# INV SHARED EXPERIMENT # ~/code/watch/scripts/generate_ta2_features.sh DVC_DPATH=$HOME/data/dvc-repos/smart_watch_dvc DVC_DPATH=${DVC_DPATH:-$HOME/data/dvc-repos/smart_watch_dvc} WORKDIR=$DVC_DPATH/training/$HOSTNAME/$USER DATASET_CODE=Drop1_October2021 ARCH=smt_it_joint_p8 EXPERIMENT_NAME=Saliency_${ARCH}_rgb_uconn_ukyshared_v002 KWCOCO_BUNDLE_DPATH=${KWCOCO_BUNDLE_DPATH:-$DVC_DPATH/drop1-S2-L8-aligned} TRAIN_FPATH=$KWCOCO_BUNDLE_DPATH/combo_train_data.kwcoco.json VALI_FPATH=$KWCOCO_BUNDLE_DPATH/combo_vali_data.kwcoco.json TEST_FPATH=$KWCOCO_BUNDLE_DPATH/combo_vali_data.kwcoco.json #python -m geowatch stats $COMBO_COCO_FPATH #CHANNELS="blue|green|red|ASI|inv_shared.0:64" TODO CHANNELS="blue|green|red|ASI|inv_shared1|inv_shared2|inv_shared3|inv_shared4|inv_shared5|inv_shared6|inv_shared7|inv_shared8|inv_shared9|inv_shared10|inv_shared11|inv_shared12|inv_shared13|inv_shared14|inv_shared15|inv_shared16|inv_shared17|inv_shared18|inv_shared19|inv_shared20|inv_shared21|inv_shared22|inv_shared23|inv_shared24|inv_shared25|inv_shared26|inv_shared27|inv_shared28|inv_shared29|inv_shared30|inv_shared31|inv_shared32|inv_shared33|inv_shared34|inv_shared35|inv_shared36|inv_shared37|inv_shared38|inv_shared39|inv_shared40|inv_shared41|inv_shared42|inv_shared43|inv_shared44|inv_shared45|inv_shared46|inv_shared47|inv_shared48|inv_shared49|inv_shared50|inv_shared51|inv_shared52|inv_shared53|inv_shared54|inv_shared55|inv_shared56|inv_shared57|inv_shared58|inv_shared59|inv_shared60|inv_shared61|inv_shared62|inv_shared63|inv_shared64" DEFAULT_ROOT_DIR=$WORKDIR/$DATASET_CODE/runs/$EXPERIMENT_NAME PACKAGE_FPATH=$DEFAULT_ROOT_DIR/final_package_$EXPERIMENT_NAME.pt #TRAIN_CONFIG_FPATH=$WORKDIR/$DATASET_CODE/configs/train_$EXPERIMENT_NAME.yml #PRED_CONFIG_FPATH=$WORKDIR/$DATASET_CODE/configs/predict_$EXPERIMENT_NAME.yml #PRED_FPATH=$DEFAULT_ROOT_DIR/pred/pred.kwcoco.json #SUGGESTIONS="$(python -m geowatch.tasks.fusion.organize suggest_paths \ # --package_fpath=$PACKAGE_FPATH \ # --test_dataset=$TEST_DATASET)" #PRED_DATASET="$(echo "$SUGGESTIONS" | jq -r .pred_dataset)" #EVAL_DATASET="$(echo "$SUGGESTIONS" | jq -r .eval_dpath)" # Write train and prediction configs export CUDA_VISIBLE_DEVICES="3" python -m geowatch.tasks.fusion.fit \ --channels=${CHANNELS} \ --method="MultimodalTransformer" \ --arch_name=$ARCH \ --chip_size=64 \ --chip_overlap=0.0 \ --time_steps=3 \ --time_span=1y \ --time_sampling=hard+distribute \ --batch_size=4 \ --accumulate_grad_batches=4 \ --num_workers=0 \ --attention_impl=performer \ --neg_to_pos_ratio=0.5 \ --global_class_weight=0.0 \ --global_change_weight=0.0 \ --global_saliency_weight=1.0 \ --negative_change_weight=0.05 \ --change_loss='dicefocal' \ --saliency_loss='focal' \ --class_loss='cce' \ --diff_inputs=False \ --max_epochs=200 \ --patience=200 \ --gpus=1 \ --learning_rate=1e-3 \ --weight_decay=1e-5 \ --num_draw=6 \ --dropout=0.1 \ --window_size=8 \ --default_root_dir=$DEFAULT_ROOT_DIR \ --package_fpath=$PACKAGE_FPATH \ --train_dataset=$TRAIN_FPATH \ --vali_dataset=$VALI_FPATH \ --test_dataset=$TEST_FPATH \ --num_sanity_val_steps=0