[ENH] Add support for TimesFM

[benHeid]

Support for TimesFM, the time series foundation model from google research:

• https://github.com/google-research/timesfm?tab=readme-ov-file

[fkiraly]

added it to the list here: #6177

One of these days, we should perhaps create our own?

[geetu040]

I have a question: What is the right way to implement this interface?

1. add the package timesfm as a dependency to sktime and create the interface on top of that?
2. repeat the model implementation using the same libraries and code that is in the actual source? - that will put jax and related libraries as new dependencies in sktime
3. convert the model code from jax to pytorch and build an interface on top of the pytorch adapter in sktime?

[benHeid]

I would prefer option 1 if possible. If this is not possible we can discuss in more detailed how to proceed

[julian-fong]

@fkiraly @geetu040 @benHeid Just pinging to confirm whether or not this item is picked up yet.

I would like to pick this issue up and create an interface for TimesFM

[geetu040]

@julian-fong did you start working on this? I was also planning to do so. If you are busy with something else as well, I can take this up.

[geetu040]

@fkiraly There are a few things with TimesFM

• it also uses freq, should we deal with it the same way we dealt with NeuralForecast in [ENH] NeuralForecastRNN should auto-detect freq #6039
• it has no training interface - it can only do zero-shot forecasting on a pre-trained model, should we keep it that way?
• user can provide device as an argument like "cpu", "gpu" or "tpu" - should we give this option as a parameter to this interface as well?

[fkiraly]

it also uses freq, should we deal with it the same way we dealt with NeuralForecast

You mean, as mandatory arg?
Yes, that might be a good idea - if it is the same logic, it might be worth moving it to a common or an adapter module.

it has no training interface - it can only do zero-shot forecasting on a pre-trained model, should we keep it that way?

No context or fine-tuning? That is odd for an FM, but if it is so, then fit is simply empty.

user can provide device as an argument like "cpu", "gpu" or "tpu" - should we give this option as a parameter to this interface as well?

Why not?

[geetu040]

Why not?

I have tried this on linux and things are working fine - but I have seen people raise issues and also discussed this with @julian-fong that there can be possible failures on windows and mac, especially when device is set to "gpu"

it might be worth moving it to a common or an adapter module.

sure, I'll look into that

[geetu040]

@fkiraly this might be blocking - TimesFM does not work for all python versions, how do we handle that?

[julian-fong]

From my understanding - the package timesfm does not work on windows and mac because the required package lingvo is not available. Threads detailing the errors can be found here google-research/timesfm#1 and google-research/timesfm#24

[geetu040]

It works on colab but when I try to debug locally (ubuntu) I run from one error to another

---

On installation, gives this error if python>=3.11

ERROR: Could not find a version that satisfies the requirement lingvo==0.12.7 (from paxml) (from versions: none)
ERROR: No matching distribution found for lingvo==0.12.7

---

On python<=3.10 when you try to debug or try creating completely new conda env from .yml file and running the code gives these different errors

1

 1 leaked semaphore objects to clean up at shutdown
  warnings.warn('resource_tracker: There appear to be %d '

2

2024-06-06 17:16:08.597909: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcudart.so.11.0'; dlerror: libcudart.so.11.0: cannot open shared object file: No such file or directory
Segmentation fault (core dumped)

3

  File "/home/geetu/miniconda3/envs/310/lib/python3.10/asyncio/locks.py", line 234, in __init__
    raise ValueError("loop argument must agree with lock")
ValueError: loop argument must agree with lock

[fkiraly]

I start wondering whether anyone anywhere has succeeded in getting this to run?

[geetu040]

well it works with no error, no warning on google colab - I have tried to mimic the library versions of jax, jaxlib and tf from colab, all in vain. It seems to really depend on the hardware other than just libraries

[fkiraly]

maybe that's just google's way to try getting everyone to use colab 😁

[geetu040]

Extending the above comment #6408 (comment)

Once the library is installed on python<=3.10 the stated errors are raised on this simple code snippet from the official documentation.

import timesfm

tfm = timesfm.TimesFm(
    context_len=<context>,
    horizon_len=<horizon>,
    input_patch_len=32,
    output_patch_len=128,
    num_layers=20,
    model_dims=1280,
    backend=<backend>,
)
tfm.load_from_checkpoint(repo_id="google/timesfm-1.0-200m")