust-remote-code",
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"--disaggregation-mode",
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"prefill",
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"--disaggregation-bootstrap-port",
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cls.bootstrap_port,
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"--tp",
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"4",
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"--enable-metrics",
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"--enable-request-time-stats-logging",
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]
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prefill_args += cls.transfer_backend + cls.rdma_devices
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cls.process_prefill = popen_launch_pd_server(
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cls.model,
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cls.prefill_url,
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timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
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other_args=prefill_args,
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)
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@classmethod
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def start_decode(cls):
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decode_args = [
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"--trust-remote-code",
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"--disaggregation-mode",
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"decode",
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"--disaggregation-bootstrap-port",
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cls.bootstrap_port,
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"--tp",
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"2",
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"--base-gpu-id",
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"4",
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"--enable-metrics",
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"--enable-request-time-stats-logging",
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]
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decode_args += cls.transfer_backend + cls.rdma_devices
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cls.process_decode = popen_launch_pd_server(
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cls.model,
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cls.decode_url,
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timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
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other_args=decode_args,
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)
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def test_gsm8k(self):
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args = SimpleNamespace(
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base_url=self.base_url,
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model=self.model,
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eval_name="gsm8k",
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api="completion",
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max_tokens=512,
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num_examples=200,
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num_threads=128,
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)
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metrics = run_eval(args)
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print(f"Evaluation metrics: {metrics}")
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self.assertGreater(metrics["score"], 0.60)
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class TestDisaggregationMooncakeMHADecodeLargerTP(PDDisaggregationServerBase):
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@classmethod
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def setUpClass(cls):
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super().setUpClass()
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# Temporarily disable JIT DeepGEMM
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envs.SGLANG_ENABLE_JIT_DEEPGEMM.set(False)
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cls.model = try_cached_model(DEFAULT_MODEL_NAME_FOR_TEST)
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# Non blocking start servers
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cls.start_prefill()
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cls.start_decode()
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# Block until both
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cls.wait_server_ready(cls.prefill_url + "/health", process=cls.process_prefill)
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cls.wait_server_ready(cls.decode_url + "/health", process=cls.process_decode)
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cls.launch_lb()
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@classmethod
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def start_prefill(cls):
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prefill_args = [
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"--trust-remote-code",
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"--disaggregation-mode",
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"prefill",
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"--disaggregation-bootstrap-port",
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cls.bootstrap_port,
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"--tp",
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"2",
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"--enable-metrics",
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"--enable-request-time-stats-logging",
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]
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prefill_args += cls.transfer_backend + cls.rdma_devices
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cls.process_prefill = popen_launch_pd_server(
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cls.model,
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cls.prefill_url,
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timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
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other_args=prefill_args,
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)
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@classmethod
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def start_decode(cls):
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decode_args = [
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"--trust-remote-code",
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"--disaggregation-mode",
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"decode",
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"--disaggregation-bootstrap-port",
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cls.bootstrap_port,
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"--tp",
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"4",
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"--base-gpu-id",
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"4",
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"--enable-metrics",
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"--enable-request-time-stats-logging",
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]
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decode_args += cls.transfer_backend + cls.rdma_devices
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cls.process_decode = popen_launch_pd_server(
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cls.model,
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cls.decode_url,
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timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
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other_args=decode_args,
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)
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def test_gsm8k(self):
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args = SimpleNamespace(
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base_url=self.base_url,
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model=self.model,
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eval_name="gsm8k",
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api="completion",
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max_tokens=512,
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num_examples=200,
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num_threads=128,
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)
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metrics = run_eval(args)
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print(f"Evaluation metrics: {metrics}")
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self.assertGreater(metrics["score"], 0.60)
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STAGING_ENV = {
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"SGLANG_DISAGG_STAGING_BUFFER": "1",
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"SGLANG_DISAGG_STAGING_BUFFER_SIZE_MB": "64",
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"SGLANG_DISAGG_STAGING_POOL_SIZE_MB": "1024",
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}
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class TestDisaggregationStagingPrefillLargerTP(PDDisaggregationServerBase):
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"""Prefill TP=4 -> Decode TP=2 with staging buffer enabled (MHA model)."""
