torch/csrc/profiler/README.md - stubs, RecordFunction, Autograd interaction #108470
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Technical details about the profiler. [ghstack-poisoned]
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Technical details about the profiler. ghstack-source-id: 1a8123894b5fe4237e33a97eb884d3a2312371b8 Pull Request resolved: #108470
Technical details about the profiler. [ghstack-poisoned]
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Technical details about the profiler. ghstack-source-id: 3a69bad5dac53f14d2b2ed84c184b79d63d0f301 Pull Request resolved: #108470
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@davidberard98 Thanks for putting this readme together. Is this PR currently a WIP or are you planning to commit it as is? |
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@anupambhatnagar I was planning to land it as is - not sure I have a good enough understanding of the other parts to write about them clearly right now. |
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torch/csrc/profiler/README.md
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| The profiler instruments PyTorch to collect information about the model's execution. Its main features are: | ||
| * Instrumenting op calls on the CPU side | ||
| * Interfacing with [Kineto](https://github.com/pytorch/kineto/) to collect information from the GPU (or other accelerators) | ||
| * Collecting python stacktraces |
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| * Collecting python stacktraces | |
| * Collecting python stack traces |
torch/csrc/profiler/README.md
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| RecordFunction is used by the profiler to instrument CPU-side events. | ||
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| RecordFunction is a general method of instrumenting function calls in pytorch. It can be used for other general applications, e.g. see [Features for Large-Scale Deployments](https://pytorch.org/docs/stable/notes/large_scale_deployments.html). In PyTorch, it is already included at some important locations; notably, in the [dispatcher](https://github.com/pytorch/pytorch/blob/247c603da9b780534e25fb1d90b6e5a528b625b1/aten/src/ATen/core/dispatch/Dispatcher.h#L650), surrounding every op. |
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| RecordFunction is a general method of instrumenting function calls in pytorch. It can be used for other general applications, e.g. see [Features for Large-Scale Deployments](https://pytorch.org/docs/stable/notes/large_scale_deployments.html). In PyTorch, it is already included at some important locations; notably, in the [dispatcher](https://github.com/pytorch/pytorch/blob/247c603da9b780534e25fb1d90b6e5a528b625b1/aten/src/ATen/core/dispatch/Dispatcher.h#L650), surrounding every op. | |
| RecordFunction is a general method of instrumenting function calls in PyTorch. It can be used for other general applications, e.g. see [Features for Large-Scale Deployments](https://pytorch.org/docs/stable/notes/large_scale_deployments.html). In PyTorch, it is already included at some important locations; notably, in the [dispatcher](https://github.com/pytorch/pytorch/blob/247c603da9b780534e25fb1d90b6e5a528b625b1/aten/src/ATen/core/dispatch/Dispatcher.h#L650), surrounding every op. |
torch/csrc/profiler/README.md
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| RecordFunction is a general method of instrumenting function calls in pytorch. It can be used for other general applications, e.g. see [Features for Large-Scale Deployments](https://pytorch.org/docs/stable/notes/large_scale_deployments.html). In PyTorch, it is already included at some important locations; notably, in the [dispatcher](https://github.com/pytorch/pytorch/blob/247c603da9b780534e25fb1d90b6e5a528b625b1/aten/src/ATen/core/dispatch/Dispatcher.h#L650), surrounding every op. | ||
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| Users (or PyTorch itself) can register callbacks that will be executed whenever a RecordFunction guard is encountered. The profiler uses this mechanism to record the start and end times for each op call, as well as user-provided RecordFunction anntations. The RecordFunction machinery is designed to have relatively low overhead, especially when there are no callbacks registered. Nevertheless, there can still be some overhead. |
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| Users (or PyTorch itself) can register callbacks that will be executed whenever a RecordFunction guard is encountered. The profiler uses this mechanism to record the start and end times for each op call, as well as user-provided RecordFunction anntations. The RecordFunction machinery is designed to have relatively low overhead, especially when there are no callbacks registered. Nevertheless, there can still be some overhead. | |
| Users (or PyTorch itself) can register callbacks that will be executed whenever a RecordFunction guard is encountered. The profiler uses this mechanism to record the start and end times for each op call, as well as user-provided RecordFunction annotations. The RecordFunction machinery is designed to have relatively low overhead, especially when there are no callbacks registered. Nevertheless, there can still be some overhead. |
…ograd interaction" Technical details about the profiler - stubs for the stuff I haven't had time to fill out yet, plus details about RecordFunction and the profiler's interaction with autograd. reviewers - see https://github.com/pytorch/pytorch/blob/06c41eea9e37b5799e4f14601c95fa7810297759/torch/csrc/profiler/README.md for rendered markdown [ghstack-poisoned]
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Technical details about the profiler. ghstack-source-id: 3b9d5a61170fd9c493a3a51d72fbfca462c2f376 Pull Request resolved: #108470
…ograd interaction" Technical details about the profiler - stubs for the stuff I haven't had time to fill out yet, plus details about RecordFunction and the profiler's interaction with autograd. reviewers - see https://github.com/pytorch/pytorch/blob/06c41eea9e37b5799e4f14601c95fa7810297759/torch/csrc/profiler/README.md for rendered markdown [ghstack-poisoned]
davidberard98
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Technical details about the profiler. ghstack-source-id: 100a8391c96b0fb76f078ad859fe2a4e74cbb17e Pull Request resolved: #108470
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@pytorchbot merge |
Merge startedYour change will be merged once all checks pass (ETA 0-4 Hours). Learn more about merging in the wiki. Questions? Feedback? Please reach out to the PyTorch DevX Team |
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Stack from ghstack (oldest at bottom):
Technical details about the profiler - stubs for the stuff I haven't had time to fill out yet, plus details about RecordFunction and the profiler's interaction with autograd.
reviewers - see https://github.com/pytorch/pytorch/blob/06c41eea9e37b5799e4f14601c95fa7810297759/torch/csrc/profiler/README.md for rendered markdown