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run_experiment_ablation_simple_networks.sh
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run_experiment_ablation_simple_networks.sh
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#!/bin/bash
# arg1: (Default:venv3) name of the virtual environment (will be stored in the main directory of this project). Default is stored in the file ./venv . if problems occur, change the name in the file
# arg2: (Default:0) the number of the gpu to use. This script does not support multiple gpus
# get the virtual environment name from the first argument to the script. if none is given, use the last virtual environment.
# change the first line in the ../venv file to match the default virtual environment name if needed
virtual_env_name=${1:-$(<.././venv)}
rm .././venv
echo "$virtual_env_name"
echo "$virtual_env_name">>.././venv
echo "Requested virtual environment: $virtual_env_name"
### In this experiment, we simplify the networks: reduce the retinanet to a cnn; autoencode english-english (no RCL)
# get dir
scripts_dir=`pwd`
project_dir="$(dirname "$(dirname "$scripts_dir")")"
echo "The project directory: " $project_dir
cd $project_dir
echo "Activating virtualenv"
source $virtual_env_name"/bin/activate"
# inside the virtual environment, run all setups
if [[ $(basename "$VIRTUAL_ENV") == $virtual_env_name ]]; then
echo "Running experiments"
# export gpu
export CUDA_VISIBLE_DEVICES=${2:-0}
# setup all the packages
cd $project_dir/modules/data_fusion/fusionnet/keras_fusionnet/bin/
# perform 3 rounds
for i in {1..3}
do
echo "ROUND $i \n\n"
# no retinanet loss and using cnn instead
python3 train.py --steps=5000 --val-steps=500 --no-snapshots --epochs=10 --batch-size=1 \
--experiment-tag "CNN_NO_RET_LOSS" --comet-api-key="$COMET_API_KEY" --comet-project-name="ir_ablation_simplenet_exp" --comet-workspace="$COMET_WORKSPACE" \
fusionnet $DS_PATH/GeneratedData/FusionMultimodalCSV/virtual/Annotations/train.csv \
--val-annotations $DS_PATH/GeneratedData/FusionMultimodalCSV/virtual/Annotations/val.csv \
--output-filter="transformer_classification:1,fusionnet_regression:1" \
--coordinate-limits $DS_PATH/GeneratedData/FusionMultimodalCSV/virtual/Annotations/joints_min_max.npz \
vision simple_cnn $DS_PATH/GeneratedData/VisionMultimodalCSV/virtual/Annotations_no_pos/train_cropped.csv \
$DS_PATH/GeneratedData/VisionMultimodalCSV/virtual/Annotations_no_pos/classmaps.csv \
--val-annotations $DS_PATH/GeneratedData/VisionMultimodalCSV/virtual/Annotations_no_pos/val_cropped.csv \
--image-min-side=360 --image-max-side=660 --no-evaluation \
language_translation transformer $DS_PATH/GeneratedData/LanguageTranslationMultimodalCSV/virtual/Annotations/train.csv \
--vocab $DS_PATH/GeneratedData/LanguageTranslationMultimodalCSV/virtual/Annotations/vocab.lst \
--val-annotations $DS_PATH/GeneratedData/LanguageTranslationMultimodalCSV/virtual/Annotations/val.csv \
--val-golden-set $DS_PATH/GeneratedData/LanguageTranslationMultimodalCSV/virtual/Annotations/val_golden.txt \
--config $scripts_dir/test_config/transformer_config.ini --no-evaluation
# all losses with english as source and target
python3 train.py --steps=5000 --val-steps=500 --no-snapshots --epochs=10 --batch-size=1 \
--experiment-tag "ENGLISH_SOURCE_TARGET" --comet-api-key="$COMET_API_KEY" --comet-project-name="ir_ablation_simplenet_exp" --comet-workspace="$COMET_WORKSPACE" \
fusionnet $DS_PATH/GeneratedData/FusionMultimodalCSV/virtual/Annotations/train.csv \
--val-annotations $DS_PATH/GeneratedData/FusionMultimodalCSV/virtual/Annotations/val.csv \
--output-filter="retinanet_regression:1,retinanet_classification:1,transformer_classification:1,fusionnet_regression:1" \
--coordinate-limits $DS_PATH/GeneratedData/FusionMultimodalCSV/virtual/Annotations/joints_min_max.npz \
vision retinanet $DS_PATH/GeneratedData/VisionMultimodalCSV/virtual/Annotations_no_pos/train_cropped.csv \
$DS_PATH/GeneratedData/VisionMultimodalCSV/virtual/Annotations_no_pos/classmaps.csv \
--val-annotations $DS_PATH/GeneratedData/VisionMultimodalCSV/virtual/Annotations_no_pos/val_cropped.csv \
--image-min-side=360 --image-max-side=660 --no-evaluation \
language_translation transformer $DS_PATH/GeneratedData/LanguageTranslationMultimodalCSV/virtual/Annotations_english_only/train.csv \
--vocab $DS_PATH/GeneratedData/LanguageTranslationMultimodalCSV/virtual/Annotations_english_only/vocab.lst \
--val-annotations $DS_PATH/GeneratedData/LanguageTranslationMultimodalCSV/virtual/Annotations_english_only/val.csv \
--config $scripts_dir/test_config/transformer_config.ini --no-evaluation
# no fusionnet loss with english as source and target
python3 train.py --steps=5000 --val-steps=500 --no-snapshots --epochs=10 --batch-size=1 \
--experiment-tag "ENGLISH_SOURCE_TARGET_NO_TRAN_LOSS" --comet-api-key="$COMET_API_KEY" --comet-project-name="ir_ablation_simplenet_exp" --comet-workspace="$COMET_WORKSPACE" \
fusionnet $DS_PATH/GeneratedData/FusionMultimodalCSV/virtual/Annotations/train.csv \
--val-annotations $DS_PATH/GeneratedData/FusionMultimodalCSV/virtual/Annotations/val.csv \
--output-filter="retinanet_regression:1,retinanet_classification:1,fusionnet_regression:1" \
--coordinate-limits $DS_PATH/GeneratedData/FusionMultimodalCSV/virtual/Annotations/joints_min_max.npz \
vision retinanet $DS_PATH/GeneratedData/VisionMultimodalCSV/virtual/Annotations_no_pos/train_cropped.csv \
$DS_PATH/GeneratedData/VisionMultimodalCSV/virtual/Annotations_no_pos/classmaps.csv \
--val-annotations $DS_PATH/GeneratedData/VisionMultimodalCSV/virtual/Annotations_no_pos/val_cropped.csv \
--image-min-side=360 --image-max-side=660 --no-evaluation \
language_translation transformer $DS_PATH/GeneratedData/LanguageTranslationMultimodalCSV/virtual/Annotations_english_only/train.csv \
--vocab $DS_PATH/GeneratedData/LanguageTranslationMultimodalCSV/virtual/Annotations_english_only/vocab.lst \
--val-annotations $DS_PATH/GeneratedData/LanguageTranslationMultimodalCSV/virtual/Annotations_english_only/val.csv \
--config $scripts_dir/test_config/transformer_config.ini --no-evaluation
done
else
echo "Activation failed - skipping experiments. Expected \"$virtual_env_name\" but got $(if [[ -z "$VIRTUAL_ENV" ]]; then echo "nothing"; else basename "$VIRTUAL_ENV"; fi) instead"
fi
cd $scripts_dir