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@classmethod
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def setUpClass(cls):
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super().setUpClass()
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envs.SGLANG_ENABLE_JIT_DEEPGEMM.set(False)
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cls.model = try_cached_model(DEFAULT_MODEL_NAME_FOR_TEST)
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cls.start_prefill()
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cls.start_decode()
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cls.wait_server_ready(cls.prefill_url + "/health", process=cls.process_prefill)
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cls.wait_server_ready(cls.decode_url + "/health", process=cls.process_decode)
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cls.launch_lb()
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@classmethod
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def start_prefill(cls):
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prefill_args = [
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"--trust-remote-code",
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"--disaggregation-mode",
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"prefill",
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"--disaggregation-bootstrap-port",
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cls.bootstrap_port,
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"--tp",
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"4",
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"--enable-metrics",
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"--enable-request-time-stats-logging",
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]
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prefill_args += cls.transfer_backend + cls.rdma_devices
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env = {**os.environ, **STAGING_ENV}
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cls.process_prefill = popen_launch_pd_server(
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cls.model,
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cls.prefill_url,
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timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
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other_args=prefill_args,
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env=env,
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)
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@classmethod
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def start_decode(cls):
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decode_args = [
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"--trust-remote-code",
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"--disaggregation-mode",
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"decode",
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"--disaggregation-bootstrap-port",
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cls.bootstrap_port,
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"--tp",
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"2",
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"--base-gpu-id",
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"4",
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"--enable-metrics",
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"--enable-request-time-stats-logging",
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]
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decode_args += cls.transfer_backend + cls.rdma_devices
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env = {**os.environ, **STAGING_ENV}
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cls.process_decode = popen_launch_pd_server(
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cls.model,
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cls.decode_url,
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timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
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other_args=decode_args,
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env=env,
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)
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def test_gsm8k(self):
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args = SimpleNamespace(
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base_url=self.base_url,
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model=self.model,
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eval_name="gsm8k",
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api="completion",
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max_tokens=512,
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num_examples=200,
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num_threads=128,
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)
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metrics = run_eval(args)
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print(f"[Staging PrefillLargerTP] Evaluation metrics: {metrics}")
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self.assertGreater(metrics["score"], 0.60)
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class TestDisaggregationStagingDecodeLargerTP(PDDisaggregationServerBase):
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"""Prefill TP=2 -> Decode TP=4 with staging buffer enabled (MHA model)."""
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@classmethod
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def setUpClass(cls):
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super().setUpClass()
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envs.SGLANG_ENABLE_JIT_DEEPGEMM.set(False)
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cls.model = try_cached_model(DEFAULT_MODEL_NAME_FOR_TEST)
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cls.start_prefill()
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cls.start_decode()
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cls.wait_server_ready(cls.prefill_url + "/health", process=cls.process_prefill)
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cls.wait_server_ready(cls.decode_url + "/health", process=cls.process_decode)
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cls.launch_lb()
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@classmethod
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def start_prefill(cls):
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prefill_args = [
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"--trust-remote-code",
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"--disaggregation-mode",
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"prefill",
|
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"--disaggregation-bootstrap-port",
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cls.bootstrap_port,
|
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"--tp",
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"2",
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"--enable-metrics",
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"--enable-request-time-stats-logging",
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]
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prefill_args += cls.transfer_backend + cls.rdma_devices
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env = {**os.environ, **STAGING_ENV}
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cls.process_prefill = popen_launch_pd_server(
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cls.model,
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cls.prefill_url,
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timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
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other_args=prefill_args,
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env=env,
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)
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@classmethod
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def start_decode(cls):
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decode_args = [
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"--trust-remote-code",
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"--disaggregation-mode",
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"decode",
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"--disaggregation-bootstrap-port",
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cls.bootstrap_port,
|
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"--tp",
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"4",
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"--base-gpu-id",
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"4",
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"--enable-metrics",
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"--enable-request-time-stats-logging",
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]
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decode_args += cls.transfer_backend + cls.rdma_devices
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env = {**os.environ, **STAGING_ENV}
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cls.process_decode = popen_launch_pd_server(
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cls.model,
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cls.decode_url,
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timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
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other_args=decode_args,
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env=env,
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)
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def test_gsm8k(self):
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args = SimpleNamespace(
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base_url=self.base_url,
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model=self.model,
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eval_name="gsm8k",
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api="completion",
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max_tokens=512,
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num_examples=200,
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num_threads=128,
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)
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metrics = run_eval(args)
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print(f"[Staging DecodeLargerTP] Evaluation metrics: {metrics}")
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self.assertGreater(metrics["score"], 0.60)
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|
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class TestDisaggregationGDNHybridHeteroTP(PDDisaggregationServerBase):
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"""Prefill TP=1 -> Decode TP=4 on a GDN-hybrid (gated-delta-net) model.
