Pointwise features generation #2
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dhdhagar#39) * Add --debug and --track_errors to log cvxpylayer errors * Fix save_to_wandb call for hyperparameters * Fix tensor serializable error * Fix for --eval_only_split flow * Add `sdp_scale` hyperparameter to scale the weight matrix to the SDP layer by the maximum element * Add `gradient_accumulation` hyperparameter * Change run defaults and sweep configs * Add sweep prefix option to run_sweep * Increase sweep agent memory * Clamp cvxpy output to [0,1] * Address meshgrid warning * Add `weighted_loss` to e2e sweep config * Modify run_sweep.sh to take in seed start and end values * Add `use_sdp` hyperparam to control whether to use the SDP during training and inference or directly use the MLP output with HAC-cut * Log errors before crashing; make error tracking the default behavior * Exception handling improvements * Make tqdm verbose even in silent mode * Save best dev model before testing * Add *-nosdp sweep configurations * Add `e2e_loss` hyperparam to control whether to use Frobenius or BCE loss * Change default subsampling to 80 (train) and 100 (dev) * Add --local to run with wandb disabled, change default weighted_loss to false to stay consistent with icml23 submission
… matix length and order.
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This request contains point-wise feature code generation as a script.