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Version 0.15 |
:::important Trains is now ClearML. :::
Trains Agent 0.15.1
Features
- Add Trains Agent Daemon and Services docker files.
Bug Fixes
- Fix initialization wizard (allow at most two verification retries, then print error).
- Add warning on
--gpus
with no detected CUDA version (GitHub trains-agent Issue 24). - Add
agent.force_git_ssh_protocol
configuration option to force all Git links tossh://
(GitHub trains-agent Issue 16). - Add Git user / pass permission into pip package installation from Git repository (GitHub trains-agent Issue 22).
Trains Agent 0.15.0
Features
- Add daemon Services Mode (
daemon --services-mode
), where the daemon spins a task in its own Docker container, and verifies start-up and shut-down. This allows multiple tasks to be launched simultaneously on the same machine (currently in CPU mode only), where each task service will register itself as a worker for the lifetime of the task. - Enhance
build --docker
mode:- Add
--install-globally
option to install required packages in the Docker's system Python. - Add
--entry-point option
to allow automatic task cloning when running the Docker container.
- Add
- Support PyTorch Nightly builds using the
agent.torch_nightly
configuration flag. If true, the agent looks for a nightly build when a stable torch wheel is not found. - Add environment variables support for git user / password:
- Using
TRAINS_AGENT_GIT_USER
/TRAINS_AGENT_GIT_PASS
. - Pass git credentials to dockerized experiment execution.
- Using
- Support running code from module (i.e. -m in execution entry point).
- Add
daemon --create-queue
to automatically create a queue and use it, if the queue name doesn't exist in the server. - Move
--gpus
and--cpu-only
to worker args (used bydaemon
,execute
andbuild
).
Bug Fixes
- Fix init wizard, correctly display the input servers (GitHub Issue #19).
- Improve docker host-mount support, use
TRAINS_AGENT_DOCKER_HOST_MOUNT
environment variable. - Support pip v20.1 local/http package reference in pip freeze.
- Fix detached mode to correctly use cache folder slots.
- Fix
CUDA_VISIBLE_DEVICES
should never be set to "all". - Do not monitor GPU when running with
--cpu-only