Caliban

Latest version: v0.4.2

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0.4.1

Small release to archive for JOSS acceptance.

- Move `cloud_sql_proxy` installation before code copy (https://github.com/google/caliban/pull/87)

0.4.0

The biggest feature in this new release is native support for logging to an
MLFlow tracking server using the [UV
Metrics](http://github.com/google/uv-metrics) project.
(https://github.com/google/caliban/pull/35) This feature is in alpha; expect
documentation soon.

More features

- minor bugfixes for GKE (https://github.com/google/caliban/pull/85)
- additional tests for gke.{types, util} (https://github.com/google/caliban/pull/84)
- re-order custom apt packages before pip requirements (https://github.com/google/caliban/pull/82)
- modify base image to our more general cloudbuild naming scheme (https://github.com/google/caliban/pull/80)
- updated `google-auth` dependency version to `1.19.0` (https://github.com/google/caliban/pull/79)
- add clearer contribution info (https://github.com/google/caliban/pull/76)
- Update uv-metrics tutorial (https://github.com/google/caliban/pull/74, https://github.com/google/caliban/pull/72)
- add support for running an embedded cloudsql_proxy (https://github.com/google/caliban/pull/60)
- bugfix for 65: do not add resource maxima when quota is < 1 (67)
- Updated accelerator regions (and globally availabe AI Platform regions to
match the current state here):
https://cloud.google.com/ai-platform/training/docs/regions

0.3.0

- ramasesh Added a fix that prevented `pip` git dependencies from working in
`caliban shell` mode (https://github.com/google/caliban/pull/55) This adds a
small update to the base image, so be sure to run


docker pull gcr.io/blueshift-playground/blueshift:cpu
docker pull gcr.io/blueshift-playground/blueshift:gpu


to get access to this fix.

- Thanks to eschnett, `--docker_run-args` can now deal with arbitrary
whitespace in the list of arguments, instead of single spaces only.
(https://github.com/google/caliban/pull/46)

- Caliban now authenticates AI Platform job submissions using the authentication
provided by `gcloud auth login`, rather than requiring a service account key.
This significantly simplifies the setup required for a first time user.

- `caliban cloud` now checks if the image exists remotely before issuing a
`docker push` command on the newly built image
(https://github.com/google/caliban/pull/36)

- Big internal refactor to make it easier to work on code, increase test
coverage, add new backends (https://github.com/google/caliban/pull/32)

- add `schema` validation for `.calibanconfig.json`. This makes it much easier
to add configuration knobs: https://github.com/google/caliban/pull/37

- Custom base image support (https://github.com/google/caliban/pull/39), thanks
to https://github.com/google/caliban/pull/20 from sagravat.
`.calibanconfig.json` now supports a `"base_image"` key. For the value, can
supply:
- a Docker base image of your own
- a dict of the form `{"cpu": "base_image", "gpu": "base_image"}` with both
entries optional, of course.

Two more cool features.

First, if you use a format string, like `"my_image-{}:latest"`, the format
block `{}` will be filled in with either `cpu` or `gpu`, depending on the mode
Caliban is using.

Second, we now have native support for [Google's Deep Learning
VMs](https://cloud.google.com/ai-platform/deep-learning-vm/docs/introduction)
as base images. The actual VM containers [live
here](https://console.cloud.google.com/gcr/images/deeplearning-platform-release/GLOBAL).
If you provide any of the following strings, Caliban will expand them out to
the actual base image location:


dlvm:pytorch-cpu
dlvm:pytorch-cpu-1.0
dlvm:pytorch-cpu-1.1
dlvm:pytorch-cpu-1.2
dlvm:pytorch-cpu-1.3
dlvm:pytorch-cpu-1.4
dlvm:pytorch-gpu
dlvm:pytorch-gpu-1.0
dlvm:pytorch-gpu-1.1
dlvm:pytorch-gpu-1.2
dlvm:pytorch-gpu-1.3
dlvm:pytorch-gpu-1.4
dlvm:tf-cpu
dlvm:tf-cpu-1.0
dlvm:tf-cpu-1.13
dlvm:tf-cpu-1.14
dlvm:tf-cpu-1.15
dlvm:tf-gpu
dlvm:tf-gpu-1.0
dlvm:tf-gpu-1.13
dlvm:tf-gpu-1.14
dlvm:tf-gpu-1.15
dlvm:tf2-cpu
dlvm:tf2-cpu-2.0
dlvm:tf2-cpu-2.1
dlvm:tf2-cpu-2.2
dlvm:tf2-gpu
dlvm:tf2-gpu-2.0
dlvm:tf2-gpu-2.1
dlvm:tf2-gpu-2.2


Format strings work here as well! So, `"dlvm:pytorch-{}-1.4"` is a totally valid
base image.

0.2.6

- Prepared for a variety of base images by setting up a cloud build matrix:
https://github.com/google/caliban/pull/25
- Added better documentation for `gcloud auth configure-docker`
https://github.com/google/caliban/pull/26
- Added `close()` to `TqdmFile`, preventing an error when piping `stdout`:
https://github.com/google/caliban/pull/30
- `tqdm` progress bars and other interactive outputs now display correctly in
`caliban run` outputs. `stdout` flushes properly! Before these changes,
`stderr` would appear before any `stdout`, making it difficult to store the
logs in a text file. Now, by default, python processes launched by `caliban
run` won't buffer. https://github.com/google/caliban/pull/31

![2020-06-26 09 48 50](https://user-images.githubusercontent.com/69635/85877300-2a3e7300-b794-11ea-9792-4cf3ae5e4263.gif)

0.2.5

- fixes the python binary that caliban notebook points to (now that we use
conda)
- adds DEBIAN_FRONTEND=noninteractive to the apt-get command, so that packages
like texlive won't freeze and wait for you to specify a timezone.

This makes it easy to add, for example, npm and latex support to your caliban
notebook invocations.

0.2.4

- fixes a bug with `parse_region` not handling a lack of default.
- converts the build to Github Actions.
- Rolls Caliban back to requiring only python 3.6 support.
- Removes some unused imports from a few files.

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