This PR adds standalone_compile API that does precompilation via caching to support vLLM use case in the short term while we work on the longer term precompilation solution.
```
standalone_compile(gm, example_inputs, options) -> CompiledArtifact
CompiledArtifact.save(path, format: binary|unpacked = binary)
CompiledArtifact.load(path, format: binary|unpacked = binary)
```
Pull Request resolved: https://github.com/pytorch/pytorch/pull/150670
Approved by: https://github.com/jamesjwu, https://github.com/zou3519
This PR adds standalone_compile API that does precompilation via caching to support vLLM use case in the short term while we work on the longer term precompilation solution.
```
standalone_compile(gm, example_inputs, options) -> CompiledArtifact
CompiledArtifact.save(path, format: binary|unpacked = binary)
CompiledArtifact.load(path, format: binary|unpacked = binary)
```
Pull Request resolved: https://github.com/pytorch/pytorch/pull/150670
Approved by: https://github.com/jamesjwu, https://github.com/zou3519
This PR adds standalone_compile API that does precompilation via caching to support vLLM use case in the short term while we work on the longer term precompilation solution.
```
standalone_compile(gm, example_inputs, options) -> CompiledArtifact
CompiledArtifact.save(path, format: binary|unpacked = binary)
CompiledArtifact.load(path, format: binary|unpacked = binary)
```
Pull Request resolved: https://github.com/pytorch/pytorch/pull/150670
Approved by: https://github.com/jamesjwu, https://github.com/zou3519
While using save_cache_artifacts on internal workloads, we have noticed that repeatedly calling this function after every batch is incredibly expensive. This PR significantly speeds up this function call by opting out of pickle and redesigning serialization algorithm.
Essentially what we want is to be able to call serialize many times without incurring costs from scratch.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/148227
Approved by: https://github.com/jamesjwu
ghstack dependencies: #148226
This PR essentially introduces two new APIs
* torch.compiler.save_cache_artifacts
* torch.compiler.load_cache_artifacts
which aim to create a mega cache experience where the user can start collecting cache artifacts, and later call the save API to fetch them. In the next attempt, the user can "hot load" the cache artifacts via the load function.
This bundling approach reduces the need to rely on porting individual files one by one, or relying on many network requests.
Note that these APIs CANNOT log to structured logging as these functions will be called before and after compilation, as opposed to during compilation. Due to this limitation, the API returns a struct that the user can log with.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/143341
Approved by: https://github.com/jansel