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Exercises the heterogeneous attn-TP *scatter* path (prefill attn_tp <
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decode attn_tp), where two independent bugs corrupt accuracy without the
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fix in this change set:
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1. GDN conv_state is cat([query|key|value]) with each sub-block
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independently head-sharded; a single contiguous slice straddles the
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q/k/v boundaries and delivers wrong channels.
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2. GQA KV heads are replicated when num_key_value_heads < decode attn_tp;
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the scatter head map must use integer division (tp_rank //
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num_kv_head_replicas), not modulo.
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Without the fix gsm8k collapses (~0.4); with it, it recovers to agg level.
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"""
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@classmethod
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def setUpClass(cls):
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super().setUpClass()
|
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envs.SGLANG_ENABLE_JIT_DEEPGEMM.set(False)
|
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cls.model = try_cached_model(DEFAULT_HYBRID_GDN_SMALL_MODEL_NAME_FOR_TEST)
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cls.start_prefill()
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cls.start_decode()
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cls.wait_server_ready(cls.prefill_url + "/health", process=cls.process_prefill)
|
|
cls.wait_server_ready(cls.decode_url + "/health", process=cls.process_decode)
|
|
|
|
cls.launch_lb()
|
|
|
|
@classmethod
|
|
def start_prefill(cls):
|
|
prefill_args = [
|
|
"--trust-remote-code",
|
|
"--disaggregation-mode",
|
|
"prefill",
|
|
"--disaggregation-bootstrap-port",
|
|
cls.bootstrap_port,
|
|
"--tp",
|
|
"1",
|
|
"--enable-metrics",
|
|
"--enable-request-time-stats-logging",
|
|
]
|
|
prefill_args += cls.transfer_backend + cls.rdma_devices
|
|
cls.process_prefill = popen_launch_pd_server(
|
|
cls.model,
|
|
cls.prefill_url,
|
|
timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
|
|
other_args=prefill_args,
|
|
)
|
|
|
|
@classmethod
|
|
def start_decode(cls):
|
|
decode_args = [
|
|
"--trust-remote-code",
|
|
"--disaggregation-mode",
|
|
"decode",
|
|
"--disaggregation-bootstrap-port",
|
|
cls.bootstrap_port,
|
|
"--tp",
|
|
"4",
|
|
"--base-gpu-id",
|
|
"4",
|
|
"--enable-metrics",
|
|
"--enable-request-time-stats-logging",
|
|
]
|
|
decode_args += cls.transfer_backend + cls.rdma_devices
|
|
cls.process_decode = popen_launch_pd_server(
|
|
cls.model,
|
|
cls.decode_url,
|
|
timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
|
|
other_args=decode_args,
|
|
)
|
|
|
|
def test_gsm8k(self):
|
|
args = SimpleNamespace(
|
|
base_url=self.base_url,
|
|
model=self.model,
|
|
eval_name="gsm8k",
|
|
api="completion",
|
|
max_tokens=512,
|
|
num_examples=200,
|
|
num_threads=128,
|
|
)
|
|
metrics = run_eval(args)
|
|
print(f"[GDNHybridHeteroTP] Evaluation metrics: {metrics}")
|
|
self.assertGreater(metrics["score"], 0.60)
|
|
|
|
|
|
if __name__ == "__main__":
|
|
unittest.main()
|