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Adding Chronos-2 as a new pipeline on Orion

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@abaranov25 seems like Chronos2 pipeline did not work well on S-1 example, do you have an idea why? I'm curious if you use S-1-test would you get different results?

},
"mlstars.custom.timeseries_preprocessing.rolling_window_sequences#1": {
"target_column": 0,
"window_size": 256
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I'm curious why 256? Orion pipelines that are forecast based are usually set to 250. For timesfm, it was set to 256 because it needs to be a multiple of 32 according to their docs.

"init_params": {
"mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1": {
"time_column": "timestamp",
"interval": 600,
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We typically set the example to interval=21600 since our example code uses NASA signals (MSL and SMAP)

Comment on lines +16 to +22
# if sys.version_info < (3, 11):
# msg = (
# '`timesfm` requires Python >= 3.11 and your '
# f'python version is {sys.version}.\n'
# 'Make sure you are using Python 3.11 or later.\n'
# )
# raise RuntimeError(msg)
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If chronos works on python 3.9+ remove this comment completely

# raise RuntimeError(msg)

try:
from chronos import Chronos2Pipeline
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add chronos to setup.py under the pretrained_requires section, then remove the try-catch since it will always be installed using pip install orion[pretrained]

Comment on lines +131 to +136
if __name__ == "__main__":
chronos2 = Chronos2()
X = np.random.rand(100, 256, 10)
y = chronos2.predict(X)
print(y.shape)
print(y) No newline at end of file
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3 participants