mirror of
https://github.com/zebrajr/pytorch.git
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6208c2800e
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/72009
This simplifies the Stats interface by merging IntervalStat and FixedCountStat into a single Stat w/ a specific window size duration and an optional max samples per window. This allows for the original intention of having comparably sized windows (for statistical purposes) while also having a consistent output bandwidth.
Test Plan:
```
buck test //caffe2/test:monitor //caffe2/test/cpp/monitor:monitor
```
Reviewed By: kiukchung
Differential Revision: D33822956
fbshipit-source-id: a74782492421be613a1a8b14341b6fb2e8eeb8b4
(cherry picked from commit 293b94e0b4)
54 lines
1.4 KiB
ReStructuredText
54 lines
1.4 KiB
ReStructuredText
torch.monitor
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=============
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.. warning::
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This module is a prototype release, and its interfaces and functionality may
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change without warning in future PyTorch releases.
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``torch.monitor`` provides an interface for logging events and counters from
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PyTorch.
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The stat interfaces are designed to be used for tracking high level metrics that
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are periodically logged out to be used for monitoring system performance. Since
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the stats aggregate with a specific window size you can log to them from
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critical loops with minimal performance impact.
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For more infrequent events or values such as loss, accuracy, usage tracking the
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event interface can be directly used.
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Event handlers can be registered to handle the events and pass them to an
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external event sink.
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API Reference
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-------------
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.. automodule:: torch.monitor
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.. autoclass:: torch.monitor.Aggregation
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:members:
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.. autoclass:: torch.monitor.Stat
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:members:
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:special-members: __init__
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.. autoclass:: torch.monitor.data_value_t
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:members:
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.. autoclass:: torch.monitor.Event
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:members:
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:special-members: __init__
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.. autoclass:: torch.monitor.EventHandlerHandle
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:members:
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.. autofunction:: torch.monitor.log_event
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.. autofunction:: torch.monitor.register_event_handler
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.. autofunction:: torch.monitor.unregister_event_handler
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.. autoclass:: torch.monitor.TensorboardEventHandler
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:members:
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:special-members: __init__
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