207 lines
6.1 KiB
Python
207 lines
6.1 KiB
Python
import os
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import tempfile
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import time
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import unittest
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from pathlib import Path
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import requests
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import torch
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import torch.distributed as dist
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import torch.multiprocessing as mp
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from sglang.test.ci.ci_register import register_amd_ci, register_cuda_ci
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from sglang.test.test_utils import CustomTestCase
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register_cuda_ci(est_time=30, suite="nightly-2-gpu", nightly=True)
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register_amd_ci(est_time=60, suite="nightly-amd", nightly=True)
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class TestDumperPureFunctions(CustomTestCase):
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def test_get_truncated_value(self):
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from sglang.srt.debug_utils.dumper import get_truncated_value
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self.assertIsNone(get_truncated_value(None))
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self.assertEqual(get_truncated_value(42), 42)
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self.assertEqual(
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len(get_truncated_value((torch.randn(10), torch.randn(20)))), 2
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)
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self.assertEqual(get_truncated_value(torch.randn(10, 10)).shape, (10, 10))
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self.assertEqual(get_truncated_value(torch.randn(100, 100)).shape, (5, 5))
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def test_obj_to_dict(self):
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from sglang.srt.debug_utils.dumper import _obj_to_dict
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self.assertEqual(_obj_to_dict({"a": 1}), {"a": 1})
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class Obj:
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x, y = 10, 20
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def method(self):
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pass
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result = _obj_to_dict(Obj())
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self.assertEqual(result["x"], 10)
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self.assertNotIn("method", result)
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def test_get_tensor_info(self):
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from sglang.srt.debug_utils.dumper import get_tensor_info
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info = get_tensor_info(torch.randn(10, 10))
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for key in ["shape=", "dtype=", "min=", "max=", "mean="]:
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self.assertIn(key, info)
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self.assertIn("value=42", get_tensor_info(42))
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self.assertIn("min=None", get_tensor_info(torch.tensor([])))
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class TestDumperDistributed(CustomTestCase):
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def test_basic(self):
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with tempfile.TemporaryDirectory(prefix="test_dumper_") as tmpdir:
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_run_distributed_test(_test_basic_func, tmpdir=tmpdir)
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def test_http_enable(self):
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_run_distributed_test(_test_http_func)
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def test_filter(self):
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with tempfile.TemporaryDirectory(prefix="test_dumper_") as tmpdir:
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_run_distributed_test(_test_filter_func, tmpdir=tmpdir)
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def test_write_disabled(self):
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with tempfile.TemporaryDirectory(prefix="test_dumper_") as tmpdir:
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_run_distributed_test(_test_write_disabled_func, tmpdir=tmpdir)
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def _test_basic_func(rank, tmpdir):
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os.environ["SGLANG_DUMPER_DIR"] = tmpdir
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from sglang.srt.debug_utils.dumper import dumper
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tensor = torch.randn(10, 10, device=f"cuda:{rank}")
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dumper.on_forward_pass_start()
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dumper.dump("tensor_a", tensor, arg=100)
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dumper.on_forward_pass_start()
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dumper.set_ctx(ctx_arg=200)
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dumper.dump("tensor_b", tensor)
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dumper.set_ctx(ctx_arg=None)
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dumper.on_forward_pass_start()
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dumper.override_enable(False)
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dumper.dump("tensor_skip", tensor)
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dumper.override_enable(True)
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dumper.on_forward_pass_start()
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dumper.dump_dict("obj", {"a": torch.randn(3, device=f"cuda:{rank}"), "b": 42})
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dist.barrier()
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filenames = _get_filenames(tmpdir)
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_assert_files(
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filenames,
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exist=["tensor_a", "tensor_b", "arg=100", "ctx_arg=200", "obj_a", "obj_b"],
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not_exist=["tensor_skip"],
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)
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def _test_http_func(rank):
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os.environ["SGLANG_DUMPER_ENABLE"] = "0"
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from sglang.srt.debug_utils.dumper import dumper
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assert not dumper._enable
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dumper.on_forward_pass_start()
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for enable in [True, False]:
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dist.barrier()
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if rank == 0:
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time.sleep(0.1)
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requests.post(
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"http://localhost:40000/dumper", json={"enable": enable}
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).raise_for_status()
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dist.barrier()
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assert dumper._enable == enable
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def _test_filter_func(rank, tmpdir):
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os.environ["SGLANG_DUMPER_DIR"] = tmpdir
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os.environ["SGLANG_DUMPER_FILTER"] = "keep"
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from sglang.srt.debug_utils.dumper import dumper
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dumper.on_forward_pass_start()
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dumper.dump("keep_this", torch.randn(5, device=f"cuda:{rank}"))
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dumper.dump("skip_this", torch.randn(5, device=f"cuda:{rank}"))
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dist.barrier()
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filenames = _get_filenames(tmpdir)
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_assert_files(filenames, exist=["keep_this"], not_exist=["skip_this"])
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def _test_write_disabled_func(rank, tmpdir):
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os.environ["SGLANG_DUMPER_DIR"] = tmpdir
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os.environ["SGLANG_DUMPER_WRITE_FILE"] = "0"
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from sglang.srt.debug_utils.dumper import dumper
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dumper.on_forward_pass_start()
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dumper.dump("no_write", torch.randn(5, device=f"cuda:{rank}"))
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dist.barrier()
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assert len(_get_filenames(tmpdir)) == 0
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def _get_filenames(tmpdir):
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return {f.name for f in Path(tmpdir).glob("sglang_dump_*/*.pt")}
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def _assert_files(filenames, *, exist=(), not_exist=()):
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for p in exist:
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assert any(p in f for f in filenames), f"{p} not found in {filenames}"
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for p in not_exist:
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assert not any(
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p in f for f in filenames
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), f"{p} should not exist in {filenames}"
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def _run_distributed_test(func, world_size=2, **kwargs):
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ctx = mp.get_context("spawn")
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result_queue = ctx.Queue()
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processes = []
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for rank in range(world_size):
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p = ctx.Process(
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target=_run_worker, args=(rank, world_size, func, result_queue, kwargs)
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)
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p.start()
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processes.append(p)
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for p in processes:
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p.join()
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errors = [result_queue.get() for _ in range(world_size)]
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errors = [e for e in errors if e]
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if errors:
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raise AssertionError("\n".join(errors))
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def _run_worker(rank, world_size, func, result_queue, kwargs):
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os.environ.update(
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MASTER_ADDR="localhost",
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MASTER_PORT="29500",
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RANK=str(rank),
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WORLD_SIZE=str(world_size),
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)
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torch.cuda.set_device(rank)
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dist.init_process_group(backend="nccl", rank=rank, world_size=world_size)
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try:
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func(rank, **kwargs)
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result_queue.put(None)
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except Exception as e:
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import traceback
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result_queue.put(f"Rank {rank}: {e}\n{traceback.format_exc()}")
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finally:
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dist.destroy_process_group()
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if __name__ == "__main__":
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unittest.main()
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