In order to initialize runtime env concurrently, this PR makes pip runtime env asynchronous. It includes,
- [x] New `check_output_cmd` in runtime env utils.
- [x] Async PipProcessor.
- [x] The `asynccontextmanager` from `https://github.com/python-trio/async_generator` for Python 3.6
- [x] Remove pip runtime env lock.
- [x] Disable pip cache.
Co-authored-by: 刘宝 <po.lb@antfin.com>
When we vendor third-party code, we should update LICENSE file. Previously we vendored two pieces of code:
- conda utilities from MLflow
- virtualenv-clone
But we only included the attribution in the relevant source files, not in our LICENSE file. This PR adds the necessary info to our LICENSE file.
* added ars
* functioning ars with regression test
* added regression tests for ARs
* fixed default config for ARS
* ARS code runs, now time to test
* ARS working and tested, changed std deviation of meanstd filter to initialize to 1
* ARS working and tested, changed std deviation of meanstd filter to initialize to 1
* pep8 fixes
* removed unused linear model
* address comments
* more fixing comments
* post yapf
* fixed support failure
* Update LICENSE
* Update policies.py
* Update test_supported_spaces.py
* Update policies.py
* Update LICENSE
* Update test_supported_spaces.py
* Update policies.py
* Update policies.py
* Update filter.py
Rename AsyncSamplesOptimizer -> AsyncReplayOptimizer
Add AsyncSamplesOptimizer that implements the IMPALA architecture
integrate V-trace with a3c policy graph
audit V-trace integration
benchmark compare vs A3C and with V-trace on/off
PongNoFrameskip-v4 on IMPALA scaling from 16 to 128 workers, solving Pong in <10 min. For reference, solving this env takes ~40 minutes for Ape-X and several hours for A3C.
