forked from openml/automlbenchmark
-
Notifications
You must be signed in to change notification settings - Fork 4
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
Autogluon timeseries, addressed comments by sebhrusen (#7)
* fixed loading test & train, changed pred.-l. 5->30 * ignore launch.json of vscode * ensuring timestamp parsing * pass config, save pred, add results * remove unused code * add readability, remove slice from timer * ensure autogluonts has required info * add comments for readability * setting defaults for timeseries task * remove outer context manipulation * corrected spelling error for quantiles * adding mape, correct available metrics * beautify config options * fixed config for public access * no outer context manipulation, add dataset subdir * add more datasets * include error raising for too large pred. length. * mergin AutoGluonTS framework folder into AutoGluon * renaming ts.yaml to timeseries.yaml, plus ext. * removing presets, correct latest config for AGTS * move dataset timeseries ext to datasets/file.py * dont bypass test mode * move quantiles and y_past_period_error to opt_cols * remove whitespaces * deleting merge artifacts * delete merge artifacts * renaming prediction_length to forecast_range_in_steps * use public dataset, reduced range to maximum * fix format string works * fix key error bug, remove magic time limit
- Loading branch information
Showing
16 changed files
with
178 additions
and
183 deletions.
There are no files selected for viewing
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Original file line number | Diff line number | Diff line change |
---|---|---|
@@ -0,0 +1,16 @@ | ||
# AutoGluon | ||
|
||
To run v0.5.2: ```python3 ../automlbenchmark/runbenchmark.py autogluon ...``` | ||
|
||
To run mainline: ```python3 ../automlbenchmark/runbenchmark.py autogluonts:latest ...``` | ||
|
||
|
||
# AutoGluonTS | ||
|
||
AutoGluonTS stands for autogluon.timeseries. This framework handles time series problems. | ||
|
||
## Run Steps | ||
|
||
To run v0.5.2: ```python3 ../automlbenchmark/runbenchmark.py autogluonts timeseries ...``` | ||
|
||
To run mainline: ```python3 ../automlbenchmark/runbenchmark.py autogluonts:latest timeseries ...``` |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Original file line number | Diff line number | Diff line change |
---|---|---|
@@ -1,25 +1,53 @@ | ||
from amlb.benchmark import TaskConfig | ||
from amlb.data import Dataset | ||
|
||
from amlb.utils import call_script_in_same_dir | ||
from amlb.benchmark import TaskConfig | ||
from amlb.data import Dataset, DatasetType | ||
from copy import deepcopy | ||
|
||
|
||
def setup(*args, **kwargs): | ||
call_script_in_same_dir(__file__, "setup.sh", *args, **kwargs) | ||
|
||
|
||
def run(dataset: Dataset, config: TaskConfig): | ||
from frameworks.shared.caller import run_in_venv | ||
|
||
data = dict( | ||
train=dict(path=dataset.train.data_path('parquet')), | ||
test=dict(path=dataset.test.data_path('parquet')), | ||
target=dict( | ||
name=dataset.target.name, | ||
classes=dataset.target.values | ||
), | ||
problem_type=dataset.type.name # AutoGluon problem_type is using same names as amlb.data.DatasetType | ||
) | ||
|
||
return run_in_venv(__file__, "exec.py", | ||
input_data=data, dataset=dataset, config=config) | ||
if dataset.type is not DatasetType.timeseries: | ||
|
||
data = dict( | ||
train=dict(path=dataset.train.data_path('parquet')), | ||
test=dict(path=dataset.test.data_path('parquet')), | ||
target=dict( | ||
name=dataset.target.name, | ||
classes=dataset.target.values | ||
), | ||
problem_type=dataset.type.name # AutoGluon problem_type is using same names as amlb.data.DatasetType | ||
) | ||
exec_file = "exec.py" | ||
|
||
else: | ||
dataset = deepcopy(dataset) | ||
if not hasattr(dataset, 'timestamp_column'): | ||
dataset.timestamp_column = None | ||
if not hasattr(dataset, 'id_column'): | ||
dataset.id_column = None | ||
if not hasattr(dataset, 'forecast_range_in_steps'): | ||
raise AttributeError("Unspecified `forecast_range_in_steps`.") | ||
|
||
data = dict( | ||
# train=dict(path=dataset.train.data_path('parquet')), | ||
# test=dict(path=dataset.test.data_path('parquet')), | ||
train=dict(path=dataset.train.path), | ||
test=dict(path=dataset.test.path), | ||
target=dict( | ||
name=dataset.target.name, | ||
classes=dataset.target.values | ||
), | ||
problem_type=dataset.type.name, # AutoGluon problem_type is using same names as amlb.data.DatasetType | ||
timestamp_column=dataset.timestamp_column, | ||
id_column=dataset.id_column, | ||
forecast_range_in_steps=dataset.forecast_range_in_steps | ||
) | ||
exec_file = "exec_ts.py" | ||
|
||
return run_in_venv(__file__, exec_file, | ||
input_data=data, dataset=dataset, config=config) |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file was deleted.
Oops, something went wrong.
Oops, something went wrong.