- B301 (pickle): add nosec B301 to pd.read_pickle calls in Kaggle templates
— files are trusted Kaggle-environment inputs, not user-supplied
- B614 (torch.load): add weights_only=True to all torch.load calls in
model benchmark GT code and gt_code.py
- B104 (binding 0.0.0.0): change run_server and CLI default to 127.0.0.1;
add nosec comment where all-interface binding is required for Docker
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
* init trail
* Add spec info
* auto unzip mlebench prepared data for out scenario
* successfully run example
* successfully run main
* simplify load traing
* extract load_from_raw_data
* split the fies(still buggy)
It should stop on ~20 epoch and reach the end
* some changes
* Fix bug to run example
* (success) until feature
* refine model and ensemble
* add metrics in ens.py
* update README & spec.md
* ens change
* fix ens bug
* Delete rdagent/scenarios/kaggle/tpl_ex/aerial-cactus-identification/train.py
* add template_path in KG_conf
* fix test kaggle
* CI
* make test_import not check kaggle template codes
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Co-authored-by: Bowen Xian <xianbowen@outlook.com>
TPTBusiness