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test_profiler.py 3.0 kB

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  1. # -*- coding: utf-8 -*-
  2. import json
  3. import os
  4. import tempfile
  5. import pytest
  6. from megengine import Parameter
  7. from megengine import distributed as dist
  8. from megengine import tensor
  9. from megengine.jit import trace
  10. from megengine.module import Module
  11. from megengine.utils.profiler import Profiler, scope
  12. class Simple(Module):
  13. def __init__(self):
  14. super().__init__()
  15. self.a = Parameter([1.23], dtype="float32")
  16. def forward(self, x):
  17. x = x * self.a
  18. return x
  19. @pytest.mark.parametrize("format", ["chrome_timeline.json", "memory_flow.svg"])
  20. @pytest.mark.parametrize(
  21. "trace_mode", [True, False, None], ids=["symbolic", "no-symbolic", "no-trace"]
  22. )
  23. @pytest.mark.require_ngpu(1)
  24. def test_profiler(format, trace_mode):
  25. tempdir = tempfile.TemporaryDirectory()
  26. profile_prefix = tempdir.name
  27. profile_path = os.path.join(profile_prefix, "{}.{}".format(os.getpid(), format))
  28. def infer():
  29. with scope("my_scope"):
  30. oup = Simple()(tensor([1.23], dtype="float32"))
  31. return oup
  32. if trace_mode:
  33. infer = trace(symbolic=trace_mode)(infer)
  34. with Profiler(profile_prefix, format=format):
  35. infer()
  36. assert os.path.exists(profile_path), "profiling results not found"
  37. if format == "chrome_timeline.json":
  38. with open(profile_path, "r") as f:
  39. events = json.load(f)
  40. if isinstance(events, dict):
  41. assert "traceEvents" in events
  42. events = events["traceEvents"]
  43. prev_ts = {}
  44. scope_count = 0
  45. for event in events:
  46. if "dur" in event:
  47. assert event["dur"] >= 0
  48. elif "ts" in event and "tid" in event:
  49. ts = event["ts"]
  50. tid = event["tid"]
  51. if ts != 0:
  52. assert (tid not in prev_ts) or prev_ts[tid] <= ts
  53. prev_ts[tid] = ts
  54. if "name" in event and event["name"] == "my_scope":
  55. scope_count += 1
  56. assert scope_count > 0 and scope_count % 2 == 0
  57. @pytest.mark.parametrize("format", ["chrome_timeline.json", "memory_flow.svg"])
  58. @pytest.mark.parametrize(
  59. "trace_mode", [True, False, None], ids=["symbolic", "no-symbolic", "no-trace"]
  60. )
  61. @pytest.mark.isolated_distributed
  62. @pytest.mark.require_ngpu(2)
  63. def test_profiler_dist(format, trace_mode):
  64. n_gpus = 2
  65. tempdir = tempfile.TemporaryDirectory()
  66. profile_prefix = tempdir.name
  67. profile_path = os.path.join(profile_prefix, "{}.{}".format(os.getpid(), format))
  68. def infer():
  69. with scope("my_scope"):
  70. oup = Simple()(tensor([1.23], dtype="float32"))
  71. return oup
  72. if trace_mode:
  73. infer = trace(symbolic=trace_mode)(infer)
  74. @dist.launcher(n_gpus=2)
  75. def worker():
  76. infer()
  77. with Profiler(profile_prefix, format=format):
  78. worker()
  79. assert os.path.exists(profile_path), "profiling results not found"
  80. assert len(os.listdir(tempdir.name)) == n_gpus + 